Grypa – Rokowania, prognozy i postęp choroby

Grypa
Rokowania, prognozy i postęp choroby

Grypa (influenza) jest istotną chorobą zakaźną układu oddechowego, charakteryzującą się znaczną chorobowością i śmiertelnością, szczególnie w grupach wysokiego ryzyka, takich jak osoby ≥65 lat, niemowlęta, kobiety w ciąży, osoby otyłe (BMI >35-40) oraz pacjenci z chorobami przewlekłymi, np. cukrzycą. Roczne epidemie powodują do 5 milionów ciężkich przypadków i 250 000–650 000 zgonów globalnie. Powikłania obejmują wtórne zakażenia bakteryjne, zapalenie płuc, ARDS oraz zaostrzenia chorób przewlekłych układu oddechowego. Wczesne rozpoznanie i leczenie przeciwwirusowe są kluczowe, zwłaszcza u pacjentów z wynikami FluA-p ≥7, co wskazuje na wysokie ryzyko 30-dniowej śmiertelności. Skale takie jak PSI i CURB-65 mają ograniczoną skuteczność w grypie, natomiast FluA-p wykazuje lepszą trafność prognostyczną. Nowoczesne modele uczenia maszynowego (ML) wykazują potencjał w prognozowaniu hospitalizacji i śmiertelności, szczególnie w oparciu o dane in vivo, co może wspierać decyzje kliniczne i działania zdrowia publicznego.

Prognoza w grypie – przegląd zagadnienia

Czynniki ryzyka powikłań

Modele predykcyjne w grypie

Specyficzne narzędzia predykcyjne
Podejścia uczenia maszynowego

Rokowanie w specyficznych typach grypy

Rokowanie w grypie sezonowej
Rokowanie w grypie ptasiej

Gotowość na pandemię grypy
Kierunki przyszłych badań

Kolejne rozdziały

Prognoza w grypie – przegląd zagadnienia

Grypa (influenza) jest poważną chorobą zakaźną układu oddechowego, która może prowadzić do znacznej chorobowości i śmiertelności. Chociaż większość osób z grypą wraca do zdrowia w ciągu jednego tygodnia, kaszel i zmęczenie mogą utrzymywać się dłużej. Niektóre osoby są bardziej podatne na rozwój powikłań, które mogą skutkować hospitalizacją, a czasami śmiercią¹. Według danych epidemiologicznych, roczne epidemie grypy odpowiadają za nawet 5 milionów przypadków ciężkiej choroby i od 250 000 do 500 000 zgonów na całym świecie². Sezonowa grypa zabija do 650 000 osób każdego roku³.

U zdrowych osób zakażenie grypą zwykle ogranicza się samo i rzadko kończy się śmiercią. Objawy zwykle trwają od 2 do 8 dni⁴. Grypa może powodować, że ludzie opuszczają pracę lub szkołę i wiąże się ze zmniejszoną wydajnością pracy, a u starszych dorosłych – ze zmniejszoną niezależnością⁵. Powikłania i śmiertelność występują głównie w populacjach wysokiego ryzyka i u osób hospitalizowanych⁶.

Czynniki ryzyka powikłań

Ryzyko hospitalizacji jest najwyższe u osób w wieku 65 lat lub starszych, małych dzieci oraz osób z przewlekłymi schorzeniami⁷. Dłuższy czas trwania objawów, dodatnie markery stanu zapalnego i krzepnięcia oraz immunosupresja są związane ze zwiększonym ryzykiem progresji choroby⁸. Pacjenci z grypą są uważani za osoby o podwyższonym ryzyku wtórnego zakażenia bakteryjnego i zapalenia płuc z powodu cytopatycznych efektów replikacji wirusa w komórkach, a także zdysregulowanych zmian w produkcji cytokin przez gospodarza⁹.

Ciężka choroba i śmiertelność są zazwyczaj przypisywane zapaleniu płuc z pierwotnego zakażenia wirusowego lub wtórnego zakażenia bakteryjnego, które może postępować do zespołu ostrej niewydolności oddechowej (ARDS)¹⁰. Inne powikłania oddechowe, które mogą wystąpić, obejmują zapalenie zatok, zapalenie oskrzeli, zapalenie oskrzelików, nadmierne gromadzenie się płynu w płucach oraz zaostrzenie przewlekłego zapalenia oskrzeli i astmy¹¹.

Grupy wysokiego ryzyka powikłań obejmują:

Osoby w wieku co najmniej 65 lat z powodu osłabionego układu odpornościowego związanego ze starzeniem się lub przewlekłą chorobą¹²
Dzieci poniżej pierwszego roku życia oraz dzieci, które nie były wcześniej wielokrotnie narażone na wirusy grypy¹³
Kobiety w ciąży, u których ryzyko wzrasta wraz z trymestrem i utrzymuje się do dwóch tygodni po porodzie¹⁴
Osoby otyłe, szczególnie o wskaźniku masy ciała większym niż 35-40, co wiąże się z większą replikacją wirusa, zwiększoną ciężkością wtórnego zakażenia bakteryjnego i zmniejszoną skutecznością szczepienia¹⁵
Osoby z cukrzycą, które mają zwiększone ryzyko poważnej choroby związanej z grypą w porównaniu z osobami bez cukrzycy¹⁶

Rola genetyki w grypie nie jest dobrze zbadana, ale może być czynnikiem wpływającym na śmiertelność z powodu grypy¹⁷.

Modele predykcyjne w grypie

Dokładne przewidywanie przyszłego obciążenia hospitalizacjami związanymi z grypą w trakcie sezonu grypowego może pomóc decydentom, urzędnikom zdrowia publicznego, świadczeniodawcom i innym zainteresowanym stronom lepiej alokować zasoby i przygotować się na oczekiwane zmiany wskaźników hospitalizacji¹⁸. Badania pokazują, że modele uczenia maszynowego mogą być skutecznym narzędziem do prognozowania hospitalizacji związanych z grypą¹⁹.

Specyficzne narzędzia predykcyjne

Wczesne rozpoznanie potencjalnie strasznych wyników jest ważne na oddziale ratunkowym. Efektywna prognoza choroby sprzyja zmniejszeniu obciążenia finansowego i zapewnieniu odpowiedniej opieki pacjentom²⁰. Szereg modeli predykcyjnych zostało opracowanych w celu oceny ryzyka powikłań i śmiertelności w grypie:

Skala FluA-p

Indeks ciężkości zapalenia płuc (PSI) i skala CURB-65 (splątanie, mocznik, częstość oddechów, ciśnienie krwi, wiek powyżej 65 lat) wykazały zdolność przewidywania śmiertelności w pozaszpitalnym zapaleniu płuc. Ich zdolność do przewidywania zapalenia płuc związanego z grypą jest jednak mniej dobrze ustalona²¹²².

W odpowiedzi na te ograniczenia opracowano skalę FluA-p, która jest prostą i wiarygodną regułą predykcyjną 30-dniowej śmiertelności u pacjentów hospitalizowanych z zapaleniem płuc związanym z grypą typu A (FluA-p). Reguła predykcyjna może pomóc klinicystom dokładniej ocenić ciężkość choroby grypowej²³. Wyniki badań wykazały, że wynik FluA-p był łatwy do uzyskania i służył jako wiarygodna reguła predykcyjna 30-dniowej śmiertelności u pacjentów z FluA-p. Skala ta może również skutecznie stratyfikować pacjentów z FluA-p do odpowiednich kategorii ryzyka, pomagając tym samym świadczeniodawcom w podejmowaniu bardziej racjonalnych decyzji klinicznych²⁴.

Zaleca się, aby klinicyści zwracali szczególną uwagę na pacjentów z wynikami FluA-p ≥7, ponieważ takie osoby mają zwiększone ryzyko zgonu²⁵. Metoda ta wykazała większą trafność predykcyjną niż powszechne skale ciężkości zapalenia płuc, takie jak PSI i CURB-65²⁶²⁷.

Inne narzędzia predykcyjne

Choroby sercowo-naczyniowe i objawy ze strony ośrodkowego układu nerwowego odgrywają ważną rolę w modelach prognostycznych grypy. Ponadto niektóre powszechnie stosowane systemy punktacji również mogą odgrywać pewną rolę w ocenie²⁸. Do innych modeli predykcyjnych należą:

Przewidywanie wyników za pomocą skali Mortality in Emergency Department Sepsis w połączeniu z prokalcytoniną dla pacjentów z grypą²⁹
Czynniki prognostyczne śmiertelnego zapalenia płuc wywołanego grypą u dorosłych³⁰
Przewidywanie śmiertelności u hospitalizowanych pacjentów z zapaleniem płuc wywołanym grypą H1N1 z 2009 roku³¹

Podejścia uczenia maszynowego

Najnowsze badania pokazują, że algorytmy uczenia maszynowego (ML) mogą być wykorzystywane do podsumowania złożonych eksperymentów in vivo w zwięzłe podsumowania, które informują i wzmacniają kryteria oceny ryzyka pandemii dla gotowości pandemicznej, które uwzględniają dane in vivo³².

Istnieje potrzeba przeprowadzenia badań w celu zidentyfikowania nie tylko właściwości wirusowych i determinantów molekularnych, które przyczyniają się do kluczowych wyników zakażenia (zwłaszcza ciężkości choroby i przenoszalności), ale również w celu dalszej oceny względnej zdolności kwantyfikowalnych punktów danych do przewidywania tych wyników w krótszym czasie po izolacji wirusa³³.

W badaniach nad modelami uczenia maszynowego analizowano trzy zmienne wynikowe modelu (śmiertelność, zachorowalność i przenoszenie), wybrane w celu reprezentowania najważniejszych pytań podejmowanych przez eksperymenty in vivo z wykorzystaniem modelu fretek³⁴. Stwierdzono, że podejścia ML mogą oferować wysoką wartość predykcyjną, gdy są informowane przez różnorodne dane generowane in vivo, ale różnią się szeroko pod względem metryk wydajności i możliwości zastosowania do szerszego wykorzystania w zależności od wybranego wyniku klasyfikacji³⁵.

Modele klasyfikacji transmisji miały ogólnie najwyższe metryki wydajności i były bardzo dokładne w przewidywaniu wyników przy użyciu danych generowanych wewnętrznie. Modele klasyfikacji śmiertelności oferowały podobnie wysoką wydajność z rozsądną zdolnością predykcyjną. Natomiast modele klasyfikacji zachorowalności oferowały minimalne możliwości predykcyjne³⁶.

Wspólnie badania wspierają pogląd, że algorytmy ML mogą wydobywać znaczące informacje z wcześniej przeprowadzonych prac in vivo i oferują obszary przyszłego udoskonalenia badań oceny ryzyka wykorzystujących dane generowane in vivo, zgodnie z innymi ostatnimi wysiłkami w tej dziedzinie mającymi na celu włączenie nowych ram analitycznych do działań związanych z oceną ryzyka³⁷.

Rokowanie w specyficznych typach grypy

Rokowanie w grypie sezonowej

U pacjentów bez chorób współistniejących, którzy zachorują na grypę sezonową, rokowanie jest bardzo dobre. Jednak niektórzy pacjenci mają przedłużony czas powrotu do zdrowia i pozostają osłabieni i zmęczeni przez tygodnie. Śmiertelność z powodu grypy sezonowej jest najwyższa u niemowląt i osób starszych³⁸.

Większość osób wraca do zdrowia po gorączce i innych objawach w ciągu tygodnia bez konieczności interwencji medycznej. Jednak grypa może powodować ciężką chorobę lub śmierć, szczególnie u osób z grup wysokiego ryzyka³⁹. Hospitalizacja i zgony z powodu grypy występują głównie wśród grup wysokiego ryzyka⁴⁰.

Skutki sezonowych epidemii grypy w krajach rozwijających się nie są w pełni znane, ale badania szacują, że 99% zgonów u dzieci poniżej 5 roku życia z zakażeniami dolnych dróg oddechowych związanymi z grypą występuje w krajach rozwijających się⁴¹.

Osoby z grup wysokiego ryzyka lub z ciężkimi objawami powinny być leczone lekami przeciwwirusowymi jak najszybciej⁴². Szczepionka może być mniej skuteczna u starszych osób, ale sprawi, że choroba będzie mniej ciężka i zmniejszy ryzyko powikłań i śmierci⁴³.

Rokowanie w grypie ptasiej

Rokowanie dla pacjentów z grypą ptasią jest związane ze stopniem i czasem trwania hipoksemii. Dotychczasowe przypadki wykazały 60% śmiertelność; jednak Wang i wsp. sugerują, że może to być zawyżony szacunek wynikający z niedostatecznego zgłaszania łagodnych przypadków⁴⁴.

Ryzyko śmiertelności z powodu grypy ptasiej zależy od stopnia choroby układu oddechowego, a nie od powikłań bakteryjnych (zapalenie płuc). Śmiertelność jest znacznie niższa wśród pacjentów leczonych w bardziej rozwiniętych krajach. Istnieje niewiele dowodów dotyczących długoterminowych skutków choroby wśród osób, które przeżyły⁴⁵.

Gotowość na pandemię grypy

„Kolejna pandemia spowodowana nowym wirusem grypy jest pewna. Ale nie wiemy, kiedy to nastąpi, jaki szczep wirusa będzie i jak poważna będzie choroba” – powiedziała dr Wenqing Zhang, kierownik Globalnego Programu Grypy WHO. Ta niepewność sprawia, że grypa bardzo różni się od wielu innych patogenów⁴⁶.

„Grypa pandemiczna jest znaczącym problemem zdrowia publicznego, któremu nie jesteśmy w stanie zapobiec ani wyeliminować, biorąc pod uwagę naszą obecną technologię i wiedzę. Tak więc wiele naszej pracy związanej z zarządzaniem pandemią musi się odbywać, gdy ona wystąpi, aby wpłynąć na zdrowie i społeczeństwo” – powiedziała dr Zhang. „Sezonowe epidemie grypy dają realne możliwości przygotowania się do następnej pandemii. Aby osiągnąć najlepszy możliwy wynik teraz i w przyszłości, istnieją trzy krytyczne czynniki: terminowość i jakość udostępniania wirusa i informacji, badania i innowacje oraz globalna koordynacja. W przypadku pandemicznej grypy świat musi pracować jako jeden zespół” – powiedziała⁴⁷.

Opracowanie i dystrybucja szczepionki podczas pandemii może potrwać do roku. Oznacza to, że środki niefarmaceutyczne – takie same jak te potrzebne do powstrzymania grypy sezonowej – będą miały kluczowe znaczenie. Niektóre z nich to działania, które mogą podejmować osoby indywidualne, w tym pozostawanie w domu podczas choroby i częste mycie rąk⁴⁸.

„Nadal mamy wyzwania związane z poprawą koordynacji międzynarodowej i mobilizacją wystarczających i zrównoważonych zasobów na rzecz gotowości i badań w celu opracowania lepszych szczepionek, leków przeciwwirusowych i diagnostyki” – powiedziała dr Briand. „Co najważniejsze, te środki zaradcze muszą być dostępne dla wszystkich krajów, szczególnie tych społeczności o najmniejszych zasobach, ponieważ będą one najbardziej narażone w następnej pandemii grypy”⁴⁹.

Kierunki przyszłych badań

Dokładne prognozy mogą informować o reakcji na epidemie. Większość wysiłków w prognozowaniu grypy koncentrowała się na przewidywaniu aktywności grypopodobnej, a mniej na hospitalizacjach związanych z grypą⁵⁰. Ensemble super learner (model uczenia się zespołowego) poprawił przewidywania dotyczące hospitalizacji związanych z grypą w porównaniu z naiwną predykcją⁵¹.

Ensemble zapewnia sposób na dokonywanie rozsądnych prognoz w warunkach niepewności co do specyfikacji modelu⁵². Stwierdzono, że ensemble super learner poprawił wyniki w porównaniu z naiwną medianą predykcji w przewidywaniu 3 miar sezonowych hospitalizacji związanych z grypą. Prognozy zespołu na początku sezonu zazwyczaj odzwierciedlały prognozy naiwnej mediany, ale szacunki zespołu poprawiały się stopniowo w trakcie sezonu⁵³.

Super learner wydaje się być narzędziem o pewnym potencjale do prognozowania hospitalizacji z powodu grypy, sugerując kilka kierunków dla przyszłych badań⁵⁴. Proponowany model może przewidywać wskaźnik grypopodobnych zachorowań (ILI) i liczbę pacjentów z ILI z większą dokładnością niż istniejące modele w poszczególnych krajach⁵⁵. Obecne wyniki sugerują, że proponowany model jest najbardziej odpowiedni do prognozowania grypy sezonowej wśród porównywanych modeli i jest odporny na wartości odstające⁵⁶.

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Materiały źródłowe

#1 Azthena logo with the word Azthena
https://www.news-medical.net/health/Influenza-Prognosis.aspx
Most people with influenza usually recover within one week, although cough and fatigue may persist longer. However, some people are more prone to developing complications that can result in hospitalizations and, occasionally, death. […] It is estimated that annual epidemics of influenza are responsible for up to 5 million cases of severe illness and between 250,000 to 500,000 deaths worldwide. The risk of hospitalization is highest in people aged 65 years or older, in young children, and in people with chronic medical conditions. […] Longer duration of symptoms, positive markers of inflammation and coagulation, and immunosuppression are associated with an increased risk of disease progression. […] Patients with influenza are thought to be at higher risk for secondary bacterial infection and pneumonia due to the cytopathic effects of viral replication in cells, as well as dysregulated changes in host cytokine production that may dampen both the ability of the immune system to clear bacteria and to accomplish appropriate modulation of the inflammatory cascade.
#2 Azthena logo with the word Azthena
https://www.news-medical.net/health/Influenza-Prognosis.aspx
Most people with influenza usually recover within one week, although cough and fatigue may persist longer. However, some people are more prone to developing complications that can result in hospitalizations and, occasionally, death. […] It is estimated that annual epidemics of influenza are responsible for up to 5 million cases of severe illness and between 250,000 to 500,000 deaths worldwide. The risk of hospitalization is highest in people aged 65 years or older, in young children, and in people with chronic medical conditions. […] Longer duration of symptoms, positive markers of inflammation and coagulation, and immunosuppression are associated with an increased risk of disease progression. […] Patients with influenza are thought to be at higher risk for secondary bacterial infection and pneumonia due to the cytopathic effects of viral replication in cells, as well as dysregulated changes in host cytokine production that may dampen both the ability of the immune system to clear bacteria and to accomplish appropriate modulation of the inflammatory cascade.
#3
https://www.who.int/news-room/spotlight/influenza-are-we-ready
Influenza may not always be thought of by most people as a serious illness the symptoms of headaches, runny nose, cough and muscle pain can make people confuse it with a heavy cold. Yet seasonal influenza kills up to 650 000 people every year. […] „Another pandemic caused by a new influenza virus is a certainty. But we do not know when it will happen, what virus strain it will be and how severe the disease will be,” said Dr Wenqing Zhang, the manager of WHOs Global Influenza Programme. This uncertainty makes influenza very different to many other pathogens, she said. […] „Pandemic influenza is a significant public health issue that we are unable to prevent or eliminate, given our current technology and knowledge. So much of our work managing the pandemic has to be when it occurs, to impact on health and society,” said Dr Zhang. „Seasonal influenza epidemics provide real opportunities to prepare for the next pandemic. To achieve the best possible outcome now and in the future, there are three critical factors: timeliness and quality of virus and information sharing, research and innovation, and global coordination. For pandemic influenza, the world has to work as one team,” she said.
#4 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#5 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#6 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#7 Azthena logo with the word Azthena
https://www.news-medical.net/health/Influenza-Prognosis.aspx
Most people with influenza usually recover within one week, although cough and fatigue may persist longer. However, some people are more prone to developing complications that can result in hospitalizations and, occasionally, death. […] It is estimated that annual epidemics of influenza are responsible for up to 5 million cases of severe illness and between 250,000 to 500,000 deaths worldwide. The risk of hospitalization is highest in people aged 65 years or older, in young children, and in people with chronic medical conditions. […] Longer duration of symptoms, positive markers of inflammation and coagulation, and immunosuppression are associated with an increased risk of disease progression. […] Patients with influenza are thought to be at higher risk for secondary bacterial infection and pneumonia due to the cytopathic effects of viral replication in cells, as well as dysregulated changes in host cytokine production that may dampen both the ability of the immune system to clear bacteria and to accomplish appropriate modulation of the inflammatory cascade.
#8 Azthena logo with the word Azthena
https://www.news-medical.net/health/Influenza-Prognosis.aspx
Most people with influenza usually recover within one week, although cough and fatigue may persist longer. However, some people are more prone to developing complications that can result in hospitalizations and, occasionally, death. […] It is estimated that annual epidemics of influenza are responsible for up to 5 million cases of severe illness and between 250,000 to 500,000 deaths worldwide. The risk of hospitalization is highest in people aged 65 years or older, in young children, and in people with chronic medical conditions. […] Longer duration of symptoms, positive markers of inflammation and coagulation, and immunosuppression are associated with an increased risk of disease progression. […] Patients with influenza are thought to be at higher risk for secondary bacterial infection and pneumonia due to the cytopathic effects of viral replication in cells, as well as dysregulated changes in host cytokine production that may dampen both the ability of the immune system to clear bacteria and to accomplish appropriate modulation of the inflammatory cascade.
#9 Azthena logo with the word Azthena
https://www.news-medical.net/health/Influenza-Prognosis.aspx
Most people with influenza usually recover within one week, although cough and fatigue may persist longer. However, some people are more prone to developing complications that can result in hospitalizations and, occasionally, death. […] It is estimated that annual epidemics of influenza are responsible for up to 5 million cases of severe illness and between 250,000 to 500,000 deaths worldwide. The risk of hospitalization is highest in people aged 65 years or older, in young children, and in people with chronic medical conditions. […] Longer duration of symptoms, positive markers of inflammation and coagulation, and immunosuppression are associated with an increased risk of disease progression. […] Patients with influenza are thought to be at higher risk for secondary bacterial infection and pneumonia due to the cytopathic effects of viral replication in cells, as well as dysregulated changes in host cytokine production that may dampen both the ability of the immune system to clear bacteria and to accomplish appropriate modulation of the inflammatory cascade.
#10 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#11 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#12 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#13 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
In healthy individuals, influenza infection is usually self-limiting and rarely fatal. […] Symptoms usually last for 28 days. […] Influenza can cause people to miss work or school, and it is associated with decreased job performance and, in older adults, reduced independence. […] Complications and mortality primarily occur in high-risk populations and those who are hospitalized. Severe disease and mortality are usually attributable to pneumonia from the primary viral infection or a secondary bacterial infection, which can progress to ARDS. […] Other respiratory complications that may occur include sinusitis, bronchitis, bronchiolitis, excess fluid buildup in the lungs, and exacerbation of chronic bronchitis and asthma. […] People who are at least 65 years of age, due to a weakened immune system from aging or a chronic illness, are a high-risk group for developing complications, as are children less than one year of age and children who have not been previously exposed to influenza viruses multiple times.
#14 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
Pregnant women are at an elevated risk, which increases by trimester and lasts up to two weeks after childbirth. […] Obesity, in particular a body mass index greater than 35-40, is associated with greater amounts of viral replication, increased severity of secondary bacterial infection, and reduced vaccination efficacy. […] The role of genetics in influenza is not well researched, but it may be a factor in influenza mortality.
#15 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
Pregnant women are at an elevated risk, which increases by trimester and lasts up to two weeks after childbirth. […] Obesity, in particular a body mass index greater than 35-40, is associated with greater amounts of viral replication, increased severity of secondary bacterial infection, and reduced vaccination efficacy. […] The role of genetics in influenza is not well researched, but it may be a factor in influenza mortality.
#16 Influenza: Practice Essentials, Background, Pathophysiology
https://emedicine.medscape.com/article/219557-overview
Diabetes increases the risk for severe flu-related illness. In a cohort study of 166,715 individuals in Manitoba, Canada, Lau and colleagues found that adults with diabetes were at significantly greater risk for serious illness related to influenza compared with those without diabetes; this justifies guideline recommendations for influenza vaccination in this population. After controlling for age, sex, socioeconomic status, location of residence, comorbidities, and vaccination, adults with diabetes had a significant increase (6%) in all-cause hospitalizations associated with influenza (P = .044). Only 16% of the patients with diabetes in the cohort and 7% of the patients without diabetes had been vaccinated.
#17 Influenza – Wikipedia
https://en.wikipedia.org/wiki/Influenza
Pregnant women are at an elevated risk, which increases by trimester and lasts up to two weeks after childbirth. […] Obesity, in particular a body mass index greater than 35-40, is associated with greater amounts of viral replication, increased severity of secondary bacterial infection, and reduced vaccination efficacy. […] The role of genetics in influenza is not well researched, but it may be a factor in influenza mortality.
#18 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#19 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#20 Prediction models for prognosis of inï¬uenza: a systematic review and critical appraisal
https://www.signavitae.com/articles/10.22514/sv.2021.148
The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. […] Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. […] Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients. […] Prognostic factors for fatal adult influenza pneumonia. […] Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.
#21 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients
https://pmc.ncbi.nlm.nih.gov/articles/PMC7206684/
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65.
#22 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients | Respiratory Research | Full Text
https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-020-01379-z
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] The 30-day mortality of FluA-p patients was 19.6% (136/693). […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65. […] We developed a simple and reliable prediction rule for 30-day mortality in patients hospitalised with FluA-p. The prediction rule could help clinicians to more accurately assess influenza disease severity.
#23 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients | Respiratory Research | Full Text
https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-020-01379-z
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] The 30-day mortality of FluA-p patients was 19.6% (136/693). […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65. […] We developed a simple and reliable prediction rule for 30-day mortality in patients hospitalised with FluA-p. The prediction rule could help clinicians to more accurately assess influenza disease severity.
#24 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients
https://pmc.ncbi.nlm.nih.gov/articles/PMC7206684/
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65.
#25 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients
https://pmc.ncbi.nlm.nih.gov/articles/PMC7206684/
We developed a simple and reliable prediction rule for 30-day mortality in patients hospitalised with FluA-p. The prediction rule could help clinicians to more accurately assess influenza disease severity. Our recommendation is that clinicians should pay particular attention to patients with FluA-p scores 7, as such individuals have an increased risk for death.
#26 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients
https://pmc.ncbi.nlm.nih.gov/articles/PMC7206684/
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65.
#27 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients | Respiratory Research | Full Text
https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-020-01379-z
The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age65years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. […] The 30-day mortality of FluA-p patients was 19.6% (136/693). […] Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. […] Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65. […] We developed a simple and reliable prediction rule for 30-day mortality in patients hospitalised with FluA-p. The prediction rule could help clinicians to more accurately assess influenza disease severity.
#28 Prediction models for prognosis of inï¬uenza: a systematic review and critical appraisal
https://www.signavitae.com/articles/10.22514/sv.2021.148
The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. […] Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. […] Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients. […] Prognostic factors for fatal adult influenza pneumonia. […] Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.
#29 Prediction models for prognosis of inï¬uenza: a systematic review and critical appraisal
https://www.signavitae.com/articles/10.22514/sv.2021.148
The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. […] Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. […] Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients. […] Prognostic factors for fatal adult influenza pneumonia. […] Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.
#30 Prediction models for prognosis of inï¬uenza: a systematic review and critical appraisal
https://www.signavitae.com/articles/10.22514/sv.2021.148
The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. […] Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. […] Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients. […] Prognostic factors for fatal adult influenza pneumonia. […] Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.
#31 Prediction models for prognosis of inï¬uenza: a systematic review and critical appraisal
https://www.signavitae.com/articles/10.22514/sv.2021.148
The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. […] Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. […] Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients. […] Prognostic factors for fatal adult influenza pneumonia. […] Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.
#32 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
In vivo assessments of influenza A virus (IAV) pathogenicity and transmissibility in ferrets represent a crucial component of many pandemic risk assessment rubrics, but few systematic efforts to identify which data from in vivo experimentation are most useful for predicting pathogenesis and transmission outcomes have been conducted. […] Our findings show that ML algorithms can be used to summarize complex in vivo experimental work into succinct summaries that inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data into account. […] There is a need for studies to identify not only viral properties and molecular determinants which contribute to key infection outcomes (notably disease severity and transmissibility), but to further assess the relative ability of quantifiable datapoints to predict these outcomes on a more rapid timeframe after viral isolation.
#33 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
In vivo assessments of influenza A virus (IAV) pathogenicity and transmissibility in ferrets represent a crucial component of many pandemic risk assessment rubrics, but few systematic efforts to identify which data from in vivo experimentation are most useful for predicting pathogenesis and transmission outcomes have been conducted. […] Our findings show that ML algorithms can be used to summarize complex in vivo experimental work into succinct summaries that inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data into account. […] There is a need for studies to identify not only viral properties and molecular determinants which contribute to key infection outcomes (notably disease severity and transmissibility), but to further assess the relative ability of quantifiable datapoints to predict these outcomes on a more rapid timeframe after viral isolation.
#34 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
Our study examined three model outcome variables (lethality, morbidity, and transmission), chosen to represent the most key questions addressed by in vivo experimentation using the ferret model in this setting. […] We found that ML approaches can offer high predictive value when informed by diverse in vivo-generated data but vary widely in performance metrics and applicability for wider use depending on the classification outcome chosen. […] In conclusion, transmission classification models had the overall highest performance metrics and were very accurate in predictive outcomes when employing internally generated data. Lethality classification models offered similarly high performance with reasonable predictive ability. In contrast, morbidity classification models offered minimal predictive capabilities.
#35 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
Our study examined three model outcome variables (lethality, morbidity, and transmission), chosen to represent the most key questions addressed by in vivo experimentation using the ferret model in this setting. […] We found that ML approaches can offer high predictive value when informed by diverse in vivo-generated data but vary widely in performance metrics and applicability for wider use depending on the classification outcome chosen. […] In conclusion, transmission classification models had the overall highest performance metrics and were very accurate in predictive outcomes when employing internally generated data. Lethality classification models offered similarly high performance with reasonable predictive ability. In contrast, morbidity classification models offered minimal predictive capabilities.
#36 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
Our study examined three model outcome variables (lethality, morbidity, and transmission), chosen to represent the most key questions addressed by in vivo experimentation using the ferret model in this setting. […] We found that ML approaches can offer high predictive value when informed by diverse in vivo-generated data but vary widely in performance metrics and applicability for wider use depending on the classification outcome chosen. […] In conclusion, transmission classification models had the overall highest performance metrics and were very accurate in predictive outcomes when employing internally generated data. Lethality classification models offered similarly high performance with reasonable predictive ability. In contrast, morbidity classification models offered minimal predictive capabilities.
#37 Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data | Communications Biology
https://www.nature.com/articles/s42003-024-06629-0
Collectively, this study supports that ML algorithms can extract meaningful information from previously conducted work in vivo and offers areas of future refinement to risk assessment studies employing in vivo-generated data, in line with other recent efforts in the field to incorporate novel analytical frameworks into risk assessment activities.
#38 Influenza: Practice Essentials, Background, Pathophysiology
https://emedicine.medscape.com/article/219557-overview
In patients without comorbid disease who contract seasonal influenza, the prognosis is very good. However, some patients have a prolonged recovery time and remain weak and fatigued for weeks. Mortality from seasonal influenza is highest in infants and the elderly. […] The prognosis for patients with avian influenza is related to the degree and duration of hypoxemia. Cases to date have exhibited a 60% mortality; however, Wang et al suggest that this may be an overestimate stemming from the underreporting of mild cases. […] The risk for mortality from avian influenza depends on the degree of respiratory disease rather than on the bacterial complications (pneumonia). Mortality is significantly lower among patients cared for in more-developed nations. Little evidence is available regarding the long-term effects of disease among survivors.
#39
https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)
Most people recover from fever and other symptoms within a week without requiring medical attention. However, influenza can cause severe illness or death, especially in people at high risk. […] Hospitalization and death due to influenza occur mainly among high-risk groups. […] The effects of seasonal influenza epidemics in developing countries are not fully known, but research estimates that 99% of deaths in children under 5 years of age with influenza related lower respiratory tract infections are in developing countries. […] People at high risk or with severe symptoms should be treated with antiviral medications as soon as possible. […] The vaccine may be less effective in older people, but it will make the illness less severe and reduces the chance of complications and death.
#40
https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)
Most people recover from fever and other symptoms within a week without requiring medical attention. However, influenza can cause severe illness or death, especially in people at high risk. […] Hospitalization and death due to influenza occur mainly among high-risk groups. […] The effects of seasonal influenza epidemics in developing countries are not fully known, but research estimates that 99% of deaths in children under 5 years of age with influenza related lower respiratory tract infections are in developing countries. […] People at high risk or with severe symptoms should be treated with antiviral medications as soon as possible. […] The vaccine may be less effective in older people, but it will make the illness less severe and reduces the chance of complications and death.
#41
https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)
Most people recover from fever and other symptoms within a week without requiring medical attention. However, influenza can cause severe illness or death, especially in people at high risk. […] Hospitalization and death due to influenza occur mainly among high-risk groups. […] The effects of seasonal influenza epidemics in developing countries are not fully known, but research estimates that 99% of deaths in children under 5 years of age with influenza related lower respiratory tract infections are in developing countries. […] People at high risk or with severe symptoms should be treated with antiviral medications as soon as possible. […] The vaccine may be less effective in older people, but it will make the illness less severe and reduces the chance of complications and death.
#42
https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)
Most people recover from fever and other symptoms within a week without requiring medical attention. However, influenza can cause severe illness or death, especially in people at high risk. […] Hospitalization and death due to influenza occur mainly among high-risk groups. […] The effects of seasonal influenza epidemics in developing countries are not fully known, but research estimates that 99% of deaths in children under 5 years of age with influenza related lower respiratory tract infections are in developing countries. […] People at high risk or with severe symptoms should be treated with antiviral medications as soon as possible. […] The vaccine may be less effective in older people, but it will make the illness less severe and reduces the chance of complications and death.
#43
https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)
Most people recover from fever and other symptoms within a week without requiring medical attention. However, influenza can cause severe illness or death, especially in people at high risk. […] Hospitalization and death due to influenza occur mainly among high-risk groups. […] The effects of seasonal influenza epidemics in developing countries are not fully known, but research estimates that 99% of deaths in children under 5 years of age with influenza related lower respiratory tract infections are in developing countries. […] People at high risk or with severe symptoms should be treated with antiviral medications as soon as possible. […] The vaccine may be less effective in older people, but it will make the illness less severe and reduces the chance of complications and death.
#44 Influenza: Practice Essentials, Background, Pathophysiology
https://emedicine.medscape.com/article/219557-overview
In patients without comorbid disease who contract seasonal influenza, the prognosis is very good. However, some patients have a prolonged recovery time and remain weak and fatigued for weeks. Mortality from seasonal influenza is highest in infants and the elderly. […] The prognosis for patients with avian influenza is related to the degree and duration of hypoxemia. Cases to date have exhibited a 60% mortality; however, Wang et al suggest that this may be an overestimate stemming from the underreporting of mild cases. […] The risk for mortality from avian influenza depends on the degree of respiratory disease rather than on the bacterial complications (pneumonia). Mortality is significantly lower among patients cared for in more-developed nations. Little evidence is available regarding the long-term effects of disease among survivors.
#45 Influenza: Practice Essentials, Background, Pathophysiology
https://emedicine.medscape.com/article/219557-overview
In patients without comorbid disease who contract seasonal influenza, the prognosis is very good. However, some patients have a prolonged recovery time and remain weak and fatigued for weeks. Mortality from seasonal influenza is highest in infants and the elderly. […] The prognosis for patients with avian influenza is related to the degree and duration of hypoxemia. Cases to date have exhibited a 60% mortality; however, Wang et al suggest that this may be an overestimate stemming from the underreporting of mild cases. […] The risk for mortality from avian influenza depends on the degree of respiratory disease rather than on the bacterial complications (pneumonia). Mortality is significantly lower among patients cared for in more-developed nations. Little evidence is available regarding the long-term effects of disease among survivors.
#46
https://www.who.int/news-room/spotlight/influenza-are-we-ready
Influenza may not always be thought of by most people as a serious illness the symptoms of headaches, runny nose, cough and muscle pain can make people confuse it with a heavy cold. Yet seasonal influenza kills up to 650 000 people every year. […] „Another pandemic caused by a new influenza virus is a certainty. But we do not know when it will happen, what virus strain it will be and how severe the disease will be,” said Dr Wenqing Zhang, the manager of WHOs Global Influenza Programme. This uncertainty makes influenza very different to many other pathogens, she said. […] „Pandemic influenza is a significant public health issue that we are unable to prevent or eliminate, given our current technology and knowledge. So much of our work managing the pandemic has to be when it occurs, to impact on health and society,” said Dr Zhang. „Seasonal influenza epidemics provide real opportunities to prepare for the next pandemic. To achieve the best possible outcome now and in the future, there are three critical factors: timeliness and quality of virus and information sharing, research and innovation, and global coordination. For pandemic influenza, the world has to work as one team,” she said.
#47
https://www.who.int/news-room/spotlight/influenza-are-we-ready
Influenza may not always be thought of by most people as a serious illness the symptoms of headaches, runny nose, cough and muscle pain can make people confuse it with a heavy cold. Yet seasonal influenza kills up to 650 000 people every year. […] „Another pandemic caused by a new influenza virus is a certainty. But we do not know when it will happen, what virus strain it will be and how severe the disease will be,” said Dr Wenqing Zhang, the manager of WHOs Global Influenza Programme. This uncertainty makes influenza very different to many other pathogens, she said. […] „Pandemic influenza is a significant public health issue that we are unable to prevent or eliminate, given our current technology and knowledge. So much of our work managing the pandemic has to be when it occurs, to impact on health and society,” said Dr Zhang. „Seasonal influenza epidemics provide real opportunities to prepare for the next pandemic. To achieve the best possible outcome now and in the future, there are three critical factors: timeliness and quality of virus and information sharing, research and innovation, and global coordination. For pandemic influenza, the world has to work as one team,” she said.
#48
https://www.who.int/news-room/spotlight/influenza-are-we-ready
However, developing and distributing a vaccine during a pandemic could take up to a year. This means that non-pharmaceutical measures – the same as those needed to stop seasonal flu – will be critical. Some of these are actions that individuals can take, including staying home when sick and washing hands frequently. […] „We still have challenges with improving international coordination and mobilizing sufficient and sustainable resources for preparedness and research to make better vaccines, antivirals and diagnostics,” said Dr Briand. „Most importantly, these counter-measures need to be available to all countries, particularly those communities with the least resources as they will be the most vulnerable in the next flu pandemic.”
#49
https://www.who.int/news-room/spotlight/influenza-are-we-ready
However, developing and distributing a vaccine during a pandemic could take up to a year. This means that non-pharmaceutical measures – the same as those needed to stop seasonal flu – will be critical. Some of these are actions that individuals can take, including staying home when sick and washing hands frequently. […] „We still have challenges with improving international coordination and mobilizing sufficient and sustainable resources for preparedness and research to make better vaccines, antivirals and diagnostics,” said Dr Briand. „Most importantly, these counter-measures need to be available to all countries, particularly those communities with the least resources as they will be the most vulnerable in the next flu pandemic.”
#50 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#51 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#52 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#53 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#54 Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study
https://pmc.ncbi.nlm.nih.gov/articles/PMC10558190/
Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. […] Accurately predicting future burden of influenza-related hospitalizations during an influenza season could help policymakers, public health officials, providers, and other stakeholders better allocate resources and prepare for expected changes in hospitalization rates. […] An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. […] The ensemble provides a means for making reasonable predictions under uncertainty regarding model specification. […] We found that an ensemble super learner improved over a naive median prediction in predicting 3 measures of seasonal influenza-related hospitalizations. Ensemble predictions at the beginning of the season tended to mirror those of the naive median, but the ensemble estimates improved progressively throughout the season. […] The super learner appears to be a tool with some promise for forecasting influenza hospitalizations, suggesting several directions for future research.
#55 Robust two-stage influenza prediction model considering regular and irregular trends | PLOS One
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233126
Influenza causes numerous deaths worldwide every year. Predicting the number of influenza patients is an important task for medical institutions. […] The proposed model is suitable for prediction of seasonal flu. […] The proposed model can predict the ILI rate and the number of ILI patients with higher accuracy than existing models in the respective countries. […] The present results suggest that the proposed model is the most suitable for seasonal flu prediction among the compared models and that it is robust to outliers.
#56 Robust two-stage influenza prediction model considering regular and irregular trends | PLOS One
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233126
Influenza causes numerous deaths worldwide every year. Predicting the number of influenza patients is an important task for medical institutions. […] The proposed model is suitable for prediction of seasonal flu. […] The proposed model can predict the ILI rate and the number of ILI patients with higher accuracy than existing models in the respective countries. […] The present results suggest that the proposed model is the most suitable for seasonal flu prediction among the compared models and that it is robust to outliers.