Hipoglikemia cukrzycowa – Rokowania, prognozy i postęp choroby

Hipoglikemia cukrzycowa
Rokowania, prognozy i postęp choroby

Hipoglikemia jatrogeniczna stanowi istotne wyzwanie kliniczne u pacjentów z cukrzycą typu 1 i 2, wiążąc się z nawracającą zachorowalnością oraz zwiększonym ryzykiem zgonu, szczególnie w ciągu roku po epizodzie ciężkiej hipoglikemii (SH). U chorych z T2DM hipoglikemia może prowadzić do poważnych powikłań sercowo-naczyniowych i neurologicznych, zwłaszcza u osób z istniejącymi schorzeniami kardiologicznymi. Kluczowymi predyktorami SH w ciągu 5 lat są intensywne leczenie hipoglikemizujące (HR=2,37; 95% CI 1,99-2,83), stosowanie insuliny (HR=2,14; 95% CI 1,77-2,59) oraz leków przeciwnadciśnieniowych (HR=1,90; 95% CI 1,26-2,86). Dodatkowo, istotne czynniki ryzyka to wcześniejsze epizody hipoglikemii, wiek, funkcja nerek, czas trwania cukrzycy i BMI. W diagnostyce i monitorowaniu ryzyka wykorzystuje się parametry takie jak glukoza na czczo (FPG), HbA1c, edukacja diabetologiczna oraz stosowanie insulin NPH lub długodziałających.

Hipoglikemia cukrzycowa – Rokowanie (przewidywanie wyników)

Konsekwencje długoterminowe hipoglikemii cukrzycowej
Czynniki ryzyka wpływające na rokowanie
Modele predykcyjne i ich skuteczność
Hipoglikemia w okresie okołooperacyjnym – przewidywanie wyników
Przewidywanie rokowania w zależności od rodzaju cukrzycy
Zapobieganie hipoglikemii – wpływ na rokowanie
Wyzwania w przewidywaniu wyników hipoglikemii cukrzycowej
Przyszłe kierunki badań
Kolejne rozdziały

Hipoglikemia cukrzycowa – Rokowanie (przewidywanie wyników)

Hipoglikemia cukrzycowa, szczególnie ta jatrogeniczna, stanowi istotny problem kliniczny powodujący nawracającą zachorowalność u większości pacjentów z cukrzycą typu 1 (T1DM) oraz u wielu z zaawansowaną cukrzycą typu 2 (T2DM), a w niektórych przypadkach może być śmiertelna. ¹ Przewidywanie ryzyka hipoglikemii oraz jej wyników długoterminowych jest kluczowe dla poprawy opieki nad pacjentami z cukrzycą, jednak obecne modele prognostyczne mają ograniczoną wartość kliniczną. ²

Konsekwencje długoterminowe hipoglikemii cukrzycowej

Ciężka hipoglikemia (SH – severe hypoglycemia) u pacjentów z cukrzycą typu 2 wiąże się z istotnymi konsekwencjami zdrowotnymi. Badania wykazały, że epizody ciężkiej hipoglikemii są powiązane ze zwiększonym ryzykiem zgonu utrzymującym się nawet do roku po incydencie. ³ Nowe dowody sugerują, że poważne konsekwencje hipoglikemii mogą być w niektórych aspektach większe u osób z cukrzycą typu 2, szczególnie w odniesieniu do wpływu na układ sercowo-naczyniowy. ⁴

Hipoglikemia może prowadzić do zaburzeń rytmu serca, zwłaszcza u pacjentów z wcześniej istniejącymi nieprawidłowościami kardiologicznymi. ⁵ Wykazano również negatywny wpływ hipoglikemii na ośrodkowy układ nerwowy u osób z cukrzycą typu 2. ⁶ Obecnie toczy się debata, czy hipoglikemia jest czynnikiem ryzyka (implikującym przyczynowość) czy jedynie markerem ryzyka, który jest częstszy u osób z większą podatnością ze względu na kruchość i choroby współistniejące. ⁷

Czynniki ryzyka wpływające na rokowanie

Analiza dostępnych badań wskazuje na kilka kluczowych czynników ryzyka hipoglikemii, które wpływają na rokowanie pacjentów z cukrzycą. Po uwzględnieniu innych zmiennych w modelach prognostycznych, trzy najsilniejsze predyktory ciężkiej hipoglikemii w ciągu 5 lat to:

Intensywne leczenie hipoglikemizujące (HR=2,37, 95% CI 1,99 do 2,83)
Stosowanie insuliny (HR=2,14, 95% CI 1,77 do 2,59)
Stosowanie leków przeciwnadciśnieniowych (HR=1,90, 95% CI 1,26 do 2,86)

⁸

Dodatkowo, wcześniejsze epizody hipoglikemii, wiek, funkcja nerek, czas trwania cukrzycy i BMI zostały zidentyfikowane jako istotne czynniki wpływające na ryzyko hipoglikemii. ⁹ W nowszych badaniach określono cztery kluczowe cechy wysoce skuteczne w przewidywaniu ciężkiej hipoglikemii:

Glukoza na czczo (FPG)
Hemoglobina glikowana (HbA1c)
Ogólna edukacja diabetologiczna
Stosowanie insulin NPH lub insulin długodziałających

¹⁰

Modele predykcyjne i ich skuteczność

Obecnie opracowywane są różne modele predykcyjne mające na celu ocenę ryzyka hipoglikemii u pacjentów z cukrzycą, choć nadal brakuje systematycznej metody przewidywania długoterminowego ryzyka ciężkiej hipoglikemii u pacjentów z cukrzycą typu 2. ¹¹

Jeden z modeli predykcyjnych został opracowany na podstawie danych z badania ACCORD i osiągnął współczynnik c-statystyki na poziomie 0,782 przy użyciu 17 zmiennych. ¹² Model ten umożliwia oszacowanie 5-letniego ryzyka ciężkiej hipoglikemii u indywidualnego pacjenta z cukrzycą typu 2.

Nowsze podejścia wykorzystują metody uczenia maszynowego. Badania pokazują, że proponowana metoda współtrenowania multi-view (multi-view co-training) wykazuje lepszą wydajność w osiąganiu wysokich poziomów specyficzności, PPV i ogólnej dokładności, przewyższając konwencjonalne algorytmy uczenia maszynowego od dwóch do ośmiu razy w takich miernikach jak PPV, specyficzność i dokładność. ¹³

Hipoglikemia w okresie okołooperacyjnym – przewidywanie wyników

Szczególnym przypadkiem jest hipoglikemia w okresie okołooperacyjnym u pacjentów z cukrzycą typu 2 poddawanych planowym zabiegom chirurgicznym. Badania wykazały częstość występowania hipoglikemii 1. stopnia na poziomie 10,7% i ciężkiej hipoglikemii 2. stopnia na poziomie 1,8% w okresie okołooperacyjnym. ¹⁴

Opracowano model predykcyjny ryzyka hipoglikemii okołooperacyjnej, który kategoryzuje ryzyko hipoglikemii przy użyciu tylko czterech predyktorów:

Czas trwania cukrzycy
BMI
Odchylenie standardowe glikemii (SDBG)
Podskórne wstrzyknięcia insuliny jako przedoperacyjny schemat leczenia hipoglikemizującego

¹⁵

Na podstawie tego modelu pacjenci są kategoryzowani na trzy poziomy ryzyka: niskie, średnie i wysokie. Model ten stanowi korzystne narzędzie dla klinicystów do badania przesiewowego ryzyka hipoglikemii i kierowania przyszłymi interwencjami w celu zmniejszenia tego ryzyka. ¹⁶

Przewidywanie rokowania w zależności od rodzaju cukrzycy

Ogólnie rzecz biorąc, dla danej osoby jatrogeniczna hipoglikemia występuje rzadziej w cukrzycy typu 2 niż w typie 1. ¹⁷ Jednak istnieją dowody, że hipoglikemia wywołana przez leki stymulujące wydzielanie insuliny i samą insulinę może być śmiertelna w cukrzycy typu 2, choć dokładne wskaźniki śmiertelności z powodu hipoglikemii nie są jeszcze znane. ¹⁸

Badania wykazały, że samooceniane ciężkie epizody hipoglikemiczne wystąpiły u około 7% grupy z cukrzycą typu 2, którzy przyjmowali insulinę przez 2 lata, z częstością porównywalną do grupy przyjmującej pochodne sulfonylomocznika. Grupa z cukrzycą typu 2 przyjmująca insulinę przez ponad 5 lat miała znacznie wyższe ryzyko ciężkiej hipoglikemii, przy czym około 25% zgłosiło ciężki epizod hipoglikemiczny podczas badania. ¹⁹

W innych badaniach wskazano, że wskaźniki ciężkiej hipoglikemii u osób z cukrzycą typu 2 leczonych insuliną wynoszą około 2,5 zdarzenia na osobę rocznie. ²⁰

Zapobieganie hipoglikemii – wpływ na rokowanie

Zapobieganie hipoglikemii można postrzegać jako proces składający się z czterech kroków. ²¹ Problem hipoglikemii powinien być poruszany przy każdym kontakcie z pacjentem leczonym lekiem pobudzającym wydzielanie insuliny lub insuliną. ²²

Zasady intensywnej terapii glikemicznej istotne dla minimalizacji ryzyka jatrogenicznej hipoglikemii w cukrzycy obejmują:

Wybór leku
Selektywne stosowanie technologii leczenia cukrzycy
Zindywidualizowane cele glikemiczne
Ustrukturyzowaną edukację pacjenta
Krótkoterminowe skrupulatne unikanie hipoglikemii

²³

Podsumowując, osoby z cukrzycą leczone pochodnymi sulfonylomocznika, glinidami lub insuliną powinny być edukowane o hipoglikemii i powinny leczyć poziomy glukozy SMPG (lub CGM) ≤ 70 mg/dL (3,9 mmol/L), aby uniknąć progresji do klinicznej jatrogenicznej hipoglikemii. ²⁴

Wyzwania w przewidywaniu wyników hipoglikemii cukrzycowej

Dokładne przewidywanie ciężkiej hipoglikemii pozostaje wyzwaniem ze względu na jej wielopłaszczyznową naturę, na którą wpływają takie czynniki jak przyjmowane leki, wybory stylu życia i pomiary metaboliczne. ²⁵ Lepswe zrozumienie barier w dokładnym raportowaniu pomogłoby społeczności diabetologicznej w oszacowaniu częstości i ciężkości epizodów hipoglikemicznych u osób z cukrzycą typu 2. ²⁶

Systematyczny przegląd modeli predykcyjnych dla hipoglikemii u pacjentów z cukrzycą wskazuje, że istniejące modele predykcyjne nie są zalecane do powszechnego stosowania klinicznego. Wysokiej jakości narzędzie do badania przesiewowego hipoglikemii powinno zostać opracowane w przyszłych badaniach. ²⁷

Spójne projekty badań klinicznych, które wykorzystują standaryzowane poziomy raportowania hipoglikemii i definicje celów dotyczących czasu w zakresie docelowym, przyczynią się do dokładnej oceny ryzyka hipoglikemii u osób z cukrzycą typu 2. ²⁸

Przyszłe kierunki badań

Główne cele przyszłych badań w zakresie rokowania hipoglikemii cukrzycowej obejmują:

Opracowanie modelu uczenia maszynowego do przewidywania długoterminowych zdarzeń ciężkiej hipoglikemii u pacjentów z cukrzycą typu 2, co umożliwi pacjentom i świadczeniodawcom podjęcie odpowiednich środków ostrożności
Identyfikację najbardziej efektywnych cech do przewidywania długoterminowych zdarzeń ciężkiej hipoglikemii

²⁹

Oszacowanie długoterminowego ryzyka ciężkiej hipoglikemii dla danej osoby z cukrzycą typu 2 może dostarczyć dodatkowych kluczowych informacji, które mogłyby zmienić praktykę kliniczną po dalszej walidacji w przyszłych badaniach. ³⁰

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Materiały źródłowe

#1 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
The major cause of hypoglycemia is iatrogenic. […] Iatrogenic hypoglycemia causes recurrent morbidity in most people with T1DM and many with advanced T2DM and is sometimes fatal. […] Iatrogenic hypoglycemia is typically the result of the interplay of mild-moderate absolute therapeutic insulin excess, reduced glucose intake, exercise, increased insulin sensitivity, sleep, and existing or induced compromised physiological and behavioral defenses against falling plasma glucose concentrations in T1DM and T2DM. […] Hypoglycemia may lead to cardiac arrhythmias, especially in patients with preexisting cardiac abnormalities. […] Furthermore, severe hypoglycemia has been associated with increased risk of death extending many months and up to one year after the sentinel episode. […] Overall, for a given individual, iatrogenic hypoglycemia is less frequent in T2DM.
#2 Prediction Models for Prognosis of Hypoglycemia in Patients with Diabetes: A Systematic Review and Meta-Analysis – PubMed
https://pubmed.ncbi.nlm.nih.gov/35839096/
Objective: To systematically summarize the reported prediction models for hypoglycemia in patients with diabetes, compare their performance, and evaluate their applicability in clinical practice. […] The existing predictive models are not recommended for widespread clinical use. A high-quality hypoglycemia screening tool should be developed in future studies.
#3 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
The major cause of hypoglycemia is iatrogenic. […] Iatrogenic hypoglycemia causes recurrent morbidity in most people with T1DM and many with advanced T2DM and is sometimes fatal. […] Iatrogenic hypoglycemia is typically the result of the interplay of mild-moderate absolute therapeutic insulin excess, reduced glucose intake, exercise, increased insulin sensitivity, sleep, and existing or induced compromised physiological and behavioral defenses against falling plasma glucose concentrations in T1DM and T2DM. […] Hypoglycemia may lead to cardiac arrhythmias, especially in patients with preexisting cardiac abnormalities. […] Furthermore, severe hypoglycemia has been associated with increased risk of death extending many months and up to one year after the sentinel episode. […] Overall, for a given individual, iatrogenic hypoglycemia is less frequent in T2DM.
#4 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
There are many misconceptions about the prevalence and effects of hypoglycemia in people with type 2 diabetes (T2D), including hypoglycemia does not occur or does not have adverse consequences in T2D. […] Recent evidence suggests serious consequences of hypoglycemia may, in some respects, be greater in individuals with T2D, particularly regarding effects on the cardiovascular system. […] The study reported in 2007 that self-reported severe hypoglycemic episodes occurred in about 7% of the group with T2D who had been taking insulin for 2 years, a frequency comparable to the group taking sulfonylureas. […] The group with T2D taking insulin for over 5 years had a significantly higher risk of severe hypoglycemia, with around 25% reporting a severe hypoglycemic episode during the study. […] The current debate is focused on whether hypoglycemia is a risk factor, implying causality or merely a risk marker such that hypoglycemia is more common in vulnerable individuals due to frailty and comorbidity.
#5 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
The major cause of hypoglycemia is iatrogenic. […] Iatrogenic hypoglycemia causes recurrent morbidity in most people with T1DM and many with advanced T2DM and is sometimes fatal. […] Iatrogenic hypoglycemia is typically the result of the interplay of mild-moderate absolute therapeutic insulin excess, reduced glucose intake, exercise, increased insulin sensitivity, sleep, and existing or induced compromised physiological and behavioral defenses against falling plasma glucose concentrations in T1DM and T2DM. […] Hypoglycemia may lead to cardiac arrhythmias, especially in patients with preexisting cardiac abnormalities. […] Furthermore, severe hypoglycemia has been associated with increased risk of death extending many months and up to one year after the sentinel episode. […] Overall, for a given individual, iatrogenic hypoglycemia is less frequent in T2DM.
#6 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
Hypoglycemia has been found to contribute to cardiovascular and central nervous system harm in people with T2D. […] Hypoglycemia is a risk for people with T2D being treated with insulin, with reported rates of severe hypoglycemia around 2.5 events per person per year. […] An improved understanding of the barriers to accurate reporting would assist the diabetes community in estimating the frequency and severity of hypoglycemic episodes in people with T2D. […] Consistent clinical study designs that use standardized hypoglycemia reporting levels and definitions of time-in-range goals will contribute to the accurate assessment of hypoglycemic risk in people with T2D.
#7 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
There are many misconceptions about the prevalence and effects of hypoglycemia in people with type 2 diabetes (T2D), including hypoglycemia does not occur or does not have adverse consequences in T2D. […] Recent evidence suggests serious consequences of hypoglycemia may, in some respects, be greater in individuals with T2D, particularly regarding effects on the cardiovascular system. […] The study reported in 2007 that self-reported severe hypoglycemic episodes occurred in about 7% of the group with T2D who had been taking insulin for 2 years, a frequency comparable to the group taking sulfonylureas. […] The group with T2D taking insulin for over 5 years had a significantly higher risk of severe hypoglycemia, with around 25% reporting a severe hypoglycemic episode during the study. […] The current debate is focused on whether hypoglycemia is a risk factor, implying causality or merely a risk marker such that hypoglycemia is more common in vulnerable individuals due to frailty and comorbidity.
#8 Development of a model to predict 5-year risk of severe hypoglycemia in patients with type 2 diabetes | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/6/1/e000527
We constructed a predictive model of long-term risk for severe hypoglycemia (SH: hypoglycemia requiring assistance) in patients with type 2 diabetes (T2DM). […] Using this information, we derived point scores to estimate the 5-year risk for SH in individual patients with T2DM. […] After adjusting for other variables in the model, the three strongest predictors for SH over 5 years were intensive glycemic management (HR=2.37, 95%CI 1.99 to 2.83), insulin use (HR=2.14, 95% CI 1.77 to 2.59), and antihypertensive medication use (HR=1.90, 95% CI 1.26 to 2.86). […] Using the ACCORD data, we identified attributes to predict 5-year risk of SH in patients with T2DM, which warrant evaluation in broader populations to determine applicability. […] Currently, we lack a systematic method to predict the long-term SH risk in patients with T2DM.
#9 Development of a model to predict 5-year risk of severe hypoglycemia in patients with type 2 diabetes | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/6/1/e000527
Our analysis identified risk factors similar to these previous models, including prior episode of hypoglycemia, insulin use, age, and renal function, with several areas of distinction. […] Our findings demonstrate that certain baseline clinical features enhance the long-term risk for SH. […] The goal of this paper was to establish a novel prediction model for 5-year risk of SH in an individual patient with T2DM. […] We established a prediction model (c-statistic: 0.782) with Cox regression using 17 variables. […] By estimating the long-term SH risk for an individual with T2DM, these findings, after further validation with future studies, may provide additional critical information that could change clinical practice.
#10 Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset | Scientific Reports
https://www.nature.com/articles/s41598-024-69844-z
The findings indicate that the suggested multi-view co-training approach exhibits superior performance in attaining elevated levels of specificity, PPV, and overall accuracy. […] However, conventional ML algorithms surpass it in terms of sensitivity, NPV, and F1 measures when predicting SH. […] The proposed multi-view co-training method achieved two to eight times higher performance measurements in metrics such as PPV, specificity, and accuracy compared to the best supervised ML methods. […] We also identified four key features highly effective in SH prediction: fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), general diabetes education (g1diabed), and use of NPH or L Insulins (NPHL insulin).
#11 Development of a model to predict 5-year risk of severe hypoglycemia in patients with type 2 diabetes | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/6/1/e000527
We constructed a predictive model of long-term risk for severe hypoglycemia (SH: hypoglycemia requiring assistance) in patients with type 2 diabetes (T2DM). […] Using this information, we derived point scores to estimate the 5-year risk for SH in individual patients with T2DM. […] After adjusting for other variables in the model, the three strongest predictors for SH over 5 years were intensive glycemic management (HR=2.37, 95%CI 1.99 to 2.83), insulin use (HR=2.14, 95% CI 1.77 to 2.59), and antihypertensive medication use (HR=1.90, 95% CI 1.26 to 2.86). […] Using the ACCORD data, we identified attributes to predict 5-year risk of SH in patients with T2DM, which warrant evaluation in broader populations to determine applicability. […] Currently, we lack a systematic method to predict the long-term SH risk in patients with T2DM.
#12 Development of a model to predict 5-year risk of severe hypoglycemia in patients with type 2 diabetes | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/6/1/e000527
Our analysis identified risk factors similar to these previous models, including prior episode of hypoglycemia, insulin use, age, and renal function, with several areas of distinction. […] Our findings demonstrate that certain baseline clinical features enhance the long-term risk for SH. […] The goal of this paper was to establish a novel prediction model for 5-year risk of SH in an individual patient with T2DM. […] We established a prediction model (c-statistic: 0.782) with Cox regression using 17 variables. […] By estimating the long-term SH risk for an individual with T2DM, these findings, after further validation with future studies, may provide additional critical information that could change clinical practice.
#13 Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset | Scientific Reports
https://www.nature.com/articles/s41598-024-69844-z
The findings indicate that the suggested multi-view co-training approach exhibits superior performance in attaining elevated levels of specificity, PPV, and overall accuracy. […] However, conventional ML algorithms surpass it in terms of sensitivity, NPV, and F1 measures when predicting SH. […] The proposed multi-view co-training method achieved two to eight times higher performance measurements in metrics such as PPV, specificity, and accuracy compared to the best supervised ML methods. […] We also identified four key features highly effective in SH prediction: fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), general diabetes education (g1diabed), and use of NPH or L Insulins (NPHL insulin).
#14 Development and validation of a prediction model of perioperative hypoglycemia risk in patients with type 2 diabetes undergoing elective surgery | BMC Surgery | Full Text
https://bmcsurg.biomedcentral.com/articles/10.1186/s12893-022-01601-3
Our study showed an incidence of 10.7% for level 1 hypoglycemia and 1.8% for level 2 severe hypoglycemia during the perioperative period. […] The perioperative hypoglycemic risk prediction model categorizes the risk of hypoglycemia using only four predictors and shows good reliability and validity. […] The high incidence of perioperative hypoglycemia poses a major challenge for perioperative management, it is thus important and urgent to pre-assess the risk of perioperative hypoglycemia before surgery and strengthen management to reduce its incidence. […] This model includes four indicators, duration of diabetes, BMI, SDBG, and subcutaneous injection of insulin as preoperative hypoglycemic regimen. Based on this model, we further categorize patients into three risk levels: low risk, medium risk, and high-risk. […] The model serves as a favorable tool for clinicians to screen for hypoglycemic risk and guide future interventions to reduce hypoglycemia risk.
#15 Development and validation of a prediction model of perioperative hypoglycemia risk in patients with type 2 diabetes undergoing elective surgery | BMC Surgery | Full Text
https://bmcsurg.biomedcentral.com/articles/10.1186/s12893-022-01601-3
Our study showed an incidence of 10.7% for level 1 hypoglycemia and 1.8% for level 2 severe hypoglycemia during the perioperative period. […] The perioperative hypoglycemic risk prediction model categorizes the risk of hypoglycemia using only four predictors and shows good reliability and validity. […] The high incidence of perioperative hypoglycemia poses a major challenge for perioperative management, it is thus important and urgent to pre-assess the risk of perioperative hypoglycemia before surgery and strengthen management to reduce its incidence. […] This model includes four indicators, duration of diabetes, BMI, SDBG, and subcutaneous injection of insulin as preoperative hypoglycemic regimen. Based on this model, we further categorize patients into three risk levels: low risk, medium risk, and high-risk. […] The model serves as a favorable tool for clinicians to screen for hypoglycemic risk and guide future interventions to reduce hypoglycemia risk.
#16 Development and validation of a prediction model of perioperative hypoglycemia risk in patients with type 2 diabetes undergoing elective surgery | BMC Surgery | Full Text
https://bmcsurg.biomedcentral.com/articles/10.1186/s12893-022-01601-3
Our study showed an incidence of 10.7% for level 1 hypoglycemia and 1.8% for level 2 severe hypoglycemia during the perioperative period. […] The perioperative hypoglycemic risk prediction model categorizes the risk of hypoglycemia using only four predictors and shows good reliability and validity. […] The high incidence of perioperative hypoglycemia poses a major challenge for perioperative management, it is thus important and urgent to pre-assess the risk of perioperative hypoglycemia before surgery and strengthen management to reduce its incidence. […] This model includes four indicators, duration of diabetes, BMI, SDBG, and subcutaneous injection of insulin as preoperative hypoglycemic regimen. Based on this model, we further categorize patients into three risk levels: low risk, medium risk, and high-risk. […] The model serves as a favorable tool for clinicians to screen for hypoglycemic risk and guide future interventions to reduce hypoglycemia risk.
#17 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
The major cause of hypoglycemia is iatrogenic. […] Iatrogenic hypoglycemia causes recurrent morbidity in most people with T1DM and many with advanced T2DM and is sometimes fatal. […] Iatrogenic hypoglycemia is typically the result of the interplay of mild-moderate absolute therapeutic insulin excess, reduced glucose intake, exercise, increased insulin sensitivity, sleep, and existing or induced compromised physiological and behavioral defenses against falling plasma glucose concentrations in T1DM and T2DM. […] Hypoglycemia may lead to cardiac arrhythmias, especially in patients with preexisting cardiac abnormalities. […] Furthermore, severe hypoglycemia has been associated with increased risk of death extending many months and up to one year after the sentinel episode. […] Overall, for a given individual, iatrogenic hypoglycemia is less frequent in T2DM.
#18 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. […] The prevention of hypoglycemia can be viewed as a process with four steps. […] The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin. […] The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia. […] In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels 70 mg/dL (3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia.
#19 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
There are many misconceptions about the prevalence and effects of hypoglycemia in people with type 2 diabetes (T2D), including hypoglycemia does not occur or does not have adverse consequences in T2D. […] Recent evidence suggests serious consequences of hypoglycemia may, in some respects, be greater in individuals with T2D, particularly regarding effects on the cardiovascular system. […] The study reported in 2007 that self-reported severe hypoglycemic episodes occurred in about 7% of the group with T2D who had been taking insulin for 2 years, a frequency comparable to the group taking sulfonylureas. […] The group with T2D taking insulin for over 5 years had a significantly higher risk of severe hypoglycemia, with around 25% reporting a severe hypoglycemic episode during the study. […] The current debate is focused on whether hypoglycemia is a risk factor, implying causality or merely a risk marker such that hypoglycemia is more common in vulnerable individuals due to frailty and comorbidity.
#20 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
Hypoglycemia has been found to contribute to cardiovascular and central nervous system harm in people with T2D. […] Hypoglycemia is a risk for people with T2D being treated with insulin, with reported rates of severe hypoglycemia around 2.5 events per person per year. […] An improved understanding of the barriers to accurate reporting would assist the diabetes community in estimating the frequency and severity of hypoglycemic episodes in people with T2D. […] Consistent clinical study designs that use standardized hypoglycemia reporting levels and definitions of time-in-range goals will contribute to the accurate assessment of hypoglycemic risk in people with T2D.
#21 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. […] The prevention of hypoglycemia can be viewed as a process with four steps. […] The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin. […] The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia. […] In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels 70 mg/dL (3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia.
#22 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. […] The prevention of hypoglycemia can be viewed as a process with four steps. […] The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin. […] The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia. […] In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels 70 mg/dL (3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia.
#23 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. […] The prevention of hypoglycemia can be viewed as a process with four steps. […] The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin. […] The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia. […] In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels 70 mg/dL (3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia.
#24 Hypoglycemia During Therapy of Diabetes – Endotext – NCBI Bookshelf
https://www.ncbi.nlm.nih.gov/books/NBK279100/
Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. […] The prevention of hypoglycemia can be viewed as a process with four steps. […] The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin. […] The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia. […] In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels 70 mg/dL (3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia.
#25 Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset | Scientific Reports
https://www.nature.com/articles/s41598-024-69844-z
Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. […] Accurate prediction of SH remains challenging due to its multifaced nature, contributed from factors such as medications, lifestyle choices, and metabolic measurements. […] One critical area of risk prediction is the estimation of SH in diabetes, as it is marked by the need for immediate medical assistance and it is believed to be a strong risk factor of long-term mortality. […] Therefore, predicting SH risks in advance is important to prevent future heart attacks and take precautions against the resulting impact. […] The primary objectives of this study are: (i) to develop a ML model for predicting long-term SH events in patients with T2DM, which will enable patients and healthcare providers to take appropriate precautions; and (ii) to identify the most effective features for predicting long-term SH events.
#26 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
Hypoglycemia has been found to contribute to cardiovascular and central nervous system harm in people with T2D. […] Hypoglycemia is a risk for people with T2D being treated with insulin, with reported rates of severe hypoglycemia around 2.5 events per person per year. […] An improved understanding of the barriers to accurate reporting would assist the diabetes community in estimating the frequency and severity of hypoglycemic episodes in people with T2D. […] Consistent clinical study designs that use standardized hypoglycemia reporting levels and definitions of time-in-range goals will contribute to the accurate assessment of hypoglycemic risk in people with T2D.
#27 Prediction Models for Prognosis of Hypoglycemia in Patients with Diabetes: A Systematic Review and Meta-Analysis – PubMed
https://pubmed.ncbi.nlm.nih.gov/35839096/
Objective: To systematically summarize the reported prediction models for hypoglycemia in patients with diabetes, compare their performance, and evaluate their applicability in clinical practice. […] The existing predictive models are not recommended for widespread clinical use. A high-quality hypoglycemia screening tool should be developed in future studies.
#28 Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/8/1/e001194
Hypoglycemia has been found to contribute to cardiovascular and central nervous system harm in people with T2D. […] Hypoglycemia is a risk for people with T2D being treated with insulin, with reported rates of severe hypoglycemia around 2.5 events per person per year. […] An improved understanding of the barriers to accurate reporting would assist the diabetes community in estimating the frequency and severity of hypoglycemic episodes in people with T2D. […] Consistent clinical study designs that use standardized hypoglycemia reporting levels and definitions of time-in-range goals will contribute to the accurate assessment of hypoglycemic risk in people with T2D.
#29 Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset | Scientific Reports
https://www.nature.com/articles/s41598-024-69844-z
Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. […] Accurate prediction of SH remains challenging due to its multifaced nature, contributed from factors such as medications, lifestyle choices, and metabolic measurements. […] One critical area of risk prediction is the estimation of SH in diabetes, as it is marked by the need for immediate medical assistance and it is believed to be a strong risk factor of long-term mortality. […] Therefore, predicting SH risks in advance is important to prevent future heart attacks and take precautions against the resulting impact. […] The primary objectives of this study are: (i) to develop a ML model for predicting long-term SH events in patients with T2DM, which will enable patients and healthcare providers to take appropriate precautions; and (ii) to identify the most effective features for predicting long-term SH events.
#30 Development of a model to predict 5-year risk of severe hypoglycemia in patients with type 2 diabetes | BMJ Open Diabetes Research & Care
https://drc.bmj.com/content/6/1/e000527
Our analysis identified risk factors similar to these previous models, including prior episode of hypoglycemia, insulin use, age, and renal function, with several areas of distinction. […] Our findings demonstrate that certain baseline clinical features enhance the long-term risk for SH. […] The goal of this paper was to establish a novel prediction model for 5-year risk of SH in an individual patient with T2DM. […] We established a prediction model (c-statistic: 0.782) with Cox regression using 17 variables. […] By estimating the long-term SH risk for an individual with T2DM, these findings, after further validation with future studies, may provide additional critical information that could change clinical practice.