Materiały źródłowe

• #1 Azthena logo with the word Azthena

  https://www.news-medical.net/health/Schizophrenia-Prognosis.aspx

  There is currently no known cure for schizophrenia and a full recovery from schizophrenia is unusual, with only approximately 15% returning to previous functioning capabilities. […] However, most individuals with the condition are able to live a meaningful and satisfying life, in the presence or absence of symptoms. […] Patients with schizophrenia are subjected to a slightly higher rate of mortality, which is 1.6 times higher than that of the general population. […] Suicide also plays a major role as suicide by patients with schizophrenia is nine times more likely than in people that are not affected by the condition. The lifetime risk of suicide for patients is 5%. […] Treatments are available that can help to reduce the symptoms of schizophrenia and decrease the number and duration of psychotic episodes.

• #2 Schizophrenia outcomes in the 21st century: A systematic review

  https://pmc.ncbi.nlm.nih.gov/articles/PMC8213926/

  We report a review of outcomes in schizophrenia in the twentyfirst century, replicating and extending work undertaken by the late Richard Warner in his seminal book, Recovery from Schizophrenia: Psychiatry and Political Economy (1985;2004). […] Overall, complete recovery is higher in this study than in Warner’s (37.75% cf 20.4%), especially for first episode psychosis (FEP) (57.1% cf 20.7%). […] Future research strategies should aim to reduce heterogeneity in clinical outcome measures and to increase the emphasis on capture and reporting of more sophisticated measures of social and functional outcome. […] This review of 21st century studies tends to confirm one of Warner’s key assertions that a significant proportion of people who receive a schizophrenia diagnosis make a good recovery.

• #3 Schizophrenia outcomes in the 21st century: A systematic review

  https://pmc.ncbi.nlm.nih.gov/articles/PMC8213926/

  While we have found that rates of complete recovery have increased substantially for people experiencing a first episode of psychosis in the 21st century, not all of our findings are positive. […] Comparison of our findings and Warner’s original findings shows significant improvements in rates of recovery FEP, with more disappointing results for MEP, especially post2008.

• #4 Schizophrenia Prognosis, Outlook, and Chances of Recovery

  https://www.webmd.com/schizophrenia/schizophrenia-outlook

  If you have schizophrenia, there is much reason for hope. Improvement and recovery happen with continued treatment. […] The earlier you get help, the better your outcome. With treatment, many recover to the point of living functional, rewarding lives in their communities. […] Ten years after diagnosis: 50% of people with schizophrenia recover or improve to the point they can work and live on their own. […] The lifetime risk of suicide for people with schizophrenia is about 5%, but getting treatment and taking medication seem to lower that risk. […] The sooner you’re treated for schizophrenia once symptoms begin, the more likely you are to improve and recover.

• #5 Azthena logo with the word Azthena

  https://www.news-medical.net/health/Schizophrenia-Prognosis.aspx

  Patients that use recreational drugs or smoke cigarettes have a poorer prognosis due to the effect of these substances on brain pathways and mental function. […] There are some particular factors that are associated with a better prognosis. […] Many patients with schizophrenia, particularly those with an insufficient support system, have difficulty coping in society and securing employment. […] It is essential that schizophrenic patients be offered adequate support and counseling to help them to integrate into society. […] With the appropriate management, most patients can improve significantly and many can become entirely independent when they have learned how to manage their symptoms.

• #6 Prognosis of schizophrenia – Wikipedia

  https://en.wikipedia.org/wiki/Prognosis_of_schizophrenia

  The prognosis of schizophrenia is varied at the individual level. In general it has great human and economics costs. It results in a decreased life expectancy of 12-15 years primarily due to its association with obesity, little exercise, and smoking, while an increased rate of suicide plays a lesser role. These differences in life expectancy increased between the 1970s and 1990s, and between the 1990s and 2000s. This difference has not substantially changed in Finland for example where there is a health system with open access to care. […] Schizophrenia is a major cause of disability. Approximately three quarters of people with schizophrenia have ongoing disability with relapses. Still some people do recover completely and additional numbers function well in society. […] Most people with schizophrenia live independently with community support. In people with a first episode of psychosis a good long-term outcome occurs in 42% of cases, an intermediate outcome in 35% of cases, and a poor outcome in 27% of cases. Outcome for schizophrenia appear better in the developing than the developed world. These conclusions however have been questioned.

• #7 Prognosis of schizophrenia – Wikipedia

  https://en.wikipedia.org/wiki/Prognosis_of_schizophrenia

  Several factors have been associated with a better overall prognosis: Being female, rapid (vs. insidious) onset of symptoms, older age of first episode, predominantly positive (rather than negative) symptoms, presence of mood symptoms, and good pre-illness functioning. The strengths and internal resources of the individual concerned, such as determination or psychological resilience, have also been associated with better prognosis. […] The attitude and level of support from people in the individual’s life can have a significant impact; research framed in terms of the negative aspects of this—the level of critical comments, hostility, and intrusive or controlling attitudes, termed high 'expressed emotion’—has consistently indicated links to relapse.

• #8 Duration of untreated psychosis as predictor of long-term outcome in schizophrenia: systematic review and meta-analysis | The British Journal of Psychiatry | Cambridge Core

  https://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/duration-of-untreated-psychosis-as-predictor-of-longterm-outcome-in-schizophrenia-systematic-review-and-metaanalysis/7C07B20A83CE7224E56036023D7E54CF

  Duration of untreated psychosis (DUP) is one of the few potentially modifiable predictors of outcomes of schizophrenia. Long DUP correlated statistically significantly with poor general symptomatic outcome, more severe positive and negative symptoms, lesser likelihood of remission and poor social functioning and global outcome. The small but mostly consistent correlation between long DUP and poor outcome indicates that early intervention in psychosis may have at least subtle positive effects on the long-term course of illness. […] The long-term consequences of prolonged untreated psychosis are unclear, with no previous systematic meta-analysis with a wide perspective of outcomes focusing also on the length of follow-up. Our hypothesis was that long DUP associates with poor long-term clinical and social outcomes.

• #9 Azthena logo with the word Azthena

  https://www.news-medical.net/health/Schizophrenia-Prognosis.aspx

  Management of schizophrenia includes a combination of pharmaceutical treatment and counseling. […] Adequate control of the disorder with these methods has led to the majority of patients improving symptoms to be able to function independently, ten years following diagnosis. […] Positive symptoms tend to respond better to antipsychotic medication than negative symptoms, which are more persistent. […] For this reason, patients with fewer negative symptoms tend to have a better prognosis and medication is more effective at helping them to live normal lives. […] There are some particular factors that are associated with a poorer prognosis. […] The prevalence of substance misuse among individuals with schizophrenia is much higher than the general population, with 36% of patients reporting a problem.

• #10 Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach

  https://pmc.ncbi.nlm.nih.gov/articles/PMC8253813/

  Schizophrenia and related disorders have heterogeneous outcomes. Individualized prediction of long-term outcomes may be helpful in improving treatment decisions. Utilizing extensive baseline data of 523 patients with a psychotic disorder and variable illness duration, we predicted symptomatic and global outcomes at 3-year and 6-year follow-ups. We classified outcomes as (1) symptomatic: in remission or not in remission, and (2) global outcome, using the Global Assessment of Functioning (GAF) scale, divided into good (GAF65) and poor (GAF65). Aiming for a robust and interpretable prediction model, we employed a linear support vector machine and recursive feature elimination within a nested cross-validation design to obtain a lean set of predictors. Generalization to out-of-study samples was estimated using leave-one-site-out cross-validation. Prediction accuracies were above chance and ranged from 62.2% to 64.7% (symptomatic outcome), and 63.5-67.6% (global outcome). Leave-one-site-out cross-validation demonstrated the robustness of our models, with a minor drop in predictive accuracies of 2.3% on average. Important predictors included GAF scores, psychotic symptoms, quality of life, antipsychotics use, psychosocial needs, and depressive symptoms. These robust, albeit modestly accurate, long-term prognostic predictions based on lean predictor sets indicate the potential of machine learning models complementing clinical judgment and decision-making. Future model development may benefit from studies scoping patients and clinicians’ needs in prognostication.

• #11 Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach | Schizophrenia

  https://www.nature.com/articles/s41537-021-00162-3

  Schizophrenia and related disorders have heterogeneous outcomes. Individualized prediction of long-term outcomes may be helpful in improving treatment decisions. Utilizing extensive baseline data of 523 patients with a psychotic disorder and variable illness duration, we predicted symptomatic and global outcomes at 3-year and 6-year follow-ups. Aiming for a robust and interpretable prediction model, we employed a linear support vector machine and recursive feature elimination within a nested cross-validation design to obtain a lean set of predictors. Important predictors included GAF scores, psychotic symptoms, quality of life, antipsychotics use, psychosocial needs, and depressive symptoms. These robust, albeit modestly accurate, long-term prognostic predictions based on lean predictor sets indicate the potential of machine learning models complementing clinical judgment and decision-making.

• #12 Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach

  https://pmc.ncbi.nlm.nih.gov/articles/PMC8253813/

  To the best of our knowledge, no prognostic models for the long-term global and symptomatic outcomes of psychosis are presently available. Our results indicate that while state-of-the-art methods may result in robust (generalizable) performance estimates, predictions are modestly accurate, similar to recent experimental prognostic models for depression based on machine learning predicting long-term clinical outcomes based on patient reportable data. The models did not reach the LOSO cross-validated accuracy of 71% in the study on the one-year outcome of first-episode psychosis, presumably due to the uncertainty introduced by time, care-as-usual setting, and the heterogeneity of baseline clinical status and illness duration within our target population. […] Features offering a clinicians integration of the clinical picture and those with a broad underlying construct (e.g. GAF; insight; schizophrenia diagnosis; quality of life; summed no need/met need items; depression) show to be the most important predictors. These resemble features found to be predictive of one-year outcome in first-episode psychosis: psychosocial needs, global functioning deficits, and affective symptoms.

• #13 Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach

  https://pmc.ncbi.nlm.nih.gov/articles/PMC8253813/

  Our models on long-term outcomes of psychosis perform with reasonable accuracies, but at present are not suitable as a stand-alone tool to stratify treatment. Regardless, the machine learning model trained here and a clinician would represent rather different takes on reality. The model sees the patient through the lens of a number of constructs, such as insight, whereas a clinician’s judgment is more globally constructed and starts from the moment the clinician meets his patient in the waiting room. Models with modest accuracy may be of use, depending on the level of uncertainty parties involved in clinical decision-making are willing to accept from a model, a level which to our knowledge is unknown for long-term outcomes of psychosis. […] In conclusion, we demonstrate the feasibility of a machine-learning approach to long-term outcome prediction in a heterogeneous target population of schizophrenia-spectrum patients, based on a lean set of patient reportable features, overlapping with those predictive of short-term outcome of first-episode psychosis. Future models may benefit from considering patients and clinicians needs, the appropriate nature of the training sample (i.e. sample similarity to the population of interest as well as richness on (contextual) features), and implementation of advancements in machine learning methodology. Individual outcome prediction based on machine learning may inform the treatment stratification needed both from a patient and a public health perspective.

• #14 Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning | BMC Psychiatry | Full Text

  https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-025-06888-z

  Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. […] Therefore, the detection of schizophrenia is a complex process that requires careful consideration of the patients symptoms, medical history, and physical and laboratory examinations. […] Developing robust diagnostic models, through stable biomarkers or easily obtainable characteristics would greatly alleviate the burden on physicians and patients alike. […] Speech analysis has emerged as a promising diagnostic tool for schizophrenia, as it reveals notable differences in speech patterns between patients with schizophrenia (SZ) and healthy controls (HC). […] The combination of speech analysis and machine learning has achieved some results in the medical field. […] The rise of deep learning has facilitated end-to-end automated prediction, which has gained popularity.

• #15 Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning | BMC Psychiatry | Full Text

  https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-025-06888-z

  This study provides a methodological foundation for constructing a personalized speech detection model for schizophrenia. […] The best discriminant model achieved an accuracy of 91.7%, sensitivity of 94.9%, specificity of 85.1%, and ROC-AUC of 0.963. […] The study demonstrated significant differences in speech patterns between SZ and mentally healthy individuals. […] The diagnostic accuracy of the log-Mel spectrogram analysis using a convolutional neural network ranged from 80.9% to 85.7% when considering a single emotional stimulus. […] Emotion fusion improved both sensitivity and specificity, resulting in an overall accuracy of 87.0%. […] By combining different emotional stimuli and individualized features, the diagnostic model achieved a remarkable individual-discriminative performance, with an accuracy of 91.7% and an AUC of 0.963.

• #16 Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning | BMC Psychiatry | Full Text

  https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-025-06888-z

  The inclusion of individual information in an automatic detection model can closely approximate the diagnostic approaches of professional physicians, thereby addressing the challenge of heterogeneity and facilitating rapid and comprehensive schizophrenia detection based on patients specific conditions.

• #17 Predicting Outcome in Schizophrenia: Neuroimaging and Clinical Assessments | SpringerLink

  https://link.springer.com/chapter/10.1007/978-3-030-35206-6_17

  Schizophrenia is a severe neuropsychiatric disorder accompanied by debilitating cognitive and psychosocial impairments over the course of the disease. […] Despite this obvious clinical need, studies examining predictors of long-term outcome in schizophrenia are still scarce, as they meet several obstacles, especially the need to acquire, maintain, and repeatedly assess large cohorts of patients over a longer course of time. […] Although only a few studies so far have yielded robust long-term predictors, the current literature suggests that clinical and neuropsychological parameters at first episode might provide useful markers for predicting long-term disease trajectories. […] These parameters might have the potential to be directly translatable to a clinical setting to improve prospective care and treatment planning for schizophrenia patients.

• #18 Predicting Outcome in Schizophrenia

  https://www.psychiatrictimes.com/view/predicting-outcome-schizophrenia

  Can sociodemographic and clinical variables predict outcome in cases of schizophrenia? Results from studies related to prognostic variables for schizophrenia have yielded interesting yet inconsistent results. […] Attempts to answer this question have been geared toward helping clinicians, patients, and family members have more informed expectations for the long-term prognosis. […] In this article, we review the plethora of variables implicated as having prognostic significance in schizophrenia and briefly discuss possible reasons why the literature has not yielded consistent conclusions. […] Our recent investigation attempted to minimize some of these concerns in order to further clarify the relationship between clinical and demographic variables and functional outcome. […] Analyses that incorporate the specific contributions of sociodemographic (eg, sex, age at onset, education, marriage) and clinical variables (eg, premorbid levels of functioning, treatment status, duration of illness, symptom severity, cognition) are useful in assessing functional prognosis as well as symptom progression. Such comprehensive evaluations can assist clinicians, patients, and family members in developing more informed expectations for the long-term prognosis based on presentation at intake.

• #19 Duration of untreated psychosis as predictor of long-term outcome in schizophrenia: systematic review and meta-analysis | The British Journal of Psychiatry | Cambridge Core

  https://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/duration-of-untreated-psychosis-as-predictor-of-longterm-outcome-in-schizophrenia-systematic-review-and-metaanalysis/7C07B20A83CE7224E56036023D7E54CF

  We found a significant association between long DUP and poor general symptomatic outcome, more severe positive and negative symptoms and failure to achieve remission, as well as decreased social functioning and global outcome. There was no significant correlation between DUP and employment, quality of life or hospital treatment. […] The small correlation between long DUP and poor long-term outcome indicates that early intervention and care in psychosis might have some positive effects on the long-term outcome on schizophrenia. However, drawing evidence-based clinical conclusions from analyses using natural experiments and observational designs is problematic as it is neither possible nor ethical to randomise people to different conditions regarding DUP.

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