Rate of and time to symptomatic remission in first-episode psychosis in Northern Malawi
Bibliographic record
Abstract
Although longer duration of untreated psychosis (DUP) is associated with poor response to antipsychotic treatment, it remains unclear whether it independently influences time to symptomatic remission in first-episode psychosis (FEP). This study examined rate of symptomatic remission, and explored if DUP, premorbid functioning, global functioning, insight and socio-demographic characteristics were independently associated with time to symptomatic remission in FEP.This prospective study enrolled 126 FEP patients (aged 18-65) between June 2009 and September 2012. Subjects were followed-up monthly over 18 months after they had received antipsychotic medication. Remission in positive and negative symptoms was defined as in the Remission in Schizophrenia Working Group (RSWG) criteria. Subjects were defined as "in symptomatic remission" if they remitted in both negative and positive symptoms. At baseline, the following explanatory variables were measured: socio-demographic characteristics; DUP as short (≤5 months) and long (>5 months); premorbid functioning as deteriorating, stable poor, and stable good according to Cannon-Spoor Premorbid Adjustment Scale; global functioning as "worst (1-10) to serious (41-50)" and "moderate (51-60) to superior (91-100)," according to the Global Assessment of Functioning Scale; and insight as poor (≤8) and good (≥9) according to the Insight Scale (Birchwood). Univariate and multivariable analyses were used to generate results.Out of 126 subjects, 98 (78%) completed follow-up, of which 70 (71.4%) achieved symptomatic remission within mean duration of 8.05 (4.54) months. Besides, having long DUP and separated/divorced/widowed (adjusted hazard ratio [aHR] = 0.07, 95%CI = [0.01, 0.46]), long DUP and poor insight (aHR = 0.18, 95%CI = [0.04, 0.89]), poor insight and separated/divorced/widowed (aHR = 0.09, 95%CI = [0.01, 0.70]), deteriorating premorbid functioning (aHR = 0.47, 95%CI = [0.23, 0.97]), family history of psychiatric disorders (aHR = 0.52, 95%CI = (0.30, 0.93]), and being male (aHR = 0.47, 95%CI = [0.24, 0.92]) delayed symptomatic remission.These results propose that psychological interventions and social support for mental health problems are warranted and may enhance better response to antipsychotic medications among separated/divorced/widowed patients with long DUP or poor insight, and poor insight patients with long DUP. Deteriorating premorbid functioning, family history of psychiatric disorders and being male continue being important risk factors for poor odds of remission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".