Prevalence and correlates of cognitive impairment in schizophrenia: a cross-sectional study from a teaching hospital southern Sri Lanka
Bibliographic record
Abstract
INTRODUCTIONS: This study assessed the prevalence of cognitive impairment, the degree of impairment in individual cognitive domains and sociodemographic and clinical correlates among patients attending to psychiatry clinics at Teaching Hospital, Karapitiya, Sri Lanka. METHODS: A cross-sectional study was carried out at the psychiatry outpatient clinics of Teaching Hospital, Karapitiya, Sri Lanka. Their cognitive functions were assessed using the culturally validated Sinhala version of Addenbrooke's Cognitive Examination - III (ACE-III-S). ACE-III-S score below 85.5 was considered as significant cognitive impairment. Linear regression analysis was used to assess the factors associated with cognitive impairment. A P value of 0.05 is considered significant. RESULTS: One hundred forty patients with schizophrenia were assessed. Of this, 125 patients had significant cognitive impairment with a prevalence of 89.3% (95% CI:84.1-94.5). Impairment in each cognitive domain was as follows: 60% in attention, 65.7% in memory, 55% in fluency, 61.4% in language, and 63.6% in visuospatial skills. Impairment was not different between cognitive domains. Advancing age (P < 0.001), shorter duration of formal education (P = < 0.001), longer duration of illness (P = < 0.001) and not having a full-time employment (P = 0.020) showed a positive association with cognitive impairment. CONCLUSIONS: Nine out of ten patients with schizophrenia experienced significant cognitive impairment. Patients showed more than 50% impairment in all cognitive domains. The cognitive domains did not show disproportionate impairment. This study highlights the importance of introducing routine cognitive assessment protocols in patients with schizophrenia.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".