Decrease in cognitive performance and increase of the neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios with higher doses of antipsychotics in women with schizophrenia: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: We explored the relationship between symptoms, cognitive performance, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) (three markers of inflammation), and antipsychotic dose (in chlorpromazine units) in male and female patients with schizophrenia. METHODS: We conducted a cross-sectional analysis in patients with schizophrenia of the complete blood count and the results of neuropsychological testing, using the Welch t-test to compare groups and the Pearson test for correlations. RESULTS: We found that the NLR and the PLR are higher among women with schizophrenia when compared with men. In women, the NLR and the PLR correlate positively with antipsychotic drug dose and inversely with a working memory test (Direct Digit Span). Higher doses of antipsychotics are associated with worse working and semantic memory and mental flexibility in the women in our sample. CONCLUSION: Higher doses of antipsychotics were associated with worse working and semantic memory and mental flexibility in women with schizophrenia. No such correlations were present in men, suggesting that, in female patients, cognitive performance deteriorates as the antipsychotic dose is increased, a finding that could be mediated by inflammatory mechanisms, given the demonstrated relationship to biomarkers of inflammation - e.g., the NLR and the PLR. TRIAL REGISTRATION: NCT03788759 (ClinicalTrials.gov).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".