Neutrophil–lymphocyte ratio as an early predictor for patients with acute paraquat poisoning
Bibliographic record
Abstract
This retrospective study aimed to investigate whether the neutrophil-lymphocyte ratio (NLR) can be used as an early predictor of 90-day survival in patients with acute paraquat (PQ) poisoning.This study enrolled 105 patients with acute PQ poisoning admitted from May 2012 to May 2018. Kaplan-Meier curve, receiver operating characteristic curve, and Cox proportional hazards regression analyses were used to investigate the predictive value of NLR for 90-day survival of patients with acute PQ poisoning.The 90-day survival rate was 40.95% (43/105). Survivors had lower NLR (P <.001), which was an independent predictor of 90-day survival according to the Cox proportional hazard regression analyses. The area under the NLR curve was 0.842 (95% CI: 0.767-0.917, P <.001) in predicting 90-day survival.Our findings showed that low NLR was a valuable early predictor of 90-day survival in patients with acute PQ poisoning.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".