SERUM ZINC LEVELS AS A PREDICTOR OF MORTALITY IN UNDER 5 CHILDREN WITH PNEUMONIA
Bibliographic record
Abstract
Objectives: 1.To assess the reliability of serum Zinc levels as predictor of mortality in children with Pneumonia; 2. and to compare serum Zinc levels in pneumonia and severe pneumonia. Method: It is a prospective observational study that included all children aged 2 months to 59 months with features of pneumonia or severe pneumonia as per the Revised WHO guidelines 2014 for paediatric pneumonia. Serum Zinc levels were measured in all children included in the study, whereas the PRISM 3 scoring system was applied only to children with Severe disease who were admitted to the PICU. Serum Zinc levels of < 80mcg/dl suggested Zinc deficiency. All children were followed up for the predefined primary outcomes – Discharge/ Death. The association of low serum Zinc levels in severe pneumonia and the accuracy of Serum Zinc levels in predicting mortality was assessed using appropriate statistical methods. Results: Of the 100 children enrolled in the study, 54% were <1 year of age, with a slight male preponderance in incidence of pneumonia. 54% of included children had features suggestive of severe pneumonia at admission. Case fatality rates were 0% in the pneumonia group and 22.4% in the severe pneumonia group. The mean Serum Zinc levels were 82.81 +/- 19.989 mcg/dl in the pneumonia group and 71.98 +/- 26.605 mcg/dl in the severe pneumonia group(p = 0.029). The mean PRISM 3 score was 25.92(SD 3.715) in the mortality group whereas it was 1.56 (SD 7.216) in the discharge group (p = <0.001).There was a strong negative correlation ( r of - 0.708) between Serum Zinc levels and the PRISM 3 score. PRISM 3 had an Area Under Curve (AUC) of 0.993 (95% CI of 0.925 to 1.000) whereas Serum Zinc had AUC of 0.958 (95% CI of 0.870 to 0.993) with a sensitivity of 92.31%, specificity of 91.95%, PPV of 63.2% and NPV of 98.8% in predicting mortality in childhood pneumonia. Conclusion: Serum Zinc levels can be a simple test to predict mortality in children with pneumonia .
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".