Performance profile of an outcome measure: morbidity assessment index for newborns
Bibliographic record
Abstract
OBJECTIVE: Few tools have been optimised for use over the entire spectrum of neonatal morbidity and standardised for use in perinatal population and community health studies. The objective of this study was to determine the performance profile of the recently developed morbidity assessment index for newborns (MAIN score). This score was designed as a discriminative index of morbidity for the entire population of babies delivered >28 weeks gestation without a major congenital anomaly. DESIGN AND SETTING: MAIN score items were extracted retrospectively from the health records of 2892 consecutively born babies delivered beyond 28 weeks gestation in Edmonton area hospitals between June and December of 1999. MAIN RESULTS: The mean MAIN score in the general newborn population was 70.3 (95% confidence intervals 64.2 to 76.4). With the MAIN score tool, 84.6% of newborns scored from 0 to 150 (no/minimal morbidity), 11.3% from 151 to 500 (mild), 3.1% from 501 to 800 (moderate), and 1% had >800 (severe) score. The MAIN score tool was sufficiently sensitive to detect significant effects of low gestational age, low birth weight, male sex, caesarean delivery, tertiary hospital delivery, twins/triplets, non-vertex presentation, prenatal illicit drug use, and medical complications of pregnancy. CONCLUSION: The MAIN score fulfills the need for a simple, universal, yet sensitive and robust tool to provide a numerical index of early neonatal outcomes of prenatal care and adverse prenatal exposures in babies delivered beyond 28 weeks gestation. The performance of the MAIN score agrees well with the current medical awareness regarding the impact of adverse prenatal exposures on newborn morbidity.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".