Urinary KIM-1 is not correlated with gestational age among 5-year-old children born prematurely
Bibliographic record
Abstract
Background: Preterm birth is associated with decreased nephron endowment. Currently, there is no reliable non-invasive biomarker to identify or monitor decreased nephron number in at-risk patients. Urinary Kidney Injury Molecule-1 (KIM-1) is a biomarker of acute and chronic renal injury. We measured urinary KIM-1 among a wide array of other potential biomarkers. Methods: We conducted an ambispective cohort study of 5-years-old children born prematurely and healthy controls identified from city schools. Detailed anthropometrics, renal ultrasound dimensions, and biochemical parameters were measured. Urinary KIM-1 was measured using Luminex® technology. Age independent z-scores were calculated and compared. Spearman correlations were used for estimating the association between measures and KIM-1. Results: We enrolled 129 children, 97 (75.2%) born pre-term and 32 (24.8%) healthy controls born at full-term. Pre-term patients had significantly lower weight and body surface area than controls. Pre-term patients and controls did not differ in current age, sex, race, height, blood pressure, urinary sodium, fractional sodium excretion, serum creatinine and estimated GFR. All spearman correlation between KIM-1 and gestational age, renal and serum measurements were weak without statistical significance. Conclusion: In 5-year-old children born prematurely, KIM-1 was not correlated with gestational age. Further prospective studies need to confirm this finding.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".