Acute Kidney Injury, Fluid Overload, and Renal Replacement Therapy Differ by Underlying Diagnosis in Neonatal Extracorporeal Support and Impact Mortality Disparately
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: We aimed to characterize acute kidney injury (AKI), fluid overload (FO), and renal replacement therapy (RRT) utilization by diagnostic categories and examine associations between these complications and mortality by category. METHODS: To test our hypotheses, we conducted a retrospective multicenter, cohort study including 446 neonates (categories: 209 with cardiac disease, 114 with congenital diaphragmatic hernia [CDH], 123 with respiratory disease) requiring extracorporeal membrane oxygenation (ECMO) between January 1, 2007, and December 31, 2011. RESULTS: AKI, FO, and RRT each varied by diagnostic category. AKI and RRT receipt were most common in those neonates with cardiac disease. Subjects with CDH had highest peak %FO (51% vs. 28% cardiac vs. 32% respiratory; p < 0.01). Hospital survival was 55% and varied by diagnostic category (45% cardiac vs. 48% CDH vs. 79% respiratory; p < 0.001). A significant interaction suggested risk of mortality differed by diagnostic category in the presence or absence of AKI. In its absence, diagnosis of CDH (vs. respiratory disease) (OR 3.04, 95% CL 1.14-8.11) independently predicted mortality. In all categories, peak %FO (OR 1.20, 95% CL 1.11-1.30) and RRT receipt (OR 2.12, 95% CL 1.20-3.73) were independently associated with mortality. DISCUSSION/CONCLUSIONS: Physiologically distinct ECMO diagnoses warrant individualized treatment strategies given variable incidence and effects of AKI, FO, and RRT by category on mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it