Incidence, Risk Factors, and Outcomes of Neonatal Renal Vein Thrombosis in Ontario: Population-Based Cohort Study
Bibliographic record
Abstract
Background There are limited data at a population level on the burden, risk factors, and long-term outcomes of neonatal renal vein thrombosis (nRVT). We conducted a population-based cohort study to understand the epidemiology and outcomes of nRVT over a 25-year period in Ontario. Methods Using linked administrative health databases, all hospitalized neonates ≤28 days born in Ontario between 1992 and 2016 with nRVT were identified. The primary outcome was to calculate the incidence of nRVT and trend over time in Ontario. We also determined the risk factors associated with nRVT as well as the risk of long-term outcomes after nRVT, including CKD, ESKD, all-cause mortality, and hypertension (HTN) compared with the healthy neonatal population without nRVT. Results The annual incidence rate of nRVT was 2.6 per 100,000 live births ( n =85). Presence of respiratory distress syndrome (OR, 8.01; 95% CI, 4.90 to 13.1), congenital heart disease (OR, 9.1; 95% CI, 5.05 to 16.4), central venous catheterization (OR, 3.9; 95% CI, 1.89 to 7.93), maternal preeclampsia (OR, 2.8; 95% CI, 1.6 to 4.79), and maternal diabetes (OR, 2.36; 95% CI, 1.36 to 4.07) conferred the highest risk for nRVT. Over a median follow-up of 15 years and after adjusting for confounders, neonates with nRVT versus the comparator cohort had a 15.5-fold risk of CKD, HTN, or death ( n =49 [58%] versus n =90,050 [3%]; 95% CI, 11.7 to 20.6); 12.3-fold increased risk of CKD or death ( n =39 [46%] versus n =32,016 [1%]; 95% CI, 8.9 to 16.8); and a 15.7-fold increased risk of HTN ( n =33 [39%] versus n =64,458 [2%]; 95% CI, 11.1 to 21.1). None of the nRVT cohort developed ESKD. The median time to composite outcome of CKD, HTN, or death was 11.1 years. Conclusions Patients with a history of nRVT remain at higher risk than the general population for long-term morbidity or mortality, indicating the need for long-term follow-up.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".