Incidence and Risk Factors for Hypertension among Children with Nephrotic Syndrome.
Bibliographic record
Abstract
Objectives To determine incidence and risk factors for hypertension in childhood nephrotic syndrome.Study Design Using data from the Insight into Nephrotic Syndrome (INSIGHT) study, a prospective observational childhood nephrotic syndrome cohort from Toronto, Canada, we evaluated hypertension incidence and time-to-hypertension overall and stratified by 1) steroid-resistance or steroid-sensitivity, and 2) frequently-relapsing, steroid dependent, or infrequently-relapsing. Hypertension was defined as stage 1-2 hypertensive blood pressure on two consecutive visits or anti-hypertensive medication initiation.Results We included 748 children with nephrotic syndrome from 1996 to 2023. Median (quartile 1-3 [Q1-3]) age at diagnosis was 4 (2.8-6) years, 473 (63%) children were male, and 240 (32%) were of South Asian ethnicity. Forty (5%) children were steroid-resistant, 177 (24%) steroid-dependent, 113 (15%) frequently-relapsing, and 418 (56%) infrequently-relapsing. Median follow-up was 5.2 years (Q1-3 3.0-9.3). During follow-up, 393 (53%) children developed hypertension or were initiated on an anti-hypertensive medication (incidence rate 8.2 per 100 person-years, 95%CI 7.4-9.1). Hypertension was more common among children steroid-resistance than steroid-sensitivity (70% vs. 52%; adjusted HR 1.47, 95%CI 1.00-2.17). Hypertension was also more common in children who were steroid-dependent (67%; adjusted HR 1.81, 95%CI 1.43-2.30) and frequently-relapsing (63%; adjusted HR 1.64, 95%CI 1.23-2.18), than infrequently-relapsing (42%). Among steroid-sensitive patients, higher BMI Z-score and academic center were also significant hypertension risk factors.Conclusions Half of children with nephrotic syndrome develop hypertension. Children who are steroid-resistant, steroid-dependent, frequently-relapsing or have obesity are at greatest risk. Close blood pressure surveillance is justified to identify and treat hypertension.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".