Pre-eclampsia is a valuable opportunity to diagnose chronic kidney disease: a multicentre study
Bibliographic record
Abstract
BACKGROUND: Pre-eclampsia (PE) and chronic kidney disease (CKD) are known to be associated. Our objective was to assess the prevalence of CKD in a large multicentre cohort of women without acknowledged CKD who experienced a PE episode. METHODS: The setting for the study was France (Le Mans, Central France) and Italy (Cagliari, Sardinia). The study participants were patients who experienced PE in 2018-19, identified from the obstetric charts. Patients with known-acknowledged CKD were excluded. Only singletons were considered. Persistent (micro)albuminuria was defined as present and confirmed at least 3 months after delivery. CKD was defined according to the Kidney Disease Outcomes Quality Initiative guidelines; urinary alterations or low eGFR confirmed at a distance of at least 3 months, or morphologic changes. Patients were divided into four groups: evidence of CKD; no evidence of CKD; unclear diagnosis-ongoing work-up; or persistent microalbuminuria. The outcome 'diagnosis of CKD' was analysed by simple and multiple logistic regressions. Temporal series (week of delivery) were analysed with Kaplan-Meier curves and Cox analysis. RESULTS: Two hundred and eighty-two PE pregnancies were analysed (Le Mans: 162; Cagliari: 120). The incidence of CKD diagnosis was identical (Le Mans: 19.1%; Cagliari: 19.2%); no significant difference was found in unclear-ongoing diagnosis (6.2%; 5.8%) and microalbuminuria (10.5%; 5.8%). Glomerulonephritis and diabetic nephropathy were more frequent in Cagliari (higher age and diabetes prevalence), and interstitial diseases in Le Mans. In the multivariate logistic regression, CKD diagnosis was associated with preterm delivery (adjusted P = 0.035). Gestation was 1 week shorter in patients diagnosed with CKD (Kaplan-Meier P = 0.007). In Cox analysis, CKD remained associated with shorter gestation after adjustment for age and parity. CONCLUSIONS: The prevalence of newly diagnosed CKD is high after PE (19% versus expected 3% in women of childbearing age), supporting a systematic nephrology work-up after PE.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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, 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".