Pregnancy Outcomes after Clinical Recovery from AKI
Bibliographic record
Abstract
The effect of clinically recovered AKI (r-AKI) on future pregnancy outcomes is unknown. We retrospectively studied all women who delivered infants between 1998 and 2007 at Massachusetts General Hospital to assess whether a previous episode of r-AKI associated with subsequent adverse maternal and fetal outcomes, including preeclampsia. AKI was defined as rise in serum creatinine concentration to 1.5-fold above baseline. We compared pregnancy outcomes in women with r-AKI without history of CKD (eGFR>90 ml/min per 1.73 m 2 before conception; n =105) with outcomes in women without kidney disease (controls; n =24,640). The r-AKI and control groups had similar prepregnancy serum creatinine measurements (0.70±0.20 versus 0.69±0.10 mg/dl; P =0.36). However, women with r-AKI had increased rates of preeclampsia compared with controls (23% versus 4%; P <0.001). Infants of women with r-AKI were born earlier than infants of controls (37.6±3.6 versus 39.2±2.2 weeks; P <0.001), with increased rates of small for gestational age births (15% versus 8%; P =0.03). After multivariate adjustment, r-AKI associated with increased risk for preeclampsia (adjusted odds ratio [aOR], 5.9; 95% confidence interval [95% CI], 3.6 to 9.7) and adverse fetal outcomes (aOR, 2.4; 95% CI, 1.6 to 3.7). When women with r-AKI and controls were matched 1:2 by age, race, body mass index, diastolic BP, parity, and diabetes status, r-AKI remained associated with preeclampsia (OR, 4.7; 95% CI, 2.1 to 10.1) and adverse fetal outcomes (OR, 2.1; 95% CI, 1.2 to 3.7). Thus, a past episode of AKI, despite return to normal renal function before pregnancy, associated with adverse outcomes in pregnancy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".