Pregnancy-associated acute kidney injury as an important driver of chronic kidney disease in females in developing countries: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Pregnancy-related AKI (PR-AKI), has profound maternal and fetal implications, including high mortality and long-term risks such as the development of chronic kidney disease (CKD). This systematic review aims to evaluate the burden of CKD owing to PR-AKI cases during follow-up in developing countries, particularly India. METHODS: A systematic search of PubMed, Embase, and Cochrane databases was performed for Indian studies published between 2000 and June 2024. We included cross-sectional, retrospective, and prospective cohort studies that reported the incidence of PR-AKI, subsequent CKD, and dialysis dependency in Indian cohorts during follow-up. Details of etiology of PRAKI, and adverse fetal and maternal outcomes were also recorded. Only studies that provided follow-up kidney outcomes were considered. RESULTS: A total of 25 studies comprising 2,306 participants were included in the analysis. The incidence of PR-AKI ranged from 1 to 12% across different studies. Sepsis was the most common cause of PR-AKI, accounting for up to 78% of cases, followed by hypertensive disorders, obstetric haemorrhage, and tropical etiologies. Hemodialysis was required in 20-85% of patients. CKD development during follow-up was observed in 12.8-35% of cases, with up to 30% remaining dialysis-dependent. Maternal mortality ranged from 2.5 to 34%, while perinatal mortality reached as high as 67.3%. Pre-term delivery rates varied between 13.9% and 58%. CONCLUSIONS: Up to one-third of PR-AKI patients may develop CKD and remain dialysis-dependent during follow-up. PR-AKI significantly impacts both maternal and fetal morbidity and mortality. Early prevention and prompt management by healthcare professionals are critical to improving outcomes in PR-AKI. Pregnancy-related acute kidney injury (PR-AKI) significantly affects maternal and fetal health, leading to high mortality and long-term complications such as chronic kidney disease (CKD). This systematic review, focusing on developing countries like India, evaluated the burden of CKD due to PR-AKI patients. The review analyzed Indian studies published between 2000 and June 2024, including 25 studies with 2,306 participants. PR-AKI incidence ranged from 1 to 12%, with sepsis being the leading cause in up to 78% of cases, followed by hypertensive disorders, obstetric hemorrhage, and tropical fevers. RRT was needed in 20-85% of patients, and 12.8-35% developed CKD during follow-up, with up to 30% remaining dialysis-dependent. Maternal mortality varied from 2.5 to 34%, while perinatal mortality reached 67.3%. The study emphasizes the critical need for early prevention timely intervention and need for long-term follow-up to reduce the high morbidity and mortality rates associated with PR-AKI.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".