Acute Kidney Injury in Pregnancy: The Need for Higher Awareness. A Pragmatic Review Focused on What Could Be Improved in the Prevention and Care of Pregnancy-Related AKI, in the Year Dedicated to Women and Kidney Diseases
Bibliographic record
Abstract
Pregnancy-related acute kidney injury (pAKI), preeclampsia (PE), and the hypertensive disorders of pregnancy are closely related conditions, which are, in turn, frequently linked to pre-existing and often non-diagnosed chronic kidney disease (CKD). The current literature and research mainly underline the effects of pregnancy complications on the offspring; this review strongly emphasizes the maternal health as well. These conditions not only negatively affect pregnancy outcomes, but have a relevant effect on the future health of affected mothers and their children. Therefore, dedicated diagnostic and follow-up programs are needed, for optimizing materno-foetal health and reducing the impact of pregnancy-related problems in the mothers and in the new generations. This narrative review, performed on the occasion of the 2018 World Kidney Day dedicated to women's health, focuses on three aspects of the problem. Firstly, the risk of AKI in the hypertensive disorders of pregnancy (the risk is the highest in developing countries; however PE is the main cause of pregnancy related AKI worldwide). Secondly, the effect of AKI and the hypertensive disorders of pregnancy on the development of CKD in the mother and offspring: long-term risks are increased; the entity and the trajectories are still unknown. Thirdly, the role of CKD in the pathogenesis of AKI and the hypertensive disorders of pregnancy: CKD is a major risk factor and the most important element in the differential diagnosis; pregnancy is a precious occasion for early diagnosis of CKD. Higher awareness on the importance of AKI in pregnancy is needed to improve short and long term outcomes in mothers and children.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".