54. The Association Between Preeclampsia and Chronic Kidney Disease: A Systematic Review
Bibliographic record
Abstract
Background: Preeclampsia is characterized by hypertension and the co-occurrence of one or more of the following symptoms, such as renal insufficiency. Renal function may also be impacted by endothelial dysfunction in Preeclampsia; a correlation has been shown between Preeclampsia and Acute Renal Dysfunction. Objective: This study aimed to examine the association, incidence rate, and risk of CKD in women who had Preeclampsia. Method: Data generated from the period of 5 years from PMC, ScienceDirect, and PubMed databases using MesH keywords “Renal Insufficiency, Chronic” and “Pre-Eclampsia”. Newcastle Ottawa Scale (NOS) was used to assess the quality of these studies. Inclusion criteria are participants who have been exposed to Preeclampsia with an outcome of CKD, and studies such as cohort, cross-sectional, and clinical trials. The exclusion criteria are systematic reviews, meta-analysis, and animal studies. Result: After reviewing 15 studies, 3 cohort studies and 1 cross sectional study were included in this study, with a total of 2,185,163 participants. All studies have demonstrated a good quality based on NOS. This study found that there was a higher chance of chronic renal disease in women who had a history of preeclampsia. The findings of research on CKD in women who have had PE are debatable due to several confounding factors. Conclusion: Women with a history of PE showed a higher risk of subsequent CKD. To validate, more thorough prospective investigations with a clear description of the severity of PE and renal illness as well as longer, sufficient follow-ups are required.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".