POSTOPERATIVE OUTCOMES IN CHRONIC DIALYSIS PATIENTS: A META‐ANALYSIS OF 42 STUDIES AND 78,805 PATIENTS
Bibliographic record
Abstract
Background: Chronic kidney disease is an independent risk factor for postoperative mortality, with an effect similar to that of diabetes mellitus or ischemic heart disease. However, the prognostic significance of dialysis‐dependence chronic kidney disease on perioperative outcomes, and its interaction with comorbid conditions is unclear. Aim: The aim of this study was to estimate the excess risk of postoperative mortality in patients receiving chronic dialysis undergoing elective non‐transplant surgery compared to those with normal kidney function, and to examine the influence on comorbidities on mortality risk. Methods: Two authors independently performed a systematic review of studies published up to 2018 was conducted using MEDLINE, EMBASE, DARE, CDSR, NICE, NIHR HTA databases. Eligible studies reported postoperative outcomes in patients on chronic dialysis and patients with normal kidney function undergoing major non‐transplant surgery. Non‐dialysis chronic kidney disease patients were excluded. Risk of bias was assessed using the Newcastle‐Ottawa Scale. Mortality risk estimates over all studies and according to surgical discipline were obtained using random effects meta‐analysis Meta‐regression analysis was performed to explore heterogeneity and assess associations of mortality with age, and comorbidities including ischemic heart disease and diabetes mellitus. (PROSPERO CRD42017076565) Results: Forty‐two studies involving 78,805 chronic dialysis and 9,984,469 non‐dialysis patients undergoing orthopaedic, vascular, cardiothoracic, general and urological procedures were included. Cohort selection and outcome ascertainment were of good quality, but comparability was poor. Absolute mortality rate varied from 0%‐8·9% in chronic dialysis patients and 0%‐3·9% in patients with normal kidney function across surgical disciplines. Patients on dialysis had a greatly increased postoperative mortality risk compared to patients with normal kidney function following all types of elective surgery (odds ratio [OR] 5·70, 95% CI 4·63 – 7·01). Adjustment for age and comorbidity attenuated this risk (OR 3·13, 95% CI 2·91 ‐ 3·34 I 290%). There was an inverse linear relationship between excess mortality risk and study‐level mean age (slope ‐0·06; P = 0·001), diabetes prevalence (slope ‐0·02; p = 0·001) and ischemic heart disease (slope ‐0·01; p = 0·049). Conclusions: Patients on chronic dialysis have a greatly increased postoperative mortality risk following elective surgery across all surgical disciplines, with the highest excess risk observed in those without other comorbidities. A comprehensive perioperative risk assessment and risk mitigation is required in patients on chronic dialysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.037 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".