Low preoperative estimated glomerular filtration rate level is a risk factor for postoperative cognitive dysfunction in elderly undergoing elective total hip replacement: a prospective observational study
Bibliographic record
Abstract
BACKGROUND: Postoperative cognitive dysfunction (POCD) is a postoperative complication of the central nervous system, especially in elderly patients. Growing evidence shows a close relationship between the kidney and cognition. This study aimed to evaluate the relationship between the subsequent risk of POCD and indicators related to the kidney. METHODS: A total of 93 eligible patients (≥65 years old) undergoing elective total hip replacement were enrolled. Before and 1 day after surgery, blood samples were collected from enrolled patients. Mini-Mental State Examination and Montreal Cognitive Assessment were conducted 1 day before surgery and 1 week after surgery or at discharge. The receiver operating characteristic curve was used to examine the predictive value of the estimated glomerular filtration rate (eGFR) for POCD. Univariate and multiple logistic regression models were used to analyze the risk factors of POCD. RESULTS: Thirty patients (32.26%) were assessed for POCD 1 week after surgery. The preoperative eGFR level in the POCD group was significantly lower than in the non-POCD group (P < 0.001). The area under the curve of eGFR was 0.739 (95% CI, 0.630-0.848; P < 0.001). The multivariable logistic regression analysis results showed that preoperative eGFR was independently associated with POCD (odds ratio = 0.965, 95% CI = 0.935-0.996, P = 0.028) after adjustment for mixed factors. CONCLUSION: Low eGFR is associated with an increased risk of POCD in patients undergoing elective total hip replacement surgery. Low eGFR is an effective predictor of incident POCD.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".