Correlation between preoperative sleep disorders and postoperative delayed neurocognitive recovery in elderly patients.
Bibliographic record
Abstract
OBJECTIVES: Perioperative neurocognitive disorders (PND) is one of the important factors affecting the recovery of the elderly after surgery, and sleep disorders are also one of the common diseases of the elderly. Previous studies have shown that the quality of postoperative sleep may be factor affecting postoperative cognitive function, but there are few studies on the relationship between preoperative sleep disorders and postoperative cognitive dysfunction. This study aims to explore the relationship between preoperative sleep disorders and postoperative delayed neurocognitive recovery in elderly patients, and provide references for improving the prognosis and quality of life of patients. METHODS: This study was porformed as a prospective cohort study. Elderly patients (age≥65 years old) underwent elective non-cardiac surgery at Xiangya Hospital of Central South University from October 2019 to January 2020 were selected and interviewed 1 day before the operation. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA) were used to assess the patient's baseline cognitive status. Patients with preoperative MMSE scores of less than 24 points were excluded. For patients meeting the criteria of inclusion, Pittsburgh Sleep Quality Index (PSQI) scale was used to evaluate the patients, and the patients were divided into a sleep disorder group and a non-sleep disorder group according to the score. General data of patients were collected and intraoperative data were recorded, such as duration of surgery, anesthetic time, surgical site, intraoperative fluid input, intraoperative blood product input, intraoperative blood loss and drug use. On consecutive 5 days after surgery, Numerical Rating Scale (NRS) was used to evaluate the sleep of the previous night and the pain of the day, which were recorded as sleep NRS score and pain NRS score; Confusion Assessment Method for ICU (CAM-ICU) scale and Confusion Assessment Method (CAM) scale were used to assess the occurrence of delirium. On the 7th day after the operation, the MMSE and MoCA scales were used to evaluate cognitive function of patients. We compared the incidence of postoperative complications, the number of deaths, the number of unplanned ICU patients, the number of unplanned secondary operations, etc between the 2 groups. The baseline and prognosis of the 2 groups of patients were analyzed by univariate and multivariate logistics to analyze their correlation. RESULTS: =0.039). CONCLUSIONS: Preoperative sleep disorders can increase the risk of delayed neurocognitive function recovery in elderly patients. Active treatment of preoperative sleep disorders may improve perioperative neurocognitive function in elderly patients.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".