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Record W4392058432 · doi:10.1186/s13019-024-02568-3

Risk factors for postoperative delirium in elderly patients undergoing heart valve surgery with cardiopulmonary bypass

2024· article· en· W4392058432 on OpenAlexaboutno aff
Na Chen, Yunchang Mo, Min Xu, Sisi Chen, Wei Gao, Qiong Zheng, Jue Wang, Xiao-chu Wang, Junlu Wang

Bibliographic record

VenueJournal of Cardiothoracic Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
FundersWenzhou Municipal Science and Technology Bureau
KeywordsMedicineCardiac surgeryIntensive care unitDeliriumCardiopulmonary bypassCardiothoracic surgeryMechanical ventilationAnesthesiaSurgeryInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Background The aim of this study was to identify the risk factors for postoperative delirium (POD) in elderly patients undergoing heart valve surgery with cardiopulmonary bypass (CPB). Methods Elderly patients undergoing elective heart valve surgery with CPB in The First Affiliated Hospital of Wenzhou Medical University between March 2022 and March 2023 were selected for this investigation. They were divided into a POD group and a non-POD group. Their baseline information was collected and recorded, and the patients were subjected to neurocognitive function assessment using the Mini-Mental State Examination and the Montreal Cognitive Assessment scales before surgery. We also recorded their intraoperative indicators such as duration of surgery, duration of CPB, duration of aortic cross-clamp, blood transfusion, and postoperative indicators such as duration of mechanical ventilation, postoperative 24-hour drainage volume, and pain score. Regional cerebral oxygen saturation was monitored intraoperatively by near-infrared spectroscopy based INVOS5100C Regional Oximeter. Patients were assessed for the occurrence of POD using Confusion Assessment Method for the Intensive Care Unit, and logistic regression analysis of risk factors for POD was performed. Results The study finally included 132 patients, with 47 patients in the POD group and 85 ones in the non-POD group. There were no significant differences in baseline information and preoperative indicators between the two groups. However, marked differences were identified in duration of surgery, duration of CPB, duration of aortic cross-clamp, duration of postoperative mechanical ventilation, postoperative length of stay in cardiac intensive care unit, postoperative length of hospital stay, intraoperative blood transfusion, postoperative pain score, and postoperative 24-hour drainage volume between the two groups ( p < 0.05). Additionally, the two groups had significant differences in rScO 2 at each intraoperative time point and in the difference of rScO 2 from baseline at each intraoperative time point ( p < 0.05). Multivariate logistic regression analysis showed that duration of surgery > 285 min (OR, 1.021 [95% CI, 1.008–1.035]; p = 0.002), duration of postoperative mechanical ventilation > 23.5 h (OR, 6.210 [95% CI, 1.619–23.815]; p = 0.008), and postoperative CCU stay > 3.5 d (OR, 3.927 [95% CI, 1.046–14.735]; p = 0.043) were independent risk factors of the occurrence of POD while change of rScO 2 at T 1 >50.5 (OR, 0.832 [95% CI 0.736–0.941]; p = 0.003) was a protective factor for POD. Conclusion Duration of surgery duration of postoperative mechanical ventilation and postoperative CCU stay are risk factors for POD while change of rScO 2 at T 1 is a protective factor for POD in elderly patients undergoing heart valve surgery with CPB.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.287
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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