Effect of Daytime Variation on PPCs in Lung Resection Surgery.

Overview

The aim of this retrospective study was to evaluate the association between daytime variation in surgery start time and the occurrence of postoperative pulmonary complications (PPCs) and postoperative adverse events (AEs) in patients who underwent lung resection under general anaesthesia.

The study included a total of 1138 patients who underwent lung resection in investigators's hospital from 2017 to 2022. Patients who underwent surgery between 7 and 11 ante meridiem (AM) versus between 12 and 5 post meridiem (PM) were compared regarding the incidence of PPCs and postoperative AEs. The patients' data were obtained from the electronic surgical case system and intraoperative anaesthesia records by professionals in the Big Data Center of the First Affiliated Hospital of Shandong First Medical University. Using medical record numbers and dates of surgery, investigators collected the following information: sex, age, height, weight, American Society of Anesthesiologists classification, complications, anesthesia and surgery duration, postoperative analgesia, type of operation, selective surgery, intraoperative blood transfusion, progress notes, postoperative imaging (e.g., chest X-ray, computed tomography) and related laboratory test results. Patients were stratified by morning or afternoon surgery. All data analyses were performed using open source statistical computing software (R, version 4.1.2; www.r-project.org). Categorical variables were expressed as frequencies and percentages, and comparisons between groups were performed using either the X² or Fisher's exact tests. Continuous variables were expressed as mean±standard deviation or median \[interquartile range\] according to whether the data conformed to a normal distribution. The independent samples t-test was used for comparisons between groups for normally distributed data, and the Mann--Whitney U test was used for non-normally distributed data. By convention, two-sided statistical significance was assumed, with P\<0.05. For variables with a missing data rate of \< 25% , investigators used multiple imputations by chained equations to meet the statistical requirements. To check the consistency of the findings, co-variate balancing propensity score matching was performed. In the propensity score matching, investigators used nearest neighbour matching with a specified caliper distance (0.25) to minimise the potential impact of differences in the baseline variables on the endpoints. In accordance with the Assess Respiratory Risk in Surgical Patients in Catalonia system, patients in the morning surgery group were matched 1:1 with patients in the afternoon surgery group regarding age, weight, American Society of Anesthesiologists classification, smoking, chronic obstructive pulmonary disease, hypertension, coronary heart disease, preoperative anaemia, diabetes, type of surgery, duration of surgery, selective surgery, and intraoperative blood transfusion. Investigators also performed a sensitivity analysis according to the department of presentation (Thoracic Surgery I and Thoracic Surgery II) and type of surgery to verify the robustness of the statistical analysis results.

Conditions

Eligibility

Locations (1)

Outcomes