This retrospective observational study was approved by the Ethics Committee of Anji County Hospital of Traditional Chinese Medicine (approval No. 2025-13). The requirement for written informed consent was waived by the Ethics Committee because this study used de-identified retrospective clinical data and involved no additional patient intervention. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline, and the completed STROBE checklist is provided as Supplementary File 1. The reagents, equipment, and software used are listed in the Table of Materials.
1. Study population and patient screening
Adult patients who underwent elective laparoscopic cholecystectomy at Anji County Hospital of Traditional Chinese Medicine between January 2025 and September 2025 were retrospectively screened using the hospital electronic medical record (EMR) system and anesthesia information system. The screening process is summarized in Supplementary Figure 1. A total of 132 potentially eligible patients were initially screened, and 36 were excluded according to the predefined eligibility criteria or because of incomplete key data. Finally, 96 patients were included in the final analysis, including 50 patients in the non-obese group and 46 patients in the obese group.
Patients were eligible if they met all of the following criteria: age 18–65 years; first-time elective laparoscopic cholecystectomy; American Society of Anesthesiologists (ASA) physical status I-II; general anesthesia with tracheal intubation; and complete records of height, body weight, perioperative variables, postoperative pain scores, and postoperative analgesic administration. Patients were excluded if they had a history of chronic pain or long-term use of analgesics, sedatives, antidepressants, or anxiolytic drugs; severe cardiac, pulmonary, hepatic, or renal dysfunction, or ASA physical status ≥III; a history of opioid or alcohol abuse; conversion from laparoscopic to open surgery; combined neuraxial anesthesia or regional nerve block; or missing or unclear key data, including pain scores, perioperative medication records, or opioid dosage information.
2. BMI grouping
Preoperative height and body weight were extracted from the EMR system. BMI was calculated as body weight in kilograms divided by height in meters squared. Patients were classified according to the Chinese adult body weight classification standard, in which obesity is defined as BMI ≥28.0 kg/m2 and non-obesity as BMI <28.0 kg/m2. BMI was used both as a categorical variable for intergroup comparisons and as a continuous variable in the multivariable logistic regression model.
3. Outcome measures and definitions
The primary outcome was moderate-to-severe postoperative pain, defined as a 24 h mean NRS score ≥4. The 24 h mean NRS score was calculated as the average of the NRS scores recorded at 6 h, 12 h, and 24 h after surgery. Secondary outcomes included the first NRS score in the post-anesthesia care unit (PACU), NRS scores at 6 h, 12 h, and 24 h after surgery, postoperative opioid consumption converted to oral morphine equivalents (OME), operative duration, anesthesia duration, time to first ambulation, length of hospital stay, and postoperative nausea and vomiting (PONV) within 24 h after surgery.
Operative duration was defined as the interval from skin incision to completion of skin closure. Anesthesia duration was defined as the interval from initiation of anesthetic induction to completion of tracheal extubation. Time to first ambulation was extracted from nursing documentation. Length of hospital stay was calculated from admission and discharge records in the EMR system.
4. NRS pain assessment
Postoperative pain intensity was assessed using the 11-point NRS, ranging from 0 to 10. A score of 0 indicated no pain, 1–3 indicated mild pain, 4–6 indicated moderate pain, and 7–10 indicated severe pain. Pain was assessed at rest using the standardized prompt: “Please rate your current pain at rest on a scale from 0 to 10, where 0 means no pain, and 10 means the most severe pain imaginable.” Only resting NRS scores were used for the present analysis.
NRS scores were recorded by trained PACU or ward nursing staff according to the institutional postoperative pain assessment routine. The first PACU NRS score was defined as the first valid pain score obtained after the patient had regained consciousness, was clinically stable, and was able to provide a self-reported pain score. Subsequent NRS scores were recorded at 6 h, 12 h, and 24 h after surgery. The first PACU NRS score was usually assessed within 30 min after PACU arrival. Because this was a retrospective study based on routine clinical care, nurses were not specifically blinded to BMI status; however, pain scores were collected before study grouping and statistical analysis. If duplicate NRS assessments were available at the same time point, the score recorded closest to the scheduled time point was used.
5. Perioperative anesthesia and monitoring
All patients underwent standardized general anesthesia with tracheal intubation (following institutionally approved protocols). After entering the operating room, routine monitoring was established, including electrocardiography, noninvasive blood pressure, pulse oxygen saturation, end-tidal carbon dioxide, and body temperature monitoring. When available, depth of anesthesia was monitored using bispectral index monitoring, with the anesthetic depth adjusted according to routine institutional practice.
Anesthesia was induced intravenously with propofol at 1.5β2.5 mg/kg, sufentanil at 0.2–0.4 µg/kg or an equivalent opioid dose, and a nondepolarizing neuromuscular blocking agent such as rocuronium at 0.6–0.9 mg/kg or cisatracurium at 0.15–0.2 mg/kg. Tracheal intubation was performed after adequate loss of consciousness and neuromuscular relaxation. Anesthesia was maintained with inhalational anesthetics and/or intravenous anesthetics according to the attending anesthesiologist’s routine practice, with opioids administered as needed to maintain hemodynamic stability and adequate analgesia. Ventilation was adjusted to maintain end-tidal carbon dioxide within the clinically acceptable range.
Intraoperative opioid administration was extracted from anesthesia records, including opioid name, route of administration, dose, and administration time. Operative duration, anesthesia duration, and intraoperative monitoring variables were obtained from the anesthesia information system. No neuraxial anesthesia or regional nerve block was used in either group, thereby reducing heterogeneity related to regional analgesic techniques. Body temperature was monitored throughout anesthesia, and warming measures were applied when clinically indicated to maintain perioperative normothermia. The consistency of key perioperative anesthesia and analgesia-related measures between groups is summarized in Supplementary Table 1.
6. Postoperative analgesic protocol and safety monitoring
The same postoperative pain assessment schedule and rescue analgesia criteria were applied to both obese and non-obese patients. Postoperative pain was routinely assessed using the NRS. Rescue analgesia was administered when NRS ≥4 according to the institutional postoperative analgesic protocol. The indication for rescue analgesia was identical between groups. Rescue analgesia consisted of intravenous opioid supplementation and/or non-steroidal anti-inflammatory drugs (NSAIDs), according to clinical judgment, patient condition, and contraindications. All postoperative analgesic exposure within the first 24 h after surgery was extracted from medical orders and nursing administration records, including drug name, dose, route, administration time, and frequency.
For patients receiving postoperative opioid rescue analgesia, respiratory safety monitoring was performed in the PACU and ward according to routine postoperative nursing practice. Monitoring included level of consciousness, respiratory rate, pulse oxygen saturation, and clinical signs of respiratory depression, including excessive sedation, hypoventilation, airway obstruction, or oxygen desaturation. In obese patients, particular attention was paid to respiratory status because obesity may increase susceptibility to opioid-related hypoventilation and airway obstruction. When clinically indicated, supplemental oxygen, intensified observation, or physician reassessment was provided according to institutional postoperative care procedures.
7. PONV assessment
Postoperative nausea and vomiting (PONV) within 24 h after surgery was extracted from nursing records and medical orders. PONV was defined as any documented nausea, retching, or vomiting episode, or the administration of rescue antiemetic medication within the first 24 h after surgery. The incidence of PONV was compared between the obese and non-obese groups.
8. Calculation of Postoperative Opioid Consumption (OME)
Postoperative opioid consumption was extracted from electronic medical orders and nursing administration records within the first 24 h after surgery. For each opioid administration, the drug name, route, dose, and administration time were recorded. To allow comparison across different opioid agents and routes, all opioid doses were converted to OME using the formula: OME (mg) = administered dose × conversion factor.
Dose units were standardized before conversion. Morphine, oxycodone, and tramadol doses were expressed in milligrams, whereas fentanyl and sufentanil doses were expressed in micrograms. The conversion factors used in this study are listed in Supplementary Table 2 and were adapted from published OME conversion literature. The total 24 h postoperative OME was calculated by summing all converted opioid doses administered during the first 24 h after surgery. Intraoperative opioid exposure was also converted to OME using the same conversion approach and included as a covariate in the multivariable regression model.
9. Data extraction and quality control
Demographic characteristics, BMI, ASA physical status, operative duration, anesthesia duration, intraoperative opioid consumption, postoperative opioid consumption, postoperative NSAID use, PONV, time to first ambulation, length of hospital stay, and postoperative NRS scores were extracted from the EMR system, anesthesia information system, and nursing records. A standardized data extraction form was used before statistical analysis.
To improve data reliability, extracted data were checked against the original electronic records. Implausible or inconsistent values, including BMI, NRS scores, opioid doses, operative duration, and anesthesia duration, were rechecked using the original source records. Records were considered incomplete if any key variable required for primary outcome definition or multivariable regression analysis was missing or unclear. Incomplete records were excluded from the final analysis rather than imputed. Nine records with missing or unclear key variables were excluded rather than imputed. After exclusion, no missing values remained for variables included in the primary outcome definition or multivariable regression analysis.
10. Statistical analysis
Statistical analyses were performed using SPSS software, version 26.0. Continuous variables were assessed for normality using the Kolmogorov-Smirnov test and for homogeneity of variance using Levene’s test. Normally distributed continuous variables were presented as mean ± standard deviation and compared using the independent-samples t-test. Non-normally distributed continuous variables were presented as median [interquartile range] and compared using the Mann-Whitney U test. Categorical variables were presented as n (%) and compared using the chi-square test or Fisher’s exact test, as appropriate.
A multivariable logistic regression model was constructed to evaluate the association between continuous BMI and moderate-to-severe postoperative pain. The dependent variable was moderate-to-severe postoperative pain, defined as a 24 h mean NRS score ≥4. The independent variables included BMI, age, sex, ASA physical status, and intraoperative opioid consumption. NRS-related variables were not included as covariates to avoid circular definition bias. The regression model was fitted using the enter method. Regression coefficients, standard errors, Wald χ2 values, odds ratios (ORs), 95% confidence intervals (CIs), and P values were reported.
Multicollinearity among regression covariates was assessed using variance inflation factors (VIFs), with VIF values <5 considered to indicate no substantial multicollinearity. Model discrimination was evaluated using the C-statistic, equivalent to the area under the receiver operating characteristic curve. Model calibration was evaluated using the Hosmer-Lemeshow goodness-of-fit test. Because sex may be clinically associated with postoperative pain, an exploratory sex × BMI interaction term was tested to assess whether the association between BMI and moderate-to-severe postoperative pain differed by sex.
Because this was a single-center retrospective study with a limited sample size, a post-hoc power analysis was performed for the primary continuous pain outcome using the observed between-group difference in the 24 h mean NRS score. The analysis was based on a two-sided independent-samples t-test, α = 0.05, n = 50 in the non-obese group, n = 46 in the obese group, and the observed group means and standard deviations. The estimated post-hoc power was >0.99. However, because the multivariable logistic regression model included 32 moderate-to-severe postoperative pain events and five covariates, corresponding to approximately 6.4 events per predictor variable, the regression analysis was interpreted cautiously as exploratory.
The number needed to harm (NNH) was calculated using the absolute risk increase in moderate-to-severe postoperative pain between the obese and non-obese groups. The formula was NNH = 1 / (risk in the obese group - risk in the non-obese group), and the result was rounded up to the nearest whole number. All statistical tests were two-sided, and P < 0.05 was considered statistically significant.