Optimization of postoperative pain management in gynecological laparoscopic surgery with combined Nalbuphine and Remifentanil: A retrospective analysis with propensity score matching.

Through retrospective analysis, this study explored the factors influencing postoperative pain following gynecological laparoscopic surgery. The analgesic effect of combining Nalbuphine and Remifentanil was significantly superior to using a single drug, suggesting the potential advantages of this combined medication strategy in postoperative pain management. The results of this study provide new evidence for postoperative pain management and point to directions for future research.

Postoperative pain is a common and important issue in perioperative management for surgical patients, particularly for those undergoing gynecological laparoscopic surgery. [ 1 ] Laparoscopic surgery has been widely applied in treating various gynecological conditions such as endometriosis, ovarian cysts, uterine fibroids, and ectopic pregnancy due to its minimally invasive nature, which offers the advantages of reduced trauma and faster recovery. [ 2 , 3 ] However, despite the smaller incisions and shorter operative time associated with laparoscopic procedures compared to traditional open surgery, postoperative pain remains a key factor that affects patients’ recovery and quality of life. [ 4 ] Postoperative pain not only includes local incisional pain but also encompasses pain caused by pneumoperitoneum-induced peritoneal stretching, diaphragmatic irritation leading to shoulder pain, and deep tissue damage from surgical instruments. [ 5 , 6 ] This pain can be most intense within 24 to 48 hours after surgery. While typically less severe than open surgery, pain can still significantly affect recovery, especially for patients undergoing more extensive or complex procedures such as hysterectomy or pelvic lymphadenectomy. Prolonged pain may also increase the risk of developing chronic postoperative pain, which can negatively impact long-term quality of life. [ 7 , 8 ] Furthermore, inadequate pain management can extend hospital stays, delay recovery, and increase healthcare costs, placing a greater burden on both patients and the healthcare system. Thus, optimizing postoperative pain management is crucial for enhancing perioperative care quality for gynecological laparoscopic surgery patients. Opioids are commonly used for postoperative analgesia due to their strong pain-relieving effects. [ 9 ] However, reliance on opioids alone has certain limitations, such as the risk of significant adverse effects, particularly when higher doses are required, which can lead to respiratory depression, nausea, and vomiting. [ 10 ] To address these issues, the field of anesthesiology has increasingly focused on combining different medications to reduce side effects while enhancing analgesic efficacy. [ 11 ] Nalbuphine and Remifentanil are 2 commonly used opioids that are widely applied in pain management for gynecological laparoscopic surgery. [ 12 ] Nalbuphine, a μ-receptor antagonist and κ-receptor agonist, has fewer respiratory depressant effects. [ 13 ] While Remifentanil, a short-acting opioid, is suitable for rapid pain control during and after surgery. [ 14 , 15 ] While both drugs have unique advantages individually, there is still insufficient clinical evidence to determine whether their combined use can more effectively alleviate postoperative pain. In addition to the choice of anesthetic drugs, postoperative pain is also influenced by various patient-specific factors, such as body mass index (BMI), smoking history, alcohol use, comorbidities, surgical type, and American Society of Anesthesiologists Physical Status Classification System (ASA) score. [ 16 ] Therefore, when evaluating the impact of different drug combinations on postoperative pain, it is important to account for these potential confounding factors. Furthermore, intraoperative parameters such as heart rate, blood pressure, respiratory rate, and end-tidal carbon dioxide (EtCO 2 ) may also influence postoperative pain, as these indicators reflect the patient’s physiological stress response and the effectiveness of analgesics. This study retrospectively analyzed data from 840 patients who underwent gynecological laparoscopic surgery. We collected data on baseline characteristics (e.g., age, BMI, smoking history), intraoperative vital signs, surgical type, and postoperative pain scores (VAS) at 6 and 24 hours postoperatively, aiming to assess the potential factors affecting postoperative pain. Through univariate and multivariate logistic regression analyses, we identified independent factors associated with postoperative pain. Additionally, to minimize the impact of confounding factors due to differences in patient characteristics between groups, we applied propensity score matching (PSM) to improve the reliability of the analysis. Moreover, by comparing the area under the receiver operating characteristic curve (AUC) for different regression models, we evaluated the predictive performance of each model to determine the optimal analgesic regimen. This study provides new evidence to support postoperative pain management and offers fresh insights into the clinical application of Nalbuphine and Remifentanil. The findings may contribute to optimizing anesthesia protocols for gynecological laparoscopic surgery patients, improving postoperative recovery outcomes.

Conceptualization: Shaohua Huang. Data curation: Shaohua Huang, Lin Lv. Formal analysis: Shaohua Huang. Investigation: Shaohua Huang. Methodology: Chunnv Jin, Lin Lv. Project administration: Chunnv Jin, Xiangru Cao. Resources: Chunnv Jin, Xiangru Cao. Software: Xiangru Cao, Lin Lv. Supervision: Shaohua Huang. Validation: Shaohua Huang. Visualization: Shaohua Huang. Writing – original draft: Shaohua Huang, Chunnv Jin, Xiangru Cao, Lin Lv. Writing – review & editing: Shaohua Huang.

A total of 840 patients who underwent gynecological laparoscopic surgery at Baoding Maternal and Child Health Hospital, Hebei Province from March 2023 to May 2024 were included in this study. These patients were divided into 3 groups: the Nalbuphine group (n = 184), the Remifentanil group (n = 456), and the Nalbuphine–Remifentanil combination group (n = 200). All surgeries were performed by experienced surgeons, and the intraoperative anesthesia management protocols were pre-established and approved by the ethics committee. Inclusion criteria were: (1) female patients aged 18 to 65 years. (2) Patients who underwent gynecological laparoscopic surgery, including but not limited to hysterectomy, pelvic lymphadenectomy, and other gynecology-related laparoscopic surgeries. (3) Patients who received postoperative pain management with Nalbuphine, Remifentanil, or a combination of both. (4) Patients who had postoperative pain assessments using VAS scores (6 hours and 24 hours after surgery). (5) Patients with complete intraoperative vital signs and postoperative pain management records. Exclusion criteria were: (1) patients with severe heart, lung, kidney, or liver dysfunction. (2) Patients with postoperative cognitive impairment or inability to cooperate with VAS score assessments. (3) Patients with mental or neurological disorders that might affect pain perception. (4) Patients with severe postoperative complications such as massive bleeding or infections that could interfere with pain assessments. (5) Patients who had to discontinue analgesic medications due to allergic reactions during surgery or postoperatively. (6) Patients who were converted to open surgery intraoperatively. This paper has been reviewed by relevant departments of our hospital, such as the Science and Education Department, Medical Department and Ethics Committee of Baoding Maternal and Child Health Hospital. Data were extracted from the hospital’s electronic medical record system, including patient baseline characteristics, intraoperative data, and postoperative pain assessments. All data were compiled and reviewed by trained researchers to ensure completeness and accuracy. Baseline characteristics included age, BMI, smoking history, alcohol use history, hypertension, diabetes, cardiovascular disease history, opioid use history, surgical type, and ASA score. Intraoperative data included heart rate, blood pressure, arterial oxygen saturation, respiratory rate, EtCO 2 , and surgical duration. Postoperative pain was assessed using the VAS, which is a widely used subjective measure of clinical pain. [ 17 ] VAS allows patients to evaluate and quantify pain intensity to objectify their pain experience: 0 = no pain; 1 to 3 = mild pain, which generally does not interfere with daily activities; 4 to 6 = moderate pain, which may affect daily activities and rest and requires intervention; 7 to 10 = severe pain, which significantly interferes with daily life and typically requires immediate pain relief. Patients were divided into 2 groups: severe pain (VAS ≥ 5) and mild pain (VAS < 5). First, univariate logistic regression analysis was performed on all statistically significant baseline and intraoperative variables to evaluate the association between each variable and postoperative pain (VAS ≥ 5). Variables with a P -value of <.05 were considered significant influencing factors. Based on the significant variables identified from statistical analyses, 3 multivariate logistic regression models were constructed: Model 1 : all statistically significant variables were included as independent variables, with postoperative pain severity as the dependent variable. The independent factors influencing postoperative pain were determined. Model 2 : the drug group variable (Nalbuphine–Remifentanil combination group vs single drug group) was added to Model 1 to further evaluate the effect of drug combinations on postoperative pain. Model 3 : PSM was applied to Model 2, matching patients based on baseline characteristics to reduce the confounding effects on the results and assess the impact of different drug combinations on postoperative pain. PSM is a statistical method commonly used in retrospective studies to reduce the influence of confounding factors on research outcomes, especially when the distribution of characteristics between 2 or more groups is unbalanced. [ 18 ] The core idea of PSM is to calculate the propensity score for each patient (i.e., the probability that they are assigned to a specific group) and match patients with similar propensity scores to ensure that different groups are more balanced in terms of baseline characteristics, thus reducing group differences and improving the reliability of conclusions. [ 19 ] We calculated propensity scores based on patients’ baseline characteristics and intraoperative data and used a 1:3 matching method to match patients, ensuring that baseline characteristics were balanced between groups. All statistical analyses were performed using R software (version 4.4.1). Quantitative data were presented as median (min–max), and between-group comparisons were made using the Mann–Whitney U test. Qualitative data were presented as percentages, and comparisons were made using the chi-square test or Fisher exact test. Both univariate and multivariate logistic regression analyses were conducted with VAS scores as the dependent variable. Statistical significance was set at P  < .05.

Most baseline characteristics showed no significant differences between the groups, such as age ( P  = .274), BMI ( P  = .222), and smoking history ( P  = .792). Notably, there were significant differences in surgical type ( P  = .000), ASA ( P  = .000) and opioid use history ( P  = .000), indicating an uneven distribution of these 3 factors across the different drug groups. Additionally, there were no significant differences in other factors such as hypertension, diabetes, or cardiovascular disease history between the groups (Table 1 ). Baseline data for different drug groups. ASA = American Society of Anesthesiologists Physical Status Classification System, BMI = body mass index. Significant differences were found in heart rate ( P  = .00234) and respiratory rate ( P  = .033) between the groups, while systolic blood pressure, diastolic blood pressure, oxygen saturation, and surgical duration showed no significant differences between the groups. There was a significant difference in EtCO 2 levels ( P  = .000), suggesting potential differences in respiratory management across the groups. Postoperative VAS scores at 6 and 24 hours also showed significant differences, with the 6-hour VAS score ( P  = .000) and 24-hour VAS score ( P  = .000) indicating that the drug groups had a significant impact on postoperative pain, with the Remifentanil group showing higher pain scores at 6 hours postoperatively (Table 2 ). Intraoperative data for different drug groups. EtCO₂ = end-tidal carbon dioxide, DBP = diastolic blood pressure, SBP = systolic blood pressure, VAS = visual analog scale. Hysterectomy and pelvic lymphadenectomy, compared to other types of surgeries, significantly increased the risk of postoperative pain ( P  = .000, Estimate = 1.680). The ASA score ( P  = .000, Estimate = 0.736) also indicated that higher ASA scores were associated with a greater risk of postoperative pain. Respiratory rate ( P  = .032, Estimate = 0.029) was significantly associated with postoperative pain, suggesting that increased respiratory rate may be linked to a higher occurrence of pain. The drug group ( P  = .000, Estimate = -2.598) was the most significant factor affecting postoperative pain. In contrast, opioid use history ( P  = .791), heart rate ( P  = .377), and EtCO 2 ( P  = .345) were not significantly associated with postoperative pain (Table 3 ). Univariate logistic regression analysis of postoperative pain. ASA = American Society of Anesthesiologists Physical Status Classification System, EtCO₂ = end-tidal carbon dioxide. Model 1 showed that the ASA score (OR = 1.723, 95% CI: 1.462–2.029, P  = .000), respiratory rate (OR = 1.030, 95% CI: 1.000–1.060, P  = .046), and surgical type (hysterectomy vs others: OR = 1.684, 95% CI: 1.472–1.992, P  = .000; pelvic lymphadenectomy vs others: OR = 1.818, 95% CI: 1.200–2.505, P  = .001) were significantly associated with postoperative pain, while opioid use history ( P  = .875), heart rate ( P  = .277), and EtCO 2 ( P  = .209) had no significant effect on postoperative pain (Table 4 ). Multivariate logistic regression models before and after PSM. ASA = American Society of Anesthesiologists Physical Status Classification System, EtCO₂ = end-tidal carbon dioxide, PSM = propensity score matching. Variable is statistically significant in the analysis ( P < .05). Model 2 (before PSM) included the drug group variable and showed that the ASA score (OR = 2.145, 95% CI: 1.782–2.582, P  = .000), surgical type (hysterectomy vs others: OR = 1.312, 95% CI: 1.198–1.491, P  = .000; pelvic lymphadenectomy vs others: OR = 1.358, 95% CI: 1.121–1.777, P  = .009), and drug group (Nalbuphine–Remifentanil combination vs Nalbuphine or Remifentanil alone: OR = 0.623, 95% CI: 0.465–0.974, P  = .017) were significant factors affecting postoperative pain, with patients in the combination group showing a significantly reduced risk of postoperative pain (Table 4 ). Standardized mean differences of variables before and after PSM indicated that most variables had reduced standardized mean differences, approaching or below 0.1, suggesting that group differences were reduced after matching, with good matching effects (Fig. 1 ). Seven hundred twenty-six patients who used Nalbuphine or Remifentanil alone were matched, 172 patients who used Nalbuphine or Remifentanil alone were excluded, and all 242 patients who used both Nalbuphine and Remifentanil in combination were matched. Model 3 (after PSM) demonstrated that the ASA score (OR = 1.742, 95% CI: 1.422–2.135, P  = .000), surgical type (hysterectomy vs others: OR = 2.087, 95% CI: 1.537–2.631, P  = .000; pelvic lymphadenectomy vs others: OR = 2.970, 95% CI: 2.236–3.578, P  = .000), and drug group (Nalbuphine–Remifentanil combination vs Nalbuphine or Remifentanil alone: OR = 0.186, 95% CI: 0.104–0.333, P  = .000) remained independent factors affecting postoperative pain, with the combination group showing the lowest risk of postoperative pain (Table 4 ). Standardized mean differences (SMD) line plot before and after PSM. PSM = propensity score matching. Model 3 (after PSM) had the highest AUC (0.719), indicating the strongest predictive ability, with a significant improvement in sensitivity (0.798), demonstrating superior performance in accurately identifying patients with postoperative pain compared to the other models. Although the specificity of Model 3 (0.611) was slightly lower than that of Model 1 (0.718), its overall performance was better, and its Youden index (0.410) was the highest, indicating that Model 3 achieved a better balance between sensitivity and specificity. Overall, Model 3, after propensity score matching, showed the best performance in predicting postoperative pain (Table 5 , Fig. 2 ). ROC curve parameters of multiple logistic regression models for 3 different models. AUC = area under the curve, PSM = propensity score matching, ROC = receiver operating characteristic. (A) ROC curve for Model 1. (B) ROC curve for Model 2. (C) ROC curve for Model 3. ROC = receiver operating characteristic.

This study explored the impact of different drug combinations on postoperative pain in patients undergoing gynecological laparoscopic surgery, focusing on the effects of Nalbuphine, Remifentanil, and their combined use. We developed 3 multivariate logistic regression models and analyzed them both before and after PSM to evaluate the main factors influencing postoperative pain and verify the efficacy of the drug combinations in postoperative analgesia. Postoperative pain is a complex physiological and psychological phenomenon influenced by multiple factors. In this study, the ASA score was found to be one of the key factors affecting postoperative pain, which is consistent with previous research. The ASA score reflects a patient’s overall health status, and a higher score is associated with a greater risk of postoperative pain. Patients with higher ASA scores are more likely to experience complications after surgery, enhanced inflammatory responses, and lower pain thresholds, requiring more intensive monitoring and more effective pain management during the perioperative period. Surgical type also significantly impacted postoperative pain in this study, especially hysterectomy and pelvic lymphadenectomy. [ 20 , 21 ] The complexity and trauma associated with these surgeries directly affect the severity of postoperative pain. More invasive surgeries are often accompanied by stronger postoperative inflammatory responses and tissue damage, leading to more intense pain perception. This finding suggests that individualized pain management strategies should be developed based on the degree of surgical trauma to ensure smooth postoperative recovery for patients undergoing different types of surgeries. Furthermore, this study confirmed the differential effects of drug combinations on postoperative pain. Patients receiving a combination of Nalbuphine and Remifentanil showed more significant pain relief, suggesting a potential synergistic effect between the 2 drugs. Nalbuphine, as a κ-receptor agonist, combined with the μ-receptor agonist effects of Remifentanil, may reduce the adverse effects associated with single opioid use while enhancing analgesic efficacy. The advantage of the combined analgesic strategy is that it not only reduces pain scores but also decreases the required opioid dosage, minimizing opioid-related side effects such as nausea, vomiting, and respiratory depression. The focus of this study was on constructing 3 multivariate logistic regression models. In Model 1, we assessed the effects of several variables on postoperative pain, including opioid use history, ASA score, surgical type, heart rate, respiratory rate, and EtCO 2 . The results indicated that ASA score and surgical type were significant influencing factors, highlighting the importance of preoperative health status and surgical complexity in postoperative pain. Notably, more complex surgeries such as hysterectomy and pelvic lymphadenectomy increased the risk of postoperative pain. In contrast, opioid use history, heart rate, and EtCO 2 did not show significant effects, indicating that these factors had minimal impact on postoperative pain in this study. Model 2 introduced the drug group variable based on Model 1, and the results showed that, in addition to the ASA score and surgical type, the drug combination became a significant factor. Specifically, patients who received a combination of Nalbuphine and Remifentanil experienced significantly less postoperative pain, suggesting a better synergistic analgesic effect. However, as baseline characteristics were imbalanced between the groups before PSM, the results of Model 2 may have been influenced by potential confounding factors, necessitating further adjustment through PSM. To more accurately evaluate the effect of the drug combination, we applied PSM in Model 3 to eliminate baseline imbalances between the groups. After matching, ASA score, surgical type, and drug group remained significant independent factors affecting postoperative pain. Notably, patients who received the combination of Nalbuphine and Remifentanil had the lowest risk of postoperative pain, further validating the advantages of combination therapy in postoperative pain management. Compared to Models 1 and 2, Model 3 had the highest AUC and significantly improved sensitivity, indicating that the matched model provided more reliable predictions of postoperative pain. By comparing the 3 models, Model 2, which included the drug group variable, had stronger predictive power for postoperative pain than Model 1, indicating that drug use is a key factor affecting postoperative pain. Additionally, the influence of drug use remained significant before and after PSM, with the combined use of Nalbuphine and Remifentanil showing the most significant analgesic effect. This suggests that combination therapy may be an effective strategy for postoperative pain management in clinical practice. The results of this study have important clinical implications. First, the significant effects of the ASA score and surgical type highlight the importance of thoroughly assessing patients’ physical condition and surgical complexity before surgery. This not only helps predict the risk of postoperative pain but also allows for the pre-planning of appropriate analgesic strategies to ensure smooth postoperative recovery. For patients with higher ASA scores or more complex surgeries, more aggressive pain intervention measures may be needed, including preoperative pain education, multimodal intraoperative analgesia, and close postoperative follow-up. Second, the analgesic effect of the combined use of Nalbuphine and Remifentanil provides new insights for postoperative pain management. The concept of multimodal analgesia has been widely accepted, and this study further supports the effectiveness of this strategy. [ 22 , 23 ] In clinical practice, combining analgesic drugs with different mechanisms of action not only improves pain relief but also reduces the dosage of individual drugs, thus minimizing adverse effects. [ 24 ] This finding provides new evidence for optimizing perioperative analgesic regimens, especially when reducing opioid use is a priority. The combined analgesic strategy has high potential for application. Despite the efforts made to reduce baseline imbalances through retrospective analysis and PSM, this study has some limitations. First, as a retrospective study, the quality and completeness of data may be limited. [ 25 ] Subjective factors such as patients’ pain perception and individual pain tolerance were not fully quantified, which may have affected the results. Although PSM was introduced to reduce confounding factors, some variables remained imbalanced after matching, particularly ASA score and surgical type, which could impact the accuracy of the results. Second, this study was conducted at a single center with a limited sample size, which may affect the generalizability of the findings. Future research should validate these results through multi-center, large-sample prospective studies. Moreover, individual differences in patients’ responses to opioids were not explored in depth, particularly regarding the influence of genetic polymorphisms on analgesic efficacy, which should be a focus of future studies. Future research should consider conducting large-scale, multi-center randomized controlled trials to further validate the analgesic effects of combination therapy. As precision medicine advances, personalized pain management is gaining more attention. Developing individualized analgesic regimens based on patients’ genetic, metabolic, and pain tolerance profiles will be a key area of future research. Additionally, exploring the combined use of non-opioid analgesics or adjuvant medications (e.g., local anesthetics, anti-inflammatory drugs) may further enhance postoperative pain management.