External Validation and Update of the RICP-A Multivariate Model to Predict Chronic Postoperative Pain

Dexmedetomidine attenuates inflammatory response and chronic pain following video-assisted thoracoscopic surgery for lung cancer

BACKGROUND

The objective of the present study was to evaluate the effect of dexmedetomidine administration during video-assisted thoracoscopic surgery for lung cancer on perioperative inflammatory response and chronic post-surgical pain.

METHODS

A cohort of 152 patients with lung cancer scheduled for elective video-assisted thoracoscopic surgery participated in this randomized controlled trial. Patients were randomly divided into 2 groups and administered an equivalent volume of dexmedetomidine (n = 63) or normal saline (n = 63). Dexmedetomidine was administered at a dose of 0.6 μg/kg 10 minutes before anesthesia induction and maintained at 0.5 μg/kg/h until 0.5 hours before surgery completed. Anesthesia and postoperative pain management protocols were standardized for both groups. The analysis included vital signs, numerical rating scales of pain, blood inflammatory and oxidative stress biomarkers, pain type and location, patient-controlled intravenous analgesia usage, consumption of general anesthetics and pain rescue medications, as well as complications.

RESULTS

The administration of dexmedetomidine resulted in decreased levels of inflammatory cytokines (interleukin-1 beta, interleukin-6, alongside tumor necrosis factor-alpha) and oxidative stress biomarkers (reactive oxygen species alongside malondialdehyde) but elevated levels of interleukin-10 and superoxide dismutase. In addition, the dexmedetomidine group showed lower postoperative numerical rating scale scores, reduced consumption of anesthetics, faster chest-tube removal, fewer patient-controlled intravenous analgesia presses, and shorter postoperative hospital stays.

CONCLUSION

The administration of dexmedetomidine effectively attenuated surgical inflammation, oxidative stress, and postoperative pain, thereby promoting patient recovery after lung cancer surgery without increasing the risk of adverse effects or complications.

Prognostic models for chronic postsurgical pain-Current developments, trends, and challenges

PURPOSE OF REVIEW

Prognostic models for chronic postsurgical pain (CPSP) aim to predict the likelihood for development and severity of CPSP in individual patients undergoing surgical procedures. Such models might provide valuable information for healthcare providers, allowing them to identify patients at higher risk and implement targeted interventions to prevent or manage CPSP effectively. This review discusses the latest developments of prognostic models for CPSP, their challenges, limitations, and future directions.

RECENT FINDINGS

Numerous studies have been conducted aiming to develop prognostic models for CPSP using various perioperative factors. These include patient-related factors like demographic variables, preexisting pain conditions, psychosocial aspects, procedure-specific characteristics, perioperative analgesic strategies, postoperative complications and, as indicated most recently, biomarkers. Model generation, however, varies and performance and accuracy differ between prognostic models for several reasons and validation of models is rather scarce.

SUMMARY

Precise methodology of prognostic model development needs advancements in the field of CPSP. Development of more accurate, validated and refined models in large-scale cohorts is needed to improve reliability and applicability in clinical practice and validation studies are necessary to further refine and improve the performance of prognostic models for CPSP.

Testing of a predictive risk index for persistent postsurgical pain on patients undergoing total knee arthroplasty: A prospective cohort study

BACKGROUND

We investigated whether a universal predictive risk index for persistent postsurgical pain (PPP) is applicable to patients who undergo total knee arthroplasty (TKA).

METHODS

In this cohort study, 392 participants of a randomized study investigating the effects of anaesthesia methods and tourniquet use on TKA were divided into low-, moderate-, and high-risk groups for PPP, as suggested in the previous risk index study. Patients reported pain using the Oxford Knee Score pain subscale and Brief Pain Inventory-short form preoperatively and 3 and 12 months postoperatively. We compared the pain scores of the low- to moderate- and high-risk groups at respective time points and investigated changes in pain scores and the prevalence of PPP at 3 and 12 months after surgery.

RESULTS

The high-risk group reported more pain 3 and 12 months after TKA than the low- to moderate-risk group. However, of seven variables, only a single difference reached the threshold for minimal clinical importance between the groups at 12 months. Additionally, at 12 months, the low- to moderate-risk group reported slightly worse improvements in three of seven pain variables than the high-risk group. Depending on the definition, the prevalence of PPP ranged from 2% to 29% in the low- to moderate-risk group and 4% to 41% in the high-risk group 12 months postoperatively.

CONCLUSIONS

Although the investigated risk index might predict clinically important differences in PPP between the risk groups at 3 months after TKA, it seems poorly applicable for predicting PPP at 12 months after TKA.

SIGNIFICANCE

Although many risk factors for persistent postsurgical pain after total knee arthroplasty have been identified, predicting the risk of this pain has remained a challenge. Results of the current study suggest that accumulation of previously presented modifiable risk factors might be associated with increased postsurgical pain at 3 months, but not at 12 months after total knee arthroplasty.

External validation of postoperative nausea and vomiting risk scores in patients with liver cancer: A single-centre prospective cohort study

OBJECTIVES

This study aimed to test the external validity of postoperative nausea and vomiting (PONV) risk assessment tools in patients undergoing hepatectomy, and to guide healthcare professionals' assessment of postoperative patients.

BACKGROUND

The identification of PONV risk is particularly important in the context of prevention. However, the predictive performance of the current PONV risk scores has not been confirmed in patients with liver cancer, and its applicability is still unknown. These uncertainties pose difficulties in performing routine risk assessment of PONV for patients with liver cancer in a clinical practice setting.

METHODS

Patients diagnosed with liver cancer and undergoing hepatectomy were prospectively consecutively recruited. All enrolled patients received PONV assessments and PONV risk assessments via the Apfel risk score and the Koivuranta risk score. Receiver operating characteristic curves (ROC curves) and calibration curves were used to assess the external validity. This study was reported according to the TRIPOD Checklist.

RESULTS

Among 214 PONV-assessed patients, 114 patients (53.3%) developed PONV. For the Apfel simplified risk score, the ROC area was 0.612 (95% confidence interval [CI]: 0.543-0.678) in the validation dataset, which demonstrated imperfect discrimination; the calibration curve showed poor calibration with a slope of 0.49. For the Koivuranta score, the ROC area was 0.628 (CI: 0.559-0.693) in the validation dataset, which showed limited discrimination; the calibration curve indicated an unsatisfactory calibration with a slope of 0.71.

CONCLUSIONS

The Apfel risk score and the Koivuranta risk score were not well validated in our study and disease-specific risk factors should be taken into account when updating or developing PONV risk stratification instruments.

Towards better predictive models of chronic post-surgical pain: fitting to the dynamic nature of the pain itself

Chronic post-surgical pain predictive scores exist, but none has yet demonstrated an impact on patient care. Van Driel and colleagues offer an additional perspective on early postoperative detection of patient at risk of chronic post-surgical pain to enable early interventions in prevention and treatment. The authors derived and validated a model based on four easily obtainable predictors that could help clinicians assess and treat patients at risk. Additional work is needed to prove reliability and clinical benefit of chronic post-surgical pain prediction and intervention.

Development and validation of a multivariable prediction model for early prediction of chronic postsurgical pain in adults: a prospective cohort study

BACKGROUND

Early identification of patients at risk of developing chronic postsurgical pain (CPSP) is an essential step in reducing pain chronification in postsurgical patients. We aimed to develop and validate a prognostic model for the early prediction of CPSP including pain characteristics indicating altered pain processing within 2 weeks after surgery.

METHODS

A prospective cohort study was conducted in adult patients undergoing orthopaedic, vascular, trauma, or general surgery between 2018 and 2019. Multivariable logistic regression models for CPSP were developed using data from the University Medical Centre (UMC) Utrecht and validated in data from the Erasmus UMC Rotterdam, The Netherlands.

RESULTS

In the development (n=344) and the validation (n=150) cohorts, 28.8% and 21.3% of patients reported CPSP. The best performing model (area under the curve=0.82; 95% confidence interval [CI], 0.76-0.87) included preoperative treatment with opioids (odds ratio [OR]=4.04; 95% CI, 2.13-7.70), bone surgery (OR=2.01; 95% CI, 1.10-3.67), numerical rating scale pain score on postoperative day 14 (OR=1.57; 95% CI, 1.34-1.83), and the presence of painful cold within the painful area 2 weeks after surgery (OR=4.85; 95% CI, 1.85-12.68). Predictive performance was confirmed by external validation.

CONCLUSIONS

As only four easily obtainable predictors are necessary for reliable CPSP prediction, the models are useful for the clinician to be alerted to further assess and treat individual patients at risk. Identification of the presence of painful cold within 2 weeks after surgery as a strong predictor supports altered pain processing as an important contributor to CPSP development.

Incidence and risk factors for chronic postsurgical pain following video-assisted thoracoscopic surgery: a retrospective study

Background

Video-assisted thoracoscopic surgery (VATS) has been widely used as an alternative for thoracotomy, but the reported incidence of chronic postsurgical pain (CPSP) following VATS varied widely. The purpose of this study was to investigate the incidence and risk factors for CPSP after VATS.

Methods

We retrospectively collected preoperative demographic, anesthesiology, and surgical factors in a cohort of patients undergoing VATS between January 2018 and October 2020. Patients were interviewed via phone survey for pain intensity, and related medical treatment 3 months after VATS. Univariate and multivariate analysis were used to explore independent risk factors associated with CPSP.

Results

2348 patients were included in our study. The incidence of CPSP after VATS were 43.99% (n = 1033 of 2348). Within those suffering CPSP, 14.71% (n = 152 of 1033) patients reported moderate or severe chronic pain. Only 15.23% (n = 23 of 152) patients with moderate to severe chronic pain sought active analgesic therapies. Age < 65 years (OR 1.278, 95% CI 1.057–1.546, P = 0.011), female (OR 1.597, 95% CI 1.344–1.898, P < 0.001), education level less than junior school (OR 1.295, 95% CI 1.090–1.538, P = 0.003), preoperative pain (OR 2.564, 95% CI 1.696–3.877, P < 0.001), consumption of rescue analgesia postoperative (OR 1.248, 95% CI 1.047–1.486, P = 0.013), consumption of sedative hypnotic postoperative (OR 2.035, 95% CI 1.159–3.574, P = 0.013), and history of postoperative wound infection (OR 5.949, 95% CI 3.153–11.223, P < 0.001) were independent risk factors for CPSP development.

Conclusions

CPSP remains a challenge in clinic because half of patients may develop CPSP after VATS.

Trial registration Chinese Clinical Trial Registry (ChiCTR2100045765), 2021/04/24

Prognostic prediction models for chronic postsurgical pain in adults: a systematic review

ABSTRACT

Chronic postsurgical pain (CPSP) affects an estimated 10% to 50% of adults depending on the type of surgical procedure. Clinical prediction models can help clinicians target preventive strategies towards patients at high risk for CPSP. Therefore, the objective of this systematic review was to identify and describe existing prediction models for CPSP in adults. A systematic search was performed in MEDLINE, Embase, PsychINFO, and the Cochrane Database of Systematic Reviews in March 2020 for English peer-reviewed studies that used data collected between 2000 and 2020. Studies that developed, validated, or updated a prediction model in adult patients who underwent any surgical procedure were included. Two reviewers independently screened titles, abstracts, and full texts for eligibility; extracted data; and assessed risk of bias using the Prediction model Risk of Bias Assessment Tool. The search identified 2037 records; 28 articles were reviewed in full text. Fifteen studies reporting on 19 prediction models were included; all were at high risk of bias. Model discrimination, measured by the area under receiver operating curves or c-statistic, ranged from 0.690 to 0.816. The most common predictors identified in final prediction models included preoperative pain in the surgical area, preoperative pain in other areas, age, sex or gender, and acute postsurgical pain. Clinical prediction models may support prevention and management of CPSP, but existing models are at high risk of bias that affects their reliability to inform practice and generalizability to wider populations. Adherence to standardized guidelines for clinical prediction model development is necessary to derive a prediction model of value to clinicians.

Factors predicting failure of internal fixations of fractures of the lower limbs: a prospective cohort study

Background

We assessed predictive factors of patients with fractures of the lower extremities caused by trauma. We examined which factors are associated with an increased risk of failure. Furthermore, the predictive factors were set into context with other long-term outcomes, concrete pain and physical functioning.

Methods

We performed a prospective cohort study at a single level I trauma center. We enrolled patients with traumatic fractures of the lower extremities treated with internal fixation from April 2017 to July 2018. We evaluated the following predictive factors: age, gender, diabetes, smoking status, obesity, open fractures and peripheral arterial diseases. The primary outcome was time to failure (nonunion, implant failure or reposition). Secondary outcomes were pain and physical functioning measured 6 months after initial surgery. For the analysis of the primary outcome, we used a stratified (according fracture location) Cox proportional hazard regression model.

Results

We included 204 patients. Overall, we observed failure in 33 patients (16.2 %). Most of the failures occurred within the first 3 months. Obesity and open fractures were associated with an increased risk of failure and decreased physical functioning. None of the predictors showed an association with pain. Age, female gender and smoking of more than ≥ 10 package years increased failure risk numerically but statistical uncertainty was high.

Conclusions

We found that obesity and open fractures were strongly associated with an increased risk of failure. These predictors seem promising candidates to be included in a risk prediction model and can be considered as a good start for clinical decision making across different types of fractures at the lower limbs. However, large heterogeneity regarding the other analyzed predictors suggests that “simple” models might not be adequate for a precise personalized risk estimation and that computer-based models incorporating a variety of detailed information (e.g. pattern of injury, x-ray and clinical data) and their interrelation may be required to significantly increase prediction precision.

Trial registration

NCT03091114.

[Chronic postoperative pain]

The problem of chronic postoperative pain has been actualized for the last 20 years all over the world. At least 10-40% of patients suffer from chronic pain after surgery. This review is devoted to the current state of the problem of chronic postoperative pain, risk factors and prediction of chronic pain. The authors emphasize the need for interdisciplinary approach to prevention and treatment of this adverse event.

Presurgical risk model for chronic postsurgical pain based on 6 clinical predictors: a prospective external validation

No externally validated presurgical risk score for chronic postsurgical pain (CPSP) is currently available. We tested the generalizability of a six-factor risk model for CPSP developed from a prospective cohort of 2929 patients in 4 surgical settings. Seventeen centers enrolled 1225 patients scheduled for inguinal hernia repair, hysterectomy (vaginal or abdominal), or thoracotomy. The 6 clinical predictors were surgical procedure, younger age, physical health (Short Form Health Survey-12), mental health (Short Form Health Survey-12), preoperative pain in the surgical field, and preoperative pain in another area. Chronic postsurgical pain was confirmed by physical examination at 4 months. The model's discrimination (c-statistic), calibration, and diagnostic accuracy (sensitivity, specificity, and positive and negative likelihood ratios) were calculated to assess geographic and temporal transportability in the full cohort and 2 subsamples (historical and new centers). The full data set after exclusions and losses included 1088 patients; 20.6% had developed CPSP at 4 months. The c-statistics (95% confidence interval) were similar in the full validation sample and the 2 subsamples: 0.69 (0.65-0.73), 0.69 (0.63-0.74), and 0.68 (0.63-0.74), respectively. Calibration was good (slope b and intercept close to 1 and 0, respectively, and nonsignificance in the Hosmer-Lemeshow goodness-of-fit test). The validated model based on 6 clinical factors reliably identifies risk for CPSP risk in about 70% of patients undergoing the surgeries studied, allowing surgeons and anesthesiologists to plan and initiate risk-reduction strategies in routine practice and researchers to screen for risk when randomizing patients in trials.

[Prediction and prevention of chronic postoperative pain]

Chronic postoperative pain has been identified as a major medical and socioeconomic problem. A prevention of the chronification processes is potentially possible and preventive treatment could start early (e.g. preoperatively). So far, however, evidence for the effectiveness of preventive strategies is basically low. Important reasons for this dilemma are the lack of appropriate risk assessment as well as effective and mechanism-based preventive (procedure-sepcific) strategies for the chronification process, a lack of stratification of treatment approaches and a so far barely investigated combination of various treatment approaches. In this review article recent findings on the appropriate identification of patients at risk for developing postoperative chronic pain are presented, predictive models for the valid estimation of the individual risk of patients are assessed and studies on pharmaceutical and regional analgesia techniques influencing the pain chronification process are discussed. As a chronification process is, however, extremely complex and dynamic and also necessitates adaptation of the prevention during the course of the process, only combinations of treatment, interdisciplinary and if necessary even longer term approaches might be successful. Future studies are needed to address with which preventive treatment strategies and in which patients chronic pain after surgery can effectively be prevented.