Effect of a risk-stratified intervention strategy on surgical complications: experience from a multicentre prospective study in China

Prediction of complications associated with general surgery using a Bayesian network

BACKGROUND

Numerous attempts have been made to identify risk factors for surgery complications, but few studies have identified accurate methods of predicting complex outcomes involving multiple complications.

METHODS

We performed a prospective cohort study of general surgical inpatients who attended 4 regionally representative hospitals in China from January to June 2015 and January to June 2016. The risk factors were identified using logistic regression. A Bayesian network model, consisting of directed arcs and nodes, was used to analyze the relationships between risk factors and complications. Probability ratios for complications for a given node state relative to the baseline probability were calculated to quantify the potential effects of risk factors on complications or of complications on other complications.

RESULTS

We recruited 19,223 participants and identified 21 nodes, representing 9 risk factors and 12 complications, and 55 direct relationships between these. Respiratory failure was at the center of the network, directly affected by 5 risk factors, and directly affected 7 complications. Cardiopulmonary resuscitation and sepsis or septic shock also directly affected death. The area under the receiver operating characteristic curve for the ability of the network to predict complications was >0.7. Notably, the probability of other severe complications or death significantly increased when a severe complication occurred. Most importantly, there was a 141-fold higher risk of death when cardiopulmonary resuscitation was required.

CONCLUSION

We have created a Bayesian network that displays how risk factors affect complications and their interrelationships and permits the accurate prediction of complications and the creation of appropriate preventive guidelines.

Network prediction of surgical complication clusters: a prospective multicenter cohort study

Complicated relationships exist in both occurrence and progression of surgical complications, which are difficult to account for using a separate quantitative method such as prediction or grading. Data of 51,030 surgical inpatients were collected from four academic/teaching hospitals in a prospective cohort study in China. The relationship between preoperative factors, 22 common complications, and death was analyzed. With input from 54 senior clinicians and following a Bayesian network approach, a complication grading, cluster-visualization, and prediction (GCP) system was designed to model pathways between grades of complication and preoperative risk factor clusters. In the GCP system, there were 11 nodes representing six grades of complication and five preoperative risk factor clusters, and 32 arcs representing a direct association. Several critical targets were pinpointed on the pathway. Malnourished status was a fundamental cause widely associated (7/32 arcs) with other risk factor clusters and complications. American Society of Anesthesiologists (ASA) score ⩾3 was directly dependent on all other risk factor clusters and influenced all severe complications. Grade III complications (mainly pneumonia) were directly dependent on 4/5 risk factor clusters and affected all other grades of complication. Irrespective of grade, complication occurrence was more likely to increase the risk of other grades of complication than risk factor clusters.

Construction and evaluation of networks among multiple postoperative complications

BACKGROUND AND OBJECTIVE

Postoperative complications confer an increased risk of reoperation, prolonged length of hospital stay, and increased mortality. Many studies have attempted to identify the complex associations among complications to preemptively interrupt their progression, but few studies have looked at complications as a whole to reveal and quantify their possible trajectories of progression. The main objective of this study was to construct and quantify the association network among multiple postoperative complications from a comprehensive perspective to elucidate the possible evolution trajectories.

METHODS

In this study, a Bayesian network model was proposed to analyze the associations among 15 complications. Prior evidence and score-based hill-climbing algorithms were used to build the structure. The severity of complications was graded according to their connection to death, with the association between them quantified using conditional probabilities. The data of surgical inpatients used in this study were collected from four regionally representative academic/teaching hospitals in a prospective cohort study in China.

RESULTS

In the network obtained, 15 nodes represented complications or death, and 35 arcs with arrows represented the directly dependent relationship between them. With three grades classified on that basis, the correlation coefficients of complications within grades increased with increased grade, ranging from -0.11 to -0.06, 0.16, and 0.21 to 0.4 in grade 1 to grade 3, respectively. Moreover, the probability of each complication in the network increased with the occurrence of any other complication, even mild complications. Most seriously, once cardiac arrest requiring cardiopulmonary resuscitation occurs, the probability of death will be up to 88.1%.

CONCLUSIONS

The present evolving network can facilitate the identification of strong associations among specific complications and provides a basis for the development of targeted measures to prevent further deterioration in high-risk patients.

Development of a nomogram to predict surgical site infection after open reduction and internal fixation for closed pilon fracture: a prospective single-center study

BACKGROUND

To explore the risk factors and develop a nomogram in order to predict surgical site infection (SSI) after open reduction and internal fixation (ORIF) for closed pilon fractures (CPF).

METHODS

A prospective cohort study with one-year follow-up was carried out in a provincial trauma center. From January 2019 to January 2021, 417 adult patients with CPFs receiving ORIF were enrolled. A Whitney U test or t test, Pearson chi-square test, and multiple logistic regression analyses were gradually used for screening the adjusted factors of SSI. A nomogram model was built to predict the risk of SSI, and the concordance index (C-index), the receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used for evaluating the prediction performance and consistency of the nomogram model. The bootstrap method was employed to test the validity of the nomogram.

RESULTS

The incidence of SSI after ORIF for CPFs was 7.2% (30/417): 4.1% (17/417) of superficial SSIs and 3.1% (13/417) of deep SSIs. The most common pathogenic bacteria were Staphylococcus aureus (36.6%, 11/30). The multivariate analysis showed tourniquet use, longer preoperative stay, lower preoperative albumin (ALB), higher preoperative body mass index (BMI) and hypersensitive C-reactive protein (Hs-CRP) were independent risk factors of SSI. Additionally, the C-index and bootstrap value of the nomogram model were 0.838 and 0.820, respectively. Finally, the calibration curve indicated that the actual diagnosed SSI had good consistency with the predicted probability, and the DCA showed that the nomogram had clinical value.

CONCLUSIONS

Tourniquet use, longer preoperative stay, lower preoperative ALB, higher preoperative BMI and Hs-CRP were five independent risk factors of SSI after closed pilon fractures treated by ORIF. These five predictors are shown on the nomogram, with which we may be able to further prevent the CPS patients from SSI. Trial registration NO 2018-026-1, October /24/2018, prospectively registered. The study was registered in October 24, 2018. The study protocol was designed based on the Declaration of Helsinki and admitted by the Institutional Review Board. The ethics committee approved the study on factors related to fracture healing in orthopedic surgery. Data analyzed in the present study were acquired from the patients who underwent open reduction and internal fixation from January 2019 to January 2021.

Expanding restrictive transfusion evidence in surgical practice: a multicentre, prospective cohort study

BACKGROUND

Findings of observational studies investigating the impact of transfusions are at odds with those of randomised controlled trials, raising concern that observational studies may be inappropriate to inform transfusion decisions. We examined whether observational data could replicate evidence from randomised controlled trials on restrictive transfusion in cardiac and orthopaedic surgery, and be generalised to broader specialties as well as to a lower haemoglobin transfusion threshold (7 g/dL).

MATERIAL AND METHODS

A multicentre, prospective cohort study was performed at three representative regional hospitals in China between 2015 and 2016. Participants were surgical inpatients (≥18 years; hospital stay ≥24 h) in six specialties: cardiac, cerebral, vascular (CCV), and orthopaedic, general, thoracic (non-CCV). Patients with a stable haemoglobin (7-10 g/dL) constituted the primary analytic sample, while patients with ≥500 mL intra-operative bleeding were analysed separately to avoid haemoglobin instability. The association of transfusion with surgical outcomes (death, in-hospital complications) was evaluated.

RESULTS

The transfusion rate was 10.7% in 36,607 patients (mean age, 52.5±14.3 years; 52.3% female). After restriction, stratification, and propensity score matching to reduce patients' heterogeneity, transfusion was unrelated to death (CCV: odds ratio [OR]=0.74, 95% confidence interval [CI]: 0.16-3.39; non-CCV: OR 0.83, 95% CI: 0.36-1.94) and the composite complication (CCV: OR 1.31, 95% CI: 0.63-2.72; non-CCV: OR=1.24, 95% CI: 0.81-1.90). The results were consistent in subgroups (elderly, coronary heart disease, malignant tumour, severe illness) and applicable to patients with significant bleeding after restoration of a stable haemoglobin.

DISCUSSION

Transfusion at a stable haemoglobin concentration of 7-10 g/dL did not alter surgical outcomes. Our results show the feasibility of observational data to expand restrictive transfusion to broader specialties and a lower transfusion threshold in surgical practice.

Developing a toolbox for identifying when to engage senior surgeons in emergency general surgery: A multicenter cohort study

BACKGROUND

Having a senior surgeon present for high-risk patients is an important safety measure in emergency surgery, but 24-h consultant cover is not efficient. We aimed to develop a user-friendly toolbox (risk identification, outcome prediction and patient stratification) to support when to involve a senior surgeon.

MATERIALS AND METHODS

We included 11,901 general surgery patients (10.0% emergencies) in a multicenter prospective cohort in China (2015-2016). Patient information and surgeons' seniority were compared between emergency and elective surgery with the same procedure codes. Risk indicators common in these two surgical timings and specific to emergency surgery were identified, and their clinical importance was evaluated by a working group of 48 experienced surgeons. Predictive models for mortality and morbidity were built using logistic regression models. Stratification rules were created to balance patients' risk and surgeons' caseload with an Acute Call Team (ACT) model.

RESULTS

Emergency patients had significantly higher risks of mortality (3.6% vs 0.6%) and morbidity (7.8% vs 4.3%) than elective patients, but disproportionally fewer senior surgeons (59.9% vs 91.4%) were present. Using three risk indicators (American Society of Anesthesiologists score, age, blood urea nitrogen), C-statistic (95% CI) for prediction of emergency mortality was high [0.90 (0.84-0.96)]. It was less complex but equally accurate as two existing and validated models (0.86 [0.79-0.93] and 0.86 [0.77-0.95]). Using five indicators, C-statistic (95% CI) was moderate for prediction of overall morbidity [0.77 (0.72-0.83)], but high for severe morbidity [0.92 (0.88-0.97)]. Based on stratification rules of the ACT model, patient mortality and morbidity were 0.5% and 5.3% in the low-risk stratum (composing 64.6% of emergency caseload), and 15.9% and 29.0% in the very high-risk stratum (6.9% of caseload).

CONCLUSION

These findings show the practical feasibility of using a risk assessment tool to direct senior surgeons' involvement in emergency general surgery.