Scoring System to Predict the Risk of Surgical Site Infection in Patients with Esophageal Cancer after Esophagectomy with Cervical Anastomosis

Esophageal surgical Apgar score (eSAS): A predictor for postoperative morbidity in patients undergoing neoadjuvant therapy and esophagectomy

BACKGROUND

The surgical Apgar score (SAS) quantifying three intraoperative indexes has been confirmed to be significantly associated with postoperative morbidity and prognosis in many surgical specialties. However, there are great limitations in its application for esophageal cancer (EC). This study aimed to assess the predictive capability of esophagectomy SAS (eSAS) in determining postoperative morbidity and overall survival (OS) in EC patients who had undergone neoadjuvant therapy.

METHODS

A retrospective evaluation was conducted on a cohort of 221 patients in which surgery- and tumor-related data were extracted and analyzed. Major morbidity was defined as complications meeting the criteria of Clavien-Dindo classification III or higher during hospitalization. Univariate and multivariate analyses were performed to identify potential risk factors for major morbidity. Kaplan-Meier analysis was utilized to calculate the OS and relapse-free survival (RFS).

RESULTS

The results exhibited that eSAS demonstrated potential predictive value for postoperative morbidity with an optimal cutoff value of 6. The eSAS and diabetes mellitus were two independent risk factors for the major morbidity; however, no correlation between the eSAS and the OS or RFS was detected.

CONCLUSION

The eSAS could be used as a predictor of major morbidity, while it was not correlated with OS and RFS.

Prediction models of surgical site infection after gastrointestinal surgery: a nationwide prospective cohort study

OBJECTIVE

This study aimed to construct and validate a clinical prediction model for surgical site infection (SSI) risk 30 days after gastrointestinal surgery.

MATERIALS AND METHODS

This multicentre study involving 57 units conducted a 30-day postoperative follow-up of 17 353 patients who underwent gastrointestinal surgery at the unit from 1 March 2021 to 28 February 2022. The authors collected a series of hospitalisation data, including demographic data, preoperative preparation, intraoperative procedures and postoperative care. The main outcome variable was SSI, defined according to the Centres for Disease Control and Prevention guidelines. This study used the least absolute shrinkage and selection operator (LASSO) algorithm to screen predictive variables and construct a prediction model. The receiver operating characteristic curve, calibration and clinical decision curves were used to evaluate the prediction performance of the prediction model.

RESULTS

Overall, 17 353 patients were included in this study, and the incidence of SSI was 1.6%. The univariate analysis combined with LASSO analysis showed that 20 variables, namely, chronic liver disease, chronic kidney disease, steroid use, smoking history, C-reactive protein, blood urea nitrogen, creatinine, albumin, blood glucose, bowel preparation, surgical antibiotic prophylaxis, appendix surgery, colon surgery, approach, incision type, colostomy/ileostomy at the start of the surgery, colostomy/ileostomy at the end of the surgery, length of incision, surgical duration and blood loss were identified as predictors of SSI occurrence ( P <0.05). The area under the curve values of the model in the train and test groups were 0.7778 and 0.7868, respectively. The calibration curve and Hosmer-Lemeshow test results demonstrated that the model-predicted and actual risks were in good agreement, and the model forecast accuracy was high.

CONCLUSIONS

The risk assessment system constructed in this study has good differentiation, calibration and clinical benefits and can be used as a reference tool for predicting SSI risk in patients.

Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting

The objective of this work was to predict the risk of mortality rate in patients with coronary artery bypass grafting (CABG) based on the risk prediction model of CABG using artificial intelligence (AI) and big data technologies. The clinical data of 2,364 patients undergoing CABG in our hospital from January 2019 to August 2021 were collected in this work. Based on AI and big data technology, business requirement analysis, system requirement analysis, complication prediction module, big data mining technology, and model building are carried out, respectively; the successful CABG risk prediction system includes case feature analysis service, risk warning service, and case retrieval service. The commonly used precision, recall, and F1-score were adopted to evaluate the quality of the gradient-boosted tree (GBT) model. The analysis proved that the GBT model was the best in terms of precision, F1-score, and area under the receiver operating characteristic curve (ROC). According to the CABG risk prediction model, 1,382 patients had a score of <0, 463 patients had a score of 0 ≤ score ≤ 2, 252 patients had a score of 2 < score ≤ 5, and 267 patients had a score of >5, which were stratified into four groups: A, B, C, and D. The actual number of in-hospital deaths was 25, and the in-hospital mortality rate was 1.05%. The mortality rate predicted by the CABG risk prediction model was 2.67 ± 1.82% (95% confidential interval (CI) (2.87-2.98)), which was higher than the actual value. The CABG risk prediction model showed the credible results only in group B with AUC = 0.763 > 0.7. In group B, 3 patients actually died, the actual mortality rate was 0.33%, and the predicted mortality rate was 0.96 ± 0.78 (95% CI (0.82-0.87)), which overestimated the mortality rate of patients in group B. It successfully constructed a CABG risk prediction model based on the AI and big data technologies, which would overestimate the mortality of patients with intermediate risk, and it is suitable for different types of heart diseases through continuous research and development and innovation, and provides clinical guidance value.

Prospective study of surgical site infections post-open esophageal cancer surgery, and the impact of care bundles

SSIs represent common infection-related morbidity following major surgery. Modern care bundles have been established as prophylactic measures aimed at preventing SSI occurring postoperatively. SSI incidence and data on common culprit pathogens post-esophagectomy for cancer have not been previously reported. Patients (2013-2018) treated with curative intent were studied. SSI was defined as per the Center for Disease Control (CDC) definition. A care bundle pathway following the National Institute for Clinical Excellence (NICE) guidelines for prevention of SSIs was introduced in 2013 and was audited quarterly. Risk factors and associations of SSIs were analyzed, as was the prevalence of isolated pathogens. Multivariable logistic regression examined independently predictive factors of SSIs and oncologic outcomes. Of 343 patients, 34 (9.9%) developed a postoperative SSI, with a median (range) of 8 (6-17). Quarterly audit carried out over 6 years showed no significant annual variance or trend. The most prevalent pathogen cultured was Methicillin-sensitive Staphylococcus aureus (MSSA) in nine patients (32%) followed by Candida albicans (29%), Escherichia coli (14%), and Enterococcus faecium (11%). SSI was significantly associated with pneumonia (P = 0.001), respiratory failure (P = 0.014), atrial fibrillation (P = 0.004), anastomotic leak (P < 0.001), and in-hospital blood transfusions (P = 0.031). SSI did not impact the overall survival (P = 0.951). SSI rates can be maintained at less than 10% using strict care bundles and regular audit. The most common culprit pathogen is gram-positive MSSA representing 32% of cases. These data are novel and may represent a modern benchmark for SSI post-open esophagectomy for cancer. This study highlights the incidence and associations of SSI post-esophageal cancer surgery.

Complications After Immediate 2-Stage Tissue Expander/Implant Breast Reconstruction: A Deeper Look at the Second Stage

BACKGROUND

Complications after 2-stage tissue expander/implant breast reconstruction have been studied as outcomes of a single procedure. We separately evaluated complications after the second stage and assessed factors associated with the outcomes of the second stage of breast reconstruction.

METHODS

Patients who underwent immediate 2-stage breast reconstruction between February 2010 and April 2017 were retrospectively reviewed. Patient demographics, surgical factors of the first stage of breast reconstruction, and complications and number of revision surgeries after the second stage were recorded. Factors associated with postoperative complications were analyzed, and a risk-scoring system was devised.

RESULTS

We analyzed 619 patients who underwent 653 immediate 2-stage breast reconstructions. Multivariate analysis showed that complications were associated independently with smoking history, radiotherapy, and a final inflation volume of 450 mL or greater. Each factor contributed 1 point in the creation of a risk-scoring system. The overall complication rate was increased as the risk score increased (1.2%, 4.7%, and 16.0% for 0, 1, and 2 risk scores, respectively, P < 0.001). Revision operation rate was also significantly different across the 3 groups (0.2%, 1.6%, and 12.0% for 0, 1, and 2 risk scores, respectively, P < 0.001). The area under the receiver operating characteristic curve was 0.732 and 0.731 for the logistic regression model and risk-scoring system, respectively (P = 0.975).

CONCLUSIONS

In the second stage of immediate 2-stage tissue expander/implant breast reconstruction, the rate of complication and revision surgery can be predicted by a novel risk-scoring system. Greater attention and preventive measures for complications are needed for high-risk patients.

Hypoalbuminemia as Surrogate and Culprit of Infections

Hypoalbuminemia is associated with the acquisition and severity of infectious diseases, and intact innate and adaptive immune responses depend on albumin. Albumin oxidation and breakdown affect interactions with bioactive lipid mediators that play important roles in antimicrobial defense and repair. There is bio-mechanistic plausibility for a causal link between hypoalbuminemia and increased risks of primary and secondary infections. Serum albumin levels have prognostic value for complications in viral, bacterial and fungal infections, and for infectious complications of non-infective chronic conditions. Hypoalbuminemia predicts the development of healthcare-associated infections, particularly with Clostridium difficile. In coronavirus disease 2019, hypoalbuminemia correlates with viral load and degree of acute lung injury and organ dysfunction. Non-oncotic properties of albumin affect the pharmacokinetics and pharmacodynamics of antimicrobials. Low serum albumin is associated with inadequate antimicrobial treatment. Infusion of human albumin solution (HAS) supplements endogenous albumin in patients with cirrhosis of the liver and effectively supported antimicrobial therapy in randomized controlled trials (RCTs). Evidence of the beneficial effects of HAS on infections in hypoalbuminemic patients without cirrhosis is largely observational. Prospective RCTs are underway and, if hypotheses are confirmed, could lead to changes in clinical practice for the management of hypoalbuminemic patients with infections or at risk of infectious complications.

The impact of skeletal muscle wasting during neoadjuvant chemotherapy on postoperative anastomotic leakage in patients with esophageal cancer

BACKGROUND

Sarcopenia is defined by low muscle mass and low muscle strength and is a prognostic factor of unfavorable outcomes in various diseases. The purpose of this study is to examine the correlation between skeletal muscle wasting (SMW) during neoadjuvant chemotherapy (NAC) and postoperative complications in patients with esophageal cancer, particularly in relation to anastomotic leakage.

METHODS

The present study involved 99 patients with thoracic esophageal cancer and esophago-gastric junctional cancer who received NAC followed by radical esophagectomy between August 2008 to June 2019, and who were pStage 0-III. Patient demographics and clinical variables were retrospectively reviewed. For assessing the extent of SMW, the rate of change in skeletal muscle mass index (SMI) was measured from CT images at the level of the third lumbar vertebra. Factors associated with postoperative complications were also examined.

RESULTS

The median rate of change in total SMI in patients was - 1.87%. The decreased rates in SMI of the side abdominal muscles and rectus abdominis were significantly greater than that of the psoas major (side abdominal muscles: p = 0.0084, rectus abdominis: p = 0.036). Multivariate analysis showed a decreased rate in SMI, especially in the erector spinae muscle, and the Charlson comorbidity index (CCI) was significantly associated with Grade IIIa of higher anastomotic leakage (Grade ≥ IIIa) (SMI cutoff (favorable): ≤ - 7.84, p = 0.0040; CCI cutoff (favorable): ≥ 2, p = 0.0032).

CONCLUSION

In patients with esophageal cancer, SMI tend to decrease during NAC treatment. It is therefore important to prevent the additional impact that SMW during NAC has on postoperative anastomotic leakage.

The Change of Laboratory Tests Could Be Predictive Factors for Infection after McKeown Esophagogastrectomy

Aim

To analyze whether the change of laboratory tests (postoperative day 1 (POD1) minus pre-operation) could be predictive factors for postoperative infection in patients who have undergone McKeown esophagogastrectomy.

Methods

We retrospectively investigated the clinical data of 358 patients who have undergone McKeown esophagogastrectomy, and divided them into infection and noninfection groups. SPSS 22.0 software was performed for data analysis.

Results

In the two groups, smoking status (66.7% vs. 42.3%; P = 0.014), male gender (86.1% vs. 72.0%; P < 0.001), hoarseness (23.6% vs. 8.7%; P < 0.001), poor coughing ability (51.4% vs. 9.1%; P < 0.001), the change of WBC count (5.59 ± 4.75 × 10⁹/L vs. 4.51 ± 4.11 × 10⁹/L; P = 0.05), the change of glucose (6.03 ± 3.97 g/L vs. 3.78 ± 3.18 g/L), the change of ALB (−12.83 ± 3.45 g/L vs. −10.69 ± 3.86 g/L), the change of CRE (0.17 ± 19.94 umol/L vs. −4.02 ± 15.40 umol/L, P = 0.047) were significantly different. These factors were assessed using logistic regression analysis, and factors with P ≤ 0.05 in the univariate analysis were entered into multivariate analysis based on the forward stepwise (conditional) method. Poor coughing ability (odds ratio [OR], 11.034, 95% confidence interval [CI], 5.358–22.724), smoking status (OR, 4.218; 95% CI, 2.110–8.431), the change of WBC count (OR, 1.079; 95% CI, 1.000–1.164), the change of serum ALB level (OR, 0.849; 95% CI, 0.772–0.935), and the change of blood glucose levels (OR, 1.237; 95% CI, 1.117–1.371) were determined as independent risk factors for postoperative infection. We established a scoring system based on these 5 factors, and the area under the curve for this predictive model was 0.843 (range, 0.793–0.894); the sensitivity, specificity, and cut-off score were 70.8%, 85.3%, and 2.500, respectively.

Conclusion

Poor coughing ability, smoking habit, the high change of WBC and blood glucose levels, and low change of serum ALB levels can be used to predict the occurrence of postoperative infections among patients who have undergone McKeown esophagogastrectomy.

Evaluation of preoperative risk factors and postoperative indicators for anastomotic leak of minimally invasive McKeown esophagectomy: a single-center retrospective analysis

BACKGROUND

Minimally invasive McKeown esophagectomy is an important surgical approach for esophageal cancer. Anastomotic leak is one of its common and serious complications. We assumed that the preoperative risk factors and postoperative indicators would predict or detect anastomotic leak.

METHODS

Between December 2016 and July 2017, patients underwent minimally invasive McKeown esophagectomy were identified and their preoperative variables and postoperative test indicators were recorded. Fisher's exact test, 2-tailed unpaired t test, nonparametric test and logistic regression were used to compare these datum between patients with or without anastomotic leak (AL). Receiver Operator Characteristic (ROC) curve was used to identify the best cut-off value of drainage amylase concentration for distinguishing anastomotic leak.

RESULTS

In all the 96 patients included, 12 patients were diagnosed as anastomotic leak by the esophagram. No differences in preoperative variables were observed between patients with and without AL. Patients in AL group appeared to have a lower prealbumin concentration in AL group on POD (postoperative day) 4(P = 0.05), POD 5(P = 0.04), POD 6 (P = 0.06). Prealbumin concentration cutoff value of 128 g/L on postoperative day 5 is 100.00% sensitive and 50.00% specific for predicting esophageal leaks. Drain amylases levels were higher in patients with anastomotic leak than those without anastomotic leak on POD 3(P = 0.03), POD 4(P = 0.01), POD 5(P < 0.001), POD 6(P < 0.001). The drain amylase cutoff value of 85 IU/L on postoperative day 4 was 75.00% sensitive and 84.00% specific for detecting esophageal leaks; the cutoff value of 65 IU/L on postoperative day 5 was 91.67% sensitive and 80.77% specific. The cutoff of 55/L on POD 6 is 100% sensitive and 86.96% specific.

CONCLUSION

Drainage amylase concentration on postoperative days may help to discover anastomotic leak in early stage after minimally invasive McKeown esophagectomy. Prealbumin concentration below 128 g/L on POD 5 might be potential risk factor for anastomotic leak.