Development and validation of a nomogram for predicting post-operative abdominal infection in patients undergoing pancreaticoduodenectomy

A scoring model based on the pleural effusion adenosine deaminase-to-serum C-reactive protein ratio for differentiating tuberculous pleural effusion from non-tuberculous benign pleural effusion

BACKGROUND

Differentiating tuberculous pleural effusion (TPE) from non-tuberculous benign pleural effusion (non-TB BPE) can be challenging, especially in patients with low levels of pleural effusion adenosine deaminase (pADA) and negative etiological evidence. This study aimed to evaluate the diagnostic performance of the pADA to serum C-reactive protein ratio (pADA/sCRP) and to develop a scoring model for diagnosing TPE.

METHODS

This retrospective study included 364 patients with pleural effusion, comprising 121 with TPE and 243 with non-TB BPE from Peking Union Medical College Hospital. Clinical, laboratory, and imaging data were collected, and comparisons were made between the two groups. The diagnostic performance of the pADA/sCRP ratio and other statistically significant variables was assessed. Six valuable factors were selected for multivariate regression analysis to establish a predictive model, which was displayed as a nomogram.

RESULTS

The pADA/sCRP ratio demonstrated superior diagnostic performance compared to pADA alone, with an area under the curve (AUC), sensitivity, and specificity for identifying TPE of 0.68, 71%, and 64%, respectively. Six variables were selected to develop a nomogram, including night sweats, calcification on chest computed tomography, pleural effusion lymphocyte ratio, pADA/sCRP, hemoglobin, and neutrophil. With a cutoff value of 20 points, the AUC, sensitivity, and specificity for distinguishing TPE from non-TB BPE were 0.836, 83.4%, and 64.9%, respectively. The validation cohort confirmed the model with the AUC, sensitivity, and specificity of 0.815, 61.1%, and 82.4%, respectively.

CONCLUSION

The pADA/sCRP ratio exhibited improved diagnostic performance compared to pADA alone. The novel scoring system based on a nomogram demonstrated good diagnostic efficacy in differentiating TPE from non-TB BPE.

Risk stratification of postoperative pancreatic fistula and other complications following pancreatoduodenectomy. How far are we? A scoping review

PURPOSE

Pancreatoduodenectomy (PD) is a challenging procedure which is associated with high morbidity rates. This study was performed to make an overview of risk factors included in risk stratification methods both logistic regression models and models based on artificial intelligence algorithms to predict postoperative pancreatic fistula (POPF) and other complications following PD and to provide insight in the extent to which these tools were validated.

METHODS

Five databases were searched to identify relevant studies. Calculators, equations, nomograms, and artificial intelligence models that addressed POPF and other complications were included. Only PD resections were considered eligible. There was no exclusion of the minimally invasive techniques reporting PD resections. All other pancreatic resections were excluded.

RESULTS

90 studies were included. Thirty-five studies were related to POPF, thirty-five studies were related to other complications following PD and twenty studies were related to artificial intelligence predication models after PD. Among the identified risk factors, the most used factors for POPF risk stratification were the main pancreatic duct diameter (MPD) (80%) followed by pancreatic texture (51%), whereas for other complications the most used factors were age (34%) and ASA score (29.4%). Only 26% of the evaluated risk stratification tools for POPF and other complications were externally validated. This percentage was even lower for the risk models using artificial intelligence which was 20%.

CONCLUSION

The MPD was the most used factor when stratifying the risk of POPF followed by pancreatic texture. Age and ASA score were the most used factors for the stratification of other complications. Insight in clinically relevant risk factors could help surgeons in adapting their surgical strategy and shared decision-making. This study revealed that the focus of research still lies on developing new risk models rather than model validation, hampering clinical implementation of these tools for decision support.

A novel model based on clinical and computed tomography (CT) indices to predict the risk factors of postoperative major complications in patients undergoing pancreaticoduodenectomy

Background

Postoperative complications are prone to occur in patients after radical pancreaticoduodenectomy (PD). This study aimed to construct and validate a model for predicting postoperative major complications in patients after PD.

Methods

The clinical data of 360 patients who underwent PD were retrospectively collected from two centers between January 2019 and December 2023. Visceral adipose volume (VAV) and subcutaneous adipose volume (SAV) were measured using three-dimensional (3D) computed tomography (CT) reconstruction. According to the Clavien-Dindo classification system, the postoperative complications were graded. Subsequently, a predictive model was constructed based on the results of least absolute shrinkage and selection operator (LASSO) multivariate logistic regression analysis and stepwise (stepAIC) selection. The nomogram was internally validated by the training and test cohort. The discriminatory ability and clinical utility of the nomogram were evaluated by area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA).

Results

The major complications occurred in 13.3% (n = 48) of patients after PD. The nomogram revealed that high VAV/SAV, high system inflammation response index (SIRI), high triglyceride glucose-body mass index (TyG-BMI), low prognostic nutritional index (PNI) and CA199 ≥ 37 were independent risk factors for major complications. The C-index of this model was 0.854 (95%CI [0.800-0.907]), showing excellent discrimination. The calibration curve demonstrated satisfactory concordance between nomogram predictions and actual observations. The DCA curve indicated the substantial clinical utility of the nomogram.

Conclusion

The model based on clinical and CT indices demonstrates good predictive performance and clinical benefit for major complications in patients undergoing PD.

The clinical significance of intraoperative lavage fluid culture during pancreaticoduodenectomy on organ/space surgical site infection

Organ/space surgical site infection (SSI) are common after pancreaticoduodenectomy (PD). There is limited research on the clinical impact of intraoperative lavage fluid contamination in patients undergoing PD. One hundred five patients who underwent PD between August 2022 and July 2023 were retrospectively enrolled. The intraoperative bile and peritoneal lavage were collected for bacterial culture. Postoperative drainage bacterial cultures were performed every 2-3 days thereafter until drains were all removed. The bacteria isolated from intraoperative lavage fluid, intraoperative bile, and postoperative drainage fluid were examined in detail. The risk factors associated with positive intraoperative lavage fluid culture were analyzed through both univariate and multivariate analyses. Organ/space SSI occurred in 59(56.2%) of the 105 patients. The positivity rates of cultures in intraoperative lavage fluid, intraoperative bile, and postoperative drainage fluid were found to be 41.0%, 67.6%, and 84.8%, respectively. Patients with positive intraoperative lavage fluid culture had a significantly higher occurrence of organ/space SSI compared to the negative group (69.0% vs. 29.4%, P < 0.001). Preoperative biliary drainage (PBD) was identified as the only independent risk factor for the contamination of intraoperative lavage fluid (OR = 7.687, 95% CI: 2.164-27.300, P = 0.002). K. pneumoniae was the most common isolates both in the intraoperative lavage fluid and postoperative drainage fluid. Intraoperative lavage fluid contamination closely correlated with organ/space SSI after PD. Meanwhile, PBD was the only risk factor for the contamination of intraoperative lavage fluid.

Implications of the microbiome after pancreatic cancer resection with regard to morbidity and mortality

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with an extremely poor prognosis. The most common complications after a pancreaticoduodenectomy (PD) include surgical site infection (SSI), postoperative pancreatic fistula (POPF), and delayed gastric emptying (DGE). The potential role and mechanisms of microbial colonization of key surgical sites resulting in perioperative complications after PD remain to be fully elucidated. In this key paper evaluation, the role of different microbiota in perioperative morbidity and mortality following PD are discussed, and key microbial signatures are identified that may shape the future management of post-operative surgical care.

Meta-lasso: new insight on infection prediction after minimally invasive surgery

Surgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important factor influencing the direct and indirect economic implications, patient prognosis, and the 5-year survival rate for early-stage lung cancer patients. In the realm of predictive healthcare, machine learning algorithms have been instrumental in anticipating various surgical outcomes, including SSI. However, accurately predicting infection after minimally invasive surgery remains a clinical challenge due to the multitude of physiological and surgical factors associated with it. Furthermore, clinical patient data, in addition to being high-dimensional, often exists the long-tail problem, posing difficulties for traditional machine learning algorithms in effectively processing such data. Based on this insight, we propose a novel approach called meta-lasso for infection prediction following minimally invasive surgery. Our approach leverages the sparse learning algorithm lasso regression to select informative features and introduces a meta-learning framework to mitigate bias towards the dominant class. We conducted a retrospective cohort study on patients who had undergone minimally invasive surgery for lung cancer at Shanghai Chest Hospital between 2018 and 2020. The evaluation encompassed key performance metrics, including sensitivity, specificity, precision (PPV), negative predictive value (NPV), and accuracy. Our approach has surpassed the performance of logistic regression, random forest, Naive Bayes classifier, gradient boosting decision tree, ANN, and lasso regression, with sensitivity at 0.798, specificity at 0.779, precision at 0.789, NPV at 0.798, and accuracy at 0.788 and has greatly improved the classification performance of the inferior class.

Comparison of prognosis and postoperative morbidities between standard pancreaticoduodenectomy and the TRIANGLE technique for resectable pancreatic ductal adenocarcinoma

BACKGROUND

Radical surgery combined with systemic chemotherapy offers the possibility of long-term survival or even cure for patients with pancreatic ductal adenocarcinoma (PDAC), although tumor recurrence, especially locally, still inhibits the treatment efficacy. The TRIANGLE technique was introduced as an extended dissection procedure to improve the R0 resection rate of borderline resectable or locally advanced PDAC. However, there was a lack of studies concerning postoperative complications and long-term outcomes of this procedure on patients with resectable PDAC.

AIM

To compare the prognosis and postoperative morbidities between standard pancreaticoduodenectomy (PD) and the TRIANGLE technique for resectable PDAC.

METHODS

Patients with resectable PDAC eligible for PD from our hospital between June 2018 and December 2021 were enrolled in this retrospective cohort study. All the patients were divided into PDstandard and PDTRIANGLE groups according to the surgical procedure. Baseline characteristics, surgical data, and postoperative morbidities were recorded. All of the patients were followed up, and the date and location of tumor recurrence, and death were recorded. The Kaplan-Meier method and log-rank test were used for the survival analysis.

RESULTS

There were 93 patients included in the study and 37 underwent the TRIANGLE technique. Duration of operation was longer in the PDTRIANGLE group compared with the PDstandard group [440 (410-480) min vs 320 (265-427) min] (P = 0.001). Intraoperative blood loss [700 (500-1200) mL vs 500 (300-800) mL] (P = 0.009) and blood transfusion [975 (0-1250) mL vs 400 (0-800) mL] (P = 0.009) were higher in the PDTRIANGLE group. There was a higher incidence of surgical site infection (43.2% vs 12.5%) (P = 0.001) and postoperative diarrhea (54.1% vs 12.5%) (P = 0.001) in the PDTRIANGLE group. The rates of R0 resection and local recurrence, overall survival, and disease-free survival did not differ significantly between the two groups.

CONCLUSION

The TRIANGLE technique is safe, with acceptable postoperative morbidities compared with standardized PD, but it does not improve prognosis for patients with resectable PDAC.

Nomogram for predicting surgical site infections in elderly patients after open lumbar spine surgery: A retrospective study

The aim of this study is to develop a nomogram to assess the risk of surgical site infection in elderly patients undergoing open lumbar spine surgery and explore related risk factors. We reviewed the records of 578 elderly patients who had undergone open lumbar spine surgery. The clinical parameters were subjected to lasso regression and logistic regression analyses. Subsequently, a nomogram was constructed to predict the risk of postoperative surgical site infection and validated using bootstrap resampling. A total of 578 patients were included in the analysis, of which 17 were diagnosed as postoperative surgical site infection. Following the final logistic regression analysis, obesity, hypoalbuminemia and drinking history were identified as independent risk factors and subsequently incorporated into the nomogram. The nomogram demonstrated excellent discrimination, with an area under the receiver-operating characteristic curve of 0.879 (95% CI 0.769 ~ 0.989) after internal validation. The calibration curve exhibited a high level of consistency. Decision curve analysis revealed that this nomogram had greater clinical value when the risk threshold for surgical site infection occurrence was >1% and <89%. We had developed a nomogram for predicting the risk of postoperative surgical site infection in elderly patients who had undergone open lumbar spine surgery. Validation using bootstrap resampling demonstrated excellent discrimination and calibration, indicating that the nomogram may hold potential clinical utility as a simple predictive tool for healthcare professionals.

Antibiotic prophylaxis with piperacillin-tazobactam reduces organ/space surgical site infection after pancreaticoduodenectomy: a retrospective and propensity score-matched analysis

BACKGROUND

The occurrence of surgical site infection (SSI) after pancreaticoduodenectomy (PD) is still relatively high. The aim of this retrospective study is to evaluate the efficacy of piperacillin-tazobactam as perioperative prophylactic antibiotic on organ/space SSI for patients underwent PD.

METHODS

Four hundred seven consecutive patients who underwent PD between January 2018 and December 2022 were enrolled and analyzed retrospectively. The univariate and multivariate analysis were used to identify independent risk factors of organ/space SSI. Postoperative complications were compared between the two groups according to the use of prophylactic antibiotics by a ratio of 1:1 propensity score-matched (PSM) analysis.

RESULTS

Based on perioperative prophylactic antibiotic use, all 407 patients were divided into the ceftriaxone group (n = 192, 47.2%) and piperacillin-tazobactam group (n = 215, 52.8%). The rate of organ/space SSI was 31.2% with the choice of perioperative antibiotics (OR = 2.837, 95%CI = 1.802-4.465, P < 0.01) as one of independent risk factors. After PSM, there were similar baseline characteristics among the groups. Meanwhile, the piperacillin-tazobactam group had a significant lower rate of organ/space SSI compared to the ceftriaxone group both before and after PSM(P < 0.05).

CONCLUSIONS

The adoption of piperacillin-tazobactam as perioperative prophylaxis for patients underwent PD reduced organ/space SSI significantly.

Predicting survival and prognosis in early-onset locally advanced colon cancer: a retrospective observational study

OBJECTIVE

To predict cancer-specific survival, a refined nomogram model and brand-new risk-stratifying system were established to classify the risk levels of patients with early-onset locally advanced colon cancer (LACC).

METHODS

The clinical factors and survival outcomes of LACC cases from the SEER database from 2010 to 2019 were retrieved retrospectively. Early-onset and late-onset colon cancer were grouped according to the age (50 years old) at diagnosis. Differences between groups were compared to identify mutual significant variables. A multivariate Cox regression analysis was further performed and then constructed a nomogram. We compared it with the AJCC-TNM system. The external validation was performed for evaluation. Finally, a risk-stratifying system of patients with early-onset LACC was established.

RESULTS

A total of 32,855 LACC patients were enrolled in, 4548 (13.84%) patients were included in the early-onset LACC group, and 28,307 (86.16%) patients were included in the late-onset LACC group. The external validation set included 228 early-onset LACC patients. Early-onset colon cancers had poorer prognosis (T4, N2, TNM stage III, CEA, tumor deposit, and nerve invasion), and a higher proportion received radiotherapy and systemic therapy (P<0.001). In the survival analysis, cancer-specific survival (CSS) was better in patients with early-onset LACC than in those with late-onset LACC (P <0.001). This nomogram constructed based on the results of COX analysis showed better accuracy in CSS prediction of early-onset LACC patients than AJCC-TNM system in the training set and external validation set (0.783 vs 0.728; 0.852 vs 0.773).

CONCLUSION

We developed a novel nomogram model to predict CSS in patients with early-onset LACC it provided a reference in prognosis prediction and selection of individualized treatment, helping clinicians in decision-making.

Comparation between novel online models and the AJCC 8th TNM staging system in predicting cancer-specific and overall survival of small cell lung cancer

Background

Most of previous studies on predictive models for patients with small cell lung cancer (SCLC) were single institutional studies or showed relatively low Harrell concordance index (C-index) values. To build an optimal nomogram, we collected clinicopathological characteristics of SCLC patients from Surveillance, Epidemiology, and End Results (SEER) database.

Methods

24,055 samples with SCLC from 2010 to 2016 in the SEER database were analyzed. The samples were grouped into derivation cohort (n=20,075) and external validation cohort (n=3,980) based on America's different geographic regions. Cox regression analyses were used to construct nomograms predicting cancer-specific survival (CSS) and overall survival (OS) using derivation cohort. The nomograms were internally validated by bootstrapping technique and externally validated by calibration plots. C-index was computed to compare the accuracy and discrimination power of our nomograms with the 8th of version AJCC TNM staging system and nomograms built in previous studies. Decision curve analysis (DCA) was applied to explore whether the nomograms had better clinical efficiency than the 8th version of AJCC TNM staging system.

Results

Age, sex, race, marital status, primary site, differentiation, T classification, N classification, M classification, surgical type, lymph node ratio, radiotherapy, and chemotherapy were chosen as predictors of CSS and OS for SCLC by stepwise multivariable regression and were put into the nomograms. Internal and external validations confirmed the nomograms were accurate in prediction. C-indexes of the nomograms were relatively satisfactory in derivation cohort (CSS: 0.761, OS: 0.761) and external validation cohort (CSS: 0.764, OS: 0.764). The accuracy of the nomograms was superior to that of nomograms built in previous studies. DCA showed the nomograms conferred better clinical efficiency than 8th version of TNM staging system.

Conclusions

We developed practical nomograms for CSS (https://guowei2020.shinyapps.io/DynNom-CSS-SCLC/) and OS (https://drboidedwater.shinyapps.io/DynNom-OS-SCLC/) prediction of SCLC patients which may facilitate clinicians in individualized therapeutics.

Clinical Validation of the Comprehensive Complication Index in a Pancreaticoduodenectomy Cohort

INTRODUCTION

Although the Clavien-Dindo classification (CDC) is the most widely utilized method for quantifying surgical complications, it fails to properly capture all events. To address this, the comprehensive complication index (CCI) was introduced. The purpose of this study was to compare the CCI and CDC as predictors of postoperative length of stay (PLOS) and total hospitalization costs in patients undergoing pancreaticoduodenectomy (PD).

METHODS

Data were collected from February 2018 to February 2021. Complications were graded on the CDC scale and the CCI was calculated for each patient. The correlations between CDC and CCI with PLOS and hospitalization costs were compared. Linear analyses were performed to identify factors associated with PLOS and costs.

RESULTS

291 patients were enrolled with an average age of 61.2 years. 286 of them developed postoperative complications at CDC grade 1 (17.8%), 2 (59.9%), 3a (13.4%), 3b (4.5%), 4 (2.1%), and 5 (0.6%). Median CCI of the study cohort was 30.8. Spearman's correlation analysis showed the CDC and CCI were significantly correlated with PLOS and hospitalization costs, but the CCI showed a stronger correlation with PLOS (+0.552 day of stay for each additional CCI point; CCI: ρ = 0.663 vs. CDC: ρ = 0.581; p = 0.036). There were no significant differences in the correlations between total hospitalization costs and the CDC or CCI (CCI: ρ = 0.566 vs. CDC: ρ = 0.565; p = 0.78).

CONCLUSION

CCI is an accurate tool for quantifying morbidities after PD and shows a stronger correlation with PLOS compared with the CDC.