Machine learning models in clinical practice for the prediction of postoperative complications after major abdominal surgery

Complications after surgery have a major impact on short- and long-term outcomes, and decades of technological advancement have not yet led to the eradication of their risk. The accurate prediction of complications, recently enhanced by the development of machine learning algorithms, has the potential to completely reshape surgical patient management. In this paper, we reflect on multiple issues facing the implementation of machine learning, from the development to the actual implementation of machine learning models in daily clinical practice, providing suggestions on the use of machine learning models for predicting postoperative complications after major abdominal surgery

Implementation of robot-assisted Ivor Lewis procedure: Robotic hand-sewn, linear or circular technique?

Background: Robot-assisted surgery for esophageal cancer is increasingly applied. Despite this upsurge, the preferential technique to create a robot-assisted intrathoracic anastomosis has not been established. Data sources: Bibliographic databases were searched to identify studies that performed a robot-assisted Ivor Lewis esophagectomy and described the technical details of the anastomotic technique. Out of 1701 articles, 16 studies were included for systematic review. Conclusions: This review shows that all technique used to create a thoracoscopic anastomosis can be adopted to robotic surgery. Techniques can be divided into three categories: robotic hand-sewn, circular stapling or linear stapling and robotic hand-sewn closure of the stapler defect. With limited robotic experience, circular stapling might be the preferred technique, however requires a well-trained bedside assistant. The linear stapling technique or hand-sewn technique are more challenging but enable experienced robotic surgeons to perform a controlled anastomosis without bedside support

The effect of anastomotic leakage on the incidence of recurrence after tri-modality therapy for esophageal adenocarcinomas

Background: Neoadjuvant chemoradiotherapy (nCRTx) reduces the incidence of recurrence, while anastomotic leakage has shown increase the risk of recurrence. The primary objective of this retrospective study was to investigate the incidence and pattern of recurrence and secondary median recurrence-free interval and post-recurrence survival in patients with and without anastomotic leakage after multimodal therapy for esophageal adenocarcinoma. Methods: Patients with recurrence after multimodal therapy between 2010 and 2018 were included. Results: Six hundred and eighteen patients were included, 91 (14.7%) had leakage and 278 (45.0%) recurrence. Patients with leakage did not develop recurrence more often (48.4%) than those without (44.4%, [p = 0.484]). Recurrence-free interval for patients with (n = 44) and without leakage (n = 234) was 39 and 52 weeks, respectively (p = 0.049). Post-recurrence survival was 11 and 16 weeks, respectively (p = 0.702). Specified by recurrence site, post-recurrence survival for loco-regional recurrences was 27 versus 33 weeks (p = 0.387) for patients with and without leakage, for distant 9 versus 13 (p = 0.999), and for combined 11 versus 18 weeks (p = 0.492). Conclusion and Discussion: No higher incidence of recurrent disease was observed in patients with anastomotic leakage, however it is associated with a shorter recurrence-free interval. This could have implications for surveillance, as early detection of recurrent disease could influence therapeutic options

Machine learning versus logistic regression for the prediction of complications after pancreatoduodenectomy

BACKGROUND: Machine learning is increasingly advocated to develop prediction models for postoperative complications. It is, however, unclear if machine learning is superior to logistic regression when using structured clinical data. Postoperative pancreatic fistula and delayed gastric emptying are the two most common complications with the biggest impact on patient condition and length of hospital stay after pancreatoduodenectomy. This study aimed to compare the performance of machine learning and logistic regression in predicting pancreatic fistula and delayed gastric emptying after pancreatoduodenectomy. METHODS: This retrospective observational study used nationwide data from 16 centers in the Dutch Pancreatic Cancer Audit between January 2014 and January 2021. The area under the curve of a machine learning and logistic regression model for clinically relevant postoperative pancreatic fistula and delayed gastric emptying were compared. RESULTS: Overall, 799 (16.3%) patients developed a postoperative pancreatic fistula, and 943 developed (19.2%) delayed gastric emptying. For postoperative pancreatic fistula, the area under the curve of the machine learning model was 0.74, and the area under the curve of the logistic regression model was 0.73. For delayed gastric emptying, the area under the curve of the machine learning model and logistic regression was 0.59. CONCLUSION: Machine learning did not outperform logistic regression modeling in predicting postoperative complications after pancreatoduodenectomy

Identification and isolation of the FEEBLY gene from tomato by transposon tagging

The Ac/Ds transposon system from maize was used for insertional mutagenesis in tomato. Marker genes were employed for the selection of plants carrying a total of 471 unique Ds elements. Three mutants were obtained with Ds insertions closely linked to recessive mutations: feebly (fb), yellow jim (yj) and dopey (dp). The fb seedlings produced high anthocyanin levels, developed into small fragile plants, and were insensitive to the herbicide phosphinothricin. The yj plants had yellow leaves as a result of reduced levels of chlorophyll. The dp mutants completely or partially lacked inflorescences. The fb and yj loci were genetically linked to the Ds donor site on chromosome 3. Reactivation of the Ds element in the fb mutants by crosses with an Ac-containing line resulted in restoration of the wild-type phenotypes. Plant DNA fragments flanking both sides of the Ds element in the fb mutant were isolated by the inverse polymerase chain reaction. Molecular analysis showed that phenotypic reversions of fb were correlated with excisions of Ds. DNA sequence analysis of Fb reversion alleles showed the characteristic Ds footprints. Northern and cDNA sequence analysis indicated that transcription of the FEEBLY (FB) gene was impeded by the insertion of Ds in an intron. Comparison of the predicted amino acid sequence of the FB protein with other database sequences indicated that FB is a novel gene

Erratum to “Practice variation in anastomotic leak after esophagectomy:Unravelling differences in failure to rescue (vol 49, pg 974, 2023)

The publisher regrets that when the article was published the following collaboration authors from the “TENTACLE – Esophagus collaborative group” appeared incorrectly in the main author list due to a technical error: Writing Committee, Joos Heisterkamp, Fatih Polat, Jeroen Schouten, Pritam Singh, Study collaborators. This has now been corrected. The publisher would like to apologise for any inconvenience caused

Practice variation in anastomotic leak after esophagectomy: Unravelling differences in failure to rescue

Introduction: Failure to rescue (FTR) is an important outcome measure after esophagectomy and reflects mortality after postoperative complications. Differences in FTR have been associated with hospital resection volume. However, insight into how centers manage complications and achieve their outcomes is lacking. Anastomotic leak (AL) is a main contributor to FTR. This study aimed to assess differences in FTR after AL between centers, and to identify factors that explain these differences. Methods: TENTACLE – Esophagus is a multicenter, retrospective cohort study, which included 1509 patients with AL after esophagectomy. Differences in FTR were assessed between low-volume (<20 resections), middle-volume (20–60 resections) and high-volume centers (≥60 resections). Mediation analysis was performed using logistic regression, including possible mediators for FTR: case-mix, hospital resources, leak severity and treatment. Results: FTR after AL was 11.7%. After adjustment for confounders, FTR was lower in high-volume vs. low-volume (OR 0.44, 95%CI 0.2–0.8), but not versus middle-volume centers (OR 0.67, 95%CI 0.5–1.0). After mediation analysis, differences in FTR were found to be explained by lower leak severity, lower secondary ICU readmission rate and higher availability of therapeutic modalities in high-volume centers. No statistically significant direct effect of hospital volume was found: high-volume vs. low-volume 0.86 (95%CI 0.4–1.7), high-volume vs. middle-volume OR 0.86 (95%CI 0.5–1.4). Conclusion: Lower FTR in high-volume compared with low-volume centers was explained by lower leak severity, less secondary ICU readmissions and higher availability of therapeutic modalities. To reduce FTR after AL, future studies should investigate effective strategies to reduce leak severity and prevent secondary ICU readmission

Treatment of anastomotic leak after oesophagectomy for oesophageal cancer : large, collaborative, observational TENTACLE cohort study

Background: Anastomotic leak is a severe complication after oesophagectomy. Anastomotic leak has diverse clinical manifestations and the optimal treatment strategy is unknown. The aim of this study was to assess the efficacy of treatment strategies for different manifestations of anastomotic leak after oesophagectomy. Methods: A retrospective cohort study was performed in 71 centres worldwide and included patients with anastomotic leak after oesophagectomy (2011-2019). Different primary treatment strategies were compared for three different anastomotic leak manifestations: interventional versus supportive-only treatment for local manifestations (that is no intrathoracic collections; well perfused conduit); drainage and defect closure versus drainage only for intrathoracic manifestations; and oesophageal diversion versus continuity-preserving treatment for conduit ischaemia/necrosis. The primary outcome was 90-day mortality. Propensity score matching was performed to adjust for confounders. Results: Of 1508 patients with anastomotic leak, 28.2 per cent (425 patients) had local manifestations, 36.3 per cent (548 patients) had intrathoracic manifestations, 9.6 per cent (145 patients) had conduit ischaemia/necrosis, 17.5 per cent (264 patients) were allocated after multiple imputation, and 8.4 per cent (126 patients) were excluded. After propensity score matching, no statistically significant differences in 90-day mortality were found regarding interventional versus supportive-only treatment for local manifestations (risk difference 3.2 per cent, 95 per cent c.i. -1.8 to 8.2 per cent), drainage and defect closure versus drainage only for intrathoracic manifestations (risk difference 5.8 per cent, 95 per cent c.i. -1.2 to 12.8 per cent), and oesophageal diversion versus continuity-preserving treatment for conduit ischaemia/necrosis (risk difference 0.1 per cent, 95 per cent c.i. -21.4 to 1.6 per cent). In general, less morbidity was found after less extensive primary treatment strategies. Conclusion: Less extensive primary treatment of anastomotic leak was associated with less morbidity. A less extensive primary treatment approach may potentially be considered for anastomotic leak. Future studies are needed to confirm current findings and guide optimal treatment of anastomotic leak after oesophagectom