Fluid management and vasopressor use during colorectal surgery: the search for the optimal balance

BackgroundAlthough it is known that excessive intraoperative fluid and vasopressor agents are detrimental for anastomotic healing, optimal anesthesiology protocols for colorectal surgery are currently lacking.ObjectiveTo scrutinize the current hemodynamic practice and vasopressor use and their relation to colorectal anastomotic leakage.DesignA secondary analysis of a previously published prospective observational study: the LekCheck study.Study settingAdult patients undergoing a colorectal resection with the creation of a primary anastomosis.Outcome measuresColorectal anastomotic leakage (CAL) within 30 days postoperatively, hospital length of stay and 30-day mortality.ResultsOf the 1548 patients, 579 (37%) received vasopressor agents during surgery. Of these, 201 were treated with solely noradrenaline, 349 were treated with phenylephrine, and 29 received ephedrine. CAL rate significantly differed between the patients receiving vasopressor agents during surgery compared to patients without (11.8% vs 6.3%, p < 0.001). CAL was significantly higher in the group receiving phenylephrine compared to noradrenaline (14.3% vs 6%, p < 0.001). Vasopressor agents were used more often in patients treated with Goal Directed Therapy (47% vs 34.6%, p < 0.001). There was a higher mortality rate in patients with vasopressors compared to the group without (2.8% vs 0.4%, p = 0.01, OR 3.8). Mortality was higher in the noradrenaline group compared to the phenylephrine and those without vasopressors (5% vs. 0.4% and 1.7%, respectively, p < 0.001). In multivariable analysis, patients with intraoperative vasopressor agents had an increased risk to develop CAL (OR 2.1, CI 1.3-3.2, p = 0.001).ConclusionThe present study contributes to the evidence that intraoperative use of vasopressor agents is associated with a higher rate of CAL. This study helps to create awareness on the (necessity to) use of vasopressor agents in colorectal surgery patients in striving for successful anastomotic wound healing. Future research will be required to balance vasopressor agent dosage in view of colorectal anastomotic leakage

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

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

Radiomics preoperative-Fistula Risk Score (RAD-FRS) for pancreatoduodenectomy: development and external validation

Background: Accurately predicting the risk of clinically relevant postoperative pancreatic fistula after pancreatoduodenectomy before surgery may assist surgeons in making more informed treatment decisions and improved patient counselling. The aim was to evaluate the predictive accuracy of a radiomics-based preoperative-Fistula Risk Score (RAD-FRS) for clinically relevant postoperative pancreatic fistula. Methods: Radiomic features were derived from preoperative CT scans from adult patients after pancreatoduodenectomy at a single centre in the Netherlands (Amsterdam, 2013-2018) to develop the radiomics-based preoperative-Fistula Risk Score. Extracted radiomic features were analysed with four machine learning classifiers. The model was externally validated in a single centre in Italy (Verona, 2020-2021). The radiomics-based preoperative-Fistula Risk Score was compared with the Fistula Risk Score and the updated alternative Fistula Risk Score. Results: Overall, 359 patients underwent a pancreatoduodenectomy, of whom 89 (25 per cent) developed a clinically relevant postoperative pancreatic fistula. The radiomics-based preoperative-Fistula Risk Score model was developed using CT scans of 118 patients, of which three radiomic features were included in the random forest model, and externally validated in 57 patients. The model performed well with an area under the curve of 0.90 (95 per cent c.i. 0.71 to 0.99) and 0.81 (95 per cent c.i. 0.69 to 0.92) in the Amsterdam test set and Verona data set respectively. The radiomics-based preoperative-Fistula Risk Score performed similarly to the Fistula Risk Score (area under the curve 0.79) and updated alternative Fistula Risk Score (area under the curve 0.79). Conclusion: The radiomics-based preoperative-Fistula Risk Score, which uses only preoperative CT features, is a new and promising radiomics-based score that has the potential to be integrated with hospital CT report systems and improve patient counselling before surgery. The model with underlying code is readily available via www.pancreascalculator.com and www.github.com/PHAIR-Consortium/POPF-predictor

Early Miocene pollen and spores from western Jylland, Denmark - environmental and climatic implications

A palynological analysis of a Lower Miocene cored section from Sonder Vium in western Jylland, Denmark, provides new data regarding the vegetation and climate during the earliest Neogene. Most samples yielded well-preserved palynomorphs. Terrestrial pollen and spores dominate, with lesser proportions of dinoflagellates. A fluvial input into the marine setting is corroborated by the presence of freshwater algae, indicating, an inner-neritic setting. A level containing comparatively abundant dinoflagellate cysts probably represents a transgressional event. The late Aquitanian age of the sequence as suggested by previous studies is supported by the composition of the palynoflora, e.g., by the presence of Ephedripites, Platycarya, and the relatively frequent occurrence of Engelhardtia. The pollen record is dominated by Taxodiaceae-Cupressaceae suggesting that swamp forests dominated the onshore region, which is consistent with previous results from central and northern Europe. Besides Taxodium, the swamp forest also contained angiosperm taxa such as Myricaceae, Nyssa, Betula, and Alnus. Elevated or better drained hinterland areas hosted a diverse mesophytic forest, with a ground cover of reeds, sedges and pteridophytes. Abundant pollen taxa derived from mesophytic forests indicates the presence of evergreen conifers, such as Pinus, Sequoia and Sciadopitys, and deciduous angiosperms, including Fagus and Quercus. A decrease in relative abundances of thermophilous elements such as Arecaceae (palms), Ilex, Mastixiaceae and Engelhardtia, in the middle part of the studied succession indicates a possible correlation to the late Aquitanian climatic deterioration. The composition of the palynological assemblages including widely distributed Taxodium swamps, suggests a warm, frost-free temperate climate during the Aquitanian in Denmark