Risk Of Emergency Surgery Research Articles

The early biomarker of immature granulocyte count in predicting right-side colonic complicated acute diverticulitis: a retrospective cohort study

ObjectiveEarly identification of complicated acute diverticulitis(cAD) is especially significant for clinical physician and surgeon to reduce the antibiotic usage and the risk of emergency surgery. This study was aimed to investigate the significance of immature granulocyte(IG) count in early prediction for right-side(Rt-side) cAD.MethodsThe patients with Rt-side colonic acute diverticulitis was enrolled between January, 2019 and March, 2024, and divided into complicated and simple acute diverticulitis group(cAD and sAD). The data about demographic, clinical and laboratory parameters were collected and compared. Logistic regression analysis and receiver operator characteristic(ROC) curves were used to assess the predictive values of these parameters for Rt-side complicated diverticulitis.Results289 participants who met the inclusion criteria were followed as 31 patients in cAD group and 258 in sAD group. Compared to sAD group, cAD group had the higher body mass index(BMI) and peripheral blood routine parameters, especially IG count, systemic immune inflammation index(SII) and neutrophil-to-lymphocyte ratio(NLR), with the statistically significant differences(P<0.001). Moreover, logistic regression analysis indicated that IG count was a significant and independent predictors for cAD(OR 4.92, 95%CI 3.86–8.39). In the ROC analysis, area under the ROC curves (AUC) was found for IG count(0.93(95%CI 0.88–0.99) ) and SII(0.88(95%CI 0.820–0.95)). The optimal cut-off value of IG count was 0.10 with the largest sensitivity of 80.60% and specificity of 100.00% for identifying Rt-side colonic complicated diverticulitis.ConclusionIG count was a more comparable and independent predictor for Rt-side colonic complicated diverticulitis with a largest AUC than other markers in complete blood count (CBC). Given its early arise, easy accessibility and no-radiation, it can largely convince physicians’ decision-making of antibiotic abuse and surgeons’ early intervention in Rt-side colonic cAD.

Despite multi-disciplinary team discussions the socioeconomic disparities persist in the oncological treatment of non-metastasized colorectal cancer

BackgroundThe introduction of national guidelines should eliminate previously observed associations between socioeconomic status (SES) and colorectal cancer treatment. The aim of the study was to investigate whether inequalities remain. MethodsCRCBaSe, a register-linkage originating from the Swedish Colorectal Cancer Registry, was used to identify information on patient and tumour characteristics, for 83,460 patients with stage I-III disease diagnosed 2008–2021. SES was measured as disposable income (quartiles) and the highest level of education. Outcomes of interest were emergency surgery, multidisciplinary team (MDT) conference discussion, and oncological treatment. Differences in treatment between SES groups were explored using multivariable logistic regression adjusted for year of diagnosis, age at diagnosis, sex, civil status, comorbidities, tumour location and stage. ResultsPatients in the highest income quartile had a lower risk of emergency surgery (OR 0.73 95%CI 0.68–0.80), a higher chance of being discussed at the preoperative (OR 1.39 95%CI 1.28–1.51) and postoperative MDT (OR 1.41 95%CI 1.30–1.53), receiving neoadjuvant (OR 1.15 95%CI 1.06–1.25) and adjuvant treatment (OR 2.04 95%CI 1.88–2.20). Higher education level increased the odds of MDT discussion but was not associated with oncological treatment. The proportion of patients discussed at the MDT increased, with almost all patients discussed since 2016. Despite this, treatment differences remained when patients diagnosed since 2016 were analysed separately. ConclusionThere were significant differences in how patients with different SES were treated for colorectal cancer. Further action is required to investigate the drivers of these differences as well as their impact on mortality and, ultimately, eliminate the inequalities.

Comparative outcomes of acute colonic diverticulitis in immunocompromised versus immunocompetent patients: a systematic review and meta-analysis.

Immunocompromised patients with acute colonic diverticulitis are at high risk for complications and failure of non-surgical treatment. However, evidence on the comparative outcomes of immunocompromised and immunocompetent patients with diverticulitis is lacking. This systematic review and meta-analysis investigated the outcomes of medical treatment in immunocompromised and immunocompetent patients with diverticulitis. A comprehensive literature search was conducted in PubMed, Embase, and the Cochrane Library. Studies comparing the clinical outcomes of immunocompromised and immunocompetent patients with diverticulitis were included. A total of 10 studies with 1,946,461 subjects were included in the quantitative synthesis. The risk of emergency surgery and postoperative mortality after emergency surgery was significantly higher in immunocompromised patients than in immunocompetent patients with diverticulitis (risk ratio [RR], 1.76; 95% confidence interval [CI], 1.31-2.38 and RR, 3.05; 95% CI, 1.70-5.45, respectively). Overall risk of complications associated with diverticulitis was non-significantly higher in immunocompromised than in immunocompetent patients (RR, 1.24; 95% CI, 0.95-1.63). Overall mortality irrespective of surgery was significantly higher in immunocompromised than in immunocompetent patients with diverticulitis (RR, 3.65; 95% CI, 1.73-7.69). By contrast, postoperative mortality after elective surgery was not significantly different between immunocompromised and immunocompetent patients with diverticulitis. In subgroup analysis, the risk of emergency surgery and recurrence was significantly higher in immunocompromised patients with complicated diverticulitis, whereas no significant difference was shown in mild disease. Immunocompromised patients with diverticulitis should be given the best medical treatment with multidisciplinary approach because they had increased risks of surgery, postoperative morbidity, and mortality than immunocompetent patients.

The Outcome Of Sigmoid Volvulus Cases: A Single Centre Experiences Over 8 Years

Introduction&#x0D; Sigmoid volvulus is one of the causes of large bowel obstruction. Its management can be challenging because of its prevalence in high-risk individuals. This study was designed to review the management and outcome of all patients admitted with sigmoid volvulus.&#x0D; Methods&#x0D; A retrospective review of all patients admitted at Hospital Sultanah Nur Zahirah, Terengganu, for Sigmoid Volvulus from January 2015 to December 2022 was performed. The data was extracted from Hospital Information System (HIS) and analysed using SPSS 27.&#x0D; Results&#x0D; Twenty-four patients were admitted, a total of 41 admissions for sigmoid volvulus during the study periods. The majority of the patients (n=16, 66.7%) were male and (n=8,33.3%) were female. Seven (29.2%) patients underwent emergency surgery on the presentation, and three (12.5%) patients died on admission due to septic shock. The remaining 14 (58.3%) were managed by endoscopic decompression. 13 (92.9%) patients had successful decompression procedures, and one patient (7.1%) failed, which required emergency surgery. About seven patients (53.8%) were readmitted for recurrence of sigmoid volvulus after successful decompression on initial admission, in which subsequently all of them required emergency surgery. The remaining six (46.2%) did not experience any recurrence episodes, and three (50%) of them underwent subsequent elective surgery. In our series, three patients died on initial presentation due to perforation and septic shock without any intervention, two patients died after emergency surgery due to septic shock and multi-organ failure, and one patient died due to covid 19 pneumonia. There was no mortality after elective surgery.&#x0D; Conclusion&#x0D; Sigmoid volvulus is a surgical emergency in which the majority (58.3%) can be successfully decompressed non-operatively. Emergency surgery in these patients is associated with 13.3% mortality in our series. Elective definitive surgery is suggested in view of the high recurrence rate (&gt;50%) and considerable risk of emergency surgery.

Diverticulitis with abscess formation: Outcomes of non-operative management and nomogram for predicting emergency surgery: The Diplicab Study Collaborative Group

BackgroundTo assess short- and long-term outcomes from non-surgical management of diverticulitis with abscess formation and to develop a nomogram to predict emergency surgery. MethodsThis nationwide retrospective cohort study was performed in 29 Spanish referral centers, including patients with a first episode of a diverticular abscess (modified Hinchey Ib–II) from 2015 to 2019. Emergency surgery, complications, and recurrent episodes were analyzed. Regression analysis was used to assess risk factors, and a nomogram for emergency surgery was designed. ResultsOverall, 1,395 patients were included (1,078 Hinchey Ib and 317 Hinchey II). Most (1,184, 84.9%) patients were treated with antibiotics without percutaneous drainage, and 194 (13.90%) patients required emergency surgery during admission. Percutaneous drainage (208 patients) was associated with a lower risk of emergency surgery in patients with abscesses of ≥5 cm (19.9% vs 29.3%, P = .035; odds ratio 0.59 [0.37–0.96]). The multivariate analysis showed that immunosuppression treatment, C-reactive protein (odds ratio: 1.003; 1.001–1.005), free pneumoperitoneum (odds ratio: 3.01; 2.04–4.44), Hinchey II (odds ratio: 2.15; 1.42–3.26), abscess size 3 to 4.9 cm (odds ratio: 1.87; 1.06–3.29), abscess size ≥5 cm (odds ratio: 3.62; 2.08–6.32), and use of morphine (odds ratio: 3.68; 2.29–5.92) were associated with emergency surgery. A nomogram was developed with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval: 0.77–0.85). ConclusionPercutaneous drainage must be considered in abscesses ≥5 cm to reduce emergency surgery rates; however, there are insufficient data to recommend it in smaller abscesses. The use of the nomogram could help the surgeon develop a targeted approach.

Artificial Intelligence versus Surgeon Gestalt in Predicting Risk of Emergency General Surgery.

Artificial Intelligence (AI) risk prediction algorithms such as the smartphone-available POTTER for emergency general surgery (EGS) are superior to traditional risk calculators because they account for complex nonlinear interactions between variables, but how they compare to surgeons' gestalt remains unknown. Herein, we sought to: (1) compare POTTER to surgeons' surgical risk estimation and (2) assess how POTTER influences surgeons' risk estimation. A total of 150 patients who underwent EGS at a large quaternary care center between May 2018 and May 2019 were prospectively followed for 30-day postoperative outcomes (mortality, septic shock, ventilator dependence, bleeding requiring transfusion, pneumonia), and clinical cases were systematically created representing their initial presentation. POTTER's outcome predictions for each case were also recorded. Thirty acute care surgeons with diverse practice settings and levels of experience were then randomized into 2 groups: 15 surgeons (SURG) were asked to predict the outcomes without access to POTTER's predictions while the remaining 15 (SURG-POTTER) were asked to predict the same outcomes after interacting with POTTER. Comparing to actual patient outcomes, the Area Under the Curve (AUC) methodology was used to assess the predictive performance of 1) POTTER vs. SURG, and 2) SURG vs. SURG-POTTER. POTTER outperformed SURG in predicting all outcomes (mortality - AUC: 0.880 vs. 0.841; ventilator dependence - AUC: 0.928 vs. 0.833; bleeding - AUC: 0.832 vs. 0.735; pneumonia - AUC: 0.837 vs. 0.753) except septic shock (AUC: 0.816 vs 0.820). SURG-POTTER outperformed SURG in predicting mortality (AUC: 0.870 vs 0.841), bleeding (AUC: 0.811 vs 0.735), pneumonia (AUC: 0.803 vs 0.753) but not septic shock (AUC: 0.712 vs 0.820) or ventilator dependence (AUC: 0.834 vs 0.833). The AI risk calculator POTTER outperformed surgeons' gestalt in predicting the postoperative mortality and outcomes of EGS patients, and when used, improved the individual surgeons' risk prediction. AI algorithms such as POTTER could prove useful as a bedside adjunct to surgeons when preoperatively counselling patients. Level II, Prognostic/Epidemiological.

Surgical Management of the Primary Tumor in Stage IV Small Intestinal Neuroendocrine Tumors: To Operate or Not to Operate, That Is the Question

Small intestinal neuroendocrine tumors (SI-NET) are rare tumors, often with distant metastases at diagnosis. The objective of this review is to provide an overview of the latest literature regarding surgical management of the primary tumor in stage IV SI-NET. Primary tumor resection (PTR) seems to be associated with improved survival in patients with stage IV SI-NET, independent of treatment of distant metastases. A watch and wait approach of the primary tumor increases the risk of needing an emergency resection. PTR improves survival in patients with stage IV SI-NET, decreases the risk of emergency surgery, and should be considered in all patients with stage IV disease and unresectable liver metastasis.

Prospective multicenter external validation of postoperative mortality prediction tools in patients undergoing emergency laparotomy.

Accurate preoperative risk assessment in emergency laparotomy (EL) is valuable for informed decision making and rational use of resources. Available risk prediction tools have not been validated adequately across diverse health care settings. Herein, we report a comparative external validation of four widely cited prognostic models. A multicenter cohort was prospectively composed of consecutive patients undergoing EL in 11 Greek hospitals from January 2020 to May 2021 using the National Emergency Laparotomy Audit (NELA) inclusion criteria. Thirty-day mortality risk predictions were calculated using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), NELA, Portsmouth Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (P-POSSUM), and Predictive Optimal Trees in Emergency Surgery Risk tools. Surgeons' assessment of postoperative mortality using predefined cutoffs was recorded, and a surgeon-adjusted ACS-NSQIP prediction was calculated when the original model's prediction was relatively low. Predictive performances were compared using scaled Brier scores, discrimination and calibration measures and plots, and decision curve analysis. Heterogeneity across hospitals was assessed by random-effects meta-analysis. A total of 631 patients were included, and 30-day mortality was 16.3%. The ACS-NSQIP and its surgeon-adjusted version had the highest scaled Brier scores. All models presented high discriminative ability, with concordance statistics ranging from 0.79 for P-POSSUM to 0.85 for NELA. However, except the surgeon-adjusted ACS-NSQIP (Hosmer-Lemeshow test, p = 0.742), all other models were poorly calibrated ( p < 0.001). Decision curve analysis revealed superior clinical utility of the ACS-NSQIP. Following recalibrations, predictive accuracy improved for all models, but ACS-NSQIP retained the lead. Between-hospital heterogeneity was minimum for the ACS-NSQIP model and maximum for P-POSSUM. The ACS-NSQIP tool was most accurate for mortality predictions after EL in a broad external validation cohort, demonstrating utility for facilitating preoperative risk management in the Greek health care system. Subjective surgeon assessments of patient prognosis may optimize ACS-NSQIP predictions. Diagnostic Test/Criteria; Level II.

The impact of a patient's social network on emergency surgery for colon cancer.

The aim of this study was to investigate if patients with a weak social network and colon cancer are more likely to be operated as an emergency than those with a strong social network. Data from patients living in Västerbotten County, Sweden, who underwent colon cancer surgery between 2007 and 2020 were extracted from the Swedish Colorectal Cancer Registry (SCRCR). Patients identified were matched against the Västerbotten Intervention Program (VIP) and the longitudinal study Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA). These two databases include a survey that includes questions regarding quality and size of the patient's social network. Multivariable logistic regression was used for analysis. Six items from the questions on social network, and the composite variables availability of social integration (AVSI) and availability of attachment (AVAT) were analysed. Data from 801 patients were analysed. The odds ratio for emergency surgery was significantly higher for divorced patients (OR 2.01 (CI 1.03-3.91)) and for male gender (OR 1.51 (CI 1.02-2.24)). A higher OR was seen amongst those with no-one to share feelings with (OR 1.57 (CI 0.82-3.03)) or to comfort them (OR1.33 (CI 0.78-2.28)). Quantitative aspects of social life such as the number of people greater than 10 that feel relaxed at the patient's home, showed a lower OR (OR 0.71(CI 0.35-1.43)). The impact of social network on the risk for emergency surgery for colon cancer is limited. Divorced status and male gender were associated with an increased risk for emergency surgery.

The use of POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator to predict mortality and complications in patients submitted to Emergency Surgery.

the ability of the care team to reliably predict postoperative risk is essential for improvements in surgical decision-making, patient and family counseling, and resource allocation in hospitals. The Artificial Intelligence (AI)-powered POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator represents a user-friendly interface and has since been downloaded in its iPhone and Android format by thousands of surgeons worldwide. It was originally developed to be used in non-traumatic emergency surgery patients. However, Potter has not been validated outside the US yet. In this study, we aimed to validate the POTTER calculator in a Brazilian academic hospital. mortality and morbidity were analyzed using the POTTER calculator in both trauma and non-trauma emergency surgery patients submitted to surgical treatment between November 2020 and July 2021. A total of 194 patients were prospectively included in this analysis. regarding the presence of comorbidities, about 20% of the population were diabetics and 30% were smokers. A total of 47.4% of the patients had hypertensive prednisone. After the analysis of the results, we identified an adequate capability to predict 30-day mortality and morbidity for this group of patients. the POTTER calculator presented excellent performance in predicting both morbidity and mortality in the studied population, representing an important tool for surgical teams to define risks, benefits, and outcomes for the emergency surgery population.

The use of POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator to predict mortality and complications in patients submitted to Emergency Surgery

RESUMO Introdução: a capacidade da equipe de atendimento de prever de forma confiável o risco pós-operatório é essencial para melhorar a tomada de decisões cirúrgicas, o aconselhamento ao paciente e à família e a alocação de recursos nos hospitais. A calculadora POTTER (Predictive Optimal Trees in Emergency Surgery Risk), alimentada por inteligência artificial (IA) e com uma interface amigável, foi baixada em seu formato para iPhone e Android por milhares de cirurgiões em todo o mundo e foi originalmente desenvolvida para ser usada em pacientes de cirurgia de emergência não traumática. No entanto, a POTTER ainda não foi validada fora dos EUA. Neste estudo, nosso objetivo foi validar a calculadora POTTER em um hospital acadêmico brasileiro. Métodos: a mortalidade e a morbidade foram analisadas usando a calculadora POTTER em pacientes de cirurgia de emergência com e sem trauma submetidos a tratamento cirúrgico entre novembro de 2020 e julho de 2021. Um total de 194 pacientes foi incluído prospectivamente nessa análise. Resultados: Em relação à presença de comorbidades, cerca de 20% da população era diabética e 30%, fumante. Um total de 47,4% dos pacientes eram hipertensos antes da admissão. Após a análise dos resultados, identificamos uma capacidade adequada de prever a mortalidade e a morbidade em 30 dias para esse grupo de pacientes. Conclusão: a calculadora POTTER apresentou um excelente desempenho para prever a morbidade e a mortalidade na população estudada, representando uma ferramenta importante para as equipes cirúrgicas definirem riscos, benefícios e resultados para a população de cirurgia de emergência.

Racial and Ethnic Differences in Elective Versus Emergency Surgery for Colorectal Cancer.

To evaluate differences in presentation and outcomes of surgery for colorectal cancer. Although racial and socioeconomic disparities in colorectal cancer outcomes are well documented, disparities in access affecting disease presentation are less clear. We conducted a statewide retrospective study of patients who underwent resection for colorectal cancer between January 1, 2015, and April 30, 2021. The primary outcome was undergoing emergency surgery. Secondary outcomes included preoperative evaluation and postoperative outcomes. Covariates of interest included race/ethnicity, social deprivation index, and insurance type. A total of 4869 patients underwent surgery for colorectal cancer, of whom 1122 (23.0%) underwent emergency surgery. Overall, 28.1% of Black non-Hispanic patients and 22.5% of White non-Hispanic patients underwent emergency surgery. On multivariable logistic regression, Black non-Hispanic race was independently associated with a 5.8 (95% CI, 0.3-11.3) percentage point increased risk of emergency surgery compared with White non-Hispanic race. Patients who underwent emergency surgery were significantly less likely to have preoperative carcinoembryonic antigen measurement, staging for rectal cancer, and wound/ostomy consultation. Patients who underwent emergency surgery had a higher incidence of 30-day mortality (5.5% vs 1.0%, P <0.001), positive surgical margins (11.1% vs 4.9%, P <0.001), complications (29.2% vs 16.0%, P <0.001), readmissions (12.5% vs 9.6%, P =0.005), and reoperations (12.2% vs 8.2%, P <0.001). Among patients with colorectal cancer, Black non-Hispanic patients were more likely to undergo emergency surgery than White non-Hispanic patients, suggesting they may face barriers to timely screening and evaluation. Undergoing emergency surgery was associated with incomplete oncologic evaluation, increased incidence of postoperative complications including mortality, and increased surgical margin positivity. These results suggest that racial and ethnic differences in the diagnosis and treatment of colorectal cancer impact near-term and long-term outcomes.

Accuracy of Risk Estimation for Surgeons Versus Risk Calculators in Emergency General Surgery

IntroductionSurgical risk calculators have expanded in both number and sophistication of their predictive approach. These calculators are gaining popularity as validated tools to help surgeons estimate mortality and complications following emergency general surgery (EGS). However, the accuracy of risk estimates generated by these calculators compared to risk estimation by practicing surgeons has not been explored. MethodsAcute care surgeons at a quaternary care center prospectively estimated 30-d mortality and complications for adult EGS patients (2019-2021). Surgeon predictions were compared to Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) and NSQIP estimates. Observed-to-expected (O:E) ratios of median aggregate estimates were calculated. C-statistics for surgeon and calculator estimations were utilized to quantify predictive accuracy. ResultsAmong 150 patients (median 61 y, 45% male), 30-d mortality was 15% (n = 23). Observed rates of prolonged mechanical ventilation and acute renal failures were 30% and 10%, respectively. Overall, surgeon predictions were similar to risk calculator estimates for mortality (c-statistics 0.843 [surgeon] versus 0.848 [POTTER] and 0.815 [NSQIP]) and need for prolonged ventilation (c-statistics 0.801 versus 0.722 and 0.689, respectively). Surgeons tended to overestimate complication risks. Surgeon experience was not significantly associated with mortality prediction in an adjusted model. ConclusionsAcute care surgeons at a quaternary care center predicted postoperative mortality and complications with similar discrimination when compared to surgical risk calculators. Surgeon expertise should be utilized in conjunction with risk calculators when counseling EGS patients regarding anticipated postoperative outcomes. Surgeons should be cognizant of patterns in overestimation or underestimation of complications.

Application of the New Preoperative Frailty Risk Score in Elderly Patients Undergoing Emergency Surgery

Background: Predicting preoperative frailty risk in emergency surgery is difficult with limited information because preoperative evaluation is not commonly performed properly. A recent study attempted to predict preoperative frailty risk using only diagnostic and surgical codes that can be extracted from the electronic medical records system. Objective: This study aimed to validate whether the prediction model of preoperative frailty risk presented in the previous study is well applied to other medical hospitals’ data. Methods: This is a retrospective cohort study including 1,557 patients (≥75 years old) who were admitted to a single institution for emergency operations between January 1, 2010, and December 31, 2019, for study analysis. The Charlson comorbidity index, Hospital Frailty Risk Score, and the recently developed Operation Frailty Risk Score (OFRS) were calculated using the patient’s diagnostic and operation codes. The predictive performances of these calculated risk scores and the American Society of Anesthesiologists-Physical Status classification for postoperative 90-day mortality were compared by using the receiver operating characteristic curve analysis. Findings: The predictive performance of the OFRS, Charlson comorbidity index, American Society of Anesthesiologists-Physical Status, and Hospital Frailty Risk Score for postoperative 90-day mortality was 0.81, 0.630, 0.699, and 0.549 on a c-statistics basis, respectively. Conclusions: The OFRS using diagnostic and operation codes may show the best predictive performance for 90-day mortality compared to other risk scores, and it can be the clinically applicable model to evaluate the preoperative frailty risk in elderly patients undergoing emergency surgery.

POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery

BackgroundDelays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care costs. We aimed to use interpretable artificial intelligence technology to create a preoperative predictor for postoperative intensive care unit need in emergency surgery patients. MethodsA novel, interpretable artificial intelligence technology called optimal classification trees was leveraged in an 80:20 train:test split of adult emergency surgery patients in the 2007–2017 American College of Surgeons National Surgical Quality Improvement Program database. Demographics, comorbidities, and laboratory values were used to develop, train, and then validate optimal classification tree algorithms to predict the need for postoperative intensive care unit admission. The latter was defined as postoperative death or the development of 1 or more postoperative complications warranting critical care (eg, unplanned intubation, ventilator requirement ≥48 hours, cardiac arrest requiring cardiopulmonary resuscitation, and septic shock). An interactive and user-friendly application was created. C statistics were used to measure performance. ResultsA total of 464,861 patients were included. The mean age was 55 years, 48% were male, and 11% developed severe postoperative complications warranting critical care. The Predictive OpTimal Trees in Emergency Surgery Risk Intensive Care Unit application was created as the user-friendly interface of the complex optimal classification tree algorithms. The number of questions (ie, tree depths) needed to predict intensive care unit admission ranged from 2 to 11. The Predictive OpTimal Trees in Emergency Surgery Risk Intensive Care Unit application had excellent discrimination for predicting the need for intensive care unit admission (C statistics: 0.89 train, 0.88 test). ConclusionWe recommend the Predictive OpTimal Trees in Emergency Surgery Risk Intensive Care Unit application as an accurate, artificial intelligence–based tool for predicting severe complications warranting intensive care unit admission after emergency surgery. The Predictive OpTimal Trees in Emergency Surgery Risk Intensive Care Unit application can prove useful to triage patients to the intensive care unit and to potentially decrease failure to rescue in emergency surgery patients.

Application of the Predictive Optimal Trees in Emergency Surgery Risk Calculator (POTTER) to Emergency Surgical Debridement for Necrotizing Skin and Soft Tissue Infection

Application of the Predictive Optimal Trees in Emergency Surgery Risk Calculator (POTTER) to Emergency Surgical Debridement for Necrotizing Skin and Soft Tissue Infection

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study

Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial resources, identifying surgical patients at a high risk of postoperative complications and providing personalised precision medicine-based treatment strategies provides an obvious pathway for reducing patient morbidity and mortality. We aimed to leverage deep learning to create, through training on structured electronic health-care data, a multilabel deep neural network to predict surgical postoperative complications that would outperform available models in surgical risk prediction. In this retrospective study, we used data on 58 input features, including demographics, laboratory values, and 30-day postoperative complications, from the American College of Surgeons (ACS) National Surgical Quality Improvement Program database, which collects data from 722 hospitals from around 15 countries. We queried the entire adult (≥18 years) database for patients who had surgery between Jan 1, 2012, and Dec 31, 2018. We then identified all patients who were treated at a large midwestern US academic medical centre, excluded them from the base dataset, and reserved this independent group for final model testing. We then randomly created a training set and a validation set from the remaining cases. We developed three deep neural network models with increasing numbers of input variables and so increasing levels of complexity. Output variables comprised mortality and 18 different postoperative complications. Overall morbidity was defined as any of 16 postoperative complications. Model performance was evaluated on the test set using the area under the receiver operating characteristic curve (AUC) and compared with previous metrics from the ACS-Surgical Risk Calculator (ACS-SRC). We evaluated resistance to changes in the underlying patient population on a subset of the test set, comprising only patients who had emergency surgery. Results were also compared with the Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) calculator. 5 881 881 surgical patients, with 2941 unique Current Procedural Terminology codes, were included in this study, with 4 694 488 in the training set, 1 173 622 in the validation set, and 13 771 in the test set. The mean AUCs for the validation set were 0·864 (SD 0·053) for model 1, 0·871 (0·055) for model 2, and 0·882 (0·053) for model 3. The mean AUCs for the test set were 0·859 (SD 0·063) for model 1, 0·863 (0·064) for model 2, and 0·874 (0·061) for model 3. The mean AUCs of each model outperformed previously published performance metrics from the ACS-SRC, with a direct correlation between increasing model complexity and performance. Additionally, when tested on a subgroup of patients who had emergency surgery, our models outperformed previously published POTTER metrics. We have developed unified prediction models, based on deep neural networks, for predicting surgical postoperative complications. The models were generally superior to previously published surgical risk prediction tools and appeared robust to changes in the underlying patient population. Deep learning could offer superior approaches to surgical risk prediction in clinical practice. The Novo Nordisk Foundation.

Prospective multicentre study of a new bowel obstruction treatment in colorectal surgery: Reduced morbidity and mortality

IntroductionBowel obstruction patients are at increased risk of emergency surgery and have poor nutritional and physical conditions. These patients could benefit from prehabilitation and prevention of emergency surgery. This study assessed the effect of a multimodal obstruction treatment for bowel obstruction patients in colorectal surgery on the risk of emergency surgery and postoperative morbidity and mortality. Materials and methodsThis multicenter observational cohort study included all consecutive bowel obstruction patients who received obstruction treatment (obstruction protocol) in the period 2019–2020 in two Dutch hospitals. Benign and malignant causes of bowel obstruction were included. Treatment consisted of 1. dietary adjustments, 2. postponing surgery for three weeks, 3. laxatives, and 4. prehabilitation. We compared emergency surgery and postoperative morbidity and mortality rates to known rates from the literature. ResultsEighty-nine patients were included: obstruction treatment was successful in 77 patients (87%) who underwent elective surgery and unsuccessful in 12 patients (13%) who underwent emergency surgery. Sixty-six (74%) had colorectal cancer, and 22 (25%) had benign disease. Thirty-day mortality of 0% in our study was significantly lower than the national average of 4% in colorectal cancer patients in the Netherlands (p = 0.049). Anastomotic leakage rate was 3%, severe complications (Clavien-Dindo ≥ III) 8%, and bowel perforation 0%. These rates did not differ significantly from rates reported in literature. ConclusionThe obstruction treatment prevented emergency surgery in most patients with bowel obstruction and reduced postoperative morbidity and mortality. The obstruction treatment seems to be a safe and efficient alternative to emergency surgery.

Validation of the Artificial Intelligence-Based Predictive Optimal Trees in Emergency Surgery Risk (POTTER) Calculator in Emergency General Surgery and Emergency Laparotomy Patients

The Predictive Optimal Trees in Emergency Surgery Risk (POTTER) tool is an artificial intelligence-based calculator for the prediction of 30-day outcomes in patients undergoing emergency operations. In this study, we sought to assess the performance of POTTER in the emergency general surgery (EGS) population in particular. All patients who underwent EGS in the 2017 American College of Surgeons NSQIP database were included. The performance of POTTER in predicting 30-day postoperative mortality, morbidity, and 18 specific complications was assessed using the c-statistic metric. As a subgroup analysis, the performance of POTTER in predicting the outcomes of patients undergoing emergency laparotomy was assessed. A total of 59,955 patients were included. Median age was 50 years and 51.3% were women. POTTER predicted mortality (c-statistic= 0.93) and morbidity (c-statistic= 0.83) extremely well. Among individual complications, POTTER had the highest performance in predicting septic shock (c-statistic= 0.93), respiratory failure requiring mechanical ventilation for 48 hours or longer (c-statistic= 0.92), and acute renal failure (c-statistic= 0.92). Among patients undergoing emergency laparotomy, the c-statistic performances of POTTER in predicting mortality and morbidity were 0.86 and 0.77, respectively. POTTER is an interpretable, accurate, and user-friendly predictor of 30-day outcomes in patients undergoing EGS. POTTER could prove useful for bedside counseling of patients and their families and for benchmarking of EGS care.

Maternal and neonatal outcomes of repeated antepartum bleeding in 493 placenta previa cases: a retrospective study

Objective To explore the effect of antepartum bleeding caused by PP on pregnancy outcomes. Study design We retrospectively analyzed 493 pregnant women complicated with PP. Patients were divided into antepartum repeated bleeding and non-bleeding groups. Maternal characteristics and pregnancy outcomes were compared. Results The risk of antepartum hemorrhage was 2.038 times higher when gravidity was 5 (95% CI 1.104–3.760, p = .023). Pregnant women with a history of more than three intrauterine procedures had a 1.968 times higher risk of antepartum hemorrhage (95% CI 1.135–3,412, p = .016) compared to pregnant women without any intrauterine procedures. The risk of antepartum bleeding was found to be decreasing with the pregnancy advancing; When the placenta edge was noted to be over cervical os, the risk of antepartum bleeding was 4.385-fold than the low-lying plcaenta cases (95%CI2.454–8.372, p = .000). In the respect of maternal outcomes, the repeated bleeding group, the risk of emergency surgery was 7.213 times higher than elective surgery (95% CI 4.402–11.817, p = .000). As for the neonatal outcomes, the risk of asphyxia was 2.970 times and the risk of neonatal intensive care unit (NICU) admission was 2.542-fold higher in repeated bleeding group compared to non-bleeding group, respectively. Conclusions Obstetricians should be aware of the increased risk of antepartum bleeding especially for ≤34 weeks and placenta edge over cervical os PP patients, they have a higher risk of antepartum bleeding. These women have higher possibility of emergency C-section and need preterm newborn resuscitation.