Predictive value of E-PASS and POSSUM systems for postoperative risk assessment of spinal surgery

2014 ◽  
Vol 20 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Jun Hirose ◽  
Takuya Taniwaki ◽  
Toru Fujimoto ◽  
Tatsuya Okada ◽  
Takayuki Nakamura ◽  
...  
Keyword(s):  
Postoperative Complications ◽  
Risk Score ◽  
Severity Score ◽  
Spinal Surgery ◽  
Surgical Stress ◽  
Morbidity Rate ◽  
Preoperative Risk ◽  
Operative Severity Score ◽  
Postoperative Risk ◽  
Stress Score

Object The Estimation of Physiological Ability and Surgical Stress (E-PASS) and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems are surgical risk scoring systems that take into account both the patient's preoperative condition and intraoperative variables. While they predict postoperative morbidity and mortality rates for several types of surgery, spinal surgeries are currently not included. The authors assessed the usefulness of E-PASS and POSSUM algorithms and compared the predictive ability of both systems in patients with spinal disorders considered for surgery. Methods The E-PASS system includes a preoperative risk score, a surgical stress score, and a comprehensive risk score that is determined by both the preoperative risk score and surgical stress score. The POSSUM system is composed of a physiological score and an operative severity score; its total score is based on both the physiological score and operative severity score. The authors calculated the E-PASS and POSSUM scores for 601 consecutive patients who had undergone spinal surgery and investigated the relationship between the individual scores of both systems and the incidence of postoperative complications. They also assessed the correctness of the predicted morbidity rate of both systems. Results Postoperative complications developed in 64 patients (10.6%); there were no in-hospital deaths. All EPASS scores (p ≤ 0.001) and the operative severity score and total score of the POSSUM (p < 0.03) were significantly higher in patients with postoperative complications than in those without postoperative complications. The morbidity rates correlated linearly and significantly with all E-PASS scores (p ≤ 0.001); their coefficients (preoperative risk score, ρ = 0.179; surgical stress score, ρ = 0.131; and comprehensive risk score, ρ = 0.198) were higher than those for the POSSUM scores (physiological score, ρ = 0.059; operative severity score, ρ = 0.111; and total score, ρ = 0.091). The area under the receiver operating characteristic curve for the predicted morbidity rate was 0.668 for the E-PASS and 0.588 for the POSSUM system. Conclusions As E-PASS predicted morbidity more correctly than POSSUM, it is useful for estimating the postoperative risk of patients considered for spinal surgery.

scholarly journals A New Preoperative Risk Score for Predicting Postoperative Complications in Elderly Patients Undergoing Hepatectomy

2021 ◽  
Author(s):  
Koichi Tomita ◽  
Itsuki Koganezawa ◽  
Masashi Nakagawa ◽  
Shigeto Ochiai ◽  
Takahiro Gunji ◽  
...  
Keyword(s):  
Risk Factors ◽  
Skeletal Muscle ◽  
Postoperative Complications ◽  
Elderly Patients ◽  
Risk Score ◽  
Surgical Procedure ◽  
Evaluation Method ◽  
Preoperative Risk ◽  
Preoperative Serum ◽  
Independent Risk Factors

Abstract Background Postoperative complications are not rare in the elderly population after hepatectomy. However, predicting postoperative risk in elderly patients undergoing hepatectomy is not easy. We aimed to develop a new preoperative evaluation method to predict postoperative complications in patients above 65 years of age using biological impedance analysis (BIA). Methods Clinical data of 59 consecutive patients (aged 65 years or older) who underwent hepatectomy at our institution between 2017 and 2020 were retrospectively analyzed. Risk factors for postoperative complications (Clavien-Dindo ≥ III) were evaluated using multivariate regression analysis. Additionally, a new preoperative risk score was developed for predicting postoperative complications. Results Fifteen patients (25.4%) had postoperative complications, with biliary fistula being the most common complication. Abnormal skeletal muscle mass index from BIA and type of surgical procedure were found to be independent risk factors in the multivariate analysis. These two variables and preoperative serum albumin levels were used for developing the risk score. The postoperative complication rate was 0.0% with a risk score of ≤ 1 and 57.1% with a risk score of ≥ 4. The area under the receiver operating characteristic curve of the risk score was 0.810 (p = 0.001), which was better than that of other known surgical risk indexes. Conclusion Decreased skeletal muscle and the type of surgical procedure for hepatectomy were independent risk factors for postoperative complications after elective hepatectomy in elderly patients. The new preoperative risk score is simple, easy to perform, and will help in the detection of high-risk elderly patients undergoing elective hepatectomy.

scholarly journals Preoperative predictions of in-hospital mortality using electronic medical record data

2018 ◽  
Author(s):  
Brian Hill ◽  
Robert Brown ◽  
Eilon Gabel ◽  
Christine Lee ◽  
Maxime Cannesson ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Random Forest ◽  
Hospital Mortality ◽  
Risk Score ◽  
Surgical Mortality ◽  
Physical Status ◽  
Preoperative Risk ◽  
Physical Status Classification ◽  
Postoperative Risk ◽  
Status Classification

AbstractBackgroundPredicting preoperative in-hospital mortality using readily-available electronic medical record (EMR) data can aid clinicians in accurately and rapidly determining surgical risk. While previous work has shown that the American Society of Anesthesiologists (ASA) Physical Status Classification is a useful, though subjective, feature for predicting surgical outcomes, obtaining this classification requires a clinician to review the patient’s medical records. Our goal here is to create an improved risk score using electronic medical records and demonstrate its utility in predicting in-hospital mortality without requiring clinician-derived ASA scores.MethodsData from 49,513 surgical patients were used to train logistic regression, random forest, and gradient boosted tree classifiers for predicting in-hospital mortality. The features used are readily available before surgery from EMR databases. A gradient boosted tree regression model was trained to impute the ASA Physical Status Classification, and this new, imputed score was included as an additional feature to preoperatively predict in-hospital post-surgical mortality. The preoperative risk prediction was then used as an input feature to a deep neural network (DNN), along with intraoperative features, to predict postoperative in-hospital mortality risk. Performance was measured using the area under the receiver operating characteristic (ROC) curve (AUC).ResultsWe found that the random forest classifier (AUC 0.921, 95%CI 0.908-0.934) outperforms logistic regression (AUC 0.871, 95%CI 0.841-0.900) and gradient boosted trees (AUC 0.897, 95%CI 0.881-0.912) in predicting in-hospital post-surgical mortality. Using logistic regression, the ASA Physical Status Classification score alone had an AUC of 0.865 (95%CI 0.848-0.882). Adding preoperative features to the ASA Physical Status Classification improved the random forest AUC to 0.929 (95%CI 0.915-0.943). Using only automatically obtained preoperative features with no clinician intervention, we found that the random forest model achieved an AUC of 0.921 (95%CI 0.908-0.934). Integrating the preoperative risk prediction into the DNN for postoperative risk prediction results in an AUC of 0.924 (95%CI 0.905-0.941), and with both a preoperative and postoperative risk score for each patient, we were able to show that the mortality risk changes over time.ConclusionsFeatures easily extracted from EMR data can be used to preoperatively predict the risk of in-hospital post-surgical mortality in a fully automated fashion, with accuracy comparable to models trained on features that require clinical expertise. This preoperative risk score can then be compared to the postoperative risk score to show that the risk changes, and therefore should be monitored longitudinally over time.Author summaryRapid, preoperative identification of those patients at highest risk for medical complications is necessary to ensure that limited infrastructure and human resources are directed towards those most likely to benefit. Existing risk scores either lack specificity at the patient level, or utilize the American Society of Anesthesiologists (ASA) physical status classification, which requires a clinician to review the chart. In this manuscript we report on using machine-learning algorithms, specifically random forest, to create a fully automated score that predicts preoperative in-hospital mortality based solely on structured data available at the time of surgery. This score has a higher AUC than both the ASA physical status score and the Charlson comorbidity score. Additionally, we integrate this score with a previously published postoperative score to demonstrate the extent to which patient risk changes during the perioperative period.

Risk evaluation of postoperative complication in patients undergoing rectal cancer surgery.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 756-756
Author(s):  
Hiroshi Miyakita ◽  
Sotaro Sadahiro ◽  
Toshiyuki Suzuki ◽  
Akira Tanaka ◽  
Kazutake Okada ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Postoperative Complications ◽  
Intestinal Obstruction ◽  
Risk Score ◽  
Surgical Stress ◽  
Infectious Complications ◽  
Risk Scores ◽  
Rectal Cancer Surgery ◽  
Stoma Creation ◽  
Severity Scores

756 Background: Colorectal cancer patients with postoperative complications have poor long-term outcomes. Rectal cancer is associated with a higher incidence of complications than colon cancer. Reliable predictors of complications would facilitate determination of surgical procedures such as stoma creation. We examined the relations between five kinds of risk score and postoperative complications in patients(pts) with rectal cancer. Methods: The subjects were 261 pts with cStage II/III rectal cancer from 2003 to 2013. We categorized complications into all complications, leakage, infectious complications and intestinal obstruction. Estimation of physiologic ability and surgical stress comprehensive risk scores (E-PASS CRS), surgical Apgar scores (SAS), prognostic nutritional index (PNI), colorectal physiological and operative severity scores for the enumeration of mortality and morbidity (CR-POSSUM), and neutrophil-lymphocyte ratios (NLR) were assessed. Clavien-Dindo (CD) Grade 3a or higher requiring surgically invasive treatment were considered complications. For leakage, CD Grade 3b or higher were considered complications. Results: Complications occurred in 56 pts (21%), leakage (L) in 12 (14%), infectious complications (IC) in 19 (7%), and intestinal obstruction (IO) in 16 (6%). E-PASS CRS significantly correlated with all complications (OR 3.45; p < 0.001), IC (OR 0.26; p = 0.008), L (OR 4.94; p = 0.027), and IO (OR 3.92; p = 0.007). PNI correlated with all complications (OR 0.38; p = 0.002) and IO (OR 3.08; p = 0.024). NLR correlated with all complications (OR 0.40; p = 0.003), IC (OR 0.25; p = 0.004), L (OR 8.66; p < 0.001), and IO (OR 3.86; p = 0.007). SAS correlated with IC (OR 0.19; p = 0.004). CR-POSSUM correlated with all complications, (OR 2.26; p = 0.009), IC (OR 5.02; p < 0.001), and IO (OR 0.28; p = 0.014). Multivariate analysis revealed E-PASS CRS (OR 6.17 p = 0.020) and NLR (OR 7.11 p = 0.011) were independent risk factors for L. Conclusions: Five kinds of risk score were all useful for assessing the risk of complications in rectal cancer. NLR was the only risk factor for leakage that could be used before surgery. Our results suggest NLR might be an auxiliary means of evaluating the need for creation of diverting stoma.

Evaluation of the Estimation of Physiologic Ability and Surgical Stress Score as a Prognostic Indicator for Older Patients with Gastric Cancer

2019 ◽  
Vol 37 (2) ◽  
pp. 171-178 ◽  
Author(s):  
Yuki Murakami ◽  
Hiroaki Saito ◽  
Shota Shimizu ◽  
Yusuke Kono ◽  
Yuji Shishido ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Risk Score ◽  
Surgical Stress ◽  
Survival Rates ◽  
Prognostic Significance ◽  
Prognostic Indicator ◽  
Histopathological Diagnosis ◽  
Receiver Operating Characteristic Curves ◽  
Auc Value ◽  
Stress Score

Background: The incidence of gastric cancer (GC) among the older adults is increasing. Therefore, determining postoperative age-associated prognostic factors is clinically important. This present study retrospectively investigated the prognostic significance of the estimation of physiologic ability and surgical stress (E-PASS) of such patients with GC. Methods: We enrolled 136 patients aged ≥75 years with a histopathological diagnosis of gastric adenocarcinoma who underwent gastrectomy. Results: Receiver operating characteristic curves were generated to evaluate survival, and AUC values were compared to assess the discriminatory ability of carcinoembryonic antigen, the perioperative risk score, the surgical stress score, and the comprehensive risk score (CRS) of E-PASS. The AUC value of CRS was of the highest AUC value as a function of overall survival (OS) and disease-specific survival. The 5-year OS rates of CRSHigh and CRSLow groups were 50.6 and 76.9% (p = 0.0007) respectively. The 5-year DSS rates of the CRSHigh and CRSLow groups were 78.8 and 95.2% (p = 0.028) respectively. Further, the 5-year survival rates unrelated to cancer of the CRSHigh and CRSLow groups were 64.2 and 80.9% (p = 0.0096) respectively. Multivariate analysis identified that CRS was an independent prognostic indicator. Conclusions: E-PASS was a useful prognostic indicator for older GC patients.

scholarly journals New score for prediction of morbidity in patients undergoing open pancreaticoduodenectomy

2021 ◽  
Vol 49 (3) ◽  
pp. 030006052110019
Author(s):  
Lian Chen ◽  
Li Peng ◽  
Chao Wang ◽  
Sheng-Chao Li ◽  
Meng Zhang
Keyword(s):  
Postoperative Complications ◽  
Risk Score ◽  
Characteristic Curve ◽  
Fistula Formation ◽  
Power Prediction ◽  
Retrospective Case ◽  
Operative Severity Score ◽  
Prediction Probability ◽  
Score Model ◽  
Open Pancreaticoduodenectomy

Objective The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) is commonly used to predict the risk of postoperative complications in general surgery. However, use of the POSSUM is not absolutely suitable for open pancreaticoduodenectomy (OPD), which has unique complications such as pancreatic fistula formation. This study was performed to establish a new risk score for assessing the incidence of postoperative complications of OPD. Methods This retrospective case-control study involved 159 patients who underwent standard OPD from 2 January 2017 to 1 February 2019. The risk factors for post-OPD complications were statistically investigated, and a risk score model was established by multivariate logistic regression. Results Among all 159 patients, 72 (42.28%) developed complications. A scoring system was developed based on the following five independent variables: sodium concentration of <141.20 mmol/L, white blood cell count of >6.35 × 109/L, pancreatic texture grade, body mass index of >25.06 kg/m2, and basic respiratory diseases. Our risk score model demonstrated better discriminating power, prediction power, and prediction probability than the POSSUM model in the receiver operating characteristic curve analysis. Conclusion This novel risk score may help to predict postoperative complications after OPD with higher accuracy than the POSSUM system.

scholarly journals POSSUM escore como preditor de mortalidade em pacientes cirúrgicos

2009 ◽  
Vol 43 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Adriana Cristina Galbiatti Parminondi Elias ◽  
Tiemi Matsuo ◽  
Cíntia Magalhães Carvalho Grion ◽  
Lucienne Tibery Queiroz Cardoso ◽  
Paulo Henrique Verri
Keyword(s):  
Severity Score ◽  
Apache Ii ◽  
Mortality And Morbidity ◽  
Operative Severity Score

O estudo avaliou a utilização do escore POSSUM (Physiological and Operative Severity Score for Enumeration of Mortality and Morbidity) para predizer a mortalidade na prática cirúrgica.Foram analisados 416 pacientes cirúrgicos com internação na UTI para cuidados de pós-operatório. Foram realizadas comparações entre as taxas de mortalidade predita e observada de acordo com 4 grupos de risco: 0-4%, 5-14%, 15-49%, 50% ou mais, e calculada a área sob a curva ROC do escore POSSUM e APACHE II para a mortalidade. A taxa de mortalidade foi de 22,4%. O escores POSSUM e APACHE II superestimaram o risco de morte, e a área sob a curva ROC do POSSUM foi de 0,762 e a do APACHE II de 0,737, sugerindo a utilização do POSSUM como ferramenta auxiliar na predição de risco de morte em pacientes cirúrgicos.

scholarly journals Prevalence of Hirschsprung-associated enterocolitis in patients with Hirschsprung disease

2021 ◽  
Author(s):  
J. Hagens ◽  
K. Reinshagen ◽  
C. Tomuschat
Keyword(s):  
Subgroup Analysis ◽  
Hirschsprung Disease ◽  
Cochrane Library ◽  
Segment Length ◽  
Preoperative Risk ◽  
Pooled Data ◽  
Postoperative Risk ◽  
Pooled Prevalence ◽  
Significant Difference ◽  
Considerable Morbidity

Abstract Purpose Hirschsprung's associated enterocolitis (HAEC) is a complication of Hirschsprung's Disease (HD) with considerable morbidity and mortality. The variability in presentation leads to a wide variety of the reported prevalence pre-and postoperatively. This systematic review aimed to clarify the prevalence of HAEC in short—(S-HD), long (L-HD), TCA and the type of operation used. Methods A systematic literature-based search for relevant cohorts was performed using Pubmed/Medline, Cochrane Library from its inception to May 2021. Studies reporting on pre-and postoperative enterocolitis, segment length, and surgical procedure (Soave, Swenson, Duhamel) were included. Pooled prevalence and subgroup analysis have been calculated for pre-and postoperative HAEC. Results 4738 articles were identified from the literature search, among which 57 studies, including 9744 preoperative and 8568 postoperative patients, were included. The groups were sorted by length of the aganglionic segment for further analysis. The pooled prevalence for preoperative HAEC was 18.3% for all types, 15.2% for S-HD and 26.1% for TCA. The pooled prevalence for postoperative HAEC was in total 18.2% for all segment lengths and used techniques. Subgroup analysis showed no significant difference in the occurrence of postoperative enterocolitis between the three techniques. Conclusion The prevalence of preoperative HAEC increases with segment length. However, pooled data suggest that the postoperative risk for developing HAEC, independently of the employed method and segment length, is comparable to the preoperative risk.

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