669 Mortality Risk Prediction for Emergency Laparotomy: Are We Utilising the Best Tool?

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
M Barghash ◽  
A Iskandar ◽  
S Fawzy ◽  
T Elghobashy ◽  
F Salimi ◽  
...  
Keyword(s):  
Predictive Power ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Emergency Laparotomy ◽  
Discriminative Power ◽  
Entire Cohort ◽  
Possum Score ◽  
The Common ◽  
The Uk

Abstract Aim Emergency laparotomy is one of the common operations performed in the UK. To aid in more objective decision making, several scoring systems have been formulated. In this project, we aimed to explore the predictive power of both NELA and P-Possum mortality scores against 30 days and 90 days observed mortality for emergency laparotomy patients. Method Patient details from two large district general hospitals were extracted from the NELA database over a period of three years. Pre-operative NELA, post-operative NELA, and P-POSSUM predicted mortality were calculated and compared with the observed 30 days and 90 days mortality for the entire cohort. Model discrimination (statistical accuracy) was tested by calculating the area under the receiver operating characteristic curve (AUC), which was used to assess how accurately the model could discriminate. Results There were 378 patients eligible for inclusion with a median age of 64. 39 patients (10.3%) died within 30 days and 52 patients (13.8%) died within 90 days. P-POSSUM score, pre-operative NELA, and post-operative NELA scores predicted the 30 days mortality as (2.7%, 3.7%, and 2.4%) and 90 days mortality as (2.9%, 4.8%, and 4%) respectively. The discriminative power for 30 days and 90 days mortality was highest for the pre-operative NELA score (AUC 0.870, CI: 0.824 – 0.916), (AUC 0.826, CI: 0.769 – 0.884) respectively. Conclusions Both NELA and P-Possum scores underpredicted actual 30 days and 90 days mortality. It was however noted that the pre-operative NELA mortality score showed more accurate mortality discriminative power than the other 2 tested tools.

A validated novel preoperative index to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology: A cohort study

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Emergency Laparotomy ◽  
Contamination Index ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

Mortality risk scoring in emergency general surgery: Are we using the best tool?

2020 ◽  
pp. 175045892092013
Author(s):  
Azeem Thahir ◽  
Rui Pinto-Lopes ◽  
Stavroula Madenlidou ◽  
Laura Daby ◽  
Chandima Halahakoon
Keyword(s):  
Mortality Rate ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Emergency Laparotomy ◽  
Receiver Operator Characteristic ◽  
Characteristic Analysis ◽  
Goodness Of Fit Test ◽  
Risk Of Death ◽  
Possum Score ◽  
Operative Severity Score

Background It is imperative that an accurate assessment of risk of death is undertaken preoperatively on all patients undergoing an emergency laparotomy. Portsmouth-Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (P-POSSUM) is one of the most widely used scores. National Emergency Laparotomy Audit (NELA) presents a novel, validated score, but no direct comparison with P-POSSUM exists. We aimed to determine which would be the best predictor of mortality. Methods We analysed all the entries on the online NELA database over a four-and-a-half-year period. The Hosmer–Lemeshow goodness of fit test was performed to assess model calibration. For the outcome of death and for each scoring system, a non-parametric receiver operator characteristic analysis was done. The sensitivity, specificity, area under receiver operator characteristic curve and their standard errors were calculated. Results Data pertaining to 650 patients were included. There were 59 deaths, giving an overall observed mortality rate of 9.1%. Predicted mortality rate for the P-POSSUM score and NELA score were 15.2% and 7.8%, respectively. The discriminative power for mortality was highest for the NELA score (C-index = 0.818, CI: 0.769–0.867, p < 0.001), when compared to P-POSSUM (C-index = 0.769, CI: 0.712–0.827, p < 0.001). Conclusions The NELA score showed good discrimination in predicting mortality in the entire cohort. The P-POSSUM over-predicted observed mortality and the NELA score under-predicted observed mortality.

Development and Validation of a UK-Specific Prostate Cancer Staging Predictive Model: UK Prostate Cancer Tables

2012 ◽  
Vol 5 (5) ◽  
pp. 224-235
Author(s):  
Thomas B.L. Lam ◽  
Olivier Regnier-Coudert ◽  
John McCall ◽  
Sam McClinton
Keyword(s):  
Prostate Cancer ◽  
Predictive Power ◽  
Characteristic Curve ◽  
Clinical Stage ◽  
Cancer Staging ◽  
Fundamental Limitations ◽  
Lookup Tables ◽  
Biopsy Gleason Score ◽  
The Uk ◽  
Prostate Cancer Staging

Objectives: To construct new prostate cancer staging lookup tables based on a dataset collated by the British Association of Urological Surgeons (BAUS) and to validate them and compare their predictive power with Partin tables. Patients and methods: Complete data on 1701 patients was collated between 1999 and 2008 across 57 UK centres. Lookup tables were created for prediction of pathological stage (PS) using PSA level, biopsy Gleason score (GS) and clinical stage, replicating Partin's original approach. Tables were generated using logistic regression (LR) and bootstrap resampling methods and were internally validated and externally validated using concordance indices (CI) and area under the receiver operating characteristic curve (AUROC) respectively. Results: The CI and AUROC analyses indicate that Partin tables performed poorly on UK data in comparison with US data. The UK prostate cancer tables performed better than Partin tables but the predictive power of all models was relatively poor. Conclusion: The study shows that the predictive power of Partin tables is reduced when applied to the UK population. Models generated using LR methodology have fundamental limitations, and we suggest alternative modelling methods such as Bayesian networks.

External Validation of Different Scoring Systems for Suspected Choledocholithiasis

2019 ◽  
Vol 36 (6) ◽  
pp. 530-538
Author(s):  
Nicolò Tamini ◽  
Davide Paolo Bernasconi ◽  
Luca Gianotti
Keyword(s):  
Operating Characteristic ◽  
Bile Duct Stone ◽  
Characteristic Curve ◽  
External Validation ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Youden Index ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Symptoms And Signs

Aim of the Study: The diagnosis of choledocholithiasis is challenging. Previously published scoring systems designed to calculate the risk of choledocholithiasis were evaluated to appraise the diagnostic performance. Patients and Methods: Data of patients who were admitted between 2013 and 2015 with the following characteristics were retrieved: bile stone-related symptoms and signs, and indication to laparoscopic cholecystectomy. To validate and appraise the performance of the 6 scoring systems, the acknowledged domains of each metrics were applied to the present cohort. Sensitivity, specificity, positive, negative predictive, Youden index, and receiver operating characteristic curve with the area under the curve (AUC) values of the scores were calculated. Results: Two-hundred patients were analyzed. The highest sensitivity and specificity were obtained from the Menezes’ (96.6%) and Telem’s (99.3%) metrics respectively. The Telem’s and Menezes’ scores had the best positive (75.0%) and negative (96.4%) predictive values respectively. The best accuracy, as computed by the Youden index and AUC, was found for the Soltan’s scoring system (0.628 and 0.88, respectively). Conclusion: The available scoring systems are precise only in identifying patients with a negligible risk of common bile duct stone, but overall insufficiently accurate to suggest the routine use in clinical practice.

scholarly journals Shoulder Muscle Imbalance as a Risk for Shoulder Injury in Elite Adolescent Swimmers: A Prospective Study

2020 ◽  
Vol 75 (1) ◽  
pp. 103-113
Author(s):  
Joffrey Drigny ◽  
Antoine Gauthier ◽  
Emmanuel Reboursière ◽  
Henri Guermont ◽  
Vincent Gremeaux ◽  
...  
Keyword(s):  
Predictive Power ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Shoulder Injuries ◽  
Shoulder Injury ◽  
Shoulder Muscle ◽  
Increased Risk ◽  
A Prospective Study ◽  
External Rotator

Abstract Muscle strength imbalances between the internal and external rotators of the shoulder are frequent in swimmers, but their role in shoulder injury remains unknown. We aimed to evaluate the association of shoulder rotator strength and injury in elite adolescent swimmers. Eighteen adolescent swimmers performed preseason isokinetic tests of the internal and external rotator muscles in concentric (con) and eccentric (ecc) modes. Conventional (conER:conIR and eccER:eccIR) and functional ratios (eccER:conIR and eccIR:conER) were calculated. Thirteen swimmers completed a weekly questionnaire about swimming habits and shoulder injuries throughout the season. Preseason testing showed a significant negative association between the functional eccER:conIR ratio and years of practice (p < 0.05). Over the season, 46% of athletes experienced at least one shoulder injury. At the end of the season, peak torques increased for both internal and external rotator muscles strength, but only concentrically, resulting in a decrease in the eccER:conIR functional ratio (p < 0.05). The receiver operating characteristic curve analysis highlighted good predictive power for the preseason functional eccER:conIR ratio, as values below 0.68 were associated with a 4.5-fold (95% CI 1.33-15.28, p < 0.05) increased risk of shoulder injuries during the season.

scholarly journals Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Cancers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1268 ◽  
Author(s):  
Yuqian Gao ◽  
Yi-Ting Wang ◽  
Yongmei Chen ◽  
Hui Wang ◽  
Denise Young ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Survival Rates ◽  
Standard Of Care ◽  
Driver Genes ◽  
Primary Tumors ◽  
Entire Cohort ◽  
Risk Patients ◽  
Prostate Cancers

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Comparison of CHA2DS2-VASc and C2HEST scores for predicting the incidence of atrial fibrillation among patients with end-stage renal disease

Perfusion ◽  
2020 ◽  
Vol 35 (8) ◽  
pp. 842-846
Author(s):  
Wei-Syun Hu ◽  
Cheng-Li Lin
Keyword(s):  
Atrial Fibrillation ◽  
Renal Disease ◽  
End Stage Renal Disease ◽  
Predictive Power ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Predictive Capability ◽  
Stage Renal Disease ◽  
End Stage ◽  
Insurance Database

Purpose: The authors have studied assessment of CHA2DS2-VASc score versus C2HEST score in atrial fibrillation risk prediction in end-stage renal disease patients. Methods: The authors conducted this study by Longitudinal Health Insurance Database 2000. The authors totally enrolled 4,601 end-stage renal disease patients. The predictive capability of atrial fibrillation by using CHA2DS2-VASc and C2HEST score was estimated by area under the receiver operating characteristic curve (AUROC). Results: The AUROC for CHA2DS2-VASc score in predicting atrial fibrillation events was 0.5786, and AUROC for C2HEST score for atrial fibrillation prediction was 0.5983. Conclusion: Both scores yield almost identical AUROC values implying no difference in predictive power. Further work is warranted to verify the prognostic value of the current scores.

scholarly journals A Comparison of KL-6 and Clara Cell Protein as Markers for Predicting Bronchopulmonary Dysplasia in Preterm Infants

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Keyi Wang ◽  
Xianmei Huang ◽  
Hui Lu ◽  
Zhiqun Zhang
Keyword(s):  
Preterm Infants ◽  
Bronchopulmonary Dysplasia ◽  
Predictive Power ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Clara Cell ◽  
Cell Protein ◽  
Preterm Neonates ◽  
Operating Characteristic Curve ◽  
Time Point

Objectives. To evaluate the predictive characteristics of KL-6 and CC16 for bronchopulmonary dysplasia (BPD) in preterm infants, either independently or in combination.Study Design. This prospective cohort study was performed from 2011 to 2013 with preterm neonates of gestational age ≤32 weeks and birth weight ≤1500 g. Serum KL-6 and CC16 levels were determined 7 and 14 days after birth.Results. Seventy-three preterm infants were studied. BPD was identified in 24 of these infants. After adjusting for potential confounders, serum KL-6 concentrations were found to be elevated in BPD infants at both time points relative to non-BPD infants, while serum CC16 concentrations were lower at 14 days. At both 7 d and 14 d of life the predictive power of KL-6 levels exceeded that of CC16 (area under receiver operating characteristic curve: at 7 d, 0.91 cf. 0.73,P=0.02; at 14 d, 0.95 cf. 0.85,P=0.05). The combination of these markers enhanced the sensitivity further.Conclusions. Serum KL-6 levels higher than 79.26 ng/mL at 14 days postpartum in preterm infants predict the occurrence of BPD. CC16 was less predictive than KL-6 at this time point, but KL-6 and CC16 together enhanced the prediction.

scholarly journals Integrative Analysis of Metabolome and Microbiome in Patients with Progressive Alcohol-Associated Liver Disease

Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 766
Author(s):  
Bei Gao ◽  
Yixin Zhu ◽  
Nan Gao ◽  
Weishou Shen ◽  
Peter Stärkel ◽  
...  
Keyword(s):  
Liver Disease ◽  
Predictive Power ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Disease Status ◽  
Integrated Analysis ◽  
Data Types ◽  
Serum Metabolites ◽  
Microbial Species ◽  
Progressive Liver Disease

Alcohol-associated liver disease is one of the most prevalent diseases around the world, with 10–20% of patients developing progressive liver disease. To identify the complex and correlated nature of metabolic and microbial data types in progressive liver disease, we performed an integrated analysis of the fecal and serum metabolomes with the gut microbiome in a cohort of 38 subjects, including 15 patients with progressive liver disease, 16 patients with non-progressive liver disease, and 7 control subjects. We found that although patients were generally clustered in three groups according to disease status, metabolites showed better separation than microbial species. Furthermore, eight serum metabolites were correlated with two microbial species, among which seven metabolites were decreased in patients with progressive liver disease. Five fecal metabolites were correlated with three microbial species, among which four metabolites were decreased in patients with progressive liver disease. When predicting progressive liver disease from non-progressive liver disease using correlated metabolic and microbial signatures with the random forest model, correlated serum metabolites and microbial species showed great predictive power, with the area under the receiver operating characteristic curve achieving 0.91. The multi-omics signatures identified in this study are helpful for the early identification of patients with progressive alcohol-associated liver disease, which is a key step for therapeutic intervention.

scholarly journals P-EUS03 Risk prediction in patients undergoing Endoscopic Necrosectomy for infected pancreatic necrosis

2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Emily Britton ◽  
Eleanor Smith ◽  
Marianne Hollyman ◽  
Andrew Strickland
Keyword(s):  
Pancreatic Necrosis ◽  
Demographic Data ◽  
Scoring Systems ◽  
Infected Pancreatic Necrosis ◽  
Emergency Laparotomy ◽  
Operating Characteristics ◽  
Infected Necrosis ◽  
Safe Alternative ◽  
Endoscopic Necrosectomy ◽  
Possum Score

Abstract Background Laparotomy for the treatment of patients with infected pancreatic necrosis is associated with high rates of morbidity (∼95%) and mortality (∼50%); this has driven the development of minimally invasive alternatives for the treatment of such cases. Endoscopic Transgastric Necrosectomy (ETN) is an accepted method for debriding infected necrosis in these challenging cases. The National Emergency Laparotomy Audit (NELA) and P-POSSUM scoring systems are well-validated risk stratification tools used nationally for patients undergoing emergency laparotomy. This work aims to determine whether patients undergoing ETN for infected pancreatic necrosis can be risk stratified accurately using both the NELA and P-POSSUM scoring systems. Methods A prospective database of all patients in a single UK centre undergoing ETN from 2011 to 2021 for infected pancreatic necrosis has been maintained.  All patients initially underwent an EUS guided stent placement to create a cystgastrostomy before subsequent transgastric necrosectomy.    Patient demographics, timing of procedures and short-term post procedural outcomes were recorded. The NELA and P-POSSUM score was calculated at the time of the endoscopic cystgastrostomy.  Demographic data were descriptively summarized and ROC analysis was performed to assess the diagnostic accuracy of both the P-POSSUM and NELA score. Data are presented as median (range) Results Sixty-nine patients underwent ETN between 2011 and 2021 with a median age of 54 years-(15-86). Twenty-nine patients-(42%) required ITU admission during their admission. The actual mortality was 10.1%-(7), which was slightly higher than the median of the NELA predicted mortality-(6.7%) but half the median of the P-POSSUM predicted mortality-(21.1%). Median overall predicted mortality for ETN using P-POSSUM was 21.1%-(2.6-85.7%) and with NELA was 6.7%-(0.4-34.3%). The median P-POSSUM score of the patients who died was 33.2%-(6.9-52.4%) compared to the median NELA score which was 17.2%-(0.8-34.3%). The area under the receiver operating characteristics curve-(AUROC) was similar for both the NELA-(0.82, SE = 0.13) and P-POSSUM-(0.75,-SE=0.1). Conclusions Endoscopic Transgastric Necrosectomy is a safe alternative to emergency laparotomy for the debridement of infected pancreatic necrosis.  Both the NELA and P-POSSUM scoring systems can effectively stratify those patients at highest risk, however where P-POSSUM scoring may overestimate mortality NELA scoring may underestimate the severity of illness and mortality associated with the disease.

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