External Validation of the Strate's Predictive Model of Severity in Lower Intestinal Bleeding

2008 ◽  
Vol 67 (5) ◽  
pp. AB320
Author(s):  
Ana Berrozpe ◽  
Francisco Rodriguez-Moranta ◽  
Jordi Guardiola ◽  
Mireia PeñAlva ◽  
Josep M. Botargues ◽  
...  
2018 ◽  
Vol 36 (12) ◽  
pp. 1973-1980 ◽  
Author(s):  
Lorenzo Marconi ◽  
Roderick de Bruijn ◽  
Erik van Werkhoven ◽  
Christian Beisland ◽  
Kate Fife ◽  
...  

Author(s):  
Parastou Fatemi ◽  
Yi Zhang ◽  
Summer S. Han ◽  
Natasha Purington ◽  
Corinna C. Zygourakis ◽  
...  

2021 ◽  
Author(s):  
Manraj Singh ◽  
Jayne Chiang ◽  
Andre Seah ◽  
Nan Liu ◽  
Ronnie Mathew ◽  
...  

Abstract Background: Lower Gastro-Intestinal Bleeding (LGIB) is a common presentation of surgical admissions, imposing a significant burden on healthcare costs and resources. There is a paucity of standardised clinical predictive tools available for the initial assessment and risk stratification of patients with LGIB. We propose a simple clinical scoring model to prognosticate patients at risk of severe LGIB and an algorithm to guide management of such patients.Methods: A retrospective cohort study was conducted, identifying consecutive patients admitted to our institution for LGIB over a 1-year period. Baseline demographics, clinical parameters at initial presentation and treatment interventions were recorded. Severe LGIB was the primary outcome measure. Multivariate logistic regression was performed to identify factors predictive of severe LGIB. A clinical management algorithm was developed to discriminate between patients requiring admission, and to guide endoscopic, angiographic and/or surgical intervention.Results: 226/649 (34.8%) patients had severe LGIB. Six variables were entered into a clinical predictive model for risk stratification of LGIB: Tachycardia (HR>100), hypotension (SBP<90mmHg), anemia (Hb<9g/dL), metabolic acidosis, use of antiplatelet/anticoagulants, and active per-rectal bleeding. The optimum cut-off score of >1 had a sensitivity of 91.9%, specificity of 39.8%, and Positive and Negative Predictive Values of 45% and 90.2% respectively for predicting severe LGIB. The Area Under Curve (AUC) was 0.77.BConclusion: Early diagnosis and management of severe LGIB remains a challenge for the acute care surgeon. The predictive model described comprises objective clinical parameters routinely obtained at initial triage to guide risk stratification, disposition and inpatient management of patients.


2017 ◽  
Vol 33 (5) ◽  
pp. 405-413 ◽  
Author(s):  
Björn Stessel ◽  
Audrey A.A. Fiddelers ◽  
Marco A. Marcus ◽  
Sander M.J. van Kuijk ◽  
Elbert A. Joosten ◽  
...  

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Thibaut Benoit ◽  
Thomas Prudhomme ◽  
Aurélien Adypagavane ◽  
Bernard Malavaud ◽  
Michel Soulié ◽  
...  

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