A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding

Abstract Background Lower gastrointestinal 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 pa...

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Autores principales:	Manraj Singh, Jayne Chiang, Andre Seah, Nan Liu, Ronnie Mathew, Sachin Mathur
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Lower gastrointestinal bleeding Predictive model Per-rectal bleed Haematochezia Haemorrhagic Shock Surgery RD1-811 Medical emergencies. Critical care. Intensive care. First aid RC86-88.9
Acceso en línea:	https://doaj.org/article/b083bee09789431b9f5fb0d0acc7d17a
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spelling	oai:doaj.org-article:b083bee09789431b9f5fb0d0acc7d17a2021-11-28T12:38:00ZA clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding10.1186/s13017-021-00402-y1749-7922https://doaj.org/article/b083bee09789431b9f5fb0d0acc7d17a2021-11-01T00:00:00Zhttps://doi.org/10.1186/s13017-021-00402-yhttps://doaj.org/toc/1749-7922Abstract Background Lower gastrointestinal 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. 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 < 90 mmHg), anaemia (Hb < 9 g/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. Conclusion 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.Manraj SinghJayne ChiangAndre SeahNan LiuRonnie MathewSachin MathurBMCarticleLower gastrointestinal bleedingPredictive modelPer-rectal bleedHaematocheziaHaemorrhagicShockSurgeryRD1-811Medical emergencies. Critical care. Intensive care. First aidRC86-88.9ENWorld Journal of Emergency Surgery, Vol 16, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Lower gastrointestinal bleeding Predictive model Per-rectal bleed Haematochezia Haemorrhagic Shock Surgery RD1-811 Medical emergencies. Critical care. Intensive care. First aid RC86-88.9
spellingShingle	Lower gastrointestinal bleeding Predictive model Per-rectal bleed Haematochezia Haemorrhagic Shock Surgery RD1-811 Medical emergencies. Critical care. Intensive care. First aid RC86-88.9 Manraj Singh Jayne Chiang Andre Seah Nan Liu Ronnie Mathew Sachin Mathur A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
description	Abstract Background Lower gastrointestinal 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. 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 < 90 mmHg), anaemia (Hb < 9 g/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. Conclusion 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.
format	article
author	Manraj Singh Jayne Chiang Andre Seah Nan Liu Ronnie Mathew Sachin Mathur
author_facet	Manraj Singh Jayne Chiang Andre Seah Nan Liu Ronnie Mathew Sachin Mathur
author_sort	Manraj Singh
title	A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
title_short	A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
title_full	A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
title_fullStr	A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
title_full_unstemmed	A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
title_sort	clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding
publisher	BMC
publishDate	2021
url	https://doaj.org/article/b083bee09789431b9f5fb0d0acc7d17a
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A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding

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