78
views
0
recommends
+1 Recommend
0 collections
    14
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Development of a triage protocol for patients presenting with gastrointestinal hemorrhage: a prospective cohort study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          Many patients presenting with acute gastrointestinal hemorrhage (GIH) are admitted to the intensive care unit (ICU) for monitoring. A simple triage protocol based upon validated risk factors could decrease ICU utilization.

          Methods

          Records of 188 patients admitted with GIH from the emergency department (ED) were reviewed for BLEED criteria (visualized red blood, systolic blood pressure below 100 mm Hg, elevated prothrombin time [PT], erratic mental status, and unstable comorbid disease) and complication within the first 24 hours of admission. Variables associated with early complication were reassessed in 132 patients prospectively enrolled as a validation cohort. A triage model was developed using significant predictors.

          Results

          We studied 188 patients in the development set and 132 in the validation set. Red blood (relative risk [RR] 4.53, 95% confidence interval [CI] 2.04, 10.07) and elevated PT (RR 3.27, 95% CI 1.53, 7.01) were significantly associated with complication in the development set. In the validation cohort, the combination of red blood or unstable comorbidity had a sensitivity of 0.73, a specificity of 0.55, a positive predictive value of 0.24, and a negative predictive value of 0.91 for complication within 24 hours. In simulation studies, a triage model using these variables could reduce ICU admissions without increasing the number of complications.

          Conclusion

          Patients presenting to the ED with GIH who have no evidence of ongoing bleeding or unstable comorbidities are at low risk for complication during hospital admission. A triage model based on these variables should be tested prospectively to optimize critical care resource utilization in this common condition.

          Related collections

          Most cited references22

          • Record: found
          • Abstract: found
          • Article: not found

          Risk assessment after acute upper gastrointestinal haemorrhage.

          The aim of this study was to establish the relative importance of risk factors for mortality after acute upper gastrointestinal haemorrhage, and to formulate a simple numerical scoring system that categorizes patients by risk. A prospective, unselected, multicentre, population based study was undertaken using standardised questionnaires in two phases one year apart. A total of 4185 cases of acute upper gastrointestinal haemorrhage over the age of 16 identified over a four month period in 1993 and 1625 cases identified subsequently over a three month period in 1994 were included in the study. It was found that age, shock, comorbidity, diagnosis, major stigmata of recent haemorrhage, and rebleeding are all independent predictors of mortality when assessed using multiple logistic regression. A numerical score using these parameters has been developed that closely follows the predictions generated by logistical regression equations. Haemoglobin, sex, presentation (other than shock), and drug therapy (non-steroidal anti-inflammatory drugs and anticoagulants) are not represented in the final model. When tested for general applicability in a second population, the scoring system was found to reproducibly predict mortality in each risk category. In conclusion, a simple numerical score can be used to categorize patients presenting with acute upper gastrointestinal haemorrhage by risk of death. This score can be used to determine case mix when comparing outcomes in audit and research and to calculate risk standardised mortality. In addition, this risk score can identify 15% of all cases with acute upper gastrointestinal haemorrhage at the time of presentation and 26% of cases after endoscopy who are at low risk of rebleeding and negligible risk of death and who might therefore be considered for early discharge or outpatient treatment with consequent resource savings.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A risk score to predict need for treatment for upper-gastrointestinal haemorrhage.

            Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to identify a patient's need for treatment. Our first study used data from 1748 patients admitted for upper-gastrointestinal haemorrhage. By logistic regression, we derived a risk score that predicts patients' risks of needing blood transfusion or intervention to control bleeding, rebleeding, or dying. From this score, we developed a simplified fast-track screen for use at initial presentation. In a second study, we prospectively validated this score using receiver operating characteristic (ROC) curves--a measure of the validity of a scoring system--and chi2 goodness-of-fit testing with data from 197 patients. We also validated the quicker screening tool. We calculated risk scores from patients' admission haemoglobin, blood urea, pulse, and systolic blood pressure, as well as presentation with syncope or melaena, and evidence of hepatic disease or cardiac failure. The score discriminated well with a ROC curve area of 0.92 (95% CI 0.88-0.95). The score was well calibrated for patients needing treatment (p=0.84). Our score identified patients at low or high risk of needing treatment to manage their bleeding. This score should assist the clinical management of patients presenting with upper-gastrointestinal haemorrhage, but requires external validation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model.

              Models based on artificial neural networks (ANN) are useful in predicting outcome of various disorders. There is currently no useful predictive model for risk assessment in acute lower-gastrointestinal haemorrhage. We investigated whether ANN models using information available during triage could predict clinical outcome in patients with this disorder. ANN and multiple-logistic-regression (MLR) models were constructed from non-endoscopic data of patients admitted with acute lower-gastrointestinal haemorrhage. The performance of ANN in classifying patients into high-risk and low-risk groups was compared with that of another validated scoring system (BLEED), with the outcome variables recurrent bleeding, death, and therapeutic interventions for control of haemorrhage. The ANN models were trained with data from patients admitted to the primary institution during the first 12 months (n=120) and then internally validated with data from patients admitted to the same institution during the next 6 months (n=70). The ANN models were then externally validated and direct comparison made with MLR in patients admitted to an independent institution in another US state (n=142). Clinical features were similar for training and validation groups. The predictive accuracy of ANN was significantly better than that of BLEED (predictive accuracy in internal validation group for death 87% vs 21%; for recurrent bleeding 89% vs 41%; and for intervention 96% vs 46%) and similar to MLR. During external validation, ANN performed well in predicting death (97%), recurrent bleeding (93%), and need for intervention (94%), and it was superior to MLR (70%, 73%, and 70%, respectively). ANN can accurately predict the outcome for patients presenting with acute lower-gastrointestinal haemorrhage and may be generally useful for the risk stratification of these patients.
                Bookmark

                Author and article information

                Journal
                Crit Care
                Critical Care
                BioMed Central
                1364-8535
                1466-609X
                2008
                22 April 2008
                : 12
                : 2
                : R57
                Affiliations
                [1 ]Sleep Institute of Augusta, 3685 Wheeler Road, Suite 101, Augusta, GA 30909, USA
                [2 ]201 Davis Heart and Lung Research Institute, 473 West 12th Avenue, Columbus, OH 43210, USA
                [3 ]University of Colorado Health Sciences Center, 4200 East 9th Avenue, Mailbox C272, Denver, CO 80262, USA
                [4 ]Division of Pulmonary and Critical Care Medicine, 130 Mason Farm Road, 4th Floor Bioinformatics Building, CB# 7020, University of North Carolina at Chapel Hill, NC 27599-7020, USA
                Article
                cc6878
                10.1186/cc6878
                2447612
                18430209
                4218152f-2e08-465b-8cc5-91026c306064
                Copyright © 2008 Das et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 January 2008
                : 20 February 2008
                : 8 April 2008
                : 22 April 2008
                Categories
                Research

                Emergency medicine & Trauma
                Emergency medicine & Trauma

                Comments

                Comment on this article