Preparation and validation of a systemic loxoscelism prediction protocol
Elaboración y validación de una regla de predicción clinica para identificar compromiso sistemico en casos de loxoscelismo
DOI:
https://doi.org/10.25176/RFMH.v20i1.2642Keywords:
Spider venoms, Brown Recluse Spider, PredictionAbstract
Introduction: Systemic loxoscelism is the most severe complication of loxoscelism. The management of the cadre by health personnel presents a high variability due to factors that are currently unknown. There is no standard of reference or a clinical prediction model that can guide our decisions when approaching a spider bite patient. Objective: Develop and validate a clinical prediction rule for systemic loxoscelism. Methods: An observational study of derivation and validation of a clinical prediction model was carried out with diagnostic test validation based on a historical single-arm cohort in patients treated at Vitarte Hospital between 2007 and 2016 and international clinical reports published. Results: Systemic loxoscelism occurred only in 32.9% (n = 24) of cases. For the bivariate analysis, the variables that showed a statistically significant association (P <0.05) were sex, bite in an independent abdomen in relation to other parts of the body, bite in other parts of the body than the abdomen, vomiting , fever and hemoglobinuria. The regression analysis included in the analysis the variables: sex, vomit, fever and hemoglobinuria. Bootstrapping determined the internal validity of the model. The area under the curve was 0.91 (P <0.05) and the sensitivity, specificity, LR + and LR- were 79.1%, 93.8%, 12.9 and 0.22 respectively. Conclusions: The protocol of prediction of systemic derived loxoscelism is valid, for the moment.
Downloads
![](http://revistas.urp.edu.pe/public/journals/1/article_2642_cover_es_ES.png)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Revista de la Facultad de Medicina Humana
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.