You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Emergency general surgery specific frailty index: A validation study Assessment of operative risk in geriatric patients undergoing emergency general surgery (EGS) is challenging. Frailty is an established measure for risk assessment in surgical cases. The aim of our study was to validate a modified 15 variable emergency general surgery specific frailty index (EGSFI). We prospectively collected geriatric (age > 65) emergency general surgery patients for 1- year. Post-operative complications were collected. Frailty Index was calculated for 200 patients based on their pre-admission condition using 50- variable modified Rockwood Frailty Index (FI). EGSFI was developed based on the regression model for complications and the most significant factors in the FI. ROC curve analysis was performed to determine cutoff for frail status. We validated our results using 60 patients for predicting complications. A total of 260 patients (200 developing, 60 Validation) were enrolled in this study. Mean age was 71 ± 11 years, and 33% developed complications. Most common complications were pneumonia (12%), UTI (9%), and wound infection (7%). Univariate analysis identified 15 variables significantly associated with complications that were used to develop the EGSFI. A cutoff frailty score of 0.325 was identified using ROC curve analysis for frail status .Sixty- patients (frail: 18, non-frail: 42) were enrolled in the validation cohort. Frail patients were more likely to have post-operative complications (47% vs. 20%, p < 0.001) compared to nonfrail patients. Frail status based on EGSFI was a significant predictor of post-operative complications (OR =7.3, 95% CI = 1.7 - 19.8; p=0.006). Age was not associated with postoperative complications (OR =0.99, 95% CI = 0.92 -1.06; p=0.86). The 15- variable validated EGSFI is a simple and reliable bedside tool to determine the frailty status of patients undergoing emergency general surgery. Frail status as determined by Abstract the EGSFI is an independent predictor of post-operative complications and mortality in geriatric emergency general surgery patients. Level II, Prognostic Studies - Investigating the Effect of a Patient Characteristic on the Outcome of Disease.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["post-operative complications", "Post-operative complications", "UTI", "pneumonia", "complications", "postoperative complications", "wound infection"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["Patient Characteristic"], "Eukaryote": [], "Finding": ["non-frail", "frailty status", "Frailty", "Frail", "Outcome of Disease", "frail", "frailty score"], "Food": [], "HealthCareActivity": ["emergency general surgery specific frailty index", "calculated", "enrolled", "EGSFI", "risk assessment", "Assessment"], "InjuryOrPoisoning": [], "IntellectualProduct": ["specific frailty index", "Frailty Index", "FI", "regression model", "Rockwood Frailty Index"], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["cohort"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study", "Prognostic Studies", "Validation", "validation", "validation study", "validate", "validated"], "SpatialConcept": [], "Virus": []}