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:

Risk factors for hepatitis C virus infection in the Colombian Caribbean coast: A case-control study An estimated 6.8-8.9 million people are infected with hepatitis C virus in Latin America, of which less than 1% receives antiviral treatment. Studies so far in Colombia have attempted to determine the prevalence of the disease in some risk groups, thus preventing the identification of other factors potentially involved in the spread of the infection. To identify traditional and non-traditional risk factors for chronic hepatitis C in the Colombian Caribbean coast. This was a case-control study (1:3) matched by health care provider and age (± 10 years) conducted at the primary care level of gastroenterology and hepatology outpatient services. All patients with a positive ELISA underwent a confirmatory viral load test. A multivariate logistic regression analysis identified the independent predictors of infection. Blood transfusion (OR =159.2; 95% CI: 35.4-715; p<0.001) and history of hospitalization before 1994 (OR =4.7; 95% CI: 1.3-17.1; p=0.018) were identified as the only two independent predictors of infection. It is necessary to check the reproducibility of these results and to conduct cost-effectiveness studies before recommending their use in the design of new screening strategies.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["disease", "hepatitis C virus infection", "chronic hepatitis C", "infection"], "BiomedicalOccupationOrDiscipline": ["gastroenterology", "hepatology"], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["history of hospitalization"], "Eukaryote": [], "Finding": ["Risk factors", "risk factors", "infected", "positive"], "Food": [], "HealthCareActivity": ["Blood transfusion", "primary care level", "outpatient services", "ELISA", "antiviral treatment"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["people", "groups"], "ProfessionalOrOccupationalGroup": ["health care provider"], "ResearchActivity": ["case-control study", "studies", "Studies", "new screening strategies"], "SpatialConcept": ["Latin America", "Caribbean coast", "Colombia"], "Virus": ["hepatitis C virus"]}