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:

The clinical and economic burden of significant bleeding during lung resection surgery: A retrospective matched cohort analysis of real - world data The objective of this retrospective study was to quantify the clinical and economic burden of significant bleeding in lung resection surgery in the US. This study utilized 2009-2012 data from the Premier Perspective Database(TM). Adult patients with primary pulmonary lobectomy or segmentectomy procedures were categorized by the surgical approach (VATS vs open) and primary diagnosis (primary or metastatic lung cancer vs non-lung cancer). Patients requiring ≥3 units of blood products with at least 1 unit of PRBCs: " significant bleeding " cohort; those requiring <3 units: " non-significant bleeding " cohort; and those not requiring blood products: " no bleeding " cohort. A matched cohort analysis was performed between the " significant bleeding " and the " no bleeding cohort " using matching variables: hospital, lung cancer diagnosis, year of surgery, APR-DRG severity score, procedure type and approach, age, and gender. The " All - patient " cohort comprised 21,429 patients: 213 " significant bleeding "; 2,780 " non-significant bleeding "; and 18,436 " no bleeding ". Overall incidence of significant chest bleeding was 0.99%. Patients from " significant bleeding " cohort and " non-significant bleeding " cohort had 2.5 days and 2 days (p < 0.0001) longer length of stay in the hospital compared to those in the " no bleeding " cohort, respectively. Overall, hospital costs for " significant bleeding " cohort were higher than " no bleeding " cohort for those who were covered under Medicare ($59,871 vs $23,641), were ≥76 years of age ($64,010 vs $24,243), had greater severity of illness ($97,813 vs $51,871) and underwent open segmentectomy ($74,220 vs $21,903). Hospital costs for " significant bleeding " cohort and " non-significant bleeding " were significantly higher ($11,589 and $5,280, respectively, p < 0.0001) than no bleeding cohort. Although significant bleeding during lung resection surgery is rare, patients with such complication could stay longer at the hospital and cost an average of $13,103 more than those without.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["complication", "bleeding"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["blood products", "PRBCs"], "ClinicalAttribute": ["procedure type"], "Eukaryote": [], "Finding": ["non-significant"], "Food": [], "HealthCareActivity": ["open", "primary pulmonary lobectomy", "non-lung cancer", "segmentectomy procedures", "VATS", "segmentectomy", "metastatic lung cancer", "lung resection surgery", "lung cancer diagnosis", "primary"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Premier Perspective Database(TM)"], "MedicalDevice": [], "Organization": ["hospital"], "PopulationGroup": ["world", "cohort"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study", "cohort analysis", "retrospective matched cohort analysis", "retrospective study"], "SpatialConcept": ["US", "chest"], "Virus": []}