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:

Nationwide reduction in the number of corneal transplantations for keratoconus following the implementation of cross-linking Keratoconus is characterized by corneal ectasia and irregular astigmatism, which can lead to diminished vision and corneal scarring. Approximately 10-20% of patients with keratoconus eventually require a corneal transplant. Corneal cross-linking (CXL) is a relatively new treatment that may help prevent the need for corneal transplantation. Here, we investigated whether the introduction of CXL has reduced the number of corneal transplants performed annually. Data regarding the transplantation procedures performed in patients under the age of 50 years were extracted from the Dutch National Organ Transplant Registry. The number of corneal transplants performed prior to (i.e. in 2005 through 2007) and following the introduction of CXL (i.e. in 2012 through 2014) were compared. Furthermore, a trend analysis on annual keratoplasties over time was performed. Approximately 25% fewer corneal transplants were performed in the 3- year period following the introduction of CXL compared to the 3- year period prior to the introduction of CXL (201 versus 269 transplants, respectively; p = 0.005). Age, gender and visual acuity were similar between the patient groups in the two time periods. Trend analysis also demonstrated a significant decrease in the amount of corneal transplants (p = 0.001). Significantly fewer corneal transplants were performed for treating keratoconus following the nationwide introduction of CXL. This reduction suggests that corneal cross-linking can significantly reduce the need for corneal transplantation.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["Keratoconus", "corneal ectasia", "irregular astigmatism", "keratoconus", "diminished vision"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["visual acuity"], "Eukaryote": [], "Finding": ["corneal scarring"], "Food": [], "HealthCareActivity": ["corneal transplantation", "corneal transplants", "keratoplasties", "corneal transplant", "transplantation procedures", "transplants", "treatment", "corneal transplantations"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Dutch National Organ Transplant Registry"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": [], "SpatialConcept": [], "Virus": []}