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:

Correlation between preoperative physical signs and functional outcomes after laminoplasty for ossification of the posterior longitudinal ligament Ossification of the posterior longitudinal ligament (OPLL) can cause myelopathy that is often managed surgically. Knowledge of predictors of surgical outcomes can provide decision support to surgeons. The aims of this study were to investigate the relationships between preoperative physical signs and postoperative functional outcomes in patients with OPLL and to clarify whether physical signs could predict functional outcomes. Fifty-five patients with OPLL who had undergone cervical laminoplasty were included in this study. Six physical signs including hyperreflexia, Babinski sign, sensory disturbance, grip strength, 10-s grip and release test, and bladder dysfunction, and four other factors including age, duration of symptoms, history of minor trauma and preoperative Japanese Orthopaedic Association (JOA) score were investigated as potential predictive prognostic factors using both univariate and multivariate analyses. The mean recovery rate of JOA score was 62.5 ± 32.5%. The neurological recovery rate was negatively associated with age (P = 0.002), the duration of symptoms (P = 0.002) and Babinski sign (P = 0.007), whereas it was positively correlated with grip strength (P = 0.011). Multiple logistic regression analyses revealed that age (Odds ratio: 0.89, 95% CI: 0.81-0.99) and Babinski sign (Odds ratio: 0.18, 95% CI: 0.04-0.89) were factors associated with functional outcomes. Satisfactory functional outcomes could be expected for patients who are young and do not exhibit the Babinski sign, showing that the Babinski sign could be useful as an indicator of the window of opportunity for achieving satisfactory functional outcomes.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["bladder dysfunction", "OPLL", "Knowledge", "ossification of the posterior longitudinal ligament", "sensory disturbance", "myelopathy", "Ossification of the posterior longitudinal ligament"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["prognostic factors"], "Eukaryote": [], "Finding": ["Babinski sign", "hyperreflexia", "positively", "physical signs", "negatively"], "Food": [], "HealthCareActivity": ["surgically", "surgical", "cervical laminoplasty", "laminoplasty"], "InjuryOrPoisoning": ["minor trauma"], "IntellectualProduct": ["expected", "Multiple logistic regression analyses"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": ["surgeons"], "ResearchActivity": ["study"], "SpatialConcept": [], "Virus": []}