The clinical value of a thorough diagnostic evaluation for neurotologic complaints.

PURPOSE: Determine the clinical efficacy of comprehensive neurotologic testing in patients presenting with complaints of hearing loss, tinnitus and/or dizziness. METHODS: This is a retrospective analysis of 1170 consecutive charts of patients who presented between 1980 and 2013 with neurotologic complaints. Demographic data, chief complaint, diagnostic imaging, audiograms, and blood tests were evaluated. RESULTS: Retrospective analysis of 1170 patient charts was performed. 762/1170 (65%) patients presented with subjective hearing loss, 575/1170 (49%) with dizziness, and 657/1170 (56%) with tinnitus. Audiometric testing revealed hearing loss in 1059/1169 (91%) patients. 536/1120 (48%) patients had abnormalities on Magnetic Resonance Imaging, and 343/1087 (32%) on Computed Tomography imaging. Endocrine and immunologic testing revealed 108/1135 (9.5%) patients were hyperglycemic; 125/1124 (11%) patients had elevated TSH; 149/1141 (13%) patients had a positive ANA; and 82/1133 (7.2%) patients were positive for RF. 198/1083 (18%) of patients were positive for HLA-B35, 246/1083 (23%) for HLA-Cw4, 454/1083 (42%) for HLA-Cw7, and 747/1060 (70%) of patients had absent HLA-DR4. 112/1085 (10%) of patients were positive for anti-68kD antibodies and 154/936 (17%) for protein 0. Many patients were diagnosed with previously unrecognized medical conditions. CONCLUSION: Comprehensive neurotological workup results in diagnoses that would go unrecognized otherwise, allowing patients to receive prompt treatment for medically important conditions, some of which may be causally related to their neurotologic complaints. However, the value of each study for routine testing of patients with neurotologic complaints remains controversial; and the evidence presented herein should help practitioners determine what studies should be included in their patient assessments.

Flight of the COVID-19 patient: experience with a Wuhan evacuee: a case report.

BACKGROUND: Coronavirus disease 2019, caused by severe acute respiratory syndrome coronavirus 2, was declared a global pandemic by the World Health Organization in March 2020. CASE PRESENTATION: We report a case of a 51-year-old Chinese woman who was evacuated from Wuhan, China and diagnosed with coronavirus disease 2019 infection at a Southern California quarantine facility. Her clinical course was notable for high fevers, night sweats, productive cough, transient leukopenia, lymphopenia, thrombocytopenia, and transaminitis. Evolving hypoxia and infiltrates on chest imaging warranted the trial of an investigational antiviral drug - remdesivir. Our patient recovered and was discharged after 2 weeks of hospitalization. CONCLUSIONS: This case highlights our patient's clinical course, including diagnostic work-up, medical management, and challenges in defining non-infectivity in a relatively unknown disease.

Machine Learning Algorithms for Objective Remission and Clinical Outcomes with Thiopurines.

BACKGROUND AND AIMS: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods using 6-thioguanine nucleotide [6-TGN] metabolites have failed in randomized controlled trials [RCTs], and have not been used to predict objective remission [OR]. Our aims were to: 1) develop machine learning algorithms [MLA] using laboratory values and age to identify patients in objective remission on thiopurines; and 2) determine whether achieving algorithm-predicted objective remission resulted in fewer clinical events per year. METHODS: Objective remission was defined as the absence of objective evidence of intestinal inflammation. MLAs were developed to predict three outcomes: objective remission, non-adherence, and preferential shunting to 6-methylmercaptopurine [6-MMP]. The performance of the algorithms was evaluated using the area under the receiver operating characteristic curve [AuROC]. Clinical event rates of new steroid prescriptions, hospitalisations, and abdominal surgeries were measured. RESULTS: Retrospective review was performed on medical records of 1080 IBD patients on thiopurines. The AuROC for algorithm-predicted remission in the validation set was 0.79 vs 0.49 for 6-TGN. The mean number of clinical events per year in patients with sustained algorithm-predicted remission [APR] was 1.08 vs 3.95 in those that did not have sustained APR [p < 1 x 10-5]. Reductions in the individual endpoints of steroid prescriptions/year [-1.63, p < 1 x 10-5], hospitalisations/year [-1.05, p < 1 x 10-5], and surgeries/year [-0.19, p = 0.065] were seen with algorithm-predicted remission. CONCLUSIONS: A machine learning algorithm was able to identify IBD patients on thiopurines with algorithm-predicted objective remission, a state associated with significant clinical benefits, including decreased steroid prescriptions, hospitalisations, and surgeries.