Development of a Gait Feature-Based Model for Classifying Cognitive Disorders Using a Single Wearable Inertial Sensor.

BACKGROUND AND OBJECTIVES: Gait changes are potential markers of cognitive disorders (CDs). We developed a model for classifying older adults with CD from those with normal cognition using gait speed and variability captured from a wearable inertial sensor and compared its diagnostic performance for CD with that of the model using the Mini-Mental State Examination (MMSE). METHODS: We enrolled community-dwelling older adults with normal gait from the Korean Longitudinal Study on Cognitive Aging and Dementia and measured their gait features using a wearable inertial sensor placed at the center of body mass while they walked on a 14-m long walkway thrice at comfortable paces. We randomly split our entire dataset into the development (80%) and validation (20%) datasets. We developed a model for classifying CD using logistic regression analysis from the development dataset and validated it in the validation dataset. In both datasets, we compared the diagnostic performance of the model with that using the MMSE. We estimated optimal cutoff score of our model using receiver operator characteristic analysis. RESULTS: In total, 595 participants were enrolled, of which 101 of them experienced CD. Our model included both gait speed and temporal gait variability and exhibited good diagnostic performance for classifying CD from normal cognition in both the development (area under the receiver operator characteristic curve [AUC] = 0.788, 95% CI 0.748-0.823, p < 0.001) and validation datasets (AUC = 0.811, 95% CI 0.729-0.877, p < 0.001). Our model showed comparable diagnostic performance for CD with that of the model using the MMSE in both the development (difference in AUC = 0.026, standard error [SE] = 0.043, z statistic = 0.610, p = 0.542) and validation datasets (difference in AUC = 0.070, SE = 0.073, z statistic = 0.956, p = 0.330). The optimal cutoff score of the gait-based model was >-1.56. DISCUSSION: Our gait-based model using a wearable inertial sensor may be a promising diagnostic marker of CD in older adults. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that gait analysis can accurately distinguish older adults with CDs from healthy controls.

Epidemiologic and Clinical Outcomes of Pediatric Renal Tumors in Korea: A Retrospective Analysis of The Korean Pediatric Hematology and Oncology Group (KPHOG) Data.

PURPOSE: Renal tumors account for approximately 7% of all childhood cancers. These include Wilms tumor (WT), clear cell sarcoma of the kidney (CCSK), malignant rhabdoid tumor of the kidney (MRTK), renal cell carcinoma (RCC), congenital mesoblastic nephroma (CMN) and other rare tumors. We investigated the epidemiology of pediatric renal tumors in Korea. MATERIALS AND METHODS: From January 2001 to December 2015, data of pediatric patients (0-18 years) newly-diagnosed with renal tumors at 26 hospitals were retrospectively analyzed. RESULTS: Among 439 patients (male, 240), the most common tumor was WT (n=342, 77.9%), followed by RCC (n=36, 8.2%), CCSK (n=24, 5.5%), MRTK (n=16, 3.6%), CMN (n=12, 2.7%), and others (n=9, 2.1%). Median age at diagnosis was 27.1 months (range 0-225.5) and median follow-up duration was 88.5 months (range 0-211.6). Overall, 32 patients died, of whom 17, 11, 1, and 3 died of relapse, progressive disease, second malignant neoplasm, and treatment-related mortality. Five-year overall survival and event free survival were 97.2% and 84.8% in WT, 90.6% and 82.1% in RCC, 81.1% and 63.6% in CCSK, 60.3% and 56.2% in MRTK, and 100% and 91.7% in CMN, respectively (p < 0.001). CONCLUSION: The pediatric renal tumor types in Korea are similar to those previously reported in other countries. WT accounted for a large proportion and survival was excellent. Non-Wilms renal tumors included a variety of tumors and showed inferior outcome, especially MRTK. Further efforts are necessary to optimize the treatment and analyze the genetic characteristics of pediatric renal tumors in Korea.

Healthcare Quality Improvement Analytics: An Example Using Computerized Provider Order Entry.

Evaluation of sustainability after quality improvement (QI) projects in healthcare settings is an essential part of monitoring and future QI planning. With limitations in adopting quasi-experimental study design in real-world practice, healthcare professionals find it challenging to present the sustained effect of QI changes effectively. To provide quantitative methodological approaches for demonstrating the sustainability of QI projects for healthcare professionals, we conducted data analyses based on a QI project to improve the computerized provider order entry system to reduce patients' dosing frequencies in Korea. Data were collected for 5 years: 24-month pre-intervention, 12-month intervention, and 24-month post-intervention. Then, analytic approaches including control chart, Analysis of Variance (ANOVA), and segmented regression were performed. The control chart intuitively displayed how the outcomes changed over the entire period, and ANOVA was used to test whether the outcomes differed between groups. Last, segmented regression analysis was conducted to evaluate longitudinal effects of interventions over time. We found that the impact of QI projects in healthcare settings should be initiated following the Plan-Do-Study-Act cycle and evaluated long-term effects while widening the scope of QI evaluation with sustainability. This study can serve as a guide for healthcare professionals to use a number of statistical methodologies in their QI evaluations.

Association of asthma comorbidity with poor prognosis of coronavirus disease 2019.

BACKGROUND: While global health agencies have listed asthma as a vulnerability for severe cases of coronavirus disease 2019 (COVID-19), the evidence supporting this is scarce. METHODS: A nationwide cohort study was conducted using the validated Korean national health insurance claim data of patients diagnosed with COVID-19 between January 1 and April 8, 2020. Asthma comorbidity was determined using a diagnosis code assigned by the physician and the prescription of asthma-related medications. The clinical course of COVID-19 was classified into 3 severity grades according to the requirements for oxygen supply and mechanical ventilation. We also evaluated the association of asthma with overall and in-hospital mortality of COVID-19. RESULTS: Asthma morbidity was a significant risk factor for severe COVID-19 (grade 2 requiring oxygen supply) (adjusted odds ratio [aOR] = 1.341, 95% confidence interval [CI], 1.051-1.711, P = 0.018) and grade 3 requiring mechanical ventilation or leading to death (aOR = 1.723, 95% CI: 1.230-2.412, P = 0.002) multinomial logistic regression adjusting co-risk factors. Asthma was also significantly associated with mortality of COVID-19 (aOR = 1.453, 95% CI: 1.015-2.080, P = 0.041) and was revealed to have a shorter time to in-hospital mortality of COVID-19 (P < 0.001). Patients with recent asthma exacerbation showed more severe COVID-19 of grade 3 (OR = 7.371, 95% CI: 2.018-26.924, P = 0.003) and higher mortality (OR = 9.208, 95% CI: 2.597-32.646, P < 0.001) in univariable analysis, but the statistical significance was not found in multivariable analysis. CONCLUSION: Asthma morbidity was associated with severity and mortality of COVID-19. Patients with asthma should pay more attention to avoid worsening of COVID-19.

Vitamin D levels and influenza vaccine immunogenicity among HIV-infected and HIV-uninfected adults.

BACKGROUND: Vaccination is the most important preventive strategy against influenza, however post-vaccination antibody responses are often inadequate especially among HIV-infected persons. Vitamin D deficiency has been suggested to adversely influence immune responses and is highly prevalent among HIV-infected adults. Therefore, we evaluated the association between 25-hydroxyvitamin D [25(OH)D] levels and post-influenza vaccination responses. METHODS: We conducted a prospective cohort study evaluating the immunogenicity of monovalent influenza A (H1N1) vaccination among both HIV-infected and HIV-uninfected adults (18-50years of age) during the 2009-2010 influenza season. Antibody titers were evaluated at baseline, day 28, and 6months post-vaccination using hemagluttination inhibition assays. Serum 25(OH)D levels were measured at day 28. Univariate and multivariate regression analyses examined the association between 25(OH)D levels [categorized as <20ng/ml (deficiency) vs. ⩾20ng/ml] with the primary outcome of seroconversion. Secondary outcomes included seroprotection; a ⩾4-fold increase in titers; and geometric mean titers post-vaccination. Analyses were repeated using 25(OH)D levels as a continuous variable. RESULTS: A total of 128 adults [64 HIV-infected (median CD4 count 580cells/mm(3)) and 64 HIV-uninfected] were included. Seroconversion at day 28 post-vaccination was achieved in fewer HIV-infected participants compared with HIV-uninfected participants (56% vs. 74%, p=0.03). Vitamin D deficiency was more prevalent among HIV-infected persons vs. HIV-uninfected persons (25% vs. 17%), although not significantly different (p=0.39). There were no associations found between lower 25(OH)D levels and poorer antibody responses at day 28 or 6months for any of the study outcomes among either HIV-infected or HIV-uninfected adults. CONCLUSION: Vitamin D deficiency was common among both HIV-infected and HIV-uninfected adults, but lower levels did not predict antibody responses after H1N1 (2009) influenza vaccination. Low 25(OH)D levels do not explain poorer post-vaccination responses among HIV-infected persons.