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Objectives@#Coronavirus disease 2019 (COVID-19)–associated mucormycosis (CAM) has emerged as a formidable infection in patients with COVID-19. The aggressive management ofCAM affects quality of life (QOL); thus, this study was designed to assess the QOL in patients with CAM at a tertiary healthcare institution. @*Methods@#This cross-sectional study of 57 patients with CAM was conducted over 6 monthsusing a semi-structured standard questionnaire (the abbreviated World Health Organization Quality of Life questionnaire [WHO-BREF]) and a self-rated improvement (SRI) scale ranging from 0 to 9. Cut-off values of ≤52 and < 7 were considered to indicate poor QOL and poor improvement, respectively. The correlations of QOL and SRI scores were evaluated using Spearman rho values. @*Results@#In total, 27 patients (47.4%; 95% confidence interval [CI], 34.9%–60.1%) and 26 patients (45.6%; 95% CI, 33.4%–58.4%) had poor QOL and poor SRI scores, respectively. The overall median (interquartile range) QOL score was 52 (41–63). Headache (adjusted B, −12.3), localized facial puffiness (adjusted B , −16.4), facial discoloration (adjusted B, −23.4), loosening of teeth (adjusted B, −18.7), and facial palsy (adjusted B, −38.5) wer e significantly associated with the QOL score in patients with CAM. @*Conclusion@#Approximately 1 in 2 patients with CAM had poor QOL and poor improvement.Various CAM symptoms were associated with QOL in these patients. Early recognition is the key to optimal treatment, improved outcomes, and improved QOL in patients with CAM.
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The soluble urokinase plasminogen activator receptor (suPAR) has been proposed as a biomarker for the risk stratification of patients presenting with acute infections. However, most studies evaluating suPAR have used platform-based assays, the diagnostic accuracy of which may differ from point-of-care tests capable of informing timely patient triage in settings without established laboratory capacity. Using samples and data collected during a prospective cohort study of 425 patients presenting with moderate Covid-19 to two hospitals in India, we evaluated the analytical performance and diagnostic accuracy of a commercially-available rapid diagnostic test (RDT) for suPAR, using an enzyme-linked immunoassay (ELISA) as the reference standard. Although agreement between the two tests was limited (bias = -2.46 ng/mL [95% CI = -2.65 to -2.27 ng/mL]), diagnostic accuracy to predict progression to supplemental oxygen requirement was comparable, whether suPAR was used alone (area under the receiver operating characteristic curve [AUC] of RDT = 0.73 [95% CI = 0.68 to 0.79] vs. AUC of ELISA = 0.70 [95% CI = 0.63 to 0.76]; p = 0.12) or as part of a previously published multivariable clinical prediction model (AUC of RDT-based model = 0.74 [95% CI = 0.66 to 0.83] vs. AUC of ELISA-based model = 0.72 [95% CI = 0.64 to 0.81]; p = 0.78). Lack of agreement between the suPAR RDT and ELISA in our cohort warrants further investigation and highlights the importance of assessing candidate point-of-care tests to ensure management algorithms reflect the assay that will ultimately be used to inform patient care. The availability of a quantitative point-of-care test for suPAR opens the door to suPAR-guided risk stratification of patients with Covid-19 and other acute infections in settings with limited laboratory capacity.
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BackgroundIn locations where few people have received COVID-19 vaccines, health systems remain vulnerable to surges in SARS-CoV-2 infections. Tools to identify patients suitable for community-based management are urgently needed. MethodsWe prospectively recruited adults presenting to two hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 in order to develop and validate a clinical prediction model to rule-out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 bpm; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex and SpO2) and one of seven shortlisted biochemical biomarkers measurable using near-patient tests (CRP, D-dimer, IL-6, NLR, PCT, sTREM-1 or suPAR), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration and clinical utility of the models in a temporal external validation cohort. Findings426 participants were recruited, of whom 89 (21{middle dot}0%) met the primary outcome. 257 participants comprised the development cohort and 166 comprised the validation cohort. The three models containing NLR, suPAR or IL-6 demonstrated promising discrimination (c-statistics: 0{middle dot}72 to 0{middle dot}74) and calibration (calibration slopes: 1{middle dot}01 to 1{middle dot}05) in the validation cohort, and provided greater utility than a model containing the clinical parameters alone. InterpretationWe present three clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources. FundingMedecins Sans Frontieres, India. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA living systematic review by Wynants et al. identified 137 COVID-19 prediction models, 47 of which were derived to predict whether patients with COVID-19 will have an adverse outcome. Most lacked external validation, relied on retrospective data, did not focus on patients with moderate disease, were at high risk of bias, and were not practical for use in resource-limited settings. To identify promising biochemical biomarkers which may have been evaluated independently of a prediction model and therefore not captured by this review, we searched PubMed on 1 June 2020 using synonyms of "SARS-CoV-2" AND ["biomarker" OR "prognosis"]. We identified 1,214 studies evaluating biochemical biomarkers of potential value in the prognostication of COVID-19 illness. In consultation with FIND (Geneva, Switzerland) we shortlisted seven candidates for evaluation in this study, all of which are measurable using near-patient tests which are either currently available or in late-stage development. Added value of this studyWe followed the TRIPOD guidelines to develop and validate three promising clinical prediction models to help clinicians identify which patients presenting with moderate COVID-19 can be safely managed in the community. Each model contains three easily ascertained clinical parameters (age, sex, and SpO2) and one biochemical biomarker (NLR, suPAR or IL-6), and would be practical for implementation in high-patient-throughput low resource settings. The models showed promising discrimination and calibration in the validation cohort. The inclusion of a biomarker test improved prognostication compared to a model containing the clinical parameters alone, and extended the range of contexts in which such a tool might provide utility to include situations when bed pressures are less critical, for example at earlier points in a COVID-19 surge. Implications of all the available evidencePrognostic models should be developed for clearly-defined clinical use-cases. We report the development and temporal validation of three clinical prediction models to rule-out progression to supplemental oxygen requirement amongst patients presenting with moderate COVID-19. The models are readily implementable and should prove useful in triage and resource allocation. We provide our full models to enable independent validation.
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Methods@#Forty-eight iSCI participants will be recruited based on the inclusion criteria. The participants will be randomly assigned to any of the three groups: virtual reality-based balance training along with the electrical stimulation group, virtual reality-based balance training along with sham stimulation group, or virtual reality-based balance training group. The intervention will be delivered as 60-minute sessions, thrice a week for 4 weeks. @*Results@#The performance of the participants will be assessed using the lower extremity motor score, static and dynamic balance assessment using TechnoBody ProKin tilting platform and Berg Balance Scale, Walking Index for Spinal Cord Injury, and World Health Organization Quality of Life-BREF at pre-intervention, after 4 weeks post-intervention, and at 1-month follow-up. @*Conclusions@#The trial will provide new knowledge about the effectiveness of electrical stimulation-augmented virtual reality training in improving balance in individuals with iSCI. The study results will contribute to the design of better rehabilitation programs for individuals with iSCI.