ABSTRACT
Background: In the early phases of the 2019 novel coronavirus (COVID-19) pandemic, health system leaders faced the urgent task of translating the unknown into forecasting models for hospital capacity. Our study objective was to demonstrate the application of a practical, locally informed model to estimate the hospital capacity needed even though the community COVID-19 caseload was unknown. Methods: We developed a susceptible-infected-recovered (SIR) model that was adopted from the University of Pennsylvania COVID-19 Hospital Impact Model for Epidemics and employed at 8 hospitals within Ochsner Health, the largest integrated delivery system in Louisiana, between March 16 and April 15, 2020. Intensive care unit (ICU) admissions of cases in the New Orleans area were used to estimate the community case load when testing was delayed. Results: Initially, the observed ICU census trended near R0=2.0, whereas the ventilator census trended between R0=2.0 and 3.0. After implementing social distancing, both the ICU and ventilator capacity trended toward R0=1.3, while non-ICU medical/surgical beds trended toward R0=1.5. The model accurately predicted peak ICU (n=250) and hospital bed (n=487) usage by April 6, 2020. In response to model trends, Ochsner added 130 ICU beds across its hospitals by opening a new ICU and converting operating rooms and parts of emergency departments to ICU beds. Conclusion: When disease testing is limited or results are delayed, ICU admissions data can inform SIR models of the rate of spread of COVID-19 in a community. Our model used various R0 plots to demonstrate an array of scenarios to guide planning for hospital and political leaders.
ABSTRACT
OBJECTIVE: Olfactory dysfunction is a common problem that is most frequently attributed to upper respiratory infection. Postviral olfactory dysfunction (PVOD) can be prolonged and clinically challenging to treat. Olfactory training (OT) has demonstrated potential benefit for patients with nonspecific olfactory dysfunction. We sought to evaluate the efficacy of OT specifically for PVOD by pooled analysis of the existing evidence. DATA SOURCES: PubMed, Embase, and Web of Science. REVIEW METHODS: Following PRISMA guidelines, PubMed, Embase, and Web of Science databases were queried and abstracts screened independently by 2 investigators. We included studies evaluating the efficacy of OT for PVOD and excluded studies evaluating pharmacologic interventions or olfactory loss from other causes. RESULTS: Of the initial 1981 abstracts reviewed, 16 full-text articles were included. Sniffin' Sticks olfactory testing results were reported in 15 (93%) studies as threshold (T), discrimination (D), and identification (I) subscores and TDI total scores. All studies reported clinically significant results after OT, defined as a score improvement of TDI >5.5. Four studies were included in the meta-analysis, in which pooled estimates revealed that patients with PVOD who received OT had a 2.77 (95% confidence interval, 1.67-4.58) higher odds of achieving a clinically important difference in TDI scores compared to controls. CONCLUSION: Meta-analysis of existing data demonstrates clinically significant improvements in PVOD associated with OT. Variability exists among OT protocols and may benefit from further optimization. Existing data supports the use of OT for the treatment of existing and newly emerging cases of PVOD.