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The COVID-19 pandemic has heightened the urgency to understand and prevent pathogen transmission, specifically regarding infectious airborne particles. Extensive studies validate the understanding of larger (droplets) and smaller (aerosols) particles in disease transmission. Similarly, N95 respirators, and other forms of respiratory protection, have proven efficacy in reducing the risk of infection across various environments. Even though multiple studies confirm their protective effect when adopted in healthcare and public settings for infection prevention, studies on their adoption over the last several decades in both clinical trials and observational studies have not provided as clear an understanding. Here we show that the standard analytical equations used in the analysis of these studies do not accurately represent the random variables impacting study results. By correcting these equations, it is demonstrated that conclusions drawn from these studies are heavily biased and uncertain, providing little useful information. Despite these limitations, we show that when outcome measures are properly analyzed, existing results consistently point to the benefit of N95 respirators over medical masks, and masking over its absence. Correcting errors in widely reported meta-analyses also yields statistically significant estimates. These findings have important implications for study design and using existing evidence for infection control policy guidelines.
Subject(s)
COVID-19ABSTRACT
Introduction: The Post-Covid-19 Functional Status (PCFS) is a simple and validated tool to assess the functional status of Covid-19 recovered patients. The aim of the study is to identify the predictive factors for referring severe and critical Covid-19 patients for rehabilitation to a specialized and centralized center. Method(s): Functional status of the Covid-19 patients admitted to Hotel-Dieu de France hospital was assessed at their hospital discharge using the PCFS. Dependency was categorized as low if PCFS <= 2 (A) and high if PCFS >= 3 (B). The patients' demographic and clinical data were obtained. After identifying univariate related variables, a multivariate analysis using the binominal logistic regression was performed. Result(s): Over 540 hospitalized patients, death rate was 13.0%. Survivors were classified as 74% in A and 26% in B. Risk factors identified on admission were: age, female sex, arterial hypertension, diabetes mellitus, higher need of oxygen, high News-2, high neutrophil count, high LDH, high D-dimers and high procalcitonin. Risk factors during follow-up period were: longer hospital stay, ICU admission, high scan severity score, thromboembolic or hemorrhagic event, treatment with steroids, baricitinib and tocilizumab. Multivariate analysis showed that age (OR=1.029;p=0.04), female sex (OR=3.537;p<10-3), procalcitonin (OR=1.186;p<10-2), a lobar condensation (OR=0.063;p<10-2) and an admission to ICU (OR=3.758;p=0.015) were independent risk factors. Conclusion(s): Multiple confounding risk factors determined functional outcome of severe Covid-19 using PCFS. This can be of a great benefit to early identify the candidates for a centralized rehabilitation with customized program.
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Introduction: Post-Covid-19 functional status scale (PCFS) is a validated tool to estimate the functional status of hospitalized covid patients. The aim of the study is to evaluate the differences in clinical and functional outcomes between covid-19 hospitalized and outpatients. Method(s): We compared the ventilatory and the functional status of 474 patients admitted to hospital for Covid between March 2020 and March 2021, to that of a positive control group of 465 outpatients infected with Covid and matched them for sex and age. The ventilatory status was collected according to spontaneous ventilation or the need of oxygen requirements, ventilation assistance and tracheostomy. The functional status was assessed using the PCFS score. The data were collected at discharge/two weeks (S2) and two months (M2) after infection. Result(s): 23.6% of the outpatients (age 59 +/- 17, 66.9% male) had a PCFS >= 3 at S2 and 2.5% at M2 compared to 22.1% and 5.5% respectively for the hospitalized patients (age 64 +/- 16, 67.5% male). 11.4% of the outpatients needed oxygen at S2 and 3.1% at M2 compared to 21.3% and 6.3% for the hospitalized group. No difference was noted between both groups in the PCFS at S2 (related-samples sign test;p=0.705) and at M2 (p=0.940). However, the ventilatory status was significantly different between both groups at S2 (p=0.021) and M2 (p=0.015). Conclusion(s): Being hospitalized did not seem to be a risk factor for pure functional impairment after recovering from Covid-19. However, recovered hospitalized patients are more oxygen dependent at hospital discharge which will be maintained even 2 months later.
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Background: The Covid-19 (C-19) pandemic plugged the global economy into its worst recession since World War II. To avoid hospitals overload, physicians need simple and accurate early tools to predict clinical evolution of C-19 patients. This can help sorting patients to an intra-hospital stay or to an outpatient confinement. Method(s): A retrospective study was conducted in Hotel Dieu de France Hospital;baseline serum LDH level measured on hospital admission was obtained. The length of intra-hospital stay, number of patients transferred to the critical care unit and started on mechanical ventilation (MV) were recorded. The News-2 score on admission (N2), scan severity score (SSS), intra-hospital evolution of patients according to the Clinical Progression Scale published by the World Health Organization (WHO- CPS) and Post C-19 functional status scale (PCFS) at discharge (T0) and two months later (T2) were noted. Correlation between admission serum LDH and these parameters used the Spearman (r) and Mann-Whitney-Wilcoxon tests. Result(s): 524 C-19 patients with baseline LDH were included in the study with 359 males(68.5%) and a mean age of 63+/-16 years. Median LDH values were 328(248-430)U/L. Higher LDH values were correlated with: longer length of stay(r=0.22), ICU admission and MV with a p-value< 10 . LDH values were also correlated with: N2(r=0.45), SSS on admission(r=0.52) and follow-up(r=0.26), WHO-CPS(r=0.41), PCFS T0(r=0.2) and T2(r=0.12) all with a p-value< 10 . No correlation was found between baseline LDH and risk of death(p=0.06). Conclusion(s): LDH on admission can predict clinical degradation of C-19 patients in hospitals and after discharge. This can help to anticipate the treatment plan.
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Declaration de liens d'interets: Les auteurs declarent ne pas avoir de liens d'interets. Copyright © 2022
ABSTRACT
Declaration de liens d'interets: Les auteurs declarent ne pas avoir de liens d'interets. Copyright © 2022