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All Studies   Meta Analysis    Recent:   
0 0.5 1 1.5 2+ Mortality -79% Improvement Relative Risk HCQ for COVID-19  Texeira et al.  LATE TREATMENT Is late treatment with HCQ beneficial for COVID-19? Retrospective 161 patients in the USA Higher mortality with HCQ (not stat. sig., p=0.1) Texeira et al., Open Forum Infectious .., Dec 2020 Favors HCQ Favors control

Characteristics and outcomes of COVID-19 patients admitted to a regional health system in the southeast

Texeira et al., Open Forum Infectious Diseases, doi:10.1093/ofid/ofaa439.560
Dec 2020  
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HCQ for COVID-19
1st treatment shown to reduce risk in March 2020
*, now known with p < 0.00000000001 from 422 studies, recognized in 42 countries.
No treatment is 100% effective. Protocols combine complementary and synergistic treatments. * >10% efficacy in meta analysis with ≥3 clinical studies.
4,000+ studies for 60+ treatments.
Retrospective 161 hospitalized patients in the USA showing non-statistically significant unadjusted increased mortality with HCQ. Confounding by indication is likely.
Time varying confounding is likely. HCQ became controversial and was suspended towards the end of the period studied, therefore HCQ use was likely more frequent toward the beginning of the study period, a time when overall treatment protocols were significantly worse.
This study is excluded in the after exclusion results of meta analysis: unadjusted results with no group details; no treatment details; substantial confounding by time likely due to declining usage over the early stages of the pandemic when overall treatment protocols improved dramatically; substantial unadjusted confounding by indication likely.
risk of death, 79.3% higher, RR 1.79, p = 0.10, treatment 17 of 65 (26.2%), control 14 of 96 (14.6%).
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Texeira et al., 31 Dec 2020, retrospective, USA, peer-reviewed, 6 authors.
This PaperHCQAll
Poster Abstracts • OFID 2020:7 (Suppl 1) • S251
MD Joanna S Cavalier, PhD Benjamin Goldstein, MD Cara L O'brien, MD, MMCi Armando Bedoya
Session: P-12. COVID-19 Complications, Co-infections, and Clinical Outcomes Background: The novel coronavirus disease (COVID-19) results in severe illness in a significant proportion of patients, necessitating a way to discern which patients will become critically ill and which will not. In one large case series, 5.0% of patients required an intensive care unit (ICU) and 1.4% died. Several models have been developed to assess decompensating patients. However, research examining their applicability to COVID-19 patients is limited. An accurate predictive model for patients at risk of decompensation is critical for health systems to optimally triage emergencies, care for patients, and allocate resources. Methods: An early warning score (EWS) algorithm created within a large academic medical center, with methodology previously described, was applied to COVID-19 patients admitted to this institution. 122 COVID-19 patients were included. A decompensation event was defined as inpatient mortality or an unanticipated transfer to an ICU from an intermediate medical ward. The EWS was calculated at 12-hour and 24-hour intervals. Results: Of 122 patients admitted with COVID-19, 28 had a decompensation event, yielding an event rate of 23.0%. 8 patients died, 13 transferred to the ICU, and 6 both transferred to the ICU and died. Decompensation within 12 and 24 hours were predicted with areas under the curve (AUC) of 0.850 and 0.817, respectively. Using a three-tiered risk model, use of the customized EWS score for patients identified as high risk of decompensation had a positive predictive value of 44.4% and 11.1% and specificity of 99.3% and 99.6% and 12-and 24-hour intervals. Amongst medium-risk patients, the score had a specificity of 85.0% and 85.4%, respectively. Conclusion: This EWS allows for prediction of decompensation, defined as transfer to an ICU or death, in COVID-19 patients with excellent specificity and a high positive predictive value. Clinically, implementation of this score can help to identify patients before they decompensate in order to triage at time of presentation and allocate step-down beds, ICU beds, and treatments such as remdesivir.
Poster Abstracts • OFID 2020:7 (Suppl 1) • S253 pts admitted to our southeast U.S. HS had significant comorbidities, most commonly obesity, HTN, and diabetes. Additionally, AA comprised a disproportionate share (72%) of our cohort compared to the general population of our state (30%), those tested in our region (32.9%), and those found to be positive for . In-hospital mortality was 19.3% and intubation, particularly if delayed, was associated with death as were several complications, most notably arrhythmia, ARDS, and renal failure with HD. Disclosures: All Authors: No reported disclosures Characteristics and Outcomes of COVID-19 Patients with Fungal Infections Erica Herc, MD 1 ; Nicholas F. Yared, MD 2 ; Adam Kudirka, MD 1 ; Geehan Suleyman, MD 1 ; 1 Henry Ford Hospital, Detroit, MI; 2 Henry Ford Health System, Detroit, Michigan Session: P-12. COVID-19 Complications, Co-infections, and Clinical Outcomes Background: There is concern that patients with coronavirus disease 2019 (COVID-19) are at risk of developing secondary bacterial and fungal infections; however, data on the clinical characteristics and outcomes of COVID-19 patients with fungal infections are limited. We evaluated the risk factors and mortality of hospitalized COVID-19 patients with fungal infections. Methods: This was a retrospective chart review of 51 patients with fungal infections at an 877-bed teaching hospital in Detroit, Michigan from March through May 2020. Demographic data, comorbidities,..
Late treatment
is less effective
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