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Real-World Effectiveness of hydroxychloroquine, azithromycin, and ivermectin among hospitalized COVID-19 patients: Results of a target trial emulation using observational data from a nationwide Healthcare System in Peru

Soto-Becerra et al., medRxiv, doi:10.1101/2020.10.06.20208066
Oct 2020  
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Mortality 17% Improvement Relative Risk Mortality (b) -39% primary Ivermectin  Soto-Becerra et al.  LATE TREATMENT Is late treatment with ivermectin beneficial for COVID-19? Retrospective 2,833 patients in Peru (April - July 2020) Significant unadjusted confounding likely, see notes c19ivm.org Soto-Becerra et al., medRxiv, October 2020 Favorsivermectin Favorscontrol 0 0.5 1 1.5 2+
Ivermectin for COVID-19
4th treatment shown to reduce risk in August 2020, now with p < 0.00000000001 from 105 studies, recognized in 23 countries.
No treatment is 100% effective. Protocols combine treatments.
5,100+ studies for 109 treatments. c19ivm.org
Retrospective database study of 5683 patients, 692 received HCQ/CQ+AZ, 200 received HCQ/CQ, 203 received ivermectin, 1600 received AZ, 358 received ivermectin+AZ, and 2630 received standard of care.
This study includes anyone with ICD-10 COVID-19 codes which includes asymptomatic PCR+ patients, therefore many patients in the control group are likely asymptomatic with regards to SARS-CoV-2, but in the hospital for another reason. For those that had symptomatic COVID-19, there is also likely significant confounding by indication.
In this study all medications show higher mortality at day 30, which is consistent with asymptomatic (for COVID-19) or mild condition patients being more common in the control group.
For ivermectin they show 30 day mortality aHR = 1.39 [0.88 - 2.22]. KM curves show that the treatment groups were in more serious condition, and also that after about day 35 survival became better with ivermectin. The last day available for ivermectin shows RR 0.83, p = 0.01. More than the total excess mortality happened on the first day. This is consistent with treated patients being in more serious condition, and with many of the control group patients being in hospital for something unrelated to COVID-19.
Authors use a machine learning based propensity scoring system that appears over-parameterized and likely to result in significant overfitting and inaccurate results. Essentially they test for all interactions between two and three covariates. The nature and large number of covariates means many random correlations may be found. COVID-19 severity is not used.
This study also does not compare treatments with a control group not receiving the treatment - authors put patients receiving treatments after 48 hours in the control group.
Authors state that outcomes within 24 hours were excluded, however KM curves show significant mortality at day 1 (only for the treatment groups).
Several protocol violations and missing data have also been reported in this study:1,2.
See also:3.
Ivermectin dosage details:4
This is the 10th of 105 COVID-19 controlled studies for ivermectin, which collectively show efficacy with p<0.0000000001 (1 in 774 quintillion).
52 studies are RCTs, which show efficacy with p=0.00000021.
This study is excluded in the after exclusion results of meta analysis: substantial unadjusted confounding by indication likely; includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons.
Study covers ivermectin and HCQ.
risk of death, 17.1% lower, HR 0.83, p = 0.01, treatment 92 of 203 (45.3%), control 1,438 of 2,630 (54.7%), NNT 11, IVM vs. control day 43 (last day available) weighted KM from figure 3, per the pre-specified rules, the last available day mortality results have priority.
risk of death, 39.0% higher, HR 1.39, p = 0.16, treatment 47 of 203 (23.2%), control 401 of 2,630 (15.2%), adjusted per study, day 30, Table 2, IVM wHR, primary outcome.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Soto-Becerra et al., 8 Oct 2020, retrospective, database analysis, Peru, preprint, median age 59.4, 4 authors, study period 1 April, 2020 - 19 July, 2020, dosage 200μg/kg single dose.
This PaperIvermectinAll
Real-world effectiveness of hydroxychloroquine, azithromycin, and ivermectin among hospitalized COVID-19 patients: results of a target trial emulation using observational data from a nationwide healthcare system in Peru
Percy Soto-Becerra, Carlos Culquichicón, Yamilee Hurtado-Roca, Roger V Araujo-Castillo
doi:10.1101/2020.10.06.20208066
Introduction: In Latin America, Peru is the most impacted country due to COVID-19 pandemic. Given the authorized nationwide use of hydroxychloroquine, azithromycin, ivermectin and dexamethasone in COVID-19 patients, we aimed to evaluate their effectiveness alone or combined to prevent 30-day mortality among COVID-19 hospitalized patients without life-threatening illness. Methods : Design. Retrospective cohort study using digital clinical records to emulate a target trial. Setting. Nationwide data of mid-and high-level complexity hospitals from the Peruvian Social Health Insurance (EsSalud) between April 1 and July 19, 2020. Participants. Patients aged 18 years with confirmed SARS-CoV-2 infection by PCR, and non-severe pneumonia at admission. Interventions. We compared five treatment groups to the standard of care treatment regimen (control group) within 48 hours of admission to hospital: hydroxychloroquine/chloroquine alone (HCQ), ivermectin alone (IVM), azithromycin alone (AZIT), HCQ + AZIT group, and IVM + AZIT group with doses recommended by the Peruvian Ministry of Health. Main outcomes measures. The primary outcome was all-cause mortality rate, the secondary outcomes were survival without ICU rate, and survival without oxygen prescription rate. Analyses were adjusted for confounding factors by inverse probability of treatment weighting. A doubly-adjustment method was done for sensitivity analysis. Results: Among 5683 patients eligible for analysis, 200 received hydroxychloroquine or chloroquine within 48 hours of hospital admission, 203 received ivermectin, 1600 received azithromycin, 692 received hydroxychloroquine or chloroquine plus azithromycin, 358 received ivermectin plus azithromycin and 2630 received standard of care. AZIT + HCQ group was associated with 84% higher all-cause mortality hazard rate compared to standard care (wHR = 1.84, 95% CI: 1.12-3.02). Consistently, AZIT + HCQ treatment was associated with survival without transfer to ICU (wHR = 1.49, 95% CI: 1.01-2.19) and survival without oxygen prescription (wHR = 1.70, 95% CI: 1.07-2.69). HCQ treatment was associated with 77% higher all-cause mortality or oxygen prescription hazard rate compared to standard treatment (wHR = 1.77, 95% CI: 1.01-3.11). Surprisingly, we observed that IVM treatment was associated with less survival rate without transfer to ICU in the weighted analysis (wHR = 1.58, 95% CI:1.11-2.25) By last, we did not find evidence of effect on reduce allcause mortality or increase survival rate without transfer to ICU or survival rate without oxygen prescription for AZIT group neither AZIT + IVM group in all analyses. .
Conflicts of interest: The authors declare no conflicts of interest regarding the subject of this scientific article. Origin of the health care center
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Given the authorized use of ' 'hydroxychloroquine (HCQ), azithromycin (AZIT), and ivermectin (IVM), we aimed to evaluate ' 'their effectiveness alone or combined to reduce mortality among COVID-19 hospitalized ' 'patients without life-threatening ' 'illness.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Retrospective ' 'cohort emulating a target trial, using nationwide data of mid- and high-level hospitals from ' 'the Peruvian Social Health Insurance 01/April/2020–19/July/2020. Patients 18 yo and above ' 'with PCR-confirmed SARS-CoV-2, and no life-threatening illness at admission were included. ' 'Five treatment groups (HCQ alone, IVM alone, AZIT alone, HCQ+AZIT, and IVM+AZIT within 48 ' 'hours of admission) were compared with standard of care alone. Primary outcome was all-cause ' 'mortality rate; secondary outcomes were all-cause death and/or ICU transfer, and all-cause ' 'death and/or oxygen prescription. Analyses were adjusted using inverse probability of ' 'treatment weighting. Propensity scores were estimated using machine learning boosting models. ' 'Weighted hazard ratios (wHR) were calculated using Cox ' 'regression.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Among 5683 ' 'patients, 200 received HCT, 203 IVM, 1600 AZIT, 692 HCQ+AZIT, 358 IVM+AZIT, and 2630 standard ' 'of care. HCQ+AZIT was associated with 84% higher all-cause death hazard compared to standard ' 'care (wHR=1.84, 95%CI 1.12-3.02). Consistently, HCQ+AZIT was also associated with higher ' 'death and/or ICU transfer (wHR=1.49, 95%CI 1.01-2.19), and death and/or oxygen prescription ' '(wHR=1.70, 95%CI 1.07-2.69). HCQ only showed higher death and/or oxygen prescription hazard. ' 'No effect was found for AZIT or ' 'IVM+AZIT.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our study ' 'reported no beneficial effects of hydroxychloroquine, ivermectin, azithromycin. The HCQ+AZIT ' 'treatment seems to increase risk for all-cause ' 'death.</jats:p></jats:sec><jats:sec><jats:title>Funding</jats:title><jats:p>Instituto de ' 'Evaluación de Tecnologías en Salud e Investigación – IETSI, EsSalud</jats:p></jats:sec>', 'DOI': '10.1101/2020.10.06.20208066', 'type': 'posted-content', 'created': {'date-parts': [[2020, 10, 8]], 'date-time': '2020-10-08T16:46:34Z', 'timestamp': 1602175594000}, 'source': 'Crossref', 'is-referenced-by-count': 5, 'title': 'Real-world effectiveness of hydroxychloroquine, azithromycin, and ivermectin among hospitalized ' 'COVID-19 patients: results of a target trial emulation using observational data from a ' 'nationwide healthcare system in Peru', 'prefix': '10.1101', 'author': [ { 'ORCID': 'http://orcid.org/0000-0001-5332-9254', 'authenticated-orcid': False, 'given': 'Percy', 'family': 'Soto-Becerra', 'sequence': 'first', 'affiliation': []}, { 'ORCID': 'http://orcid.org/0000-0001-5349-3521', 'authenticated-orcid': False, 'given': 'Carlos', 'family': 'Culquichicón', 'sequence': 'additional', 'affiliation': []}, { 'ORCID': 'http://orcid.org/0000-0003-1993-6223', 'authenticated-orcid': False, 'given': 'Yamilee', 'family': 'Hurtado-Roca', 'sequence': 'additional', 'affiliation': []}, { 'ORCID': 'http://orcid.org/0000-0002-3740-1962', 'authenticated-orcid': False, 'given': 'Roger V.', 'family': 'Araujo-Castillo', 'sequence': 'additional', 'affiliation': []}], 'member': '246', 'reference': [ { 'key': '2020102108250447000_2020.10.06.20208066v3.1', 'doi-asserted-by': 'crossref', 'unstructured': 'Baby K , Maity S , Mehta CH , Suresh A , Nayak UY , Nayak Y. 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Late treatment
is less effective
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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