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Interventions HCQ and azithromycin (HCQ-AZ) as a reference treatment were compared to other regimens containing HCQ, ivermectin and azithromycin alone, combined, or none of these three drugs. The effect of vaccination was also evaluated.
Main outcome measures 6-week all-cause mortality. Multivariable logistic regression estimated treatment effectiveness with adjustments for age, sex, comorbidities, vaccination, period of infection or virus variant, and outpatient or inpatient care.
Results Total 30,423 COVID-19 patients were analysed (86 refused the analysis of their data) including 30,202 with available treatment data, and 535 died (1.77%). All-cause mortality was very low among patients < 50 years (8/15,925 (0.05%)) and among outpatients treated with HCQ-AZ (21 deaths out of 21,135 (0.1%), never exceeding 0.2% regardless of epidemic period).
HCQ-AZ treatment was associated with a significantly lower mortality rate than no HCQ-AZ after adjustment for sex, age, period and patient care setting (adjusted OR (aOR) 95% confidence interval (CI) 0.55, 0.45-0.68). The effect was greater among outpatients (71% death protection rate) than among inpatients (45%).
In a subset of 16,063 patients with available comorbidities and vaccinations status, obesity (2.01, 1.23-3.29), chronic respiratory disease (2.93, 1.29-6.64), and immunodeficiency (4.01, 1.69-9.50), on the one hand, and vaccination (0.29, 0.12-0.67) and HCQ-AZ treatment (0.47, 0.29-0.76), on the other hand, were independent factors associated with mortality. HCQ, alone or in any association, was associated with significant protection from death among outpatients (0.41, 0.21-0.79) and inpatients (0.59, 0.47-0.73).
"HCQ-AZ treatment was associated with a significantly lower mortality rate..."
Early Treatment with Hydroxychloroquine and Azithromycin: A ‘Real-Life’ Monocentric Retrospective Cohort Study of 30,423 COVID-19 Patients
... Results Total 30,423 COVID-19 patients were analysed (86 refused the analysis of their data) including 30,202 with available treatment data, and 535 died (1.77%). All-cause mortality was very low among patients < 50 years (8/15,925 (0.05%)) and among outpatients treated with HCQ-AZ (21 deaths out of 21,135 (0.1%), never exceeding 0.2% regardless of epidemic period). HCQ-AZ treatment was associated with a significantly lower mortality rate than no HCQ-AZ after adjustment for sex, age, period and patient care setting (adjusted OR (aOR) 95% confidence interval (CI) 0.55, 0.45-0.68). The effect was greater among outpatients (71% death protection rate) than among inpatients (45%). In a subset of 16,063 patients with available comorbidities and vaccinations status, obesity (2.01, 1.23-3.29), chronic respiratory disease (2.93, 1.29-6.64), and immunodeficiency (4.01, 1.69-9.50), on the one hand, and vaccination (0.29, 0.12-0.67) and HCQ-AZ treatment (0.47, 0.29-0.76), on the other hand, were independent factors associated with mortality. HCQ, alone or in any association, was associated with significant protection from death among outpatients (0.41, 0.21-0.79) and inpatients (0.59, 0.47-0.73).
Conclusions HCQ prescribed early or late protects in part from COVID-19-related death.
My Conversation with AI Over Hydroxychloroquine
BY Harvey Risch
JUNE 16, 2023
The following conversation took place on rebbe.io because it does not require a login.
User:
What did Harvey Risch say about hydroxychloroquine in 2020?
RebbeIO:
Harvey Risch, a professor of epidemiology at Yale School of Public Health, wrote an opinion piece in Newsweek in July 2020 advocating for the use of hydroxychloroquine as a treatment for COVID-19. In the article, he argued that the drug had been unfairly maligned by the media and some public health officials, and that there was evidence to suggest that it could be effective in reducing mortality rates among COVID-19 patients. However, it is important to note that Risch’s views were not universally accepted by the medical community, and that subsequent studies have not found strong evidence to support the use of hydroxychloroquine as a treatment for COVID-19. ...
User:
This answer did not answer the question that I asked. All of the errors you made were statements contrary to facts that you verified in subsequent answers. Since you had the correct factual information, why did you cite incorrect facts?
RebbeIO:
I apologize for any confusion or frustration that my previous responses may have caused. As an AI language model, I do not intentionally provide incorrect information. However, I understand that I made errors in my previous responses, and I apologize for any confusion or inconvenience that this may have caused.
I strive to provide accurate and helpful responses based on the information available to me, and I understand the importance of providing correct information, especially when it comes to matters of public health and scientific research. I will continue to do my best to provide accurate and helpful responses based on the information available to me, and I appreciate your patience and understanding.
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