Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19

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Salient features:

This article focuses on:

  • Methods
  • Setting
  • Data sources
  • Variables assessed
  • Hydroxychloroquine exposure
  • End point
  • Statistical analysis
  • Results
  • Characteristics of cohort
  • Study endpoints
  • Discussion
  • Conclusion

Detailed summary:

Methods :

Setting :

  • The study was conducted at New York–Presbyterian Hospital (NYP)–Columbia University Irving Medical Center (CUIMC)
  • Samples were obtained from all admitted adults who had a positive test result for the virus SARSCoV-2 from analysis of nasopharyngeal or oropharyngeal swab specimens obtained at any point during their hospitalization from March 7 to April 8, 2020.
  • Follow-up continued through April 25, 2020.
  • Patients who were intubated, who died, or who were transferred to another facility within 24 hours after presentation to the emergency department were excluded from the analysis.
  • A guidance developed by the Department of Medicine was distributed to all the house staff and attending staff at our medical center suggested hydroxychloroquine as a therapeutic option for patients with Covid-19 who presented with moderate-to-severe respiratory illness.
  • The suggested hydroxychloroquine regimen was a loading dose of 600 mg twice on day 1, followed by 400 mg daily for 4 additional days.
  • Azithromycin at a dose of 500 mg on day 1 and then 250 mg daily for 4 more days in combination with hydroxychloroquine was an additional suggested therapeutic option.
  • The decision to prescribe either or both medications was left to the discretion of the treating team for each individual patient.
  • Patients receiving sarilumab were allowed to continue hydroxychloroquine.
  • Patients receiving remdesivir as part of a randomized trial either did not receive or had completed a course of treatment with hydroxychloroquine.

Data sources:

  • Data was obtained from the NYP–CUIMC clinical data warehouse.
  • The data obtained included patients’ demographic details, insurance status, vital signs, laboratory test results, medication administration data, historical and current medication lists, historical and current diagnoses, clinical notes, historical discharge disposition for previous inpatient hospitalizations, and ventilator use data.

Variables assessed

  • From the clinical data warehouse, data was obtained for each patient: age; sex; patient-reported race and ethnic group; current insurance carrier; the first recorded vital signs on presentation; the ratio of the partial pressure of arterial oxygen to the fraction of inspired oxygen (Pao2 :Fio2 ) at admission, the first recorded body-mass index, the first recorded inpatient laboratory tests; past and current diagnoses; patient-reported smoking status; and medication administration at baseline.

Hydroxychloroquine exposure:

  • Patients were defined as receiving hydroxychloroquine if they were receiving it at study baseline or received it during the follow-up period before intubation or death.

End point:

  • The primary end point was the time from study baseline to intubation or death.
  • For patients who died after intubation, the timing of the primary end point was defined as the time of intubation

Statistical analysis:

  • Bivariate frequencies were calculated to examine the associations among the preadmission variables.
  • Cox proportional-hazards regression models were used to estimate the association between hydroxychloroquine use and the composite end point of intubation or death.
  • An initial multivariable Cox regression model included demographic factors, clinical factors, laboratory tests, and medications.
  • In addition, to help account for the nonrandomized treatment administration of hydroxychloroquine, propensity-score methods were used to reduce the effects of confounding.
  • The individual propensities for receipt of hydroxychloroquine treatment were estimated with the use of a multivariable logistic-regression model that included the same covariates as the Cox regression model.
  • Associations between hydroxychloroquine use and respiratory failure were then estimated by multivariable Cox regression models with the use of three propensity score methods.
  • The primary analysis used inverse probability weighting. In the inverse-probability-weighted analysis, the predicted probabilities from the propensity-score model were used to calculate the stabilized inverse-probability-weighting weight.
  • Kaplan–Meier curves and Cox models that used the inverse-probability-weighting weights were reported.
  • A secondary analysis was conducted that used propensity-score matching and another that included the propensity score as an additional covariate.
  • In the propensity-score matching analysis, the nearest-neighbor method was applied to create a matched control sample.
  • Additional sensitivity analyses included the same set of analyses with the use of a different study baseline of 48 hours after arrival to the emergency department as well as analyses that defined the exposure as receipt of the first dose of hydroxychloroquine before study baseline only.
  • Multiple imputation was used to handle missing data, and model estimates and standard errors were calculated with Rubin’s rules.
  • The nonparametric bootstrap method was used to obtain 95% pointwise confidence intervals for the inverse probability-weighted Kaplan–Meier curves.
  • The statistical analyses were performed with the use of R software, version 3.6.1

Results :

Characteristics of cohort

  • Of 1446 consecutive patients with Covid-19 who were admitted to the hospital, a total of 70 patients were excluded from this study.
  • Thus, 1376 patients were included in the analysis.
  • Over a median follow-up of 22.5 days, 346 patients had a primary end-point event.
  • At the time of data cutoff on April 25, a total of 232 patients had died, 1025 had survived to hospital discharge and 119 were still hospitalized.
  • Of the 1376 patients, 811 received hydroxychloroquine and 565 did not.
  • Among the patients who received hydroxychloroquine, 45.8% received it in the 24 hours between their presentation to the emergency department and the start of study follow-up, and 85.9% received it within 48 hours after presentation to the emergency department.
  • In the unmatched sample, hydroxychloroquine exposure differed according to age group, sex, race and ethnic group, body-mass index, insurance, smoking status, and current use of other medications.
  • Hydroxychloroquinetreated patients had a lower Pao2 :Fio2 at baseline than did patients who did not receive hydroxychloroquine.
  • In addition to the 27 patients who received remdesivir according to compassionate use, 30 patients in the study cohort were enrolled in randomized, blinded, placebo controlled trials of that investigational agent or of sarilumab.
  • The C-statistic of the propensity-score model was 0.81.
  • In the matched analytic sample, 811 patients were exposed to hydroxychloroquine and 274 were not exposed.
  • The differences between hydroxychloroquine and pretreatment variables were attenuated in the propensity-score–matched samples as compared with the unmatched samples.

Study end points:

  • Among the 1376 patients included in the analysis, the primary end point of respiratory failure developed in 346 patients; a total of 180 patients were intubated, and 166 died without intubation.
  • In the crude, unadjusted analysis, patients who had received hydroxychloroquine were more likely to have had a primary endpoint event than were patients who did not.
  • In the primary multivariable analysis with inverse probability weighting according to the propensity score, there was no significant association between hydroxychloroquine use and the composite primary end point.
  • There was also no significant association between treatment with azithromycin and the composite end point.
  • Multiple additional sensitivity analyses, including analyses that used a different baseline at 48 hours after presentation and analyses with treatment defined as receipt of the first dose of hydroxychloroquine before study baseline, showed similar results.


  • In this analysis involving a large sample of consecutive patients who had been hospitalized with Covid-19, the risk of intubation or death was not significantly higher or lower among patients who received hydroxychloroquine than among those who did not.
  • Given the observational design and the relatively wide confidence interval, the study should not be taken to rule out either benefit or harm of hydroxychloroquine treatment.
  • The findings from an early study shows a benefit of hydroxychloroquine in 26 patients who had been treated in French hospitals are difficult to interpret, given the small size of that study, the lack of a randomized control group, and the omission of 6 patients from the analysis.
  • A clinical trial testing two doses of chloroquine in patients with Covid-19 planned to include 440 patients but was halted after 81 patients had been enrolled because of excessive QTc prolongation and an indication of higher mortality in the high dose group than in the low-dose group.
  • Physicians in Wuhan randomly assigned 62 patients with mild illness to either the control group or the experimental group.
  • Investigators reported a faster mean time to clinical recovery in the experimental group than in the control group.
  • Four patients had progression to severe infection.
  • A small, randomized trial involving 30 patients in Shanghai reported on outcomes in patients treated with 400 mg of hydroxychloroquine daily for 5 days, as compared with a control group in which patients received “conventional treatment only.”
  • This trial showed that by day 7, a total of 86% of the patients in the hydroxychloroquine-treated group and 93% of those in the control group had negative results on viral throat swabs.
  • All the patients in this trial also received aerosolized interferon alfa by nebulizer.
  • A randomized clinical trial is the best approach to determine whether benefit can be ascribed to any given therapeutic intervention because this trial design minimizes the two major problems inherent in observational studies: unmeasured confounding and bias.
  • In the main analysis, a multivariable regression model with inverse probability weighting according to the propensity score, there was no significant association between hydroxychloroquine use and the risk of intubation or death.
  • A series of analyses was performed using several propensity-score approaches.
  • Findings were similar in multiple sensitivity analyses.
  • In the analysis, confounders were adjusted including age, race and ethnic group, body-mass index, diabetes, underlying kidney disease, chronic lung disease, hypertension, baseline vital signs, Pao2 :Fio2 , and inflammatory markers of the severity of illness.
  • Additional limitations of our study include missing data for some variables and potential for inaccuracies in the electronic health records, such as lack of documentation of smoking and coexisting illness for some patients.
  • Contemporary methods were used to deal with missing data to minimize bias.


  • In this observational study involving patients with Covid-19 who had been admitted to the hospital, hydroxychloroquine administration was not associated with either a greatly lowered or an increased risk of the composite end point of intubation or death.
  • Randomized, controlled trials of hydroxychloroquine in patients with Covid-19 are needed

Reference Link: https://www.nejm.org/doi/full/10.1056/nejmoa2012410

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