supplementary files.docx (6.1 MB)

Supplementary materials.docx: Efficacy of chloroquine and hydroxychloroquine for the treatment of hospitalized COVID-19 patients: A meta-analysis

dataset

posted on 2021-12-03, 10:59 authored by Jiawen Deng, Fangwen Zhou, Kiyan Heybati, Saif Ali, Qi Kang Zuo, Wenteng Hou, Thanansayan Dhivagaran, Harikrishnaa Ba Ramaraju, Oswin Chang, Chi Yi Wong, Zachary Silver

Table S1 PRISMA 2020 checklist [1]

Table S2 MEDLINE search strategy

Table S3 EMBASE search strategy

Table S4 PubMed search strategy

Table S5 CNKI search strategy

Table S6 Wanfang search strategy

Table S7 Wanfang Med Online search strategy

Table S8 SinoMed search strategy

Table S9 CQVIP search strategy

Table S10 Characteristics of included studies and patients

Table S11 Risk of bias, randomized controlled trials (RoB2)

Table S12 Risk of bias, observational studies (ROBINS-I)

Figure S1 Forest plot for subgroup analysis by study design, time to negative conversion of SARS-CoV-2 tests

There is no significant difference between the pooled mean differences from randomized studies versus non-randomized studies (P=0.64).

Figure S2 Forest plot for subgroup analysis by imputed versus non-imputed studies, time to negative conversion of SARS-CoV-2 tests

There is no significant difference between the pooled mean differences of imputed versus non-imputed studies (P=0.05).

Figure S3 Forest plot for subgroup analysis by regimen, incidence of negative test conversion at day 7

There is no significant difference between different regimen subgroups (P=0.18).

Figure S4 Forest plot for subgroup analysis by regimen, incidence of negative test conversion at day 14

There is no significant difference between different regimen subgroups (P=0.31).

Figure S5 Forest plot for subgroup analysis by study design, incidence of negative test conversion at day 7

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.08).

Figure S6 Forest plot for subgroup analysis by study design, incidence of negative test conversion at day 14

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.79).

Figure S7 Forest plot for subgroup analysis by study design, length of stay

There is no significant difference between the pooled mean differences from randomized studies versus non-randomized studies (P=0.98).

Figure S8 Forest plot for subgroup analysis by risk of bias ratings, length of stay

There is no significant difference between the pooled mean differences from studies with low/moderate risk of bias versus studies with high risk of bias (P=0.28).

Figure S9 Forest plot for subgroup analysis by imputed versus non-imputed studies, length of stay

There is no significant difference between the pooled mean differences of imputed versus non-imputed studies (P=0.17).

Figure S10 Forest plot for subgroup analysis by study design, mortality

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.16).

Figure S11 Forest plot for subgroup analysis by risk of bias ratings, mortality

There is no significant difference between the pooled odds ratios from studies with low/moderate risk of bias versus studies with high risk of bias (P=0.61).

Figure S12 Forest plot for subgroup analysis by study design, time to fever resolution

There is no significant difference between the pooled mean differences from randomized studies versus non-randomized studies (P=0.93).

Figure S13 Forest plot for subgroup analysis by imputed versus non-imputed studies, time to fever resolution

There is no significant difference between the pooled mean differences of imputed versus non-imputed studies (P=0.38).

Figure S14 Forest plot for subgroup analysis by study design, incidence of mechanical ventilation

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.39).

Figure S15 Forest plot for subgroup analysis by risk of bias ratings, incidence of mechanical ventilation

There is no significant difference between the pooled odds ratios from studies with low/moderate risk of bias versus studies with high risk of bias (P=0.77).

Figure S16 Forest plot for subgroup analysis by study design, incidence of adverse events

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.88).

Figure S17 Forest plot for subgroup analysis by risk of bias ratings, incidence of adverse events

There is no significant difference between the pooled odds ratios from studies with low/moderate risk of bias versus studies with high risk of bias (P=0.74).

Figure S18 Forest plot for subgroup analysis by study design, incidence of QT prolongations

There is no significant difference between the pooled odds ratios from randomized studies versus non-randomized studies (P=0.89).

Figure S19 Forest plot for subgroup analysis by risk of bias ratings, incidence of QT prolongations

There is no significant difference between the pooled odds ratios from studies with low/moderate risk of bias versus studies with high risk of bias (P=0.79).

Figure S20 Bubble plot for meta-regression of cumulative chloroquine base dose, incidence of adverse events

There is significant correlation between the cumulative chloroquine base dose and the treatment effect (P=0.04).

Table S13 P-values for meta-regression analyses

Figure S21 Funnel plot, incidence of mechanical ventilation

There is evidence of small study effects based on visual inspection and Egger’s regression test (PEgger=0.04).

Figure S22 Forest plot for trim-and-fill analysis, incidence of mechanical ventilation

Figure S23 Funnel plot, time to negative conversion of SARS-CoV-2 tests