ArticleBMJ open2022
Investigating the effect of macro-scale estimators on worldwide COVID-19 occurrence and mortality through regression analysis using online country-based data sources.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04486508 (Intermediate-dose Versus Standard Prophylactic Anticoagulation In cRitically-ill pATIents With COVID-19), which is not on this map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Intermediate-dose Versus Standard Prophylactic Anticoagulation In cRitically-ill pATIents With COVID-19: An opeN Label Randomized Controlled Trial---A Randomized Trial of Atorvastatin vs. Placebo In Critically-ill Patients With COVID-19
Who cites it
2 citing papers in PubMed.
- Socioeconomic determinants of COVID-19 vaccination and mortality: a cross-national path analysis.BMC public health · 2026Article
- An Ecological Study on the Mortality Impact of the COVID-19 Pandemic According to Country Development Status and Pandemic Years.Epidemiologia (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate macro-scale estimators of the variations in COVID-19 cases and deaths among countries.
designEpidemiological study.
settingCountry-based data from publicly available online databases of international organisations.
participantsThe study involved 170 countries/territories, each of which had complete COVID-19 and tuberculosis data, as well as specific health-related estimators (obesity, hypertension, diabetes and hypercholesterolaemia). PRIMARY AND SECONDARY OUTCOME MEASURES: The worldwide heterogeneity of the total number of COVID-19 cases and deaths per million on 31 December 2020 was analysed by 17 macro-scale estimators around the health-related, socioeconomic, climatic and political factors. In 139 of 170 nations, the best subsets regression was used to investigate all potential models of COVID-19 variations among countries. A multiple linear regression analysis was conducted to explore the predictive capacity of these variables. The same analysis was applied to the number of deaths per hundred thousand due to tuberculosis, a quite different infectious disease, to validate and control the differences with the proposed models for COVID-19.
resultsIn the model for the COVID-19 cases (R
conclusionsThis study recommends the new predictors explaining the global variability of COVID-19. Thus, it might assist policymakers in developing health policies and social strategies to deal with COVID-19. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT04486508).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.