Evidence map›Paper›PMID 41845376›Full record

ArticleBMC medicine2026

Effectiveness of nirmatrelvir/ritonavir and molnupiravir on post-COVID diabetes risk among an older adult cohort: a target trial emulation study.

Zihao Guo, Yuchen Wei, Aimin Yang, Carlos King Ho Wong, Xi Xiong, Kailu Wang, Guozhang Lin, Huwen Wang, Chi Tim Hung, Conglu Li and 7 more

Abstract read
In one paragraph

Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Zihao Guo *The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Yuchen Wei *The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Aimin YangDepartment of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Carlos King Ho WongLaboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong Special Administrative Region, China.
Xi XiongLaboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong Special Administrative Region, China.
Kailu WangThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Guozhang LinThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Huwen WangDuke-NUS Medical School, Singapore, Singapore.
Chi Tim HungThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Conglu LiThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Carrie Ho Kwan YamThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Tsz Yu ChowThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Shi ZhaoThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Chris Ka Pun MokThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
David S C HuiDepartment of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Eng Kiong YeohThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. yeoh_ek@cuhk.edu.hk.
Ka Chun ChongThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. marc@cuhk.edu.hk.

Funding

CUHK Direct Grant 2025.059Health and Medical Research Fund COVID190105, COVID19F03, INF-CUHK-1, COVID1903003National Natural Science Foundation of China 72574190RGC Collaborative Research Fund C6036-21GFRGC theme-based research schemes T11-705/21-N
6 · The paper itself

Abstract

backgroundAccumulating evidence indicates that SARS-CoV-2 infection is associated with a broad spectrum of post-acute COVID sequelae, including diabetes. While nirmatrelvir/ritonavir and molnupiravir have demonstrated efficacy in reducing acute COVID-19 severity, their protective effects against post-COVID diabetes remain uncertain. In this study, we aimed to evaluate the effectiveness of these antiviral agents in reducing post-COVID diabetes risks, including new-onset diabetes in non-diabetic individuals and exacerbated diabetes in those with pre-existing diabetes.

methodsWe emulate target randomized controlled trials of COVID-19 antivirals in hospitalized patients who tested positive for SARS-CoV-2 between March 11, 2022, and October 10, 2023, in Hong Kong. Two analytic patient cohorts for assessing incident diabetes and exacerbation of diabetes for rehospitalization, including those with or without diabetes confirmed before the index date, were identified. Cloning, censoring, and weighting were used to emulate the target trials of nirmatrelvir/ritonavir and molnupiravir, involving treatment arm and control arm within each trial. Cause-specific Cox proportional hazard model and an extended form of Cox model for modeling recurrent hospitalizations were used to estimate the hazard ratio (HR) between arms in each trial, adjusting for baseline covariates.

resultsAmong 88,643 hospitalized patients first time infected by SARS-CoV-2 identified, 35,997 and 18,865 eligible patients were included in the two analytic cohorts for the analysis on newly onset diabetes and exacerbated diabetes for rehospitalization, respectively. The median follow-up period ranged from 344 to 365 days across treatment and control arms of target trials. Compared with the no treatment arm, non-diabetic patients who received nirmatrelvir/ritonavir showed a significantly lower risk of post-COVID incident diabetes (HR: 0.75, 95% CI: 0.61 to 0.92). A reduced risk of diabetes rehospitalizations (HR: 0.70, 95% CI: 0.60 to 0.81) was observed among the diabetic patients. No significant associations were found for the use of molnupiravir and post-COVID diabetes outcomes.

conclusionsOur study demonstrates the effectiveness of nirmatrelvir/ritonavir in reducing the risks of post-acute COVID sequelae of diabetes in the hospitalized population, regardless of their diabetic status, whereas molnupiravir showed no significant benefit. Our findings offer valuable clinical insights for managing diabetes during the post-acute phase of SARS-CoV-2 infection.

Indexed as

Antiviral AgentsCOVID-19COVID-19 Drug TreatmentDiabetes MellitusProlineRitonavirAgedAged, 80 and overCohort StudiesDrug CombinationsFemaleHong KongHumansMaleMiddle AgedSARS-CoV-2Antiviral AgentsDrug CombinationsProlineRitonavirDiabetesHong KongMolnupiravirNirmatrelvir/ritonavirPost-acute COVID sequelaeSARS-CoV-2Target trial emulation

Identifiers

PMID41845376
PMCPMC13069708

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.