ArticleNature communications2023
Predictors of the post-COVID condition following mild SARS-CoV-2 infection.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A systematic review and meta-analysis of the impact of vaccination on prevention of long COVID.Nature communications · 2025Pooled it
- Systematic review of post-COVID condition in Nordic population-based registry studies.Nature communications · 2025Pooled it
- Evidence on the associations and safety of COVID-19 vaccination and post COVID-19 condition: an updated living systematic review.Epidemiology and infection · 2025Pooled it
- Work ability and return-to-work of patients with post-COVID-19: a systematic review and meta-analysis.BMC public health · 2024Pooled it
- Symptom-based rehabilitation in people with post-COVID-19 condition (RELOAD study): a randomised controlled trial.BMJ open respiratory research · 2026Trial
- Pre-pandemic care-seeking patterns and subsequent diagnoses of post-COVID condition, post viral fatigue syndrome, and exhaustion disorder: a registry-based cohort study of 208,050 Swedish women.Scandinavian journal of primary health care · 2026Article
- Immunoadsorption Versus Sham Treatment for Post-COVID Syndrome: A Randomised Sham-Controlled Crossover Trial.The Lancet regional health. Europe · 2026Article
- Sex-Stratified Machine Learning for the Prediction of Post-COVID Condition: A Longitudinal Cohort Study.Journal of clinical medicine · 2026Article
- Persistent Symptoms After SARS-CoV-2 Infection in a Referred Occupational Clinical Registry: Symptom Patterns and Associated Factors.Diseases (Basel, Switzerland) · 2026Article
- Long-term trends in Post-COVID severity: a machine learning analysis from the POP/COVIDOM cohort of the German NAPKON Cohort Network.EClinicalMedicine · 2026Article
- Article
- [Chronic pain syndrome in musculoskeletal diseases-how different are fibromyalgia and long COVID?-Part 2].Zeitschrift fur Rheumatologie · 2025Review
- Post-COVID-Syndrome Patients Might Overestimate Own Cognitive Impairment.European journal of neurology · 2025Article
- Self-reported Health Service Utilization and Barriers to Care Among US Adults with a History of Post COVID-19 Condition.Journal of general internal medicine · 2025Article
- Post-COVID recovery is faster after an infection with the SARS-CoV-2 Omicron variant: a population-based cohort study.Infection · 2025Article
- Risk, determinants, and persistence of long-COVID in a population-based cohort study in Catalonia.BMC medicine · 2025Article
- Risk factors for fatigue severity in the post-COVID-19 condition: A prospective controlled cohort study of nonhospitalised adolescents and young adults.Brain, behavior, & immunity - health · 2025Article
- Post-COVID-19 Condition Prediction in Hospitalised Cancer Patients: A Machine Learning-Based Approach.Cancers · 2025Article
- Article
- The utility of personal wearable data in long COVID and personalized patient care.NPJ digital medicine · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Whereas the nature of the post-COVID condition following mild acute COVID-19 is increasingly well described in the literature, knowledge of its risk factors, and whether it can be predicted, remains limited. This study, conducted in Norway, uses individual-level register data from 214,667 SARS-CoV-2 infected individuals covering a range of demographic, socioeconomic factors, as well as cause-specific healthcare utilization in the years prior to infection to assess the risk of post-COVID complaints ≥3 months after testing positive. We find that the risk of post-COVID was higher among individuals who prior to infection had been diagnosed with psychological (OR = 2.12, 95% CI 1.84-2.44), respiratory (OR = 2.03, 95% CI 1.78-2.32), or general and unspecified health problems (OR = 1.78, 95% CI 1.52-2.09). To assess the predictability of post-COVID after mild initial disease, we use machine learning methods and find that pre-infection characteristics, combined with information on the SARS-CoV-2 virus type and vaccine status, to a considerable extent (AUC = 0.79, 95% CI 0.75-0.81) could predict the occurrence of post-COVID complaints in our sample.
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