---
title: "Preadmission factors linked to acute complications, survival and long-term recovery after COVID-19"
id: "bmj-open-13-defining-the-preadmission-factors-that-modify-risk-of-acute-complications"
canonical_url: "https://medichelpline.com/clinical-feed/bmj-open-13-defining-the-preadmission-factors-that-modify-risk-of-acute-complications"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "BMJ Open"
source_url: "http://bmjopen.bmj.com/cgi/content/short/16/9/e109653?rss=1"
published_at: "2026-09-21T12:57:17.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Preadmission factors linked to acute complications, survival and long-term recovery after COVID-19
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/bmj-open-13-defining-the-preadmission-factors-that-modify-risk-of-acute-complications
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** BMJ Open
- **Source URL:** [Original Journal Publication](http://bmjopen.bmj.com/cgi/content/short/16/9/e109653?rss=1)
- **Published At:** 2026-09-21T12:57:17.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This prospective, longitudinal, multisite cohort enrolled 425 patients with COVID-19 in England from April 2020 through the first three pandemic waves, with study completion in 2022. 60% of the cohort were patients with severe COVID at recruitment. - Analyses sought pre-admission demographic factors and symptom clusters associated with disease severity at recruitment, acute complications and long-term recovery. Methods included logistic regression, time-to-event models, mixed-effect models and K-medoids clustering. - A specific **preadmission symptom cluster** was associated with higher odds of **thrombosis** (OR 2.7, 95% CI 1.6 to 6.1, p=0.021) and **renal disease** (OR 3.3, 95% CI 1.4 to 8.0, p=0.008). - Symptom duration under 1 week before admission was associated with increased odds of **pneumothorax** (OR 3.1, 95% CI 1.2 to 8.3, p=0.025) and, in survival analysis, with higher hazard of death (HR 5.6, 95% CI 1.3 to 24.4, p=0.023). - Renal complications were more frequent in the first wave versus the second (OR 3.4, 95% CI 1.5 to 7.5, p=0.003). - In a logistic regression predicting survival to discharge, factors associated with survival included **white (vs unknown) ethnicity** (OR 6.6, 95% CI 2.8 to 15.2) and **absence of comorbidities** (OR 2.7, 95% CI 1.2 to 5.9, p=0.016). A reported relationship with age (OR 4.9, 95% CI 1.2 to 20.0, p=0.027) is incompletely described in the source. - Using a time-to-event survival model, presence of **comorbidities** greatly increased hazard of death (HR 33.3, 95% CI 3.1 to 333.3, p=0.0035). - Over 80% of participants reported **long-term sequelae**, with early predominance of neuromuscular and cognitive symptoms and persistent mood disturbance and breathlessness up to 12 months. - **Gender** showed strong associations with several persistent outcomes: dyspnoea (OR 99.8, 95% CI 2.4 to 4123.1, p=0.02), persistent mood disorder (OR 8.3, 95% CI 1.7 to 39.9, p=0.008), and multiple gastrointestinal and cognitive complaints (loose bowels OR 3.3, abdominal pain OR 5.0, constipation OR 3.8, cognitive problems OR 2.3). - The authors conclude that demographic features and early symptom patterns are associated with acute complications, survival and long-term outcomes in this cohort even after accounting for disease severity at enrolment, and that mechanistic understanding is needed to guide targeted therapeutics.
## Clinical Analysis & Structured Key Points
Objectives To understand the pre-admission factors associated with COVID-19 clinical outcome with and without controlling for acute COVID-19 severity score. Design We ran a prospective, longitudinal, multicentre cohort study. Setting Patients were recruited from four hospitals and one community General Practice in England Participants 425 patients with COVID-19 from the start of the UK pandemic in April 2020 through the first three waves with study completing in 2022. Primary and secondary outcome measures Data were collected and analysed to identify demographic factors and preadmission symptoms for hospitalised patients that were associated with COVID-19 disease severity at recruitment, acute clinical course and long-term recovery. Analysis methods included logistic regression, time-to-event analysis, mixed-effect models and K-medoids clustering. Results The cohort was skewed to patients with severe COVID (60%). Preadmission symptom cluster was associated with risk of thrombosis (OR 2.7 (95% CI 1.6 to 6.1), p=0.021) and renal disease (OR 3.3 (95% CI 1.4 to 8.0), p=0.008). Duration of symptoms less than 1 week was associated with pneumothorax (OR 3.1 (95% CI 1.2 to 8.3), p=0.025). Renal complications were more likely to be seen in the first wave compared with the second wave of the pandemic (OR 3.4 (95% CI 1.5 to 7.5), p=0.003). Using a logistic regression model, survival to discharge was associated with white (vs unknown) ethnicity (OR 6.6 (95% CI 2.8 to 15.2), p 60 years, OR 4.9 (95% CI 1.2 to 20.0), p=0.027) and absence of comorbidities (OR 2.7 (95% CI 1.2 to 5.9), p=0.016). However, using a survival model, hazard of death was increased for all hospitalised who had duration of symptoms less than 1 week (HR 5.6 (95% CI 1.3 to 24.4), p=0.023) or had comorbidities (HR 33.3 (95% CI 3.1 to 333.3), p=0.0035). Over 80% of patients reported long-term sequelae with neuromuscular and cognitive effects dominating early on and mood disturbance and breathlessness persisting to 12 months. Gender had the strongest association with dyspnoea (OR 99.8 (95% CI 2.4 to 4123.1, p=0.02) and persistent mood disorder (OR 8.3 (95% CI 1.7 to 39.9), p=0.008) and associated with persistent gastrointestinal problems (loose bowels (OR 3.3 (95% CI 1.1 to 10.8), p=0.045), abdominal pain (OR 5.0 (95% CI 1.4 to 18.1), p=0.014), constipation (OR 3.8 (95% CI 1.6 to 9.2), p=0.003)) and cognitive problems (OR 2.3 (95% CI 1.1 to - 4.8), p=0.024). Conclusions These results support an association between specific demographic factors and early infection symptoms that impact on acute and long-term outcomes of COVID-19 in this cohort after accounting for COVID-19 disease severity at enrolment. Understanding the disease mechanisms that explain these relationships is needed to inform targeted therapeutics to prevent and/or manage these complications.
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