Skip to content
Research Article Open access CC BY 4.0

Characterisation of Post-COVID-19 Sequelae in a Primary Care Setting: A Cross-sectional Study

Sandy Andrea Saavedra- Contreras, Daniel Lopez- Hernandez, Nallely Blanco- Osorio, Leticia Brito- Aranda, Daniel Cannan- Perez, Karina Ayala- Lopez, Guadalupe Jacqueline Flores- Morales, Liliana Garcia- Montiel, Liliana Grisel Liceaga- Perez, Tania Castillo- Cruz, María del Rocío Thompson- Bonilla, Saul Odin Rodriguez- Ramirez, Edgar Cruz- Aviles, Rocio Liliana Jimenez- Hernandez, Emmanuel Melgarejo- Estefan, Abraham Espinoza- Perdomo, Luis Beltran- Lagunes

Current Journal of Applied Science and Technology · pp. 155–166 · Published 19 May 2025

10.9734/cjast/2025/v44i54545

Abstract

Aims: The aim of this study is to describe the population experiencing post-COVID-19 sequelae within a primary care setting. By characterising the demographic, clinical, and symptomatic features of these patients, the study seeks to enhance understanding of long COVID in the context of first-level healthcare. Study Design: A single-centre, retrospective, and cross-sectional study was conducted. Place and Duration of Study: Family Medicine Unit. The study was conducted from January 1st, 2023, to March 31st, 2025, with COVID-19 Mexican patients attending outpatient consultations in the Epidemiology Department of Family Medicine Unit No. 57, from the Mexican Institute of Social Security (IMSS), in Puebla, Mexico. Methodology: Data on clinical and sociodemographic variables were collected through medical records, such as age, sex, weight. height, Body Mass Index (BMI), comorbidities and COVID-19 vaccination status. Categorical variables were performed using Yates’ corrected chi-square or likelihood ratio test. A 95% confidence interval (CI95%) was included. Quantitative variables were compared by Mann-Whitney U or Student’s t-test, as appropriate. AsStatistical significance was set at P < 0.05 (two-tailed). Results: A total of 138 patients with long COVID-19 were included in the study. The mean age was 48.19 years old (Standard Deviation [SD] = 16.542), with a median of 45.05 years (Interquartile Range [IQR] = 36.8–58.32). The median age was slightly higher in females (45.07 years, IQR = 38.05–57.11) than in males (44.09 years, IQR = 34.08–62.07), though this difference was not statistically significant (p = 0.726). The most common comorbidities observed were hypertension (n = 36; 26.1%, 95% CI: 18.1–33.3), type 2 diabetes (n = 23; 16.7%, 95% CI: 10.9–23.2), and chronic obstructive pulmonary disease (COPD) (n = 4; 2.9%, 95% CI: 0.7–6.5). The five most frequently reported post-COVID-19 sequelae were cough (n = 60; 43.5%, 95% CI: 35.5–52.2), odynophagia (n = 22; 15.9%, 95% CI: 10.1–22.4), headache (n = 18; 13.0%, 95% CI: 8.0–18.8), myalgia (n = 17; 12.3%, 95% CI: 7.2–18.1), and both rhinorrhoea and pulmonary fibrosis (n = 14 each; 10.1%, 95% CI: 5.1–15.2). The vaccination history was significantly associated with the presence of post-COVID-19 cough (Odds Ratio [OR] = 2.254, 95% CI: 1.100–4.619, p = 0.026) and showed a protective association against post-COVID-19 dyspnoea (OR = 0.154, 95% CI: 0.032–0.745, p = 0.020). Conclusion: In patients with long COVID-19 in primary care, the most common sequelae was respiratory symptoms, particularly persistent cough and odynophagia. Vaccination appeared to offer protection, notably against symptoms such as dyspnoea. These findings highlight the value of sustained vaccination efforts and the need for tailored post-COVID follow-up based on individual risk and sociodemographic factors.

Long COVID-19 non-communicable diseases post-COVID-19 sequelae

Cited by 0

No indexed citations yet.

Article metrics

Real usage data collected on this platform.

5

Page views

0

PDF downloads

0

Outbound clicks

0

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.