tetano
Editor, Senior Moderator
BMJ Open
. 2025 Jan 9;15(1):e087920.
doi: 10.1136/bmjopen-2024-087920. Identifying people with post-COVID condition using linked, population-based administrative health data from Manitoba, Canada: prevalence and predictors in a cohort of COVID-positive individuals
Alan Katz[SUP] 1 2 [/SUP], Okechukwu Ekuma[SUP] 3 [/SUP], Jennifer E Enns[SUP] 3 [/SUP], Teresa Cavett[SUP] 2 [/SUP], Alexander Singer[SUP] 2 [/SUP], Diana C Sanchez-Ramirez[SUP] 4 [/SUP], Yoav Keynan[SUP] 5 [/SUP], Lisa Lix[SUP] 3 [/SUP], Randy Walld[SUP] 3 [/SUP], Marina Yogendran[SUP] 3 [/SUP], Nathan C Nickel[SUP] 3 [/SUP], Marcelo Urquia[SUP] 3 [/SUP], Leona Star[SUP] 6 [/SUP], Kendiss Olafson[SUP] 5 [/SUP], Sarvesh Logsetty[SUP] 7 [/SUP], Rae Spiwak[SUP] 7 [/SUP], Jillian Waruk[SUP] 6 [/SUP], Surani Matharaarachichi[SUP] 8 [/SUP]
Affiliations
Objective: Many individuals exposed to SARS-CoV-2 experience long-term symptoms as part of a syndrome called post-COVID condition (PCC). Research on PCC is still emerging but is urgently needed to support diagnosis, clinical treatment guidelines and health system resource allocation. In this study, we developed a method to identify PCC cases using administrative health data and report PCC prevalence and predictive factors in Manitoba, Canada.
Design: Cohort study.
Setting: Manitoba, Canada.
Participants: All Manitobans who tested positive for SARS-CoV-2 during population-wide PCR testing from March 2020 to December 2021 (n=66 365) and were subsequently deemed to have PCC based on International Classification of Disease-9/10 diagnostic codes and prescription drug codes (n=11 316). Additional PCC cases were identified using predictive modelling to assess patterns of health service use, including physician visits, emergency department visits and hospitalisation for any reason (n=4155).
Outcomes: We measured PCC prevalence as % PCC cases among Manitobans with positive tests and identified predictive factors associated with PCC by calculating odds ratios with 95% confidence intervals, adjusted for sociodemographic and clinical characteristics (aOR).
Results: Among 66 365 Manitobans with positive tests, we identified 15 471 (23%) as having PCC. Being female (aOR 1.64, 95% CI 1.58 to 1.71), being age 60-79 (aOR 1.33, 95% CI 1.25 to 1.41) or age 80+ (aOR 1.62, 95% CI 1.46 to 1.80), being hospitalised within 14 days of COVID-19 infection (aOR 1.95, 95% CI 1.80 to 2.10) and having a Charlson Comorbidity Index of 1+ (aOR 1.95, 95% CI 1.78 to 2.14) were predictive of PCC. Receiving 1+ doses of the COVID-19 vaccine (one dose, aOR 0.80, 95% CI 0.74 to 0.86; two doses, aOR 0.29, 95% CI 0.22 to 0.31) decreased the odds of PCC.
Conclusions: This data-driven approach expands our understanding of the prevalence and epidemiology of PCC and may be applied in other jurisdictions with population-based data. The study provides additional insights into risk and protective factors for PCC to inform health system planning and service delivery.
Keywords: COVID-19; Epidemiology; Post-Acute COVID-19 Syndrome; SARS-CoV-2 Infection.
. 2025 Jan 9;15(1):e087920.
doi: 10.1136/bmjopen-2024-087920. Identifying people with post-COVID condition using linked, population-based administrative health data from Manitoba, Canada: prevalence and predictors in a cohort of COVID-positive individuals
Alan Katz[SUP] 1 2 [/SUP], Okechukwu Ekuma[SUP] 3 [/SUP], Jennifer E Enns[SUP] 3 [/SUP], Teresa Cavett[SUP] 2 [/SUP], Alexander Singer[SUP] 2 [/SUP], Diana C Sanchez-Ramirez[SUP] 4 [/SUP], Yoav Keynan[SUP] 5 [/SUP], Lisa Lix[SUP] 3 [/SUP], Randy Walld[SUP] 3 [/SUP], Marina Yogendran[SUP] 3 [/SUP], Nathan C Nickel[SUP] 3 [/SUP], Marcelo Urquia[SUP] 3 [/SUP], Leona Star[SUP] 6 [/SUP], Kendiss Olafson[SUP] 5 [/SUP], Sarvesh Logsetty[SUP] 7 [/SUP], Rae Spiwak[SUP] 7 [/SUP], Jillian Waruk[SUP] 6 [/SUP], Surani Matharaarachichi[SUP] 8 [/SUP]
Affiliations
- PMID: 39788761
- DOI: 10.1136/bmjopen-2024-087920
Objective: Many individuals exposed to SARS-CoV-2 experience long-term symptoms as part of a syndrome called post-COVID condition (PCC). Research on PCC is still emerging but is urgently needed to support diagnosis, clinical treatment guidelines and health system resource allocation. In this study, we developed a method to identify PCC cases using administrative health data and report PCC prevalence and predictive factors in Manitoba, Canada.
Design: Cohort study.
Setting: Manitoba, Canada.
Participants: All Manitobans who tested positive for SARS-CoV-2 during population-wide PCR testing from March 2020 to December 2021 (n=66 365) and were subsequently deemed to have PCC based on International Classification of Disease-9/10 diagnostic codes and prescription drug codes (n=11 316). Additional PCC cases were identified using predictive modelling to assess patterns of health service use, including physician visits, emergency department visits and hospitalisation for any reason (n=4155).
Outcomes: We measured PCC prevalence as % PCC cases among Manitobans with positive tests and identified predictive factors associated with PCC by calculating odds ratios with 95% confidence intervals, adjusted for sociodemographic and clinical characteristics (aOR).
Results: Among 66 365 Manitobans with positive tests, we identified 15 471 (23%) as having PCC. Being female (aOR 1.64, 95% CI 1.58 to 1.71), being age 60-79 (aOR 1.33, 95% CI 1.25 to 1.41) or age 80+ (aOR 1.62, 95% CI 1.46 to 1.80), being hospitalised within 14 days of COVID-19 infection (aOR 1.95, 95% CI 1.80 to 2.10) and having a Charlson Comorbidity Index of 1+ (aOR 1.95, 95% CI 1.78 to 2.14) were predictive of PCC. Receiving 1+ doses of the COVID-19 vaccine (one dose, aOR 0.80, 95% CI 0.74 to 0.86; two doses, aOR 0.29, 95% CI 0.22 to 0.31) decreased the odds of PCC.
Conclusions: This data-driven approach expands our understanding of the prevalence and epidemiology of PCC and may be applied in other jurisdictions with population-based data. The study provides additional insights into risk and protective factors for PCC to inform health system planning and service delivery.
Keywords: COVID-19; Epidemiology; Post-Acute COVID-19 Syndrome; SARS-CoV-2 Infection.