To quantify true postacute sequelae of SARS-CoV-2 infection (PASC) prevalence vs diagnostic code–based estimates, determine the proportion representing chronic disease burden, delineate organ system heterogeneity patterns, and assess temporal trends spanning 2020 to 2024.
Key Findings:
Meta-analyses estimate PASC prevalence at 43%, while diagnostic code analyses report lower figures, highlighting the need for accurate coding.
The U09.9 code has poor sensitivity (4.9%-19.0%) across health systems, raising concerns about underreporting.
Longitudinal studies indicate that 45% of COVID-19 survivors experience unresolved symptoms at approximately 4 months, with 30% reporting persistent symptoms at 24 months.
The P2RC algorithm achieved 80% precision in identifying PASC cases.
Interpretation:
The study highlights significant discrepancies between clinical assessments and administrative coding in estimating PASC prevalence, indicating a need for improved surveillance methods to enhance patient care.
Limitations:
The study did not quantify the prevalence of U09.9 codes at participating sites due to established low sensitivity, which may skew prevalence estimates.
Potential biases in demographic data collection and representation across diverse health systems could affect the generalizability of findings.
Conclusion:
The findings suggest an emerging chronic disease epidemic requiring sustained clinical management and health care infrastructure investment, emphasizing the need for targeted interventions.
by Jiazi Tian, Alaleh Azhir, Matthew Decaro, Ngan Chau, Jonas Hügel, Michele Morris, Jingya Cheng, Pedram Fard, Ingrid V. Bassett, Douglas S. Bell, Elmer V. Bernstam, Shyam Visweswaran, Jeffrey G. Klann, Shawn N. Murphy, Hossein Estiri
