Farah, Wigdan H

The optimal patient panel size (PPS) in primary care and the factors determining it remain unclear. We conducted a meta-narrative review of the literature to evaluate factors influencing PPS and assess its association with patient outcomes. A comprehensive search of electronic databases was performed from inception through December 2023, focusing on original studies reporting factors used to determine PPS and related outcomes (eg, clinical outcomes, process measures, and resource utilization). A total of 48 studies were included, identifying 7 key factors influencing PPS. Smaller panels were associated with improved patient satisfaction, continuity of care, and health promotion, while clinical outcomes, utilization, and costs showed minimal impact by PPS. Panel size was primarily associated with patient age, sex, comorbidities, and practice type and structure. Community-based centers typically managed smaller panels, often staffed by female clinicians and serving socioeconomically disadvantaged populations with greater health needs than hospital-based practices. Female clinicians were also independently associated with managing smaller panels, higher quality care indicators, fewer emergency department visits, and improved patient satisfaction. Determining the ideal PPS is a multifaceted process influenced by practice setting, patient demographics, and clinician characteristics. While practice-related factors showed limited association with PPS, patient-reported outcomes were more closely linked to it. Primary care practices should tailor panel sizes to their patient populations, emphasizing a patient-centered approach and ensuring adequate infrastructure support to optimize care delivery.

Abstract Cycle threshold (CT) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, CT values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between CT values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between CT values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean CT values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with CT values <25 had a high risk of more severe disease and mortality than patients with CT values >30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with CT values of 25–30 compared with >30.