Integrating patient-reported physical, mental, and social impacts to classify long COVID experiences

Cluster analysis identifies long COVID subtypes in Belgian patients

Severe acute respiratory syndrome coronavirus infection presents complications known as long COVID, a multisystemic organ disease which allows multidimensional analysis. This study aims to uncover clusters of long COVID cases and establish their correlation with the clinical classification developed at the Clinical Research Unit of Brugmann University Hospital, Brussels. Such an endeavour is instrumental in customizing patient management strategies tailored to the unique needs of each distinct group. A two-stage multidimensional exploratory analysis was performed on a retrospective cohort of 205 long COVID patients, involving a factorial analysis of mixed data, and then hierarchical clustering post component analysis. The study's sample comprised 76% women, with an average age of 44.5 years. Three clinical forms were identified: long, persistent, and post-viral syndrome. Multidimensional analysis using demographic, clinical, and biological variables identified three clusters of patients. Biological data did not provide sufficient differentiation between clusters. This emphasizes the importance of identifying or classifying long COVID patients according to their predominant clinical syndrome. Long COVID phenotypes, as well as clinical forms, appear to be associated with distinct pathophysiological mechanisms or genetic predispositions. This underscores the need for further research.

Capturing the emotional and social experiences of COVID-19 through journal entries: A qualitative study of COVID-19 experiences over six weeks following infection

COVID-19's wide-ranging effects on patients' physical health are well-documented, but comparatively less research has explored the impact on patients' emotional and social experiences. We examined how patients across a multi-state health system experience the emotional and social aspects of COVID-19 during the first six weeks of recovery from infection. We leveraged the larger My COVID Diary project to capture open-ended journal data from an app-based platform available to patients who test positive for COVID-19 within the health system. Our sample was limited to participants with multiple journal entries during the first six weeks after infection, with one entry in the top 5% of all participants for word count to ensure sufficient journal content was available for analysis. We randomly selected 100 eligible participants and coded and analyzed all of their journal entries in weeks 1-6 after infection, utilizing a thematic analysis approach. Despite journal entry prompts' orientation towards physical symptoms, the majority of participants discussed emotional experiences (such as anxiety, depression, and gratitude) and social factors (such as work and family) when describing their COVID-19-related experiences. Physical, emotional, and social experiences related to COVID-19 infection and recovery were often interconnected and overlapping. These findings demonstrate that a holistic understanding of the patient experience that extends beyond physical symptoms is necessary to fully support patient care and recovery.

Mapping of the PROMIS global health measure to the PROPr in the United States

BACKGROUND

The Patient-Reported Outcomes Measurement and Information System (PROMIS®) global health items (global-10) yield physical and mental health scale scores and the PROMIS-Preference (PROPr) scoring system estimated from PROMIS domain scores (e.g., PROMIS-29 + 2) produces a single score anchored by 0 (dead or as bad as being dead) to 1 (full health). A link between the PROMIS global-10 and the PROPr is needed.

METHODS

The PROMIS-29 + 2 and the PROMIS global-10 were administered to 4102 adults in the Ipsos KnowledgePanel in 2022. The median age was 52 (range 18-94), 50% were female, 70% were non-Hispanic White, and 64% were married or living with a partner. The highest level of education completed for 26% of the sample was a high school degree or general education diploma and 44% worked full-time. We estimated correlations of the PROPr with the PROMIS global health items and the global physical and mental health scales. We examined the adjusted R2 and estimated correlations between predicted and observed PROPr scores.

RESULTS

Product-moment correlations between the PROMIS global health items and the PROPr ranged from 0.50 to 0.63. The PROMIS global physical health and mental health scale scores correlated 0.74 and 0.60, respectively, with the PROPr. The adjusted R2 in the regression of the PROPr on the PROMIS global health items was 64%. The equated PROPr preference scores correlated (product-moment) 0.80 (n = 4043; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation (two-way random effects model) was 0.80. The normalized mean absolute error (NMAE) was 0.45 (SD = 0.43). The adjusted R2 in the OLS regression of the PROPr on the PROMIS global health scales was 59%. The equated PROPr preference scores correlated (product-moment) was 0.77 (n = 4046; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation was 0.77. The NMAE was 0.49 (SD = 0.45).

CONCLUSIONS

Regression equations provide a reasonably accurate estimate of the PROPr preference-based score from the PROMIS global health items or scales for group-level comparisons. These estimates facilitate cost-effectiveness research and meta-analyses. The estimated PROPr scores are not accurate enough for individual-level applications. Future evaluations of the prediction equations are needed.