Who develops long COVID? Longitudinal pre-pandemic predictors of long COVID and symptom clusters in a representative Dutch population.

OBJECTIVES: Prior studies show that long COVID has a heterogeneous presentation. Whether specific risk factors are related to subclusters of long COVID remains unknown. This study aimed to determine pre-pandemic predictors of long COVID and symptom clustering. METHODS: A total of 3,022 participants of a panel representative of the Dutch population completed an online survey about long COVID symptoms. Data was merged into 2018/2019 panel data covering sociodemographic, medical, and psychosocial predictors. A total of 415 participants were classified as having long COVID. K-means clustering was used to identify patient clusters. Multivariate and lasso regression was used to identify relevant predictors compared to a COVID-19 positive control group. RESULTS: Predictors of long-term COVID included older age, Western ethnicity, BMI, chronic disease, COVID-19 reinfections, severity, and symptoms, lower self-esteem, and higher positive affect (AUC = 0.79, 95%CI 0.73-0.86). Four clusters were identified: a low and a high symptom severity cluster, a smell-taste and respiratory symptoms cluster, and a neuro-cognitive, psychosocial, and inflammatory symptom cluster. Predictors for the different clusters included regular health complaints, healthcare use, fear of COVID-19, anxiety, depressive symptoms, and neuroticism. CONCLUSIONS: A combination of sociodemographic, medical, and psychosocial factors predicted long COVID. Heterogenous symptom clusters suggest that there are different phenotypes of long COVID-19 presentation.

The role of sex and gender in somatic complaints among patients with coronary heart disease: A longitudinal study on acute and long-term changes.

BACKGROUND: Somatic complaints are persistently reported in patients with coronary heart disease (CHD). Sex and gender influence health and well-being in a variety of ways, but it is unknown how they affect somatic complaints over time after percutaneous coronary intervention (PCI). Therefore, we examined the association between sex and gender on somatic health complaints during the first month (acute) and the first two years (recovery) after PCI. METHODS: 514 patients (Mage = 64.2 ± 8.9, 84.2% male) completed the somatic scale of the Health Complaints Scale (including the subscales: cardiopulmonary complaints, fatigue, sleep problems) at baseline, one, 12-, and 24-months post-PCI. In a follow-up study, they filled in additional questionnaires to gauge gender norms, traits, and identity. Linear mixed modeling analyses were used to assess the influence of sex, gender, their interaction, and covariates on somatic complaints for the acute and recovery phases separately. RESULTS: A general decline in somatic complaints over time was observed during the acute phase, followed by a stabilization in the recovery phase. Females and individuals with more feminine traits, norms, and identities reported increased somatic complaints. Males with more pronounced feminine norms and females with more masculine norms likewise reported more somatic, cardiopulmonary, and fatigue complaints. Furthermore, age, cardiac history, and comorbid diseases partly explained the associations with somatic complaints. CONCLUSION: While somatic complaints improve post-PCI, there are still conspicuous sex and gender differences that need to be considered. Future research should further elaborate upon these discrepancies and incorporate sex and gender in prevention and develop tailored interventions to diminish somatic complaints.

Long COVID is not a uniform syndrome: Evidence from person-level symptom clusters using latent class analysis.

BACKGROUND: The current study aims to enhance insight into the heterogeneity of long COVID by identifying symptom clusters and associated socio-demographic and health determinants. METHODS: A total of 458 participants (Mage 36.0 ± 11.9; 46.5% male) with persistent symptoms after COVID-19 completed an online self-report questionnaire including a 114-item symptom list. First, a k-means clustering analysis was performed to investigate overall clustering patterns and identify symptoms that provided meaningful distinctions between clusters. Next, a step-three latent class analysis (LCA) was performed based on these distinctive symptoms to analyze person-centered clusters. Finally, multinominal logistic models were used to identify determinants associated with the symptom clusters. RESULTS: From a 5-cluster solution obtained from k-means clustering, 30 distinctive symptoms were selected. Using LCA, six symptom classes were identified: moderate (20.7%) and high (20.7%) inflammatory symptoms, moderate malaise-neurocognitive symptoms (18.3%), high malaise-neurocognitive-psychosocial symptoms (17.0%), low-overall symptoms (13.3%) and high overall symptoms (9.8%). Sex, age, employment, COVID-19 suspicion, COVID-19 severity, number of acute COVID-19 symptoms, long COVID symptom duration, long COVID diagnosis, and impact of long COVID were associated with the different symptom clusters. CONCLUSIONS: The current study's findings characterize the heterogeneity in long COVID symptoms and underscore the importance of identifying determinants of different symptom clusters.

Sex and Gender Differences in Psychosocial Risk Profiles Among Patients with Coronary Heart Disease - the THORESCI-Gender Study.

BACKGROUND: Psychosocial factors tend to cluster and exhibit differences associated with sex assigned at birth. Gender disparities, though, remain uncharted so far. The current study aimed to first explore the clustering of eight established psychosocial risk factors among patients with coronary heart disease (CHD), followed by examining how sex and gender differences characterize these psychosocial risk profiles, while adjusting for the effect of age. METHOD: In total, 532 patients with CHD (Mage = 68.2 ± 8.9; 84% male) completed the comprehensive psychosocial screener and questionnaires to gauge gender identity, traits, and sociocultural norm scores. A three-step latent profile analysis (LPA) was performed to identify latent profiles and their correlates. RESULTS: LPA revealed six psychosocial risk profiles: (1) somewhat distressed overall (32%); (2) low distress (27%); (3) anger, hostility, and Type D (15%); (4) emotional distress and trauma (11%); (5) anxiety (9%); and (6) high overall distress (7%). Masculine traits and older age increased the odds to belong to the low distress profile (#2), while feminine traits and a feminine gender norm score increased the chance to belong to profiles with moderate to high distress. The effects of gender identity and feminine traits were sex dependent. CONCLUSION: The current study's findings explain heterogeneity among patients with CHD by considering the joint occurrence of psychosocial risk factors, and the role of sex, age, and gender within those profiles. Being more sensitive to the roles that sex, gender, and an integrated set of risk factors play may ultimately improve treatment and adherence.

Patient and healthcare professionals' perceived barriers and facilitators to the implementation of psychosocial screening in cardiac practice: A Delphi study.

BACKGROUND: Psychosocial risk factors contribute to the incidence and progression of coronary heart disease (CHD). Psychosocial screening may identify individuals who are at risk and aid them with getting appropriate care. To successfully implement psychosocial screening in the cardiology practice, the current study aims to identify key barriers and facilitators to its implementation and evaluate their perceived importance among health care professionals (HCPs) and patients. METHODS: We took a modified 3-round Delphi study approach to gain insight into key determinants that could either impede or ease implementation. Round 1 gathered data from HCPs (n = 9; cardiologists, medical psychologists, cardiac nurses) and CHD patients (n = 21), which we transcribed verbatim, coded, and processed into unique determinants. In rounds 2 and 3, participants were asked to select the most relevant determinants and rank them based on importance. Subsequently, determinants were classified by implementation level. RESULTS: Patients were generally more positive towards screening. HCP barriers included time-constraints, disruption of primary activities, and limited knowledge on psychosocial risk and screening, while patient barriers were commonly related to accessibility and patient characteristics (e.g., health literacy, motivation). Facilitators of both groups mainly pertained to the use of the screener and follow-up care, such as increasing the accessibility and the benefits of the screener. CONCLUSION: Barriers may be targeted by enhancing the effects of the facilitators. Increasing the accessibility to the screener and interventions, improving information provision, and appointing a contact person to oversee the screening process may ease the screening and care process for both patients and HCPs.

A Network Analysis of Cardiovascular Risk Factors in Patients With Heart Disease: The Role of Socioeconomic Status and Sex.

OBJECTIVE: Diverse risk factors influence the development and prognosis of coronary heart disease (CHD) independently and mutually. Low socioeconomic status (SES) seems to exacerbate these risk factors' influences. In addition, sex differences have been identified for individual risk factors. Network analysis could provide in-depth insight into the interrelatedness of the risk factors, their predictability, and the moderating role of sex, to ultimately contribute to more refinement in prevention and cardiac rehabilitation. METHODS: A total of 1682 participants (78% male; mean [standard deviation] age = 69.2 [10.6] years) with CHD completed questionnaires on psychosocial factors and health behaviors. Cardiometabolic data were retrieved through medical records. An SES index was created based on self-reported occupation, education, and area (i.e., postal code)-based median family income. Using R, we conducted a mixed graphical model network analysis on all risk factors combined with and without the moderating role of sex. RESULTS: SES belonged to the more influential risk factors with moderate to high levels of expected influence and degree centrality, indicating that it plays a considerable role in the risk factor network. When considering the moderating role of sex, relationships between SES and most risk factors were found to be stronger for women ( b = 0.06-0.48). CONCLUSIONS: The current study provided an insight into an interrelated network of psychosocial and medical risk factors among CHD patients. With SES belonging to the more influential risk factors and female sex influencing the strength of all the SES-risk factor relationships, cardiac rehabilitation and prevention techniques could be more refined by accounting for both influences.