Selecting symptom instruments for cardiovascular populations

Placing patient-reported outcomes at the centre of cardiovascular clinical practice: implications for quality of care and management

Patient-reported outcomes (PROs) provide important insights into patients' own perspectives about their health and medical condition, and there is evidence that their use can lead to improvements in the quality of care and to better-informed clinical decisions. Their application in cardiovascular populations has grown over the past decades. This statement describes what PROs are, and it provides an inventory of disease-specific and domain-specific PROs that have been developed for cardiovascular populations. International standards and quality indices have been published, which can guide the selection of PROs for clinical practice and in clinical trials and research; patients as well as experts in psychometrics should be involved in choosing which are most appropriate. Collaborations are needed to define criteria for using PROs to guide regulatory decisions, and the utility of PROs for comparing and monitoring the quality of care and for allocating resources should be evaluated. New sources for recording PROs include wearable digital health devices, medical registries, and electronic health record. Advice is given for the optimal use of PROs in shared clinical decision-making in cardiovascular medicine, and concerning future directions for their wider application.

Advanced statistics identification of participant and treatment predictors associated with severe adverse effects induced by fluoropyrimidine-based chemotherapy

PURPOSE

Adverse effects following fluoropyrimidine-based chemotherapy regimens are common. However, there are no current accepted diagnostic markers for prediction prior to treatment, and the underlying mechanisms remain unclear. This study aimed to determine genetic and non-genetic predictors of adverse effects.

METHODS

Genomic DNA was analyzed for 25 single nucleotide polymorphisms (SNPs). Demographics, comorbidities, cancer and fluoropyrimidine-based chemotherapy regimen types, and adverse effect data were obtained from clinical records for 155 Australian White participants. Associations were determined by bivariate analysis, logistic regression modeling and Bayesian network analysis.

RESULTS

Twelve different adverse effects were observed in the participants, the most common severe adverse effect was diarrhea (12.9%). Bivariate analysis revealed associations between all adverse effects except neutropenia, between genetic and non-genetic predictors, and between 8 genetic and 12 non-genetic predictors with more than 1 adverse effect. Logistic regression modeling of adverse effects revealed a greater/sole role for six genetic predictors in overall gastrointestinal toxicity, nausea and/or vomiting, constipation, and neutropenia, and for nine non-genetic predictors in diarrhea, mucositis, neuropathy, generalized pain, hand-foot syndrome, skin toxicity, cardiotoxicity and fatigue. The Bayesian network analysis revealed less directly associated predictors (one genetic and six non-genetic) with adverse effects and confirmed associations between six adverse effects, eight genetic predictors and nine non-genetic predictors.

CONCLUSION

This study is the first to link both genetic and non-genetic predictors with adverse effects following fluoropyrimidine-based chemotherapy. Collectively, we report a wealth of information that warrants further investigation to elucidate the clinical significance, especially associations with genetic predictors and adverse effects.

Patient-centered care in Coronary Heart Disease: what do you want to measure? A systematic review of reviews on patient-reported outcome measures

Background

The number of published articles on Patient-Reported Outcomes Measures (PROMs) in Coronary Heart Disease (CHD), a leading cause of disability-adjusted life years lost worldwide, has been growing in the last decades. The aim of this study was to identify all the disease-specific PROMs developed for or used in CHD and summarize their characteristics (regardless of the construct), to facilitate the selection of the most adequate one for each purpose.

Methods

A systematic review of reviews was conducted in MEDLINE, Scopus, and the Cochrane Database of Systematic Reviews. PROQOLID and BiblioPRO libraries were also checked. PROMs were classified by construct and information was extracted from different sources regarding their main characteristics such as aim, number of items, specific dimensions, original language, and metric properties that have been assessed.

Results

After title and abstract screening of 1224 articles, 114 publications were included for full text review. Finally, we identified 56 PROMs: 12 symptoms scales, 3 measuring functional status, 21 measuring Health-Related Quality of Life (HRQL), and 20 focused on other constructs. Three of the symptoms scales were specifically designed for a study (no metric properties evaluated), and only five have been included in a published study in the last decade. Regarding functional status, reliability and validity have been assessed for Duke Activity Index and Seattle Angina Questionnaire, which present multiple language versions. For HRQL, most of the PROMs included physical, emotional, and social domains. Responsiveness has only been evaluated for 10 out the 21 HRQL PROMs identified. Other constructs included psychological aspects, self-efficacy, attitudes, perceptions, threats and expectations about the treatment, knowledge, adjustment, or limitation for work, social support, or self-care.

Conclusions

There is a wide variety of instruments to assess the patients’ perspective in CHD, covering several constructs. This is the first systematic review of specific PROMs for CHD including all constructs. It has practical significance, as it summarizes relevant information that may help clinicians, researchers, and other healthcare stakeholders to choose the most adequate instrument for promoting shared decision making in a trend towards value-based healthcare.

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

Symptoms of cardiovascular disease drive health care use and are a major contributor to quality of life. Symptoms are of fundamental significance not only to the diagnosis of cardiovascular disease and appraisal of response to medical therapy but also directly to patients' daily lives. The primary purpose of this scientific statement is to present the state of the science and relevance of symptoms associated with cardiovascular disease. Symptoms as patient-reported outcomes are reviewed in terms of the genesis, manifestation, and similarities or differences between diagnoses. Specifically, symptoms associated with acute coronary syndrome, heart failure, valvular disorders, stroke, rhythm disorders, and peripheral vascular disease are reviewed. Secondary aims include (1) describing symptom measurement methods in research and application in clinical practice and (2) describing the importance of cardiovascular disease symptoms in terms of clinical events and other patient-reported outcomes as applicable.

Self-management and psychological resilience moderate the relationships between symptoms and health-related quality of life among patients with hypertension in China

PURPOSE

To examine whether and how self-management and psychological resilience could moderate the relationships between symptoms and health-related quality of life (HRQoL) among hypertensive patients in China.

METHODS

This was a cross-sectional study of 220 participants recruited from January to May, 2018. Demographic and clinical information were obtained from medical records and by patient interview. The Chinese version of 17-item Hypertension-specific Symptom Scale, 21-item Self-Management Scale, and 10-item Connor-Davidson Resilience Scale (CD-RISC-10) as well as Short Form 12 Health Survey (SF-12) were used to collect information in this research. The moderation effects of self-management and psychological resilience were explored using the PROCESS macro for SPSS.

RESULTS

Among all patients, 128 (58.2%) were female, 106 (48.2%) had a bachelor degree or higher, and 133 (60.5%) had moderate to severe Charlson Comorbidity Index. Both self-management and psychological resilience were negatively correlated to symptoms (r = - 0.259, p < 0.001; r = - 0.282, p < 0.001) but positively correlated to physical (r = 0.316, p < 0.001; r = 0.344, p < 0.001) and mental (r = 0.273, p < 0.001; r = 0.309, p < 0.001) HRQoL. After controlling for potential covariates, self-management could moderate the associations between symptoms and physical HRQoL (p = 0.041, ΔR² = 0.010), while psychological resilience could moderate the relationships between symptoms and mental HRQoL (p = 0.02, ΔR² = 0.010).

CONCLUSIONS

For hypertension patients, HRQoL is dependent on the severity of symptoms, engagement of self-management behaviors, and psychological resilience, which should be carefully considered when to improve patients' HRQoL by health care providers.

Symptom clusters and treatment time delay in Korean patients with ST-elevation myocardial infarction on admission

Most patients with acute myocardial infarction (AMI) experience more than one symptom at onset. Although symptoms are an important early indicator, patients and physicians may have difficulty interpreting symptoms and detecting AMI at an early stage. This study aimed to identify symptom clusters among Korean patients with ST-elevation myocardial infarction (STEMI), to examine the relationship between symptom clusters and patient-related variables, and to investigate the influence of symptom clusters on treatment time delay (decision time [DT], onset-to-balloon time [OTB]). This was a prospective multicenter study with a descriptive design that used face-to-face interviews. A total of 342 patients with STEMI were included in this study. To identify symptom clusters, two-step cluster analysis was performed using SPSS software. Multinomial logistic regression to explore factors related to each cluster and multiple logistic regression to determine the effect of symptom clusters on treatment time delay were conducted. Three symptom clusters were identified: cluster 1 (classic MI; characterized by chest pain); cluster 2 (stress symptoms; sweating and chest pain); and cluster 3 (multiple symptoms; dizziness, sweating, chest pain, weakness, and dyspnea). Compared with patients in clusters 2 and 3, those in cluster 1 were more likely to have diabetes or prior MI. Patients in clusters 2 and 3, who predominantly showed other symptoms in addition to chest pain, had a significantly shorter DT and OTB than those in cluster 1. In conclusion, to decrease treatment time delay, it seems important that patients and clinicians recognize symptom clusters, rather than relying on chest pain alone. Further research is necessary to translate our findings into clinical practice and to improve patient education and public education campaigns.