Multivariate modeling to identify patterns in clinical data: the example of chest pain

<p>Abstract</p> <p>Background</p> <p>In chest pain, physicians are confronted with numerous interrelationships between symptoms and with evidence for or against classifying a patient into different diagnostic categories. The aim of our study was to find natural groups of patients on the basis of risk factors, history and clinical examination data which should then be validated with patients' final diagnoses.</p> <p>Methods</p> <p>We conducted a cross-sectional diagnostic study in 74 primary care practices to establish the validity of symptoms and findings for the diagnosis of coronary heart disease. A total of 1199 patients above age 35 presenting with chest pain were included in the study. General practitioners took a standardized history and performed a physical examination. They also recorded their preliminary diagnoses, investigations and management related to the patient's chest pain. We used multiple correspondence analysis (MCA) to examine associations on variable level, and multidimensional scaling (MDS), k-means and fuzzy cluster analyses to search for subgroups on patient level. We further used heatmaps to graphically illustrate the results.</p> <p>Results</p> <p>A multiple correspondence analysis supported our data collection strategy on variable level. Six factors emerged from this analysis: „chest wall syndrome“, „vital threat“, „stomach and bowel pain“, „angina pectoris“, „chest infection syndrome“, and „ self-limiting chest pain“. MDS, k-means and fuzzy cluster analysis on patient level were not able to find distinct groups. The resulting cluster solutions were not interpretable and had insufficient statistical quality criteria.</p> <p>Conclusions</p> <p>Chest pain is a heterogeneous clinical category with no coherent associations between signs and symptoms on patient level.</p

Physical activity and trajectories of frailty among older adults:evidence from the English Longitudinal Study of Ageing

BACKGROUND: Frail older adults are heavy users of health and social care. In order to reduce the costs associated with frailty in older age groups, safe and cost-effective strategies are required that will reduce the incidence and severity of frailty. OBJECTIVE: We investigated whether self-reported intensity of physical activity (sedentary, mild, moderate or vigorous) performed at least once a week can significantly reduce trajectories of frailty in older adults who are classified as non-frail at baseline (Rockwood's Frailty Index [FI] ≤ 0.25). METHODS: Multi-level growth curve modelling was used to assess trajectories of frailty in 8649 non-frail adults aged 50 and over and according to baseline self-reported intensity of physical activity. Frailty was measured in five-year age cohorts based on age at baseline (50-54; 55-59; 60-64; 65-69; 70-74; 75-79; 80+) on up to 6 occasions, providing an average of 10 years of follow-up. All models were adjusted for baseline sex, education, wealth, cohabitation, smoking, and alcohol consumption. RESULTS: Compared with the sedentary reference group, mild physical activity was insufficient to significantly slow the progression of frailty, moderate physical activity reduced the progression of frailty in some age groups (particularly ages 65 and above) and vigorous activity significantly reduced the trajectory of frailty progression in all older adults. CONCLUSION: Healthy non-frail older adults require higher intensities of physical activity for continued improvement in frailty trajectories

Prevalence of physical and verbal aggressive behaviours and associated factors among older adults in long-term care facilities

BACKGROUND: Verbal and physical aggressive behaviours are among the most disturbing and distressing behaviours displayed by older patients in long-term care facilities. Aggressive behaviour (AB) is often the reason for using physical or chemical restraints with nursing home residents and is a major concern for caregivers. AB is associated with increased health care costs due to staff turnover and absenteeism. METHODS: The goals of this secondary analysis of a cross-sectional study are to determine the prevalence of verbal and physical aggressive behaviours and to identify associated factors among older adults in long-term care facilities in the Quebec City area (n = 2 332). RESULTS: The same percentage of older adults displayed physical aggressive behaviour (21.2%) or verbal aggressive behaviour (21.5%), whereas 11.2% displayed both types of aggressive behaviour. Factors associated with aggressive behaviour (both verbal and physical) were male gender, neuroleptic drug use, mild and severe cognitive impairment, insomnia, psychological distress, and physical restraints. Factors associated with physical aggressive behaviour were older age, male gender, neuroleptic drug use, mild or severe cognitive impairment, insomnia and psychological distress. Finally, factors associated with verbal aggressive behaviour were benzodiazepine and neuroleptic drug use, functional dependency, mild or severe cognitive impairment and insomnia. CONCLUSION: Cognitive impairment severity is the most significant predisposing factor for aggressive behaviour among older adults in long-term care facilities in the Quebec City area. Physical and chemical restraints were also significantly associated with AB. Based on these results, we suggest that caregivers should provide care to older adults with AB using approaches such as the progressively lowered stress threshold model and reactance theory which stress the importance of paying attention to the severity of cognitive impairment and avoiding the use of chemical or physical restraints