Prescribing Analgesics to Older People: A Challenge for GPs

Majnarić, Ljiljana Trtica; Wittlinger, Thomas; Stolnik, Dunja; Babič, František; Bosnić, Zvonimir; Rudan, Stjepan

doi:10.3390/ijerph17114017

Cited by 9 publications

(5 citation statements)

References 37 publications

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“…By mechanisms of sarcopenia and reduced mobility, these diseases might have contributed to higher levels of frailty in individuals in cluster DFUN ( 79 , 80 ). The close association of musculoskeletal diseases with chronic pain, poor sleep quality, and anxious-depressive disorders, may also explain higher burden of individuals in cluster DFUN with symptoms of mental disorders, compared to individuals in cluster COG-IMP ( 73 , 81 ). The marked expression of symptoms of mental disorders, found in patients in cluster DFUN, may also suggest psychological distraction as a mechanism of the possible importance for cognitive impairments, in patients in this cluster ( 82 ).…”

Section: Discussionmentioning

confidence: 99%

Patterns of the physical, cognitive, and mental health status of older individuals in a real-life primary care setting and differences in coping styles

Wittlinger

Bekić²,

Guljaš³

et al. 2022

Front. Med.

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BackgroundPhysical frailty and cognitive decline are two major consequences of aging and are often in older individuals, especially in those with multimorbidity. These two disorders are known to usually coexist with each other, increasing the risk of each disorder for poor health outcomes. Mental health disorders, anxiety and depression, are common in older people with multimorbidity, in particular those with functional or sensory deficits, and frailty.PurposeThe aim of this study was to show how physical frailty, cognitive impairments and mental disorders, cluster in the real life setting of older primary care (PC) patients, and how these clusters relate to age, comorbidities, stressful events, and coping strategies. Knowing that, could improve risk stratification of older individuals and guide the action plans.MethodsParticipants were older individuals (≥60, N = 263), attenders of PC, independent of care of others, and not suffering from dementia. For screening participants on physical frailty, cognitive impairment, and mental disorders, we used Fried‘s phenotype model, the Mini-Mental State Examination (MMSE), the Geriatric Anxiety Scale (GAS), and the Geriatric Depression Scale (GDS). For testing participants on coping styles, we used the 14-scale Brief-Coping with Problems Experienced (Brief-COPE) questionnaire. To identify clusters, we used the algorithm fuzzy k-means. To further describe the clusters, we examined differences in age, gender, number of chronic diseases and medications prescribed, some diagnoses of chronic diseases, the number of life events, body mass index, renal function, expressed as the glomerular filtration rate, and coping styles.ResultsThe most appropriate cluster solution was the one with three clusters, that were termed as: functional (FUN; N = 139), with predominant frailty or dysfunctional (DFUN; N = 81), and with predominant cognitive impairments or cognitively impaired (COG-IMP; N = 43). Participants in two pathologic clusters, DFUN and COG-IMP, were in average older and had more somatic diseases, compared to participants in cluster FUN. Significant differences between the clusters were found in diagnoses of osteoporosis, osteoarthritis, anxiety/depression, cerebrovascular disease, and periphery artery disease. Participants in cluster FUN expressed mostly positive reframing coping style. Participants in two pathological clusters were represented with negative coping strategies. Religion and self-blame were coping mechanisms specific only for cluster DFUN; self-distraction only for cluster COG-IMP; and these two latter clusters shared the mechanisms of behavioral disengagement and denial.ConclusionThe research approach presented in this study may help PC providers in risk stratification of older individuals and in getting insights into behavioral and coping strategies of patients with similar comorbidity patterns and functional disorders, which may guide them in preparing prevention and care plans. By providing some insights into the common mechanisms and pathways of clustering frailty, cognitive impairments and mental disorders, this research approach is useful for creating new hypotheses and in accelerating geriatric research.

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Section: Discussionmentioning

confidence: 99%

Patterns of the physical, cognitive, and mental health status of older individuals in a real-life primary care setting and differences in coping styles

Wittlinger

Bekić²,

Guljaš³

et al. 2022

Front. Med.

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“…When integrating several pieces of this evidence, there is indication of a close association between chronic pain and mental disorders, anxiety, and depression and that mental disorders usually coexist with musculoskeletal diseases in comorbidity patterns [ 60 , 63 ]. Older persons with chronic pain experience and anxiety and depression use opioid analgesics or psychotropic medications more often than others [ 64 ]. These medications might contribute to the higher expression of functional organ impairments and the development of the physical frailty phenotype in individuals in the PhyF cluster [ 65 ].…”

Section: Discussionmentioning

confidence: 99%

Clusters of Physical Frailty and Cognitive Impairment and Their Associated Comorbidities in Older Primary Care Patients

et al. 2021

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(1) Objectives: We aimed to identify clusters of physical frailty and cognitive impairment in a population of older primary care patients and correlate these clusters with their associated comorbidities. (2) Methods: We used a latent class analysis (LCA) as the clustering technique to separate different stages of mild cognitive impairment (MCI) and physical frailty into clusters; the differences were assessed by using a multinomial logistic regression model. (3) Results: Four clusters (latent classes) were identified: (1) highly functional (the mean and SD of the “frailty” test 0.58 ± 0.72 and the Mini-Mental State Examination (MMSE) test 27.42 ± 1.5), (2) cognitive impairment (0.97 ± 0.78 and 21.94 ± 1.95), (3) cognitive frailty (3.48 ± 1.12 and 19.14 ± 2.30), and (4) physical frailty (3.61 ± 0.77 and 24.89 ± 1.81). (4) Discussion: The comorbidity patterns distinguishing the clusters depend on the degree of development of cardiometabolic disorders in combination with advancing age. The physical frailty phenotype is likely to exist separately from the cognitive frailty phenotype and includes common musculoskeletal diseases.

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“…It has been debated whether medical professionals are lacking in courage when it comes to sufficient pharmacological pain treatment in older adults [ 31 , 32 ]. The results herein indicate that analgesics are in substantial use.…”

Section: Discussionmentioning

confidence: 99%

Analgesic purchases among older adults – a population-based study

et al. 2021

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Background Pain is a frequent and inevitable factor affecting the quality of life among older people. Several studies have highlighted the ineffectiveness of treating chronic pain among the aged population, and little is known about the prevalence of analgesics administration among community-dwelling older adults. The objective was to examine older adults’ prescription analgesic purchases in relation to SF-36 pain in a population-based setting. Methods One thousand four hundred twenty community-dwelling citizens aged 62–86 years self-reported SF-36 bodily pain (pain intensity and pain-related interference) scores for the previous 4 weeks. The Social Insurance Institution of Finland register data on analgesic purchases for 6 months prior to and 6 months after the questionnaire data collection were considered. Special interest was focused on factors related to opioid purchases. Results Of all participants, 84% had purchased prescription analgesics during 1 year. NSAIDs were most frequently purchased (77%), while 41% had purchased paracetamol, 32% opioids, 17% gabapentinoids, and 7% tricyclic antidepressants. Age made no marked difference in purchasing prevalence. The number of morbidities was independently associated with analgesic purchases in all subjects and metabolic syndrome also with opioid purchases in subjects who had not reported any pain. Discussion Substantial NSAID and opioid purchases emerged. The importance of proper pain assessment and individual deliberation in terms of analgesic contraindications and pain quality, as well as non-pharmacological pain management, need to be highlighted in order to optimize older adults’ pain management.

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Prescribing Analgesics to Older People: A Challenge for GPs

Cited by 9 publications

References 37 publications

Patterns of the physical, cognitive, and mental health status of older individuals in a real-life primary care setting and differences in coping styles

Patterns of the physical, cognitive, and mental health status of older individuals in a real-life primary care setting and differences in coping styles

Clusters of Physical Frailty and Cognitive Impairment and Their Associated Comorbidities in Older Primary Care Patients

Analgesic purchases among older adults – a population-based study

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