Depressive symptoms are associated with analgesic use in people with Alzheimer's disease: Kuopio ALSOVA study.

Neuropsychiatric symptoms of Alzheimer's disease (AD) such as depression may be associated with pain, which according to the literature may be inadequately recognized and managed in this population. This study aimed to identify the factors associated with analgesic use in persons with AD; in particular, how AD severity, functional status, neuropsychiatric symptoms of AD, co-morbidities and somatic symptoms are associated with analgesic use. 236 community-dwelling persons with very mild or mild AD at baseline, and their caregivers, were interviewed over five years as part of the prospective ALSOVA study. Generalized Estimating Equations (GEEs) were used to estimate unadjusted and adjusted odds ratios (ORs) for the factors associated with analgesic use over a five year follow-up. The proportion of persons with AD using any analgesic was low (13.6%) at baseline and remained relatively constant during the follow-up (15.3% at Year 5). Over time, the most prevalent analgesic changed from non-steroidal anti-inflammatories (8.1% of persons with AD at Year 1) to acetaminophen (11.1% at Year 5). Depressive symptoms (measured by the Beck Depression Inventory, BDI) were independently associated with analgesic use, after effects of age, gender, education, AD severity, comorbidities and somatic symptoms were taken into account. For every one unit increase in BDI, the odds of analgesic use increased by 4% (OR = 1.04, 95% confidence interval CI = 1.02-1.07). Caregiver depressive symptoms were not statistically significantly associated with analgesic use of the person with AD. Depressive symptoms were significantly associated with analgesic use during the five year follow-up period. Possible explanations warranting investigation are that persons with AD may express depressive symptoms as painful somatic complaints, or untreated pain may cause depressive symptoms. Greater awareness of the association between depressive symptoms and analgesic use may lead to safer and more effective prescribing for these conditions

Eight-year trajectories of changes in health-related quality of life in knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI).

BACKGROUND:Knee osteoarthritis (OA) worsens health-related quality of life (HRQoL) but the symptom pathway varies from person to person. We aimed to identify groups of people with knee OA or at its increased risk whose HRQoL changed similarly. Our secondary aim was to evaluate if patient-related characteristics, incidence of knee replacement (KR) and prevalence of pain medication use differed between the identified HRQoL trajectory groups.METHODS:Eight-year follow-up data of 3053 persons with mild knee OA or at increased risk were obtained from the public Osteoarthritis Initiative (OAI) database. Group-based trajectory modeling was used to identify patterns of experiencing a decrease of ≥10 points (Minimal Important Change, MIC) in the Quality of Life subscale of the Knee injury and Osteoarthritis Outcome Score compared to baseline. Multinomial logistic regression, Cox regression and generalized estimating equation models were used to study secondary aims.RESULTS:Four HRQoL trajectory groups were identified. Persons in the 'no change' group (62.9%) experienced no worsening in HRQoL. 'Rapidly' (9.5%) and 'slowly' worsening (17.1%) groups displayed an increasing probability of experiencing the MIC in HRQoL. The fourth group (10.4%) had 'improving' HRQoL. Female gender, higher body mass index, smoking, knee pain, and lower income at baseline were associated with belonging to the 'rapidly worsening' group. People in 'rapidly' (hazard ratio (HR) 6.2, 95% confidence interval (CI) 3.6-10.7) and 'slowly' worsening (HR 3.4, 95% CI 2.0-5.9) groups had an increased risk of requiring knee replacement. Pain medication was more rarely used in the 'no change' than in the other groups.CONCLUSIONS:HRQoL worsening was associated with several risk factors; surgical and pharmacological interventions were more common in the poorer HRQoL trajectory groups indicating that HRQoL does reflect the need for OA treatment. These findings may have implications for targeting interventions to specific knee OA patient groups.</h4

Depressive symptoms are associated with analgesic use in people with Alzheimer's disease: Kuopio ALSOVA study

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Seasonal patterns of sickness absence due to diagnosed mental disorders: a nationwide 12-year register linkage study

Abstract Aims Although seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders. Methods We used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16–67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year. Results Unipolar depressive disorders peaked in October–November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October–November. Anxiety disorders dipped in January–February and in July–August, while non-organic sleep disorders dipped in April–August. Manic episodes reached a peak from March to July and dipped in September–November and in January–February. Seasonality was not dependent on the severity of the depressive disorder. Conclusions These results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs

Seasonal patterns of sickness absence due to diagnosed mental disorders : a nationwide 12-year register linkage study

AIMS: Although seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders. METHODS: We used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16-67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year. RESULTS: Unipolar depressive disorders peaked in October-November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October-November. Anxiety disorders dipped in January-February and in July-August, while non-organic sleep disorders dipped in April-August. Manic episodes reached a peak from March to July and dipped in September-November and in January-February. Seasonality was not dependent on the severity of the depressive disorder. CONCLUSIONS: These results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs.Peer reviewe