Journal of multimorbidity and comorbidity最新文献

Background: Older adults with stroke and multimorbidity experience frequent care transitions, which are often poorly coordinated and fragmented. We conducted a pragmatic randomized controlled trial (RCT) to test the implementation and effectiveness of the Transitional Care Stroke Intervention (TCSI), a 6-month, multi-component, evidence-informed intervention to support older adults with stroke and multimorbidity using outpatient stroke rehabilitation services. The TCSI was designed to support self-management, improve health outcomes, and enhance the quality and experience of care transitions.

Objective: To explore the facilitators and challenges to implementing the TCSI, from the perspective of healthcare providers (HCPs) (n = 12) and Managers (n = 3).

Methods: Data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR). Data were collected from study documents, individual and group interviews conducted with HCPs and a Care Coordinator, and surveys from managers. Data were analyzed using thematic analysis.

Results: Intervention implementation was facilitated by: a) strong collaborative and interdependent HCP team relationships, b) dedicated resources (funding, staffing) to support intervention delivery, c) training and ongoing support, customized to individual HCP needs, d) organizational readiness, strong leadership, and effective champions, e) structures to facilitate virtual information-sharing, and f) regular monitoring of intervention implementation. Implementation challenges included: a) COVID-19 related challenges (staff turnover, community service disruptions), b) poor communication with community service providers, c) documentation burden (intervention-related), and d) virtual care delivery.

Conclusions: This research enhances understanding of the diversity of factors influencing implementation of the TCSI, and the conditions under which implementation is more likely to succeed.

Background: Multiple long-term conditions (MLTCs; commonly referred to as multimorbidity) are highly prevalent among people admitted to hospital and are therefore of critical importance to hospital-based healthcare systems. To date, most research on MLTCs has been conducted in primary care or the general population with comparatively little work undertaken in the hospital setting.

Purpose: To describe the rationale and content of ADMISSION: a four-year UK Research and Innovation and National Institute of Health and Care Research funded interdisciplinary programme that seeks, in partnership with public contributors, to transform care for people living with MLTCs admitted to hospital.

Research design: Based across five UK academic centres, ADMISSION combines expertise in clinical medicine, epidemiology, informatics, computing, biostatistics, social science, genetics and care pathway mapping to examine patterns of conditions, mechanisms, consequences and pathways of care for people with MLTCs admitted to hospital.

Data collection: The programme uses routinely collected electronic health record data from large UK teaching hospitals, population-based cohort data from UK Biobank and routinely collected blood samples from The Scottish Health Research Register and Biobank (SHARE). These approaches are complemented by focused qualitative work exploring the perspectives of healthcare professionals and the lived experience of people with MLTCs admitted to hospital.

Conclusion: ADMISSION will provide the necessary foundations to develop novel ways to prevent and treat MLTCs and their consequences in people admitted to hospital and to improve care systems and the quality of care for this underserved group.

Background: Since comorbid conditions are frequently present in chronic obstructive pulmonary disease (COPD) and affect outcome, a composite scoring system to quantify comorbidity might be helpful in assessing mortality risk.

Methods: We tested the hypothesis that the Charlson Comorbidity Index (CCI) score at the time of an outpatient medical clinic encounter for COPD predicts all-cause mortality. Cox Proportional Hazards analyses were used in 200 randomly selected patients to relate CCI scores to all-cause mortality out to 5 years.

Results: Mean age was 62 ± 10 years, 56% were female, FEV1 was 62%, CCI was 3.08 ± 2.30, and 30% had a CCI ≥ 4, indicating 3 or more comorbid conditions. All-cause mortality was 8.5% and 20% at 3 and 5 years, respectively. In univariate testing, the CCI score and hospitalizations predicted mortality, but FEV1 did not. In multivariable testing, which included covariates of age, sex, socioeconomic status, race, FEV1 percent-predicted, and all-cause hospitalizations in the preceding year, CCI expressed as a continuous variable strongly predicted mortality: hazard ratio (HR) 1.38 for each unit increase in the score (p < 0.0001). While 1 or 2 comorbid conditions were not significantly related to mortality, 3 or more comorbid conditions (compared to none) strongly predicted mortality: HR 9.80, 95% CI 3.80 to 25.00.

Conclusion: Comorbidity, assessed with the CCI, is strongly predictive of mortality in outpatients with a clinical diagnosis of COPD, and this relationship appears to be non-linear. This instrument may be useful in determining prognosis in this population.

Background: Multimorbidity is a growing global concern, affecting patient outcomes and healthcare costs. In low- and middle-income countries, data on multimorbidity in primary care beyond prevalence is limited. Our study explored the demographic and clinical characteristics of multimorbidity among older people attending primary health care in Malawi.

Methods: We conducted a cross-sectional analysis on medical records from 15,009 older patients aged ≥50 years across three hospitals in Malawi (one tertiary, two district). Data from 2019-2021 was analyzed using R statistical software to examine patterns of multimorbidity (two or more chronic conditions). Outcome estimates were adjusted for sex, age, location, and year of clinic visit.

Results: The overall prevalence of multimorbidity, defined across 17 recorded chronic conditions, was 19.6%. Among the 2,941 cases of multimorbidity, 2,708 (92.0%) involved two chronic conditions, while 233 (8.0%) involved three. While most conditions increased steadily in prevalence with age, diabetes followed a different pattern, with higher prevalence among individuals aged 50-59 years (53.9%) and 60-69 years (52.4%) compared to those 70 years and older (40.3%). After adjusting for clinic visit year, gender, and study location, individuals aged 70 years and older were significantly less likely to have multimorbidity compared to those aged 50-59 years (AOR = 0.57, 95% CI: 0.52-0.62, p < 0.001).

Conclusion: The study revealed a wide range of multimorbidity combinations among older people attending primary health care. Strategies to address multimorbidity in older people should include efforts to identify other, less common clusters of chronic conditions.

Background: Evaluating individual health outcomes does not capture co-morbidities children experience.

Purpose: We aimed to describe profiles of child neurodevelopment and anthropometry and identify their predictors.

Methods: Using data from 501 mother-child pairs (age 3-years) in the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a prospective cohort study, we developed phenotypic profiles by applying latent profile analysis to twelve neurodevelopmental and anthropometric traits. Using multinomial regression, we evaluated odds of phenotypic profiles based on maternal, sociodemographic, and child level characteristics.

Results: For neurodevelopmental outcomes, we identified three profiles characterized by Non-optimal (9%), Typical (49%), and Optimal neurodevelopment (42%). For anthropometric outcomes, we observed three profiles of Low (12%), Average (61%), and Excess Adiposity (27%). When examining joint profiles, few children had both Non-optimal neurodevelopment and Excess Adiposity (2%). Lower household income, lower birthweight, younger gestational age, decreased caregiving environment, greater maternal depressive symptoms, and male sex were associated with increased odds of being in the Non-optimal neurodevelopment profile. Higher pre-pregnancy body mass index was associated with increased odds of being in the Excess Adiposity profile.

Conclusions: Phenotypic profiles of child neurodevelopment and adiposity were associated with maternal, sociodemographic, and child level characteristics. Few children had both non-optimal neurodevelopment and excess adiposity.

Background: Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented.

Methods: The prevalence of 18 chronic conditions (6 cardiometabolic, 7 other somatic, 5 mental health) was obtained in patients with new-onset AF from 2013-2017 from a 27-county region and controls matched 1:1 on age, sex, and county of residence. For AF patients and controls separately, clustering of conditions and co-occurrence beyond chance was estimated (using the asymmetric Somers' D statistic), overall and for ages <65, 65-74, 75-84, and ≥85 years.

Results: Among 16,509 patients with AF (median age 76 years, 57% men), few (4%) did not have any of the 18 chronic conditions, whereas nearly one-quarter of controls (23%) did not have any chronic conditions. Clustering of cardiometabolic conditions was common in both AF patients and controls, but clustering of other somatic conditions was more common in AF. Although the prevalence of most condition pairs was higher in AF patients, controls had a larger number of condition pairs occurring together beyond chance. In persons aged <65 years, AF patients more frequently exhibited concordance of condition pairs that included either pairs of somatic conditions or a combination of conditions from different condition groups. In persons aged 65-74 years, AF patients more frequently had pairs of other somatic conditions.

Conclusion: Patterns of co-existing conditions differed between patients with AF and controls, particularly in younger ages. A better understanding of the clinical consequences of multimorbidity in AF patients, including those diagnosed at younger ages, is needed.

Aim: To provide detailed descriptions of the amount of daily physical activity (PA) performed by people with multimorbidity and investigate the association between the number of conditions, multimorbidity profiles, and PA.

Methods: All adults (≥18 years) from The Lolland-Falster Health Study, conducted from 2016 to 2020, who had PA measured with accelerometers and reported medical conditions were included (n=2,158). Sedentary behavior and daily PA at light, moderate, vigorous, and moderate to vigorous intensity and number of steps were measured with two accelerometers. Associations were investigated using multivariable and quantile regression analyses.

Results: Adults with multimorbidity spent nearly half their day sedentary, and the majority did not adhere to the World Health Organization's (WHO) PA recommendations (two conditions: 63%, three conditions: 74%, ≥four conditions: 81%). Number of conditions was inversely associated with both PA for all intensity levels except sedentary time and daily number of steps. Participants with multimorbidity and presence of mental disorders (somatic/mental multimorbidity) had significantly lower levels of PA at all intensity levels, except sedentary time, and number of daily steps, compared to participants with multimorbidity combinations of exclusively somatic conditions.

Conclusion: Levels of sedentary behavior and non-adherence to PA recommendations in adults with multimorbidity were high. Inverse associations between PA and the number of conditions and mental multimorbidity profiles suggest that physical inactivity increases as multimorbidity becomes more complex.

Background: Hypertension is the leading modifiable risk factor for premature death globally despite the existence of evidence-based and cost-effective treatments. Medication nonadherence is cited as the main cause of treatment failure for hypertension. In Peru, adherence to anti-hypertensive medications of individuals with both hypertension and type 2 diabetes (T2D) is not well studied. The few studies that have investigated differences in anti-hypertensive medication adherence among patients with and without T2D have demonstrated both positive and negative effects.

Methods: In a cross-sectional study in Puno, Peru, we compared anti-hypertensive medication adherence in individuals with hypertension between those with and without comorbid T2D. The primary outcome was adherence to anti-hypertensive medications as assessed by the Hill-Bone Compliance scale. The primary exposure variable was comorbidity status (i.e., having hypertension and diabetes vs. hypertension alone).

Results: Of the 204 participants with hypertension (mean age 67 ± 11 years, 60% female), 42 (21%) had comorbid diabetes. Participants with comorbid disease had higher overall anti-hypertensive adherence scores (49.5 ± 2.8 vs. 48.0 ± 4.1 points; p<0.001) and higher medication adherence scores (32.8 ± 2.2 vs. 31.3 ± 3.7 points; p<0.01) when compared to those with hypertension alone. In multivariable regression, comorbid diabetes and monthly income above 250 soles (68 USD) were associated with higher Hill-Bone Compliance scale scores by 1.5 ± 0.7 points (p=0.025) and 2.0 ± 0.7 points (p<0.01), respectively.

Conclusions: Participants with comorbid hypertension and diabetes exhibited higher adherence to anti-hypertensive medications when compared to those with hypertension alone, suggesting that individuals with comorbid disease are more likely to adhere to anti-hypertensive medications.

Background: It is unclear how rising obesity among people with HIV (PWH) impacts their risk of type 2 diabetes mellitus (diabetes). We examined associations between HIV, prevalent diabetes and adiposity among South African PWH and their peers without HIV (PWOH).

Methods: HIV status was ascertained by antibody testing. Diabetes was defined as current use of oral hypoglycemics, insulin, and/or HbA1c ≥6.5%. Adiposity was measured by body mass index (BMI), waist circumference and waist-to-height ratio. Their associations were examined using sex-stratified multivariable fractional polynomial generalized linear models, reporting adjusted prevalence and prevalence ratios (adjPR).

Results: The mean age among 1,254 PWH and 4,381 PWOH was 41 years (95%CI 28, 56). The prevalence of diabetes among males was similar between PWH [11.3% (7.1, 15.5)] and PWOH [9.8% (8.5, 11.1); p=0.740]. By contrast, diabetes prevalence was higher among female PWOH [15.7% (14.4, 17.0)] than female PWH [10.5 (8.3, 12.8)%; adjPR: 0.67 (0.51, 0.82); p<0.001]. This difference was accentuated with obesity but reversed with leanness. At BMI ≥25 kg/m², female PWH had lower diabetes prevalence [adjPR: 0.58 (0.41, 0.76); p<0.001] than female PHIV. In contrast, at BMI <18 kg/m², female PWH had higher prevalence [adjPR: 1.72 (-1.53, 4.96); p=0.756] than female PWOH.

Conclusion: We found sex-specific differences in the relationship between adiposity and diabetes prevalence by HIV serostatus in South Africa. Notably, females living with obesity and HIV had lower prevalence of diabetes than females living with obesity and without HIV, which may have particular implications for diabetes prevention programs in the region.