[Impact of COVID-19 on the mental health of the population: Study in primary care]. / Impacto de la COVID-19 en la salud mental de la población: estudio en atención primaria.

OBJECTIVE: To determine the prevalence of COVID-19 and the characteristics of infected patients, as well as the prevalence of mental disorders associated with the infection and the associated risk factors. Secondary: to know the prevalence of the long COVID syndrome and the characteristics of this cohort. DESIGN: Incidence study of mental disorder in patients diagnosed with COVID-19 and case-control study of long COVID syndrome in the subsample of patients diagnosed with COVID-19 without a history of mental disorder. SITE: Primary care setting in Lleida. PARTICIPANTS: The 46,258 patients diagnosed of COVID-19 without a history of mental disorder were followed for 2 years. MAIN MEASUREMENTS: The dependent variable was the mental disorder in the period 03/11/2020 to 03/11/2022; and the independent variables were clinical and social variables. Its association with mental disorder was analyzed by calculating the adjusted hazard ratio using a logistic regression model. RESULTS: The average age of 46,258 patients at the beginning of the study was 43±17.9 years. 47% were women. The mental disorder rate for all period was 3.46% (59.20% anxiety). A predictive score was elaborated. The long COVID syndrome was more common in older women, without toxic habits, with obesity and associated comorbidity. CONCLUSIONS: COVID-19 has had an impact on the mental health of patients. Knowing the risk factors for developing these mental disorders and the long COVID syndrome would allow the clinician to be able to identify patients at risk in order to establish preventive measures and avoid their appearance.

Multimorbidity patterns and 18-year transitions from normal cognition to dementia and death: A population-based study.

BACKGROUND: Several chronic diseases accelerate cognitive decline; however, it is still unknown how different patterns of multimorbidity influence individuals' trajectories across the cognitive continuum. OBJECTIVES: We aimed to investigate the impact of multimorbidity and of specific multimorbidity patterns on the transitions across cognitive stages (normal cognition, cognitive impairment, no dementia [CIND], dementia) and death. METHODS: We included 3122 dementia-free individuals from the Swedish National study on Aging and Care in Kungsholmen. Using fuzzy c-means cluster analysis, multimorbid participants were classified into mutually exclusive groups characterized by commonly coexisting chronic diseases. Participants were followed up to 18 years to detect incident CIND, dementia, or death. Transition hazard ratios (HRs), life expectancies, and time spent in different cognitive stages were estimated using multistate Markov models. RESULTS: At baseline, five multimorbidity patterns were identified: neuropsychiatric, cardiovascular, sensory impairment/cancer, respiratory/metabolic/musculoskeletal, and unspecific. Compared to the unspecific pattern, the neuropsychiatric and sensory impairment/cancer ones showed reduced hazards of reverting from CIND to normal cognition (HR 0.53, 95% CI 0.33-0.85 and HR 0.60, 95% CI 0.39-0.91). Participants in the cardiovascular pattern exhibited an increased hazard of progression from CIND to dementia (HR 1.70, 95% CI 1.15-2.52) and for all transitions to death. Subjects with the neuropsychiatric and cardiovascular patterns showed reduced life expectancy at age 75, with an anticipation of CIND (up to 1.6 and 2.2 years, respectively) and dementia onset (up to 1.8 and 3.3 years, respectively). CONCLUSIONS: Multimorbidity patterns differentially steer individual trajectories across the cognitive continuum of older adults and may be used as a risk stratification tool.

Contribution of Frailty to Multimorbidity Patterns and Trajectories: Longitudinal Dynamic Cohort Study of Aging People.

BACKGROUND: Multimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people. OBJECTIVE: This study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older. METHODS: Longitudinal data were drawn from electronic health records through the SIDIAP (Sistema d'Informació pel Desenvolupament de la Investigació a l'Atenció Primària) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period. RESULTS: The study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers &peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1% (656,778/1,456,052) remained in the same pattern. CONCLUSIONS: Our results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories.

Role of ambulatory blood pressure on prediction of cardiovascular disease. A cohort study.

Ambulatory blood pressure (BP) is associated with mortality, but it is also interesting to expand its association with cardiovascular morbidity. This study sought to evaluate association with cardiovascular morbidity and cardiovascular mortality. Patients without cardiovascular disease who had a first 24-hour ambulatory BP monitoring were followed-up until the onset of the first event (a combined variable of cardiovascular mortality, coronary heart disease, cerebrovascular disease, peripheral arteriopathy, or hospital admission for heart failure). Changes in antihypertensive treatment couldn't be collected. Cox regression analysis was adjusted for risk factors and office BP. We included 3907 patients (mean age, 58.0, SD 13.8 years), of whom 85.5% were hypertensive. The follow up period was 6.6 (95% CI 5.0-8.5) years. A total of 496 (12.7%) events were recorded. The incidence rate was 19.3 (95% CI 17.7-21.1) cases per 1000 person-years. The patients with an event compared to the rest of patients were mostly men, older, with higher office and ambulatory systolic BP, higher prevalence of diabetes, chronic kidney disease, dyslipidemia, and non-dipper or riser circadian profile. In the fully adjusted model, office BP loses its significant association with the main variable. Ambulatory BP association remained significant with cardiovascular morbidity and mortality, HR 1.494 (1.326-1.685) and 0.767 (0.654-0.899) for 24-hour systolic and diastolic BP, respectively. Nighttime systolic BP also maintained this significant association, 1.270 (1.016-1.587). We conclude that nighttime systolic BP and 24-hour BP are significantly associated with cardiovascular events and cardiovascular mortality in patients without cardiovascular disease attended under conditions of routine clinical practice.

Polypharmacy Patterns in Multimorbid Older People with Cardiovascular Disease: Longitudinal Study.

(1) Introduction: Cardiovascular disease is associated with high mortality, especially in older people. This study aimed to characterize the evolution of combined multimorbidity and polypharmacy patterns in older people with different cardiovascular disease profiles. (2) Material and methods: This longitudinal study drew data from the Information System for Research in Primary Care in people aged 65 to 99 years with profiles of cardiovascular multimorbidity. Combined patterns of multimorbidity and polypharmacy were analysed using fuzzy c-means clustering techniques and hidden Markov models. The prevalence, observed/expected ratio, and exclusivity of chronic diseases and/or groups of these with the corresponding medication were described. (3) Results: The study included 114,516 people, mostly men (59.6%) with a mean age of 78.8 years and a high prevalence of polypharmacy (83.5%). The following patterns were identified: Mental, behavioural, digestive and cerebrovascular; Neuropathy, autoimmune and musculoskeletal; Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological; Non-specific; Multisystemic; Respiratory, cardiovascular, behavioural and genitourinary; Diabetes and ischemic cardiopathy; and Cardiac. The prevalence of overrepresented health problems and drugs remained stable over the years, although by study end, cohort survivors had more polypharmacy and multimorbidity. Most people followed the same pattern over time; the most frequent transitions were from Non-specific to Mental, behavioural, digestive and cerebrovascular and from Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological to Non-specific. (4) Conclusions: Eight combined multimorbidity and polypharmacy patterns, differentiated by sex, remained stable over follow-up. Understanding the behaviour of different diseases and drugs can help design individualised interventions in populations with clinical complexity.

Specific multimorbidity patterns modify the impact of an exercise intervention in older hospitalized adults.

Background: Different multimorbidity patterns present with different prognoses, but it is unknown to what extent they may influence the effectiveness of an individualized multicomponent exercise program offered to hospitalized older adults. Methods: This study is a secondary analysis of a randomized controlled trial conducted in the Department of Geriatric Medicine of a tertiary hospital. In addition to the standard care, an exercise-training multicomponent program was delivered to the intervention group during the acute hospitalization period. Multimorbidity patterns were determined through fuzzy c-means cluster analysis, over 38 chronic diseases. Functional, cognitive and affective outcomes were considered. Results: Three hundred and six patients were included in the analyses (154 control; 152 intervention), with a mean age of 87.2 years, and 58.5% being female. Four patterns of multimorbidity were identified: heart valves and prostate diseases (26.8%); metabolic diseases and colitis (20.6%); psychiatric, cardiovascular and autoimmune diseases (16%); and an unspecific pattern (36.6%). The Short Physical Performance Battery (SPPB) test improved across all patterns, but the intervention was most effective for patients in the metabolic/colitis pattern (2.48-point difference between intervention/control groups, 95% CI 1.60-3.35). Regarding the Barthel Index and the Mini Mental State Examination (MMSE), the differences were significant for all multimorbidity patterns, except for the psychiatric/cardio/autoimmune pattern. Differences concerning quality of life were especially high for the psychiatric/cardio/autoimmune pattern (16.9-point difference between intervention/control groups, 95% CI 4.04, 29.7). Conclusions: Patients in all the analyzed multimorbidity patterns improved with this tailored program, but the improvement was highest for those in the metabolic pattern. Understanding how different chronic disease combinations are associated with specific functional and cognitive responses to a multicomponent exercise intervention may allow further tailoring such interventions to older patients' clinical profile.

12-year evolution of multimorbidity patterns among older adults based on Hidden Markov Models.

BACKGROUND: The evolution of multimorbidity patterns during aging is still an under-researched area. We lack evidence concerning the time spent by older adults within one same multimorbidity pattern, and their transitional probability across different patterns when further chronic diseases arise. The aim of this study is to fill this gap by exploring multimorbidity patterns across decades of age in older adults, and longitudinal dynamics among these patterns. METHODS: Longitudinal study based on the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) on adults ≥60 years (N=3,363). Hidden Markov Models were applied to model the temporal evolution of both multimorbidity patterns and individuals' transitions over a 12-year follow-up. FINDINGS: Within the study population (mean age 76.1 years, 66.6% female), 87.2% had ≥2 chronic conditions at baseline. Four longitudinal multimorbidity patterns were identified for each decade. Individuals in all decades showed the shortest permanence time in an Unspecific pattern lacking any overrepresented diseases (range: 4.6-10.9 years), but the pattern with the longest permanence time varied by age. Sexagenarians remained longest in the Psychiatric-endocrine and sensorial pattern (15.4 years); septuagenarians in the Neuro-vascular and skin-sensorial pattern (11.0 years); and octogenarians and beyond in the Neuro-sensorial pattern (8.9 years). Transition probabilities varied across decades, sexagenarians showing the highest levels of stability. INTERPRETATION: Our findings highlight the dynamism and heterogeneity underlying multimorbidity by quantifying the varying permanence times and transition probabilities across patterns in different decades. With increasing age, older adults experience decreasing stability and progressively shorter permanence time within one same multimorbidity pattern.

Kinetics of humoral immune response over 17 months of COVID-19 pandemic in a large cohort of healthcare workers in Spain: the ProHEpiC-19 study.

BACKGROUND: Understanding the immune response to the SARS-CoV-2 virus is critical for efficient monitoring and control strategies. The ProHEpic-19 cohort provides a fine-grained description of the kinetics of antibodies after SARS-CoV-2 infection with an exceptional resolution over 17 months. METHODS: We established a cohort of 769 healthcare workers including healthy and infected with SARS-CoV-2 in northern Barcelona to determine the kinetics of the IgM against the nucleocapsid (N) and the IgG against the N and spike (S) of SARS-CoV-2 in infected healthcare workers. The study period was from 5 May 2020 to 11 November 2021.We used non-linear mixed models to investigate the kinetics of IgG and IgM measured at nine time points over 17 months from the date of diagnosis. The model included factors of time, gender, and disease severity (asymptomatic, mild-moderate, severe-critical) to assess their effects and their interactions. FINDINGS: 474 of the 769 participants (61.6%) became infected with SARS-CoV-2. Significant effects of gender and disease severity were found for the levels of all three antibodies. Median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease at day 270 after the diagnosis, while IgG(N and S) levels remained positive at least until days 450 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay with a rate depending on disease severity. IgG(S) levels remained relatively constant from day 15 over time. INTERPRETATION: IgM(N) and IgG(N, S) SARS-CoV-2 antibodies showed a heterogeneous kinetics over the 17 months. Only the IgG(S) showed a stable increase, and the levels and the kinetics of antibodies varied according to disease severity. The kinetics of IgM and IgG observed over a year also varied by clinical spectrum can be very useful for public health policies around vaccination criteria in adult population. FUNDING: Regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478).

Dynamics of multimorbidity and frailty, and their contribution to mortality, nursing home and home care need: A primary care cohort of 1 456 052 ageing people.

Background: Prevalence of both multimorbidity and frailty increases with age, but more evidence is needed to elucidate their relationship and their association with other health-related outcomes. We analysed the dynamics of both conditions as people age and calculate the associated risk of death, nursing home admission, and need for home care. Methods: Data were drawn from the primary care electronic health records of a longitudinal cohort of people aged 65 or older in Catalonia in 2010-2019. Frailty and multimorbidity were measured using validated instruments (eFRAGICAP, a cumulative deficit model; and SNAC-K, respectively), and their longitudinal evolution was described. Cox regression models accounted for the competing risk of death and adjusted by sex, socioeconomical status, and time-varying age, alcohol and smoking. Findings: We included 1 456 052 patients. Prevalence of multimorbidity was consistently high regardless of age, while frailty almost quadrupled from 65 to 99 years. Frailty worsened and also changed with age: up to 84 years, it was more related to concurrent diseases, and afterwards, to frailty-related deficits. While concurrent diseases contributed more to mortality, frailty-related deficits increased the risk of institutionalisation and the need for home care. Interpretation: The nature of people's multimorbidity and frailty vary with age, as does their impact on health status. People become frailer as they age, and their frailty is more characterised by disability and other symptoms than by diseases. Mortality is most associated with the number of comorbidities, whereas frailty-related deficits are associated with needing specialised care. Funding: Instituto de Salud Carlos III through PI19/00535, and the PFIS Grant FI20/00040 (Co-funded by European Regional Development Fund/European Social Fund).

Validation of an electronic frailty index with electronic health records: eFRAGICAP index.

OBJECTIVE: To create an electronic frailty index (eFRAGICAP) using electronic health records (EHR) in Catalunya (Spain) and assess its predictive validity with a two-year follow-up of the outcomes: homecare need, institutionalization and mortality in the elderly. Additionally, to assess its concurrent validity compared to other standardized measures: the Clinical Frailty Scale (CFS) and the Risk Instrument for Screening in the Community (RISC). METHODS: The eFRAGICAP was based on the electronic frailty index (eFI) developed in United Kingdom, and includes 36 deficits identified through clinical diagnoses, prescriptions, physical examinations, and questionnaires registered in the EHR of primary health care centres (PHC). All subjects > 65 assigned to a PHC in Barcelona on 1st January, 2016 were included. Subjects were classified according to their eFRAGICAP index as: fit, mild, moderate or severe frailty. Predictive validity was assessed comparing results with the following outcomes: institutionalization, homecare need, and mortality at 24 months. Concurrent validation of the eFRAGICAP was performed with a sample of subjects (n = 333) drawn from the global cohort and the CFS and RISC. Discrimination and calibration measures for the outcomes of institutionalization, homecare need, and mortality and frailty scales were calculated. RESULTS: 253,684 subjects had their eFRAGICAP index calculated. Mean age was 76.3 years (59.5% women). Of these, 41.1% were classified as fit, and 32.2% as presenting mild, 18.7% moderate, and 7.9% severe frailty. The mean age of the subjects included in the validation subsample (n = 333) was 79.9 years (57.7% women). Of these, 12.6% were classified as fit, and 31.5% presented mild, 39.6% moderate, and 16.2% severe frailty. Regarding the outcome analyses, the eFRAGICAP was good in the detection of subjects who were institutionalized, required homecare assistance, or died at 24 months (c-statistic of 0.841, 0.853, and 0.803, respectively). eFRAGICAP was also good in the detection of frail subjects compared to the CFS (AUC 0.821) and the RISC (AUC 0.848). CONCLUSION: The eFRAGICAP has a good discriminative capacity to identify frail subjects compared to other frailty scales and predictive outcomes.

Evolving mortality and clinical outcomes of hospitalized subjects during successive COVID-19 waves in Catalonia, Spain.

BACKGROUND: The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak. METHODS: We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a 7-joinpoint regression analysis, we split admissions into four waves. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU). FINDINGS: The analysis included 17,027 subjects admitted during the first wave (6800; 39.9%), summer wave (1807; 10.6%), second wave (3804; 22.3%), and third wave (4616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main factors contributing to differences in 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms. INTERPRETATION: Although in-hospital COVID-19 mortality remains high, it decreased substantially after the first wave and is highly dependent of patient's characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress. FUNDING: This work did not receive specific funding.

Multimorbidity patterns of chronic conditions and geriatric syndromes in older patients from the MoPIM multicentre cohort study.

OBJECTIVES: To estimate the frequency of chronic conditions and geriatric syndromes in older patients admitted to hospital because of an exacerbation of their chronic conditions, and to identify multimorbidity clusters in these patients. DESIGN: Multicentre, prospective cohort study. SETTING: Internal medicine or geriatric services of five general teaching hospitals in Spain. PARTICIPANTS: 740 patients aged 65 and older, hospitalised because of an exacerbation of their chronic conditions between September 2016 and December 2018. PRIMARY AND SECONDARY OUTCOME MEASURES: Active chronic conditions and geriatric syndromes (including risk factors) of the patient, a score about clinical management of chronic conditions during admission, and destination at discharge were collected, among other variables. Multimorbidity patterns were identified using fuzzy c-means cluster analysis, taking into account the clinical management score. Prevalence, observed/expected ratio and exclusivity of each chronic condition and geriatric syndrome were calculated for each cluster, and the final solution was approved after clinical revision and discussion among the research team. RESULTS: 740 patients were included (mean age 84.12 years, SD 7.01; 53.24% female). Almost all patients had two or more chronic conditions (98.65%; 95% CI 98.23% to 99.07%), the most frequent were hypertension (81.49%, 95% CI 78.53% to 84.12%) and heart failure (59.86%, 95% CI 56.29% to 63.34%). The most prevalent geriatric syndrome was polypharmacy (79.86%, 95% CI 76.82% to 82.60%). Four statistically and clinically significant multimorbidity clusters were identified: osteoarticular, psychogeriatric, cardiorespiratory and minor chronic disease. Patient-level variables such as sex, Barthel Index, number of chronic conditions or geriatric syndromes, chronic disease exacerbation 3 months prior to admission or destination at discharge differed between clusters. CONCLUSIONS: In older patients admitted to hospital because of the exacerbation of chronic health problems, it is possible to define multimorbidity clusters using soft clustering techniques. These clusters are clinically relevant and could be the basis to reorganise healthcare circuits or processes to tackle the increasing number of older, multimorbid patients. TRIAL REGISTRATION NUMBER: NCT02830425.

Combined Multimorbidity and Polypharmacy Patterns in the Elderly: A Cross-Sectional Study in Primary Health Care.

(1) Background: The acquisition of multiple chronic diseases, known as multimorbidity, is common in the elderly population, and it is often treated with the simultaneous consumption of several prescription drugs, known as polypharmacy. These two concepts are inherently related and cause an undue burden on the individual. The aim of this study was to identify combined multimorbidity and polypharmacy patterns for the elderly population in Catalonia. (2) Methods: A cross-sectional study using electronic health records from 2012 was conducted. A mapping process was performed linking chronic disease categories to the drug categories indicated for their treatment. A soft clustering technique was then carried out on the final mapped categories. (3) Results: 916,619 individuals were included, with 93.1% meeting the authors' criteria for multimorbidity and 49.9% for polypharmacy. A seven-cluster solution was identified: one non-specific (Cluster 1) and six specific, corresponding to diabetes (Cluster 2), neurological and musculoskeletal, female dominant (Clusters 3 and 4) and cardiovascular, cerebrovascular and renal diseases (Clusters 5 and 6), and multi-system diseases (Cluster 7). (4) Conclusions: This study utilized a mapping process combined with a soft clustering technique to determine combined patterns of multimorbidity and polypharmacy in the elderly population, identifying overrepresentation in six of the seven clusters with chronic disease and chronic disease-drug categories. These results could be applied to clinical practice guidelines in order to better attend to patient needs. This study can serve as the foundation for future longitudinal regarding relationships between multimorbidity and polypharmacy.

Multimorbidity patterns and risk of frailty in older community-dwelling adults: a population-based cohort study.

BACKGROUND: the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. METHODS: we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. RESULTS: six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59-5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13-4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25-3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59-14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45-4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05-3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. CONCLUSIONS: we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.

Medication-Related Problems in Older People with Multimorbidity in Catalonia: A Real-World Data Study with 5 Years' Follow-Up.

Aging, multimorbidity, and polypharmacy are associated with medication-related problems (MRPs). This study aimed to assess the association that multimorbidity and mortality have with MRPs in older people over time. We followed multimorbid, older (65-99 years) people in Catalonia from 2012 to 2016, using longitudinal data and Cox models to estimate adjusted hazard ratios (HR). We reviewed electronic health records to collect explanatory variables and MRPs (duplicate therapy, drug-drug interactions, potentially inappropriate medications (PIM), and contraindicated drugs in chronic kidney disease (CKD) or liver disease). There were 723,016 people (median age: 74 years; 58.9% women) who completed follow-up. We observed a significant (p < 0.001) increase in the proportion with at least one MRP (2012: 66.9% to 2016: 75.5%); contraindicated drugs in CKD (11.1 to 18.5%) and liver disease (3.9 to 5.3%); and PIMs (62.5 to 71.1%), especially drugs increasing fall risk (67.5%). People with ≥10 diseases had more MRPs (in 2016: PIMs, 89.6%; contraindicated drugs in CKD, 34.4%; and in liver disease, 9.3%). All MRPs were independently associated with mortality, from duplicate therapy (HR 1.06; 95% confidence interval (CI) 1.04-1.08) to interactions (HR 1.60; 95% CI 1.54-1.66). Ensuring safe pharmacological treatment in elderly, multimorbid patient remains a challenge for healthcare systems.

Multimorbidity Patterns and 6-Year Risk of Institutionalization in Older Persons: The Role of Social Formal and Informal Care.

OBJECTIVES: The aim was to evaluate patterns of multimorbidity that increase the risk of institutionalization in older persons, also exploring the potential buffering effect of formal and informal care. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: The population-based Swedish National study on Aging and Care in Kungsholmen, Stockholm, Sweden. MEASURES: In total, 2571 community-dwelling older adults were grouped at baseline according to their underlying multimorbidity patterns, using a fuzzy c-means cluster algorithm, and followed up for 6 years to test the association between multimorbidity patterns and institutionalization. RESULTS: Six patterns of multimorbidity were identified: psychiatric diseases; cardiovascular diseases, anemia, and dementia; metabolic and sleep disorders; sensory impairments and cancer; musculoskeletal, respiratory, and gastrointestinal diseases; and an unspecific pattern including diseases of which none were overrepresented. In total, 110 (4.3%) participants were institutionalized during the follow-up, ranging from 1.7% in the metabolic and sleep disorders pattern to 8.4% in the cardiovascular diseases, anemia, and dementia pattern. Compared with the unspecific pattern, only the cardiovascular diseases, anemia, dementia pattern was significantly associated with institutionalization [relative risk ratio (RRR) = 2.23; 95% confidence interval (CI) 1.07‒4.65)], after adjusting for demographic characteristics and disability status at baseline. In stratified analyses, those not receiving formal care in the psychiatric diseases pattern (RRR 3.34; 95% CI 1.20‒9.32) and those not receiving formal or informal care in the 'cardiovascular diseases, anemia, dementia' pattern (RRR 2.99; 95% CI 1.20‒7.46; RRR 2.79; 95% CI 1.16‒6.71, respectively) had increased risks of institutionalization. CONCLUSIONS AND IMPLICATIONS: Older persons suffering from specific multimorbidity patterns have a higher risk of institutionalization, especially if they lack formal or informal care. Interventions aimed at preventing the clustering of diseases could reduce the associated burden on residential long-term care. Formal and informal care provision may be effective strategies in reducing the risk of institutionalization.

Patterns of multimorbidity and risk of disability in community-dwelling older persons.

The aim was to analyze the association between specific patterns of multimorbidity and risk of disability in older persons. Data were gathered from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K); 2066 60 + year-old participants living in the community and free from disability at baseline were grouped according to their multimorbidity patterns and followed-up for six years. The association between multimorbidity patterns and disability in basic (ADL) and instrumental (IADL) activities of daily living was examined through multinomial models. Throughout the follow-up, 434 (21.0%) participants developed at least one ADL and 310 (15.0%) at least one IADL. Compared to the unspecific pattern, which included diseases not exceeding their expected prevalence in the total sample, belonging to the cardiovascular/anemia/dementia, the sensory impairment/cancer and the musculoskeletal/respiratory/gastrointestinal patterns was associated with a higher risk of developing both ADL and IADL, whereas subjects in the metabolic/sleep disorders pattern showed a higher risk of developing only IADL. Multimorbidity patterns are differentially associated with incident disability, which is important for the design of future prevention strategies aimed at delaying functional impairment in old age, and for a better healthcare resource planning.

Multimorbidity burden and dementia risk in older adults: The role of inflammation and genetics.

INTRODUCTION: We investigate dementia risk in older adults with different disease patterns and explore the role of inflammation and apolipoprotein E (APOE) genotype. METHODS: A total of 2,478 dementia-free participants with two or more chronic diseases (ie, multimorbidity) part of the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) were grouped according to their multimorbidity patterns and followed to detect clinical dementia. The potential modifier effect of C-reactive protein (CRP) and apolipoprotein E (APOE) genotype was tested through stratified analyses. RESULTS: People with neuropsychiatric, cardiovascular, and sensory impairment/cancer multimorbidity had increased hazards for dementia compared to the unspecific (Hazard ration (HR) 1.66, 95% confidence interval [CI] 1.13-2.42; 1.61, 95% CI 1.17-2.29; 1.32, 95% CI 1.10-1.71, respectively). Despite the lack of statistically significant interaction, high CRP increased dementia risk within these patterns, and being APOE ε4 carriers heightened dementia risk for neuropsychiatric and cardiovascular multimorbidity. DISCUSSION: Individuals with neuropsychiatric, cardiovascular, and sensory impairment/cancer patterns are at increased risk for dementia and APOE ε4, and inflammation may further increase the risk. Identifying such high-risk groups might allow tailored interventions for dementia prevention.

Medication-related problems in older people in Catalonia: A real-world data study.

PURPOSE: The aim of this study was to determine medication-related problems (MRPs) in primary care patients over 65 years of age. METHODS: Cross-sectional study based on the electronic health records of patients (65-99 years of age) visited in 284 primary health care centers during 2012 in Catalonia. VARIABLES: age, sex, sociodemographic variables, number of drugs, kidney and liver function and MRPs (duplicate therapy, drug-drug interactions, potentially inappropriate medications [PIMs] and drugs contraindicated in chronic kidney disease and in liver diseases). Unconditional logistic regression models were used to identify the factors associated with MRPs in patients with multimorbidity. RESULTS: 916 619 older people were included and 853 085 of them met the criteria for multimorbidity. Median age was 75 years and 57.7% of them were women. High percentages of MRPs were observed: PIMs (62.8%), contraindicated drugs in chronic kidney disease (12.1%), duplicate therapy (11.1%), contraindicated drugs in liver diseases (4.2%), and drug-drug interactions (1.0%). These numbers were higher in the subgroup of patients with ≥10 diseases. The most common PIMs were connected to drugs that increase the risk of fall (66.8%), antiulcer agents without criteria for gastroprotection (40.6%), and the combination of drugs with anticholinergic effects (39.7%). In the multivariate analysis, the variables associated with all MRPs among the patients with multimorbidity were the number of drugs and the number of visits. CONCLUSIONS: The coexistence of multimorbidity and polypharmacy is associated with an elevated risk of MRPs in older people. Medication safety for older patients constitutes a pressing concern for health services.