The Duke Severity of Illness Checklist (DUSOI) for measurement of severity and comorbidity

Multicentric Assessment of a Multimorbidity-Adjusted Disability Score to Stratify Depression-Related Risks Using Temporal Disease Maps: Instrument Validation Study

BACKGROUND

Comprehensive management of multimorbidity can significantly benefit from advanced health risk assessment tools that facilitate value-based interventions, allowing for the assessment and prediction of disease progression. Our study proposes a novel methodology, the Multimorbidity-Adjusted Disability Score (MADS), which integrates disease trajectory methodologies with advanced techniques for assessing interdependencies among concurrent diseases. This approach is designed to better assess the clinical burden of clusters of interrelated diseases and enhance our ability to anticipate disease progression, thereby potentially informing targeted preventive care interventions.

OBJECTIVE

This study aims to evaluate the effectiveness of the MADS in stratifying patients into clinically relevant risk groups based on their multimorbidity profiles, which accurately reflect their clinical complexity and the probabilities of developing new associated disease conditions.

METHODS

In a retrospective multicentric cohort study, we developed the MADS by analyzing disease trajectories and applying Bayesian statistics to determine disease-disease probabilities combined with well-established disability weights. We used major depressive disorder (MDD) as a primary case study for this evaluation. We stratified patients into different risk levels corresponding to different percentiles of MADS distribution. We statistically assessed the association of MADS risk strata with mortality, health care resource use, and disease progression across 1 million individuals from Spain, the United Kingdom, and Finland.

RESULTS

The results revealed significantly different distributions of the assessed outcomes across the MADS risk tiers, including mortality rates; primary care visits; specialized care outpatient consultations; visits in mental health specialized centers; emergency room visits; hospitalizations; pharmacological and nonpharmacological expenditures; and dispensation of antipsychotics, anxiolytics, sedatives, and antidepressants (P<.001 in all cases). Moreover, the results of the pairwise comparisons between adjacent risk tiers illustrate a substantial and gradual pattern of increased mortality rate, heightened health care use, increased health care expenditures, and a raised pharmacological burden as individuals progress from lower MADS risk tiers to higher-risk tiers. The analysis also revealed an augmented risk of multimorbidity progression within the high-risk groups, aligned with a higher incidence of new onsets of MDD-related diseases.

CONCLUSIONS

The MADS seems to be a promising approach for predicting health risks associated with multimorbidity. It might complement current risk assessment state-of-the-art tools by providing valuable insights for tailored epidemiological impact analyses of clusters of interrelated diseases and by accurately assessing multimorbidity progression risks. This study paves the way for innovative digital developments to support advanced health risk assessment strategies. Further validation is required to generalize its use beyond the initial case study of MDD.

Short and long-term predictors of pain severity and interference in primary care patients with chronic musculoskeletal pain and depression

BACKGROUND

Chronic pain and depression are frequent comorbidities in primary care. Depression among other psychosocial factors play a role in the clinical course of chronic pain.

OBJECTIVE

To study the short and long-term predictive factors of severity and interference of chronic pain in primary care patients with chronic musculoskeletal pain and major depression.

METHODS

Longitudinal study of a cohort of 317 patients. The outcomes are severity and functional interference of pain (Brief Pain Inventory) measured at 3 and 12 months. We performed multivariate linear regression models to estimate the effects the explanatory baseline variables on the outcomes.

RESULTS

83% participants were women; average age was 60.3 years (SD = 10.2). In multivariate models, baseline pain severity predicted pain severity at 3 months (β = 0.53; 95% CI = 0.37-0.68) and at 12 months (β = 0.48; 95% CI = 0.29-0.67). Also, pain > 2 years of evolution predicted long term pain severity (β = 0.91; CI95%=0.11-1.71). Baseline pain interference predicted interference at 3 and 12 months (β = 0.27; 95%CI = 0.11-0.43 and β = 0.21; 95%CI = 0.03-0.40, respectively). Baseline pain severity predicted interference at 3 and 12 months (β = 0.26; 95%CI = 0.10-0.42 and β = 0.20; 95%CI = 0.02-0.39, respectively). Pain > 2 years predicted greater severity and greater interference at 12 months (β = 0.91; CI95%=0.11-1.71, and β = 1.23; CI95%=0.41-2.04). Depression severity predicted more interference at 12 months (β = 0.58; CI95%=0.04-1.11). Occupational status as active worker predicted less interference throughout the follow-up (β=-0.74; CI95%=-1.36 to -0.13 and β=-0.96; CI95%=-1.71 to -0.21, at 3 and 12 months). Currently working also predicts less pain severity at 12 months (β=-0.77; CI95%=1.52 - 0.02). With regard to the psychological variables, pain catastrophizing predicted pain severity and interference at three months (β = 0.03; 95% CI = 0.00-0.05 and β = 0.03; 95% CI = 0.00-0.05), but not at long term.

CONCLUSION

In a sample of adults with chronic pain and depression, this primary care study has identified prognostic factors that independently predict the severity and functional interference of pain. If confirmed in new studies, these factors should be targeted for individualized interventions.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT02605278), registered 16/11/2015.

Development and validation of novel multimorbidity indices for older adults

BACKGROUND

Measuring multimorbidity in claims data is used for risk adjustment and identifying populations at high risk for adverse events. Multimorbidity indices such as Charlson and Elixhauser scores have important limitations. We sought to create a better method of measuring multimorbidity using claims data by incorporating geriatric conditions, markers of disease severity, and disease-disease interactions, and by tailoring measures to different outcomes.

METHODS

Health conditions were assessed using Medicare inpatient and outpatient claims from subjects age 67 and older in the Health and Retirement Study. Separate indices were developed for ADL decline, IADL decline, hospitalization, and death, each over 2 years of follow-up. We validated these indices using data from Medicare claims linked to the National Health and Aging Trends Study.

RESULTS

The development cohort included 5012 subjects with median age 76 years; 58% were female. Claims-based markers of disease severity and disease-disease interactions yielded minimal gains in predictive power and were not included in the final indices. In the validation cohort, after adjusting for age and sex, c-statistics for the new multimorbidity indices were 0.72 for ADL decline, 0.69 for IADL decline, 0.72 for hospitalization, and 0.77 for death. These c-statistics were 0.02-0.03 higher than c-statistics from Charlson and Elixhauser indices for predicting ADL decline, IADL decline, and hospitalization, and <0.01 higher for death (p < 0.05 for each outcome except death), and were similar to those from the CMS-HCC model. On decision curve analysis, the new indices provided minimal benefit compared with legacy approaches. C-statistics for both new and legacy indices varied substantially across derivation and validation cohorts.

CONCLUSIONS

A new series of claims-based multimorbidity measures were modestly better at predicting hospitalization and functional decline than several legacy indices, and no better at predicting death. There may be limited opportunity in claims data to measure multimorbidity better than older methods.

Follow-Up of a Cohort of Patients with Post-Acute COVID-19 Syndrome in a Belgian Family Practice

Fifty-five patients who suffered from COVID-19, who were still very ill after several months, with extreme fatigue, effort exhaustion, brain fog, anomia, memory disorder, anosmia, dysgeusia, and other multi-systemic health problems have been followed in a family practice setting between May 2021 and July 2022. Data extracted from the medical records of the 55 patients (40 women), mean age 42.4 (12 to 79 years), and a qualitative study of 6 of them using a semi-open-ended questionnaire allowed to highlight the clinical picture described by WHO as post-acute COVID-19 syndrome (PACS) also known as long COVID. We used brain single-photon emission computed tomography (SPECT-CT) in thirty-two patients with a high severity index and a highly impaired functional status, demonstrating vascular encephalopathy in twenty nine patients and supporting the hypothesis of a persistent cerebral vascular flow disorder in post COVID-19 condition. The patients will benefit from the consortium COVID Human Genetic Effort (covidhge.com) to explore the genetic and immunological basis of their problem, as 23/55 cases don't have immunological certainty of a COVID-19 infection. There is no known verified treatment. Analyzing the data from the first 52 patients, three categories of patients emerged over time: 16 patients made a full recovery after 6-8 months, 15 patients were able to return to life and work after 12-18 months with some sequelae, both groups being considered cured. In the third group, 21 patients are still very ill and unable to resume their work and life after 18 months. The biopsychosocial consequences on patients' lives are severe and family doctors are left out in the cold. It is necessary to test the reproducibility of this description, conducted on a small number of patients. Nevertheless, identifying, monitoring and supporting these patients is a necessity in family medicine.

Allostatic load and systemic comorbidities in psychiatric disorders

Psychiatric disorders are complex, disabling, and chronic conditions that are often accompanied by one or more systemic medical comorbidities. In this narrative review, we provide an overview of the allostatic load concept, which represents a multi-system dysregulation in response to chronic stress and link it to systemic comorbidities associated with psychiatric disorders. We synthesized published literature gathered using Medline (Ovid), Scopus, and PsychInfo and identified a high frequency of systemic comorbidities for both mood and psychotic disorders. The identified cardiovascular, metabolic, and immune comorbidities may represent the result of chronic wear and tear caused by a complex interaction between chronic psychosocial stress, health risk behaviors, pharmacological stressors, and the biological systems involved in the development of allostatic load. These findings support the notion that psychiatric disorders should be re-conceptualized as systemic disorders, affecting the brain and systemic biological pathways in an interconnected fashion to result in systemic comorbidities. We suggest that the multi-systemic and multi-dimensional approach that drives the allostatic load concept should be considered for understanding comorbidities in vulnerable psychiatric patients.

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient's unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

Unhealthy Immigrants: Sources for Health Gaps Between Immigrants and Natives in Israel

The study focuses on sources for health gaps between Jewish immigrants and native-born Israelis. Unlike traditional immigrant societies where immigration is viewed as economically motivated, immigrants returning to Israel are viewed as the "returning diaspora". Because immigrants in Israel are entitled to the same health benefits and medical services as native-born, we expect Israel to attract unhealthy immigrants in disproportionate numbers. The data for the analysis are obtained from the Israeli National Health Interview Survey (2013-2015). The data set provides detailed information on health status and illness, sociodemographic attributes and origin of immigrants. Three major origin groups of immigrants are distinguished: the former Soviet Union, Western Europeans or the Americans (mostly Ashkenazim), and Asians or North Africans (mostly Sephardim). Our findings lend support to the expectations that the health status of all immigrant groups is poorer than that of native-born Israelis. The nativity-illness gap is most pronounced in the case of male immigrants (from Europe or the Americas or South Africa or Australia) and for female immigrants (from countries in the Middle East or North Africa) and least pronounced in the case of immigrants arriving from the former Soviet Union for both gender groups. Decomposition of the gaps into components reveals that some portion of the illness gap can be attributed to nativity status, but the largest portion of the gap is attributed to demographic characteristics. Neither socioeconomic status nor health-related behavior accounts for a substantial portion of the nativity-illness gap for all subgroups of immigrants.

Derivation and validation of a novel comorbidity-based delirium risk index to predict postoperative delirium using national administrative healthcare database

OBJECTIVE

To derive and validate a comorbidity-based delirium risk index (DRI) to predict postoperative delirium.

DATA SOURCE/STUDY SETTING

Data of 506 438 hip fracture repair surgeries from 2006 to 2016 were collected to derive DRI and perform internal validation from the Premier Healthcare Database, which provided billing information on 20-25 percent of hospitalizations in the USA. Additionally, data of 1 130 569 knee arthroplasty surgeries were retrieved for external validation.

STUDY DESIGN

Thirty-six commonly seen comorbidities were evaluated by logistic regression with the outcome of postoperative delirium. The hip fracture repair surgery cohort was separated into a training dataset (60 percent) and an internal validation (40 percent) dataset. The least absolute shrinkage and selection operator (LASSO) procedure was applied for variable selection, and weights were assigned to selected comorbidities to quantify corresponding risks. The newly developed DRI was then compared to the Charlson-Deyo Index for goodness-of-fit and predictive ability, using the Akaike information criterion (AIC), Bayesian information criterion (BIC), area under the ROC curve (AUC) for goodness-of-fit, and odds ratios for predictive performance. Additional internal validation was performed by splitting the data by four regions and in 4 randomly selected hospitals. External validation was conducted in patients with knee arthroplasty surgeries.

DATA COLLECTION

Hip fracture repair surgeries, knee arthroplasty surgeries, and comorbidities were identified by using ICD-9 codes. Postoperative delirium was defined by using ICD-9 codes and analyzing billing information for antipsychotics (specifically haloperidol, olanzapine, and quetiapine) typically recommended to treat delirium.

PRINCIPAL FINDINGS

The derived DRI includes 14 comorbidities and assigns comorbidities weights ranging from 1 to 6. The DRI outperformed the Charlson-Deyo Comorbidity Index with better goodness-of-fit and predictive performance.

CONCLUSIONS

Delirium risk index is a valid comorbidity index for covariate adjustment and risk prediction in the context of postoperative delirium. Future work is needed to test its performance in different patient populations and varying definitions of delirium.

Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study

OBJECTIVE

Clinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA_1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA_1c.

RESEARCH DESIGN AND METHODS

We used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged ≥35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA_1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA_1c models.

RESULTS

A total of 139 626 patients registered in 400 general practices, aged 63±12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3±2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had ≥1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA_1c for all outcomes. Findings were consistent in the validation cohort.

CONCLUSIONS

Higher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA_1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes.

Measuring multimorbidity beyond counting diseases: systematic review of community and population studies and guide to index choice

OBJECTIVES

To identify and summarise existing indices for measuring multimorbidity beyond disease counts, to establish which indices include mental health comorbidities or outcomes, and to develop recommendations based on applicability, performance, and usage.

DESIGN

Systematic review.

DATA SOURCES

Seven medical research databases (Medline, Web of Science Core Collection, Cochrane Library, Embase, PsycINFO, Scopus, and CINAHL Plus) from inception to October 2018 and bibliographies and citations of relevant papers. Searches were limited to English language publications.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Original articles describing a new multimorbidity index including more information than disease counts and not focusing on comorbidity associated with one specific disease. Studies were of adults based in the community or at population level.

RESULTS

Among 7128 search results, 5560 unique titles were identified. After screening against eligibility criteria the review finally included 35 papers. As index components, 25 indices used conditions (weighted or in combination with other parameters), five used diagnostic categories, four used drug use, and one used physiological measures. Predicted outcomes included mortality (18 indices), healthcare use or costs (13), hospital admission (13), and health related quality of life (7). 29 indices considered some aspect of mental health, with most including it as a comorbidity. 12 indices are recommended for use.

CONCLUSIONS

35 multimorbidity indices are available, with differing components and outcomes. Researchers and clinicians should examine existing indices for suitability before creating new ones.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017074211.

Effectiveness of a collaborative care intervention for managing major depression and chronic musculoskeletal pain in primary care: A cluster-randomised controlled trial

BACKGROUND

Depression and chronic musculoskeletal pain commonly occur as comorbid conditions, which increases their negative effects on health outcomes. The objective of this study was to assess the effectiveness of the DROP (DepRessiOn and Pain) programme designed for the management of major depression and chronic musculoskeletal pain in primary care.

METHODS

A cluster-randomised controlled trial was carried out between June 2015 and December 2017 with 328 patients with major depression and chronic musculoskeletal pain, randomly allocated to either intervention arm or usual care arm. The intervention included care management, optimised management of depression, and a psychoeducational programme. Outcomes were monitored using blinded interviews over a 12-month period.

TRIAL REGISTRATION

NCT02605278 (ClinicalTrials.gov).

RESULTS

After 12 months, 274 patients were evaluated (83.5% participation). The severity of depression (Hopkins Symptom Checklist score) was 0.23 points lower in the intervention arm [1.11 vs. 1.34; CI95% = -0.42 to -0.04]. Intervention arm's response rate to antidepressant treatment was 18.9% higher [39.6% vs. 20.7%; OR = 2.74; CI95% = 1.12-6.67] and its remission rate for depression was 9.0% higher [20.1% vs. 11.1%; OR = 2.13; CI95% = 0.94-4.85] compared to the usual care arm. There were no significant differences between the two arms in terms of pain severity (Brief Pain Inventory severity score) [6.23 vs. 6.66; difference = -0.39; CI95% = -1.13-0.35] or pain response rate [18.7% vs. 18.5%; OR = 1.02; CI95% = 0.46-2.26].

LIMITATIONS

This is a pragmatic study, and poor adherence to the programme by patients and physicians was a main limitation.

CONCLUSION

The programme improves clinical outcomes for depression, although no clinical benefits were seen for pain.

Assessing the severity of Type 2 diabetes using clinical data-based measures: a systematic review

AIMS

To identify and critically appraise measures that use clinical data to grade the severity of Type 2 diabetes.

METHODS

We searched MEDLINE, Embase and PubMed between inception and June 2018. Studies reporting on clinical data-based diabetes-specific severity measures in adults with Type 2 diabetes were included. We excluded studies conducted solely in participants with other types of diabetes. After independent screening, the characteristics of the eligible measures including design and severity domains, the clinical utility of developed measures, and the relationship between severity levels and health-related outcomes were assessed.

RESULTS

We identified 6798 studies, of which 17 studies reporting 18 different severity measures (32 314 participants in 17 countries) were included: a diabetes severity index (eight studies, 44%); severity categories (seven studies, 39%); complication count (two studies, 11%); and a severity checklist (one study, 6%). Nearly 89% of the measures included diabetes-related complications and/or glycaemic control indicators. Two of the severity measures were validated in a separate study population. More severe diabetes was associated with increased healthcare costs, poorer cognitive function and significantly greater risks of hospitalization and mortality. The identified measures differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively.

CONCLUSIONS

Health records are suitable for assessment of diabetes severity; however, the clinical uptake of existing measures is limited. The need to advance this research area is fundamental as higher levels of diabetes severity are associated with greater risks of adverse outcomes. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services.

Development of the "chronic condition measurement guide": a new tool to measure chronic conditions in older people based on ICD-10 and ATC-codes

PURPOSE

The aim of the study was to develop a comprehensive open-source measurement guide of the most prevalent chronic conditions among persons aged 65+ based on registry data of both diagnoses and prescribed drugs [the chronic condition measurement guide (CCMG)]. Furthermore, to investigate proof of concept of the measurement guide, different years of history and in- and excluding data on prescribed drugs. Finally, to investigate the measurement guide with other measurement guides designed to identify chronic conditions in persons aged 65+.

METHODS

The measurement guide was based on the 200 most prevalent chronic ICD10 codes in the Danish population 65+ years in 2015; the 200 most prevalent chronic ICD10 codes and causes of death in a cohort of 209,337 people who died of non-traumatic causes (January 2011-January 2016). Prescribed drugs were included in the measurement guide based on a literature review and specialist opinions.

RESULTS

We identified 83 different chronic conditions based on 1241 unique ICD-10 codes. Multimorbidity prevalence ranged from 10% (1-year history, excluding prescribing information) to 69% (15-year history, including prescribing information). We identified 95% of the persons with multimorbidity using the 29 most prevalent chronic conditions. Inclusion of these 29 conditions affected the prevalence of multimorbidity and 1-year mortality when the CCMG was compared with other measurement guides.

CONCLUSION

The CCMG is easily implemented using registry data. When implementing the measurement guide 10 years of history and drug prescribing information should be used. Using the CCMG to study multimorbidity, we recommend using at least the 29 most prevalent chronic conditions.

Multimorbidity rehabilitation versus disease-specific rehabilitation in people with chronic diseases: a pilot randomized controlled trial

BACKGROUND

Multimorbidity (the co-existence of two or more chronic conditions in an individual) is a growing healthcare burden internationally; however, healthcare and disease management, including rehabilitation, is often delivered in single-disease siloes. The aims of this study were to (1) evaluate the safety and feasibility of multimorbidity rehabilitation compared to a disease-specific rehabilitation program in people with multimorbidity and (2) gather preliminary data regarding clinical outcomes and resource utilization to inform the design of future trials.

METHODS

A pilot feasibility randomized controlled trial with concealed allocation, assessor blinding, and intention-to-treat analysis. Seventeen individuals with a chronic disease eligible for disease-specific rehabilitation (pulmonary, cardiac, heart failure rehabilitation) and at least one other chronic condition were recruited. The intervention group attended multimorbidity exercise rehabilitation and the control group attended disease-specific exercise rehabilitation. Participants attended twice-weekly exercise training and weekly education for 8 weeks. Feasibility measures included numbers screened, recruited, and completed. Other outcome measures were change in functional exercise capacity (6-minute walk test (6MWT)), health-related quality of life (HRQoL), activities of daily living (ADL), and resource utilization.

RESULTS

Sixty-one people were screened to recruit seventeen participants (nine intervention, eight control); one withdrew prior to rehabilitation. Participants were mostly male (63%) with a mean (SD) age of 69 (9) years and body mass index of 29 (6). The intervention group attended a mean (SD) of 12 (6) sessions, and the control group attended 11 (4) sessions. One participant (6%) withdrew after commencing; two (12%) were lost to follow-up. The intervention group 6MWT distance increased by mean (SD) of 22 (45) meters (95% confidence interval - 16 to 60) compared to 22 (57) meters (95% confidence interval - 69 to 114) (control).

CONCLUSIONS

It was feasible to recruit people with multimorbidity to a randomized controlled trial of rehabilitation. A large RCT with the power to make significant conclusions about the impact on the primary and secondary outcomes is now required.

TRIAL REGISTRATION

The trial was registered with the Australian and New Zealand Clinical Trials Registry available at http://www.anzctr.org.au ACTRN12614001186640. Registered 12/11/2014.

A rehabilitation programme for people with multimorbidity versus usual care: A pilot randomized controlled trial

BACKGROUND

Multimorbidity, the coexistence of two or more chronic conditions, is common in clinical practice. Rehabilitation for people with multimorbidity may provide access to a rehabilitation programme that can address common symptoms and risk factors for multiple chronic diseases.

OBJECTIVE

The aims of this study were to (1) evaluate the feasibility of a rehabilitation programme compared to usual medical care (UMC) in people with multimorbidity and (2) gather preliminary data regarding clinical effects and impact on functional exercise capacity, activities of daily living, health-related quality of life and resource utilization.

DESIGN

A pilot feasibility parallel randomized controlled trial was undertaken. Adults with multimorbidity were randomized to the rehabilitation programme (intervention) or UMC (control). The duration of the rehabilitation programme was 8 weeks and comprised exercise (1 h, twice weekly) and education (1 h, once weekly). The UMC group did not participate in a structured exercise programme.

RESULTS

One hundred people were screened to recruit 16 participants, with a 71% completion rate for the intervention group. The rehabilitation group achieved a mean (standard deviation) improvement in 6-minute walk distance of 44 (41) m and the UMC group of 23 (29) m.

CONCLUSIONS

This study suggests that it would be feasible to conduct a larger randomized control trial investigating a rehabilitation programme for people with multimorbidity. Low uptake of the study suggests that refinement of the inclusion criteria, recruitment sources and programme model will be needed to achieve the number of participants required.

[The problem of multiple somatic and/or psychiatric pathology basic concepts and prevalence]

The literature of the last decades shows the growing interest to multiple pathologies in medicine including psychiatry and neurology. Multiple pathology is often determined as multimorbidity or comorbidity. Multiple pathology is a common phenomenon, which is the rule rather than the exception. In the medical care system, it is burden for the patient and for the physician in clinical, organizational and economic aspects. The review addresses all these issues in the aspect of terminology and prevalence.

Comorbidity assessment in localized prostate cancer: a systematic review protocol

The objective of this study is to review and summarize the methods and tools used to measure comorbidity in localized prostate cancer (PCa) and in particular to assess whether these tools are adequately validated and reliable for determining the impact of comorbidity on survival and treatment decisions for this disease.Specifically, the review questions are.

Cross-sectional examination of musculoskeletal conditions and multimorbidity: influence of different thresholds and definitions on prevalence and association estimates

BACKGROUND

Multimorbidity and musculoskeletal conditions create substantial burden for people and health systems. Quantifying the extent of co-occurring conditions is hampered by conceptual heterogeneity, imprecision and/or indecision about how multimorbidity is defined. The purpose of this study is to examine the influence of different ways of operationalising multimorbidity on multimorbidity prevalence rates with a focus on working-age adults with musculoskeletal conditions. Weighted population prevalence rates of multimorbidity among working-age Australians were estimated using data from the National Health Survey. Two nominal thresholds (2+ or 3+ co-occurring conditions) and three operational definitions of multimorbidity (survey-, policy- and research-based) were examined. Using logistic regression, we estimated the association between the prevalence of multimorbidity among persons with musculoskeletal conditions compared to persons with non-musculoskeletal conditions for each definition and threshold combination.

RESULTS

As few as 7.9% of working-age Australians have 2+ conditions using the research-based definition (95% CI 7.4-8.5%), compared to estimates of 15.3% (95% CI 14.3-16.2%) and 61.5% (95% CI 60.3-62.7%). with the policy- and survey-based definitions, respectively. Depending on definition, with the 3+ threshold multimorbidity prevalence ranged from 2.1% (research) to 41.9% (survey). Among the sub-sample with musculoskeletal conditions, multimorbidity with the 2+ threshold ranged from 20.2 to 92.2%; and with 3+ threshold from 5.9 to 75.4%, again lowest with the research-definition and highest with the survey-definition. When compared to any other condition (i.e. non-musculoskeletal conditions), all musculoskeletal conditions were positively associated with multimorbidity, regardless of definition or threshold.

CONCLUSIONS

Depending on definition and threshold, multimorbidity is either rare or endemic in working-age Australians. Irrespective of definition, musculoskeletal conditions are a near-ubiquitous feature of multimorbidity.

Effect of Multimorbidity on Health-Related Quality of Life in Adults Aged 55 Years or Older: Results from the SU.VI.MAX 2 Cohort

Introduction

Multimorbid chronic diseases are usually considered separately in trials. Here, we aimed to describe overall multimorbidity patterns in adults aged 55 years or older and assess their effect on health-related quality of life (HRQoL).

Methods

We used data for 5,647 participants included in the SUpplémentation en VItamines et Minéraux AntioXydants 2 (SU.VI.MAX 2) population-based trial. HRQoL was assessed by the French versions of the Medical Outcome Study Short Form 36 and the Duke Health Profile. An exploratory factor analysis was used to determine multimorbidity patterns, and a multimorbidity score for each resulting pattern was calculated. Adjusted multiple linear regression was used to examine the association between the identified multimorbidity and HRQoL scores by gender and for each age group (55–59, 60–64, 65–69, ≥ 70 years).

Results

More than 63% of the sample reported two or more chronic conditions (from 55.8% for those 55–59 years to 74.4% for those ≥ 70 years). Multimorbidity was more common among women than men (67.3% vs 60%). Two different multimorbidity patterns were identified. Pattern A was represented mainly by mental illness and bone impairments. Pattern B was represented mainly by cardiovascular and metabolic disorders. After adjusting for covariates, a high pattern A score was associated with reduced HRQoL for the physical and mental components of each HRQoL questionnaire, and a high pattern B score was associated with reduced HRQoL for only the physical component of each questionnaire. These multimorbidity scores affected HRQoL differently by age group.

Conclusion

Our study used a novel methodological approach to account for multimorbidity patterns in determining the link with chronic conditions. These multimorbidity scores (counted and weighted) can be used in clinical research to control for the effect of multimorbidity on patients’ HRQoL and may be useful for clinical practice.

Clinical Trial Registration

Clinicaltrial.gov (number NCT00272428).

Development and Validation of the Medication-Based Disease Burden Index

Background:

Medication lists offer an alternative source of data on comorbidities and disease burden.

Objective:

To develop and validate the Medication-Based Disease Burden Index (MDBI).

Methods:

A list of medications corresponding to the leading causes of global death was pilot tested and finalized by an expert panel. The resulting index was tested on drug regimens of patients at risk of medication misadventure. Criterion validity of the index was established against Charlson's index and Chronic Disease Score (CDS). Sensitivity, specificity, predictive validity, convergent and discriminant validity, and interrater and test–retest reliabilities of the index were also assessed.

Results:

The MDBI consisting of specific medications for 20 chronic medical conditions and corresponding disability weightings was developed. The MDBI was tested on 317 patients with mean ± SD Charlson's index scores of 2.8 ± 2.2 and CDS scores of 7.3 ± 2.8. Mean MDBI scores (0.33 ± 0.28) demonstrated significant correlations with Charlson's index scores (r = 0.31; p < 0.001) and CDS (r = 0.53; p < 0.001). MDBI had satisfactory sensitivity and high specificity. Age of the patients and number of medications had significant correlation with the MDBI scores, but the MDBI scores were not significantly different in males and females. MDBI scores could successfully predict death and planned or unplanned readmissions (OR = 4.7, 95% CI 1.4 to 15.5; p = 0.01). MDBI demonstrated high inter-rater (intraclass correlation coefficient [ICC] = 0.99) and test–retest reliabilities (ICC = 0.98).

Conclusions:

Initial testing suggests that MDBI could offer an alternative low-cost and convenient method for quantifying disease burden and predicting health outcomes.

Increasing specialty care access through use of an innovative home telehealth-based spinal cord injury disease management protocol (SCI DMP)

BACKGROUND

A spinal cord injury disease management protocol (SCI DMP) was developed to address the unique medical, physical, functional, and psychosocial needs of those living with spinal cord injuries and disorders (SCI/D). The SCI DMP was piloted to evaluate DMP clinical content and to identify issues for broader implementation across the Veterans Affairs (VA) SCI System of Care.

METHODS

Thirty-three patients with SCI/D from four VA SCI centers participated in a 6-month pilot. Patients received customized SCI DMP questions through a data messaging device (DMD). Nurse home telehealth care coordinators (HTCC) monitored responses and addressed clinical alerts daily. One site administered the Duke Severity of Illness (DUSOI) Checklist and Short Form-8 (SF-8™) to evaluate the changes in comorbidity severity and health-related quality of life while on the SCI DMP.

RESULTS

Patients remained enrolled an average of 116 days, with a mean response rate of 56%. The average distance between patient's home and their VA SCI center was 59 miles. Feedback on SCI DMP content and the DMD included requests for additional clinical topics, changes in administration frequency, and adapting the DMD for functional impairments. Improvement in clinical outcomes was seen in a subset of patients enrolled on the SCI DMP.

CONCLUSION

SCI HTCCs and patients reported that the program was most beneficial for newly injured patients recently discharged from acute rehabilitation that live far from specialty SCI care facilities. SCI DMP content changes and broader implementation strategies are currently being evaluated based on lessons learned from the pilot.

Rest-Activity Patterns in Older Adults with Heart Failure and Healthy Older Adults

The purpose of this investigation is to examine differences in rest-activity patterns and sleep characteristics in older adults with heart failure (HF) and healthy older adults. The sample included older adults with HF (n = 20) and a reference group of healthy older adults (n = 20). Traditional cosinor analysis was used to assess three parameters of rest-activity from wrist actigraphy data: amplitude (range of activity), mesor (mean activity), and acrophase (time of peak activity). Traditional sleep characteristics were also determined from actigraphy data: total sleep time (TST), sleep latency (SL), sleep efficiency (SE), and wake after sleep onset (WASO). The HF group demonstrated significantly lower mesor and amplitude than the reference group (p < .01). The HF group had significantly greater TST (p < .01), but the groups had similar SE, SL, and WASO. Despite similar sleep characteristics to healthy older adults, overall rest-activity patterns were significantly dampened in those with HF.

Changing definitions altered multimorbidity prevalence, but not burden associations, in a musculoskeletal population

OBJECTIVES

The inclusion of musculoskeletal conditions within multimorbidity research is inconsistent, and working-age populations are largely ignored. We aimed to: (1) estimate multimorbidity prevalence among working-age individuals with a range of musculoskeletal conditions; and (2) better understand the implications of decisions about the number and range of conditions constituting multimorbidity on the strength of associations between multimorbidity and burden (e.g., health status and health care utilization).

STUDY DESIGN AND SETTING

Using data from the Australian National Health Survey 2007-08, the associations between burden measures and three ways of operationalizing multimorbidity (survey, policy, and research based) within the working-age (18-64 years) musculoskeletal population were estimated using multiple logistic regression (age and gender adjusted).

RESULTS

Depending on definition, from 20.2% to 75.4% of working-age individuals with musculoskeletal conditions have multimorbidity. Irrespective of definition, multimorbidity was associated with increased likelihood of subjective health burden, pain or musculoskeletal medicines use, nonmusculoskeletal specialist and pharmacist (advice only) consultations, and reduced likelihood of not consulting health professionals. A group with intermediate health outcomes was considered multimorbid by some, but not all definitions. With the restrictive policy and research multimorbidity definitions, this intermediate group is included within the reference population (i.e., are considered nonmultimorbid). This worsens the reference group's apparent health status thereby leveling the comparative burden between those with and without multimorbidity. Consequently, dichotomous cut points lead to similar associations with burden measures despite the increasingly restrictive multimorbidity definitions used.

CONCLUSIONS

All multimorbidity definitions were associated with burden among the working-age musculoskeletal population. However, dichotomous cut points obscure the gradient of increased burden associated with restrictive definitions.

Pre-hospital medications in total hip arthroplasty: risk factors for poor outcomes

INTRODUCTION

The influence of co-morbidities on complication rates and length of hospitalisation after surgery is well recognised. Clinical instruments predicting this influence, are of increasing interest. We sought to determine whether a count of a patient's preoperative pharmaceuticals would be associated to postoperative outcomes.

MATERIAL AND METHODS

In this retrospective, consecutive case series, 668 patients undergoing elective primary total hip arthroplasty (THA) were analysed. Age, gender, BMI, ASA-classification, nicotine or alcohol abuse, and the number and type of medications were documented.

RESULTS

Mean age was 63 years (18-94), 53% were females. A total of 60 (8.9%) local and 19 (2.8%) systemic complications occurred during hospital stay. A total of 11 (1.6%) patients died, while 49 (7.3%) local complications occurred during the first postoperative year. Length of hospital stay, blood transfusions, and morbidity were found to be significantly related to the quantity of medications (p&lt;0.001). While the risk of an extended hospital stay (&gt;7 days) increased by a factor of 1.15 (CI: 1.08-1.22) with each medication, the risk of experiencing a complication within the first postoperative year was 1.19 times (CI: 1.07-1.29) for each additional medication. Type of medication also influenced morbidity: the odds ratio was 1.89 (CI: 1.05-3.41) for platelet inhibiting agents and 4.07 (CI: 1.96-8.42) for oral anticoagulants in early morbidity, which increased to 6.05 (CI:2.92-12.53) in 1-year follow-up.

CONCLUSIONS

The investigation illustrated the significant influence of the number and/or type of medication on complications, morbidity and prolonged hospital stay. This predictive tool may be useful, for physicians and non-health professionals, in estimating particular outcomes after elective THA.

Evaluation of a multicomponent programme for the management of musculoskeletal pain and depression in primary care: a cluster-randomised clinical trial (the DROP study)

BACKGROUND

Chronic musculoskeletal pain and depression are very common in primary care patients. Furthermore, they often appear as comorbid conditions, resulting in additive effect on adverse health outcomes. On the basis of previous studies, we hypothesise that depression and chronic musculoskeletal pain may benefit from an integrated management programme at primary care level. We expect positive effects on both physical and psychological distress of patients.

OBJECTIVE

To determine whether a new programme for an integrated approach to chronic musculoskeletal pain and depression leads to better outcomes than usual care.

DESIGN

Cluster-randomised controlled trial involving two arms: a) control arm (usual care); and b) intervention arm, where patients participate in a programme for an integrated approach to the pain-depression dyad.

SETTINGS

Primary care centres in the province of Tarragona, Catalonia, Spain, Participants: We will recruit 330 patients aged 18-80 with moderate or severe musculoskeletal pain (Brief Pain Inventory, average pain subscale ≥5) for at least 3 months, and with criteria for major depression (DSM-IV).

INTERVENTION

A multicomponent programme according to the chronic care model. The main components are care management, optimised antidepressant treatment, and a psychoeducational group action. Blind measurements: The patients will be monitored through blind telephone interviews held at 0, 3, 6 and 12 months.

OUTCOMES

Severity of pain and depressive symptoms, pain and depression treatment response rates, and depression remission rates.

ANALYSIS

The outcomes will be analysed on an intent-to-treat basis and the analysis units will be the individual patients. This analysis will consider the effect of the study design on any potential lack of independence between observations made within the same cluster.

ETHICS

The protocol was approved by the Research Ethics Committee of the Jordi Gol Primary Care Research Institute (IDIAP), Barcelona, (P14/142).

DISCUSSION

This project strengthens and improves treatment approaches for a major comorbidity in primary care. The design of the intervention takes into account its applicability under typical primary care conditions, so that if the programme is found to be effective it will be feasible to apply it in a generalised manner.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02605278 ; Registered 28 September, 2015.

Partial and No Recovery from Delirium in Older Hospitalized Adults: Frequency and Baseline Risk Factors

OBJECTIVES

To determine the frequency and baseline risk factors for partial and no recovery from delirium in older hospitalized adults.

DESIGN

Cohort study with assessment of recovery status approximately 1 and 3 months after enrollment.

SETTING

University-affiliated, primary, acute-care hospital.

PARTICIPANTS

Medical or surgical inpatients aged 65 and older with delirium (N = 278).

MEASUREMENTS

The Mini-Mental State Examination (MMSE), Confusion Assessment Method (CAM), Delirium Index (DI), and activities of daily living (ADLs) were completed at enrollment and each follow-up. Primary outcome categories were full recovery (absence of CAM core symptoms of delirium), partial recovery (presence of ≥1 CAM core symptoms but not meeting criteria for delirium), no recovery (met CAM criteria for delirium), or death. Secondary outcomes were changes in MMSE, DI, and ADL scores between the baseline and last assessment. Potential risk factors included many clinical and laboratory variables.

RESULTS

In participants with dementia, frequencies of full, partial, and no recovery and death at first follow-up were 6.3%, 11.3%, 74.6%, and 7.7%, respectively; in participants without dementia, frequencies were 14.3%, 17%, 50.9%, and 17.9%, respectively. In participants with dementia, frequencies at the second follow-up were 7.9%, 15.1%, 57.6%, and 19.4%, respectively; in participants without dementia, frequencies were 19.2%, 20.2%, 31.7%, and 28.8%, respectively. Frequencies were similar in participants with prevalent and incident delirium and in medical and surgical participants. The DI, MMSE, and ADL scores of many participants with partial and no recovery improved. Independent baseline risk factors for delirium persistence were chart diagnosis of dementia (odds ratio (OR) = 2.51, 95% confidence interval (CI) =1.38, 4.56), presence of any malignancy (OR = 5.79, 95% CI = 1.51, 22.19), and greater severity of delirium (OR =9.39, 95% CI = 3.95, 22.35).

CONCLUSION

Delirium in many older hospitalized adults appears to be much more protracted than previously thought, especially in those with dementia, although delirium symptoms, cognition, and function improved in many participants with partial and no recovery. It may be important to monitor the longer-term course of delirium in older hospitalized adults and develop strategies to ensure full recovery.

Time-varying impact of comorbidities on mortality after liver transplantation: a national cohort study using linked clinical and administrative data

OBJECTIVE

We assessed the impact of comorbidity on mortality in three periods after liver transplantation (first 90 days, 90 days-5 years and 5-10 years).

DESIGN

Prospective cohort study using records from the UK Liver Transplant Audit (UKLTA) linked to Hospital Episode Statistics (HES), an administrative database of hospital admissions in the English National Health Service (NHS). Comorbidities relevant for liver transplantation were identified from the 10th revision of the International Classification of Diseases (ICD-10) codes in HES records of admissions in the year preceding their operation. Multivariable Cox regression was used to estimate HRs for three different time periods after liver transplantation.

SETTING

All liver transplant centres in the NHS hospitals in England.

PARTICIPANTS

Adults who received a first elective liver transplant between April 1997 and March 2010 in the linked UKLTA-HES database.

OUTCOMES

Patient mortality in three different time periods after transplantation.

RESULTS

Among 3837 recipients, 45.1% had comorbidities. Recipients with cardiovascular disease had statistically significantly higher mortality in all three periods after transplantation (first 90 days: HR=2.0; 95% CI 1.4 to 2.9, 90 days-5 years: 1.6; 1.2 to 2.2, beyond 5 years: 2.8; 1.7 to 4.4). Prior congestive cardiac failure (3.2; 2.1 to 4.9) significantly increased mortality only in the first 90 days. History of non-hepatic malignancy appeared to increase risk over all periods, but significantly only in the first 90 days (1.9; 1.0 to 3.6). A diagnosis of connective tissue disease, dementia, diabetes, chronic pulmonary and renal disease did not have a significant impact on mortality in any period.

CONCLUSIONS

The impact of comorbidities present at the time of transplantation changes with time after transplantation. Renal disease, pulmonary disease and diabetes had no impact on mortality in contrast to previous reports.

Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis

Objectives

To investigate the use of latent class growth analysis (LCGA) in understanding onset and changes in multimorbidity over time in older adults.

Study Design and Setting

This study used primary care consultations for 42 consensus-defined chronic morbidities over 3 years (2003–2005) by 24,615 people aged >50 years at 10 UK general practices, which contribute to the Consultations in Primary Care Archive database. Distinct groups of people who had similar progression of multimorbidity over time were identified using LCGA. These derived trajectories were tested in another primary care consultation data set with linked self-reported health status.

Results

Five clusters of people representing different trajectories were identified: those who had no recorded chronic problems (40%), those who developed a first chronic morbidity over 3 years (10%), a developing multimorbidity group (37%), a group with increasing number of chronic morbidities (12%), and a multi-chronic group with many chronic morbidities (1%). These trajectories were also identified using another consultation database and associated with self-reported physical and mental health.

Conclusion

There are distinct trajectories in the development of multimorbidity in primary care populations, which are associated with poor health. Future research needs to incorporate such trajectories when assessing progression of disease and deterioration of health.

Glucocorticoid dose thresholds associated with all-cause and cardiovascular mortality in rheumatoid arthritis

OBJECTIVE

To delineate daily and cumulative glucocorticoid dose thresholds associated with increased mortality rates in rheumatoid arthritis (RA).

METHODS

We studied RA patients recruited from rheumatology clinics. Annually, we assessed the glucocorticoid dose, demographic, socioeconomic, clinical, and laboratory features of RA, cardiovascular (CV) risk factors, and vital status. We used Cox proportional hazards regression to assess associations between the daily or cumulative glucocorticoid dose and death, adjusting for potential confounders and for the propensity to receive glucocorticoids. We tested strata of the glucocorticoid dose to delineate the threshold associated with death.

RESULTS

We studied 779 RA patients with a total of 7,203 person-years of observation, during which 237 of them died, yielding a mortality rate of 3.2 per 100 person-years (95% confidence interval [95% CI] 2.8-3.7). One hundred twenty of the deaths were due to CV causes, yielding a CV mortality rate of 1.8 (95% CI 1.5-2.1). Exposure to glucocorticoids was associated with a dose-dependent increase in death from all causes, with a ratio (HR) of 1.07 per mg of prednisone per day (95% CI 1.05-1.08). Compared to patients who were not receiving corticosteroids, the minimum daily prednisone dose threshold associated with an increase in all-cause mortality was 8-15 mg, with an adjusted HR of 1.78 (95% CI 1.22-2.60). For the cumulative dose of glucocorticoids, the minimum dosage associated with all-cause mortality was 40 gm (HR 1.74 [95% CI 1.25-2.44]).

CONCLUSION

Glucocorticoid use in RA is associated with a dose-dependent increase in mortality rates, with a daily threshold dose of 8 mg, at which the number of deaths increased in a dose-dependent manner. These findings may assist clinicians in selecting the appropriate glucocorticoid dosage for RA patients who require these agents.

Development of the PRE-HIT instrument: patient readiness to engage in health information technology

Background

Technology-based aids for lifestyle change are becoming more prevalent for chronic conditions. Important “digital divides” remain, as well as concerns about privacy, data security, and lack of motivation. Researchers need a way to characterize participants’ readiness to use health technologies. To address this need, we created an instrument to measure patient readiness to engage with health technologies among adult patients with chronic conditions.

Methods

Initial focus groups to determine domains, followed by item development and refinement, and exploratory factor analysis to determine final items and factor structure. The development sample included 200 patients with chronic conditions from 6 family medicine clinics. From 98 potential items, 53 best candidate items were examined using exploratory factor analysis. Pearson’s Correlation for Test/Retest reliability at 3 months.

Results

The final instrument had 28 items that sorted into 8 factors with associated Cronbach’s alpha: 1) Health Information Need (0.84), 2) Computer/Internet Experience (0.87), 3) Computer Anxiety (0.82), 4) Preferred Mode of Interaction (0.73), 5) Relationship with Doctor (0.65), 6) Cell Phone Expertise (0.75), 7) Internet Privacy (0.71), and 8) No News is Good News (0.57). Test-retest reliability for the 8 subscales ranged from (0.60 to 0.85).

Conclusion

The Patient Readiness to Engage in Health Internet Technology (PRE-HIT) instrument has good psychometric properties and will be an aid to researchers investigating technology-based health interventions. Future work will examine predictive validity.

The prevalence of disease clusters in older adults with multiple chronic diseases--a systematic literature review

Background

Since most clinical guidelines address single diseases, treatment of patients with multimorbidity, the co-occurrence of multiple (chronic) diseases within one person, can become complicated. Information on highly prevalent combinations of diseases can set the agenda for guideline development on multimorbidity. With this systematic review we aim to describe the prevalence of disease combinations (i.e. disease clusters) in older patients with multimorbidity, as assessed in available studies. In addition, we intend to acquire information that can be supportive in the process of multimorbidity guideline development.

Methods

We searched MEDLINE, Embase and the Cochrane Library for all types of studies published between January 2000 and September 2012. We included empirical studies focused on multimorbidity or comorbidity that reported prevalence rates of combinations of two or more diseases.

Results

Our search yielded 3070 potentially eligible articles, of which 19 articles, representing 23 observational studies, turned out to meet all our quality and inclusion criteria after full text review. These studies provided prevalence rates of 165 combinations of two diseases (i.e. disease pairs). Twenty disease pairs, concerning 12 different diseases, were described in at least 3 studies. Depression was found to be the disease that was most commonly clustered, and was paired with 8 different diseases, in the available studies. Hypertension and diabetes mellitus were found to be the second most clustered diseases, both with 6 different diseases. Prevalence rates for each disease combination varied considerably per study, but were highest for the pairs that included hypertension, coronary artery disease, and diabetes mellitus.

Conclusions

Twenty disease pairs were assessed most frequently in patients with multimorbidity. These disease combinations could serve as a first priority setting towards the development of multimorbidity guidelines, starting with the diseases with the highest observed prevalence rates and those with potential interacting treatment plans.

Concepts of comorbidities, multiple morbidities, complications, and their clinical epidemiologic analogs

The proportion of older people in the world population is expected to increase rapidly during the upcoming decades. Consequently, the number of patients with multimorbidity will increase dramatically. In epidemiologic research, the concepts of multimorbidity, comorbidity, and complications have been confusing, and some of these concepts are used interchangeably. In this commentary, the authors propose a clear terminology for clinical concepts describing different aspects of multimorbidity and elucidate the relationship between these clinical concepts and their epidemiologic analogs. Depending on whether a study uses causal or predictive models, a proper distinction between concepts of multimorbidity is important. It can be very difficult to separate complications of the index disease under study from comorbidity. In this context, use of comorbidity indices as confounding scores should be done with caution. Other methodologic issues are type, duration, severity, and number of comorbidities included in the ascertainment methods, as well as sources included in the research. Studies that recognize these challenges have the potential to yield valid estimates of the comorbidity burden and results that can be compared with other studies.

Effectiveness of a multi-component programme for managing depression in primary care: a cluster randomized trial. The INDI project

BACKGROUND

There are significant shortcomings in the management and clinical outcomes of depressed patients. The objective is to assess the effectiveness of a multi-component programme to improve the management of depression in primary care.

METHODS

This is a cluster-randomized controlled trial, conducted between June 2007 and June 2010. Twenty primary care centres were allocated to intervention group or usual care group. The intervention consisted of a multi-component programme with clinical, educational and organizational procedures including primary care nurses working as case-managers. Outcomes were monitored by a blinded interviewer at 0, 3, 6 and 12 months.

TRIAL REGISTRATION

ISRCTN16384353, at http://isrctn.org.

RESULTS

In total, 338 adult patients with major depression (DSM-IV) were assessed at baseline. At 12 months, 302 patients were assessed, 172 in the intervention group and 130 in the control group. The severity of depression (mean Patient Health Questionnaire-9 score) was 1.76 points lower in the intervention group [7.15 vs. 8.78, 95% CI=-3.53 to 0.02, p=0.053]. The treatment response rate was 15.4% higher in the intervention group than in the controls [66.9% vs. 51.5%, odds ratio 1.9, 95% CI=1.2 to 3.1, p=0.011)], and the remission rate was 13.4% higher [48.8% vs. 35.4%, odds ratio 1.8, 95% CI=1.1 to 2.9, p=0.026)].

LIMITATIONS

Unblinded physicians diagnosed depression in their patients and decided whether to include them in the study, so we cannot discount a hidden selection bias.

CONCLUSIONS

The programme for managing depression leads to better clinical outcomes in patients with major depression in primary care settings.

Measures of multimorbidity and morbidity burden for use in primary care and community settings: a systematic review and guide

PURPOSE

Many patients consulting in primary care have multiple conditions (multimorbidity). Aims of this review were to identify measures of multimorbidity and morbidity burden suitable for use in research in primary care and community populations, and to investigate their validity in relation to anticipated associations with patient characteristics, process measures, and health outcomes.

METHODS

Studies were identified using searches in MEDLINE and EMBASE from inception to December 2009 and bibliographies.

RESULTS

Included were 194 articles describing 17 different measures. Commonly used measures included disease counts (n = 98), Chronic Disease Score (CDS)/RxRisk (n = 17), Adjusted Clinical Groups (ACG) System (n = 25), the Charlson index (n = 38), the Cumulative Index Illness Rating Scale (CIRS; n = 10) and the Duke Severity of Illness Checklist (DUSOI; n = 6). Studies that compared measures suggest their predictive validity for the same outcome differs only slightly. Evidence is strongest for the ACG System, Charlson index, or disease counts in relation to care utilization; for the ACG System in relation to costs; for Charlson index in relation to mortality; and for disease counts or Charlson index in relation to quality of life. Simple counts of diseases or medications perform almost as well as complex measures in predicting most outcomes. Combining measures can improve validity.

CONCLUSIONS

The measures most commonly used in primary care and community settings are disease counts, Charlson index, ACG System, CIRS, CDS, and DUSOI. Different measures are most appropriate according to the outcome of interest. Choice of measure will also depend on the type of data available. More research is needed to directly compare performance of different measures.

A randomized, controlled trial of disease management modules, including telepsychiatric care, for depression in rural primary care

Background

Most depressed patients are attended at primary care. However, there are significant shortcomings in the diagnosis, management and outcomes of these patients. The aim of this study is to determine whether the implementation of a structured programme for managing depression will provide better health outcomes than usual management.

Methods/Design

Design: A cluster-randomized controlled trial involving two groups, one of which is the control group consisting of patients who are treated for depression in the usual way and the other is the intervention group consisting of patients on a structured programme for treating depression.

Setting: 20 primary care centres in the province of Tarragona (Spain)

Sample: 400 patients over 18 years of age who have experienced an episode of major depression (DSM-IV) and who need to initiate antidepressant treatment

Intervention: A multi-component programme with clinical, educational and organisational procedures that includes training for the health care provider and evidence-based clinical guidelines. It also includes primary care nurses working as care-managers who provide educational and emotional support for the patients and who are responsible for active and systematic clinical monitoring. The programme aims to improve the primary care/specialized level interface.

Measurements: The patients will be monitored by telephone interviews. The interviewer will not know which group the patient belongs to (blind trial). These interviews will be given at 0, 3, 6 and 12 months.

Main variables: Severity of the depressive symptoms, response rate and remission rate.

Analysis: Outcomes will be analyzed on an intent-to-treat basis and the unit of analysis will be the individual patient. This analysis will take into account the effect of study design on potential lack of independence between observations within the same cluster.

Discussion

The effectiveness of caring for depression in primary care can be improved by various strategies. The most effective models involve organisational changes and a greater role of nurses. However, these models are almost exclusively from the USA, and this randomized clinical trial will determine if this approach could be effective to improve the outcomes of depression in primary care in the Spanish health care system.

Trial registration

ISRCTN16384353

Psychological disorders after stroke are an important influence on functional outcomes: a prospective cohort study

BACKGROUND AND PURPOSE

Psychological disorders are recognized as an important and common problem after stroke but little is known about their longer-term effects on functional outcomes. We investigated the trajectory of psychological symptoms after stroke and studied their impact on physical functional recovery.

METHODS

The Stroke Outcomes Study was a prospective cohort study conducted in West Yorkshire, UK, from 2002 to 2006. Baseline assessments were conducted within 2 to 6 weeks of an index stroke event and follow-up at 9, 13, 26, and 52 weeks thereafter. Measures of psychological symptoms (assessed using the 28-item General Health Questionnaire) and function (modified Barthel Index) were completed at each visit. Longitudinal latent class analysis identified psychological symptom trajectories. Logistic regression modeled poor functional outcome. Multiple imputation was used as a sensitivity analysis.

RESULTS

Five hundred ninety-two (55% of eligible patients) consented to participate. Four hundred forty-four (76%) complete sets of data (5 time points) were obtained for analysis. Four distinct classes of patients emerged from the analyses based on trajectory of psychological symptoms in the first 26 weeks after stroke. There was a strong association between functional outcome and class as defined by psychological symptom trajectory, which was not explained by age, sex, or initial disability after stroke.

CONCLUSIONS

Currently, the assessment of psychological distress is concentrated in the first weeks after stroke. Our results suggest that the timing of assessment and intervention needs to be reconsidered to take into account the trajectory of psychological symptoms rather than assessment at a single time point.

[Comorbidity in the elderly: utility and validity of assessment tools]

Comorbidity is common in the elderly and contributes to the complexity of this population subgroup. This problem is a risk factor for major adverse events such as functional decline, disability, dependency, poor quality-of-life, institutionalization, hospitalization and death, but is not the most important factor. Age and risk of functional decline rather than comorbidity (understood as a compilation of diseases) are the main characteristics defining the target population attended by geriatricians. Comorbidity indexes should not be interpreted independently in the elderly, but within a context of comprehensive geriatric assessment that includes age-related preclinical dysfunctions, frailty measures, and functional, mental and psychosocial issues. The clinical management of comorbidity in the elderly requires advanced knowledge of geriatrics because the treatment of one condition may worsen or lead to the development of others and because preclinical physiological dysfunctions modulate drug response. Recommending a specific comorbidity index is difficult and depends on multiple factors, due to their psychometric characteristics, applicability in the elderly and their construct. However, the Cumulative Illness Rating Scale, in the version adapted to the elderly, could be highly suitable. Other instruments, such as the Charlson index, the Index of CoExistent Disease and the Kaplan index are also valid and reproducible.

The Stroke Outcomes Study 2 (SOS2): a prospective, analytic cohort study of depressive symptoms after stroke

BACKGROUND

Mood disorder is recognised as an important and common problem after stroke but little is known about the longer term effects of mood on functional outcomes. This protocol paper describes the Stroke Outcomes Study 2 (SOS2), a research study conducted in two large acute NHS Trusts in the North of England, which was designed to investigate the impact of early depressive symptoms on outcomes after an acute stroke.

METHODS AND DESIGN

SOS2 was a prospective cohort study that aimed to recruit patients in the first few weeks after a stroke, and to follow them up at regular intervals for one year thereafter in order to describe the trajectory of psychological symptoms and study their impact on physical functional recovery. Measures of mood and function were completed at baseline (approximately 3 weeks) and at four follow-up time-points: approximately 9, 13, 26 and 52 weeks after the index stroke.

DISCUSSION

Recruiting patients to research studies soon after an acute stroke is difficult. Mortality following stroke is approximately 30% and in the region of half the patients that survive the initial event are significantly disabled. Together these factors reduced the number of patients available to participate in SOS2 but once recruited to the study the drop-out rate was relatively low. During the recruitment period over 6000 admissions for stroke or query stroke were screened for eligibility. A cohort of 592 study participants was finally achieved.

Seniors' self-reported multimorbidity captured biopsychosocial factors not incorporated into two other data-based morbidity measures

OBJECTIVE

To explore the constructs underlying a self-report assessment of multimorbidity.

STUDY DESIGN AND SETTING

We conducted a cross-sectional survey of 352 HMO members aged 65 years or more with, at a minimum, diabetes, depression, and osteoarthritis. We assessed self-reported 'disease burden' (a severity-adjusted count of conditions) as a function of biopsychosocial factors, two data-based comorbidity indices, and demographic variables.

RESULTS

In multivariate regression, age, 'compound effects of conditions' (treatments and symptoms interfering with each other), self-efficacy, financial constraints, and physical functioning were significantly (p<or=0.05) associated with disease burden. An ICD-9-based morbidity index did not significantly contribute to disease burden, and a pharmacy-data-based morbidity index was minimally significant.

CONCLUSION

This measure of self-reported disease burden represents an amalgamation of functional capabilities, social considerations, and medical conditions that are not captured by two administrative data-based measures of morbidity. This suggests that (a) self-reported descriptions of multimorbidity incorporate biopsychosocial constructs that reflect the perceived burden of multimorbidity, (b) a simple count of diagnoses should be supplemented by an assessment of activity limitations imposed by these conditions, and (c) choice of the morbidity measurement instrument should be based on the outcome of interest rather than on the most convenient method of measurement.

Clinical trial of wellness training: health promotion for severely mentally ill adults

This randomized controlled trial examined benefits of adding active health promotion to basic primary care (BPC) services for SMI adults. It compared BPC with BPC plus wellness training (WT), a 12 months intervention promoting individual skills in self-management. Three hundred nine participants enrolled during short-term residential treatment completed baseline assessments and were assigned to treatment groups, before discharge. Outcomes of perceived health status (SF-36), global assessment of function, and ratings of self-efficacy were assessed at follow-up interviews at 6, 12, and 18 months. The intent-to-treat analysis employed multilevel regression to examine differences by group on outcomes across time, controlling for health related covariates. The WT group showed significantly better outcomes on the SF-36 physical functioning and general health scales. Findings affirm ability of SMI adults to benefit from active health promotion.

Socio-demographic and clinical features associated with demoralization in medically ill in-patients

INTRODUCTION

In the present study we tried to identify which socio-demographic and clinical characteristics are associated with demoralization in medically ill in-patients.

METHOD

Patients (n. 296), consecutively admitted to medical wards in a 120 day period, were evaluated with the Demoralization Scale of the Psychiatric Epidemiological Research Interview (PERI-D) to assess demoralization , with the Mini International Neuropsychiatric Interview (MINI) to assess mental disorders (DSM-IV), with the Brief Disability Questionnaire for the evaluation of the functional disability, with the Duke Severity of Illness to assess severity of the medical illness. Moreover, the family support and threatening life events were also evaluated.

RESULTS

A significant effect in increasing the demoralization score was observed for presence of Major Depression or Adjustment Disorder, poor family support, severity of functional disability, number of threatening life events in the past year and female gender.

CONCLUSION

Major Depression needs to be recognized in demoralized medically ill in-patients, because it is one of the most important conditions associated with demoralization, which successfully responds to adequate treatment.

A three-page Standard Protocol to Evaluate Rheumatoid Arthritis (SPERA) for efficient capture of essential data from patients and health professionals in standard clinical care and clinical research

A Standard Protocol to Evaluate Rheumatoid Arthritis (SPERA) has been developed to collect essential data from patients and health professionals to assess, monitor, and document change in standard clinical care and clinical research. Three one-page forms are completed by a health professional assessor, which can be completed at baseline for use at all future visits: (1) clinical features of rheumatoid arthritis (RA); (2) medications taken; and (3) a 42-joint count. The patient also completes a patient questionnaire, and a radiographic scoring sheet can also be included for a comprehensive database. The 15-20 minutes involved in completing the SPERA generally add efficiency to subsequent visits in standard clinical care. Collection of additional information for clinical care and/or clinical research is also possible. The SPERA is presented not as an optimal format but rather as an example of a possible approach to develop a common format for core clinical data to be collected in standard clinical care.

Depression and physical comorbidity in primary care

OBJECTIVE

To analyse how clinical characteristics in depressed patients, as well as the management of their depression, are related to the presence of significant physical comorbidity.

METHODS

This is a two-phase cross-sectional study that took place in 10 primary care centres in Tarragona (Spain). A total of 906 consecutive patients were screened for depression with a self-rating questionnaire and 306 were subject to a structured interview that contained the diagnoses of major depression and dysthymia (DSM-IV), and the severity of the physical comorbidity (Duke Severity of Illness Scale: DUSOI). The association of several clinical variables with the presence of physical comorbidity was evaluated.

RESULTS

The comorbidity was of moderate to extreme severity (DUSOI >50) in 31.7% of cases. The patients with comorbidity visited the physician more often. There were no differences in the consumption of antidepressants, reason for the consultation (psychological/somatic), or the probability of being detected as depressed. Neither were there any differences in the severity or disability between both groups.

CONCLUSION

Physical comorbidity is frequent in primary care depressed patients. In general, the characteristics of depression and the handling by the doctor are similar in patients with and without comorbidity.