Multimorbidity in people with type 2 diabetes in the Basque Country (Spain): Prevalence, comorbidity clusters and comparison with other chronic patients

Prevalence of comorbidities and its associated factors among type-2 diabetes patients: a hospital-based study in Jashore District, Bangladesh

OBJECTIVE

This study aimed to estimate the prevalence of comorbidity and its associated factors among Bangladeshi type-2 diabetes (T2D) patients.

DESIGN

A hospital-based cross-sectional study.

SETTING

This study was conducted in two specialised diabetic centres residing in the Jashore District of Bangladesh. A systematic random sampling procedure was applied to identify the T2D patients through a face-to-face interview.

PARTICIPANTS

A total of 1036 patients with T2D were included in this study. A structured questionnaire was administered to collect data on demographic, lifestyle, medical and healthcare access-related data through face-to-face and medical record reviews.

OUTCOME MEASURES AND ANALYSES

The main outcome variable for this study was comorbidities. The prevalence of comorbidity was measured using descriptive statistics. A logistic regression model was performed to explore the factors associated with comorbidity among Bangladeshi T2D patients.

RESULTS

The overall prevalence of comorbidity was 41.4% and the most prevalent conditions were hypertension (50.4%), retinopathy (49.6%), obesity (28.7%) and oral problem (26.2). In the regression model, the odds of comorbidities increased with gender (male: OR: 1.27, 95% CI 0.62 to 1.87), age (50-64 years: OR: 2.14, 95% CI 1.32 to 2.93; and above 65 years: OR: 2.96, 95% CI 1.83 to 4.16), occupation (unemployment: OR: 3.32, 95% CI 0.92 to 6.02 and non-manual worker: OR: 2.31, 95% CI 0.91 to 5.82), duration of diabetes (above 15 years: OR: 3.28, 95% CI 1.44 to 5.37), body mass index (obese: OR: 2.62, 95% CI 1.24 to 4.26) of patients. We also found that individuals with recommended moderate to vigorous physical activity levels (OR: 0.41, 95% CI 1.44 to 5.37) had the lowest odds of having comorbidity. Meanwhile, respondents with limited self-care practice, unaffordable medicine and financial problems had 1.82 times, 1.94 times and 1.86 times higher odds of developing comorbidities.

CONCLUSION

The findings could be useful in designing and implementing effective intervention strategies and programmes for people with T2D to reduce the burden of comorbidity.

Multimorbidity Patterns among People with Type 2 Diabetes Mellitus: Findings from Lima, Peru

Background: Type 2 diabetes (T2DM) is a chronic condition with a high disease burden worldwide, and individuals with T2DM often have other morbidities. Understanding the local multimorbidity profile of patients with T2DM will inform precision medicine and public health, so that tailored interventions can be offered according to the different profiles. Methods: An analysis was conducted of electronic health records (2016–2021) in one hospital in Lima, Peru. Based on ICD-10 codes and the available measurements (e.g., body mass index), we identified all T2DM cases and quantified the frequency of the most common comorbidities (those in ≥1% of the sample). We also conducted k-means analysis that was informed by the most frequent comorbidities, to identify clusters of patients with T2DM and other chronic conditions. Results: There were 9582 individual records with T2DM (mean age 58.6 years, 61.5% women). The most frequent chronic conditions were obesity (29.4%), hypertension (18.8%), dyslipidemia (11.3%), hypothyroidism (6.4%), and arthropathy (3.6%); and 51.6% had multimorbidity: 32.8% had only one, 14.1% had two, and 4.7% had three or more extra chronic conditions in addition to T2DM. The cluster analysis revealed four unique groups: T2DM with no other chronic disease, T2DM with obesity only, T2DM with hypertension but without obesity, and T2DM with all other chronic conditions. Conclusions: More than one in two people with T2DM had multimorbidity. Obesity, hypertension, and dyslipidemia were the most common chronic conditions that were associated with T2DM. Four clusters of chronic morbidities were found, signaling mutually exclusive profiles of patients with T2DM according to their multimorbidity profile.

The Changing Nature of Mortality and Morbidity in Patients with Diabetes

The number of adults living with diabetes has increased substantially globally over the past 40 years, driven by a combination of increased age-standardized prevalence, population growth, aging, and increases in obesity prevalence. Patients with diabetes in high-income countries are living longer, with large declines in vascular disease mortality rates. This appears to be resulting in a diversification of cause of death, complications, and comorbidities that those with diabetes live with. This has large implications for prevention and management approaches, which should be reviewed to update the breadth of conditions that patients with diabetes are at excess risk of throughout their life. These trends have not yet been seen in low- and middle-income countries, where evidence is also more scarce.

Characterizing Multimorbidity from Type 2 Diabetes: Insights from Clustering Approaches

Patients with type 2 diabetes mellitus (T2DM) often live with and develop multiple co-occurring conditions, namely multimorbidity, with diffuse impacts on clinical care and patient quality of life. However, literature characterizing T2DM-related multimorbidity patterns is limited. This review summarizes the findings from the emerging literature characterizing and quantifying the association of T2DM with multimorbidity clusters. The authors' findings reveal 3 dominant cluster types appearing in patients with T2DM-related multimorbidity, such as cardiometabolic precursor conditions, vascular conditions, and mental health conditions. The authors recommend that holistic patient care centers around early detection of other comorbidities and consideration of wider risk factors.

Occurrence of comorbidities in newly diagnosed type 2 diabetes patients and their impact after 11 years' follow-up

The burden of type 2 diabetes is growing, not only through increased incidence, but also through its comorbidities. Concordant comorbidities for type 2 diabetes, such as cardiovascular diseases, are considered expected outcomes of the disease or disease complications, while discordant comorbidities are not considered to be directly related to type 2 diabetes and are less extensively addressed under diabetes management. Here we show that the combination of concordant and discordant comorbidities appears frequently in persons with diabetes (75%). Persons with combined comorbidities visited family physicians more than persons with discordant, concordant or no comorbidity (17.3 ± 10.2, 11.6 ± 6.5, 8.7 ± 6.8, 6.3 ± 6.6 visits/person/year respectively, p < 0.0001). The risk of death during the study period was highest in persons with combined comorbidities and discordant only comorbidities (HR = 33.4; 95% CI 12.5–89.2 and HR = 33.5; 95% CI 11.7–95.8), emphasizing the contribution of discordant comorbidities to the outcome. Our study is unique as a long-term follow-up of an 11-year cohort of 9725 persons with new-onset type 2 diabetes. The findings highlight the contribution of discordant comorbidity to the burden of the disease. The high prevalence of the combination of both concordant and discordant comorbidities, and their appearance before the onset of type 2 diabetes, indicates a continuum of morbidity.

Risk of Typical Diabetes-Associated Complications in Different Clusters of Diabetic Patients: Analysis of Nine Risk Factors

Objectives: Diabetic patients are often diagnosed with several comorbidities. The aim of the present study was to investigate the relationship between different combinations of risk factors and complications in diabetic patients. Research design and methods: We used a longitudinal, population-wide dataset of patients with hospital diagnoses and identified all patients (n = 195,575) receiving a diagnosis of diabetes in the observation period from 2003–2014. We defined nine ICD-10-codes as risk factors and 16 ICD-10 codes as complications. Using a computational algorithm, cohort patients were assigned to clusters based on the risk factors they were diagnosed with. The clusters were defined so that the patients assigned to them developed similar complications. Complication risk was quantified in terms of relative risk (RR) compared with healthy control patients. Results: We identified five clusters associated with an increased risk of complications. A combined diagnosis of arterial hypertension (aHTN) and dyslipidemia was shared by all clusters and expressed a baseline of increased risk. Additional diagnosis of (1) smoking, (2) depression, (3) liver disease, or (4) obesity made up the other four clusters and further increased the risk of complications. Cluster 9 (aHTN, dyslipidemia and depression) represented diabetic patients at high risk of angina pectoris “AP” (RR: 7.35, CI: 6.74–8.01), kidney disease (RR: 3.18, CI: 3.04–3.32), polyneuropathy (RR: 4.80, CI: 4.23–5.45), and stroke (RR: 4.32, CI: 3.95–4.71), whereas cluster 10 (aHTN, dyslipidemia and smoking) identified patients with the highest risk of AP (RR: 10.10, CI: 9.28–10.98), atherosclerosis (RR: 4.07, CI: 3.84–4.31), and loss of extremities (RR: 4.21, CI: 1.5–11.84) compared to the controls. Conclusions: A comorbidity of aHTN and dyslipidemia was shown to be associated with diabetic complications across all risk-clusters. This effect was amplified by a combination with either depression, smoking, obesity, or non-specific liver disease.

Prevalence of comorbidities and their associated factors in patients with type 2 diabetes at a tertiary care department in Ningbo, China: a cross-sectional study

OBJECTIVES

To determine the prevalence of comorbidities in patients with type 2 diabetes mellitus (T2DM) and identify the factors independently associated with comorbidities in a tertiary care department in Ningbo, China.

DESIGN

A computerised medical records database was used to conduct a cross-sectional study.

SETTING

The study was conducted in a tertiary care department in Ningbo, China.

PARTICIPANTS

The study was conducted on adult patients with T2DM, and it included 8 years of data, from 1 January 2012 to 31 December 2019.

THE PRIMARY OUTCOME MEASURE

Comorbidity was defined as the coexistence of at least one other chronic condition, that is, either a physical non-communicable disease (duration ≥3 months), a mental health condition (duration ≥3 months) or an infectious disease (duration ≥3 months).

RESULTS

In total, 4777 patients with T2DM satisfied the eligibility criteria. Over 8 years, the prevalence of comorbidities was 93.7%. The odds of comorbidities increased with the age of patients (18 to 39 years: 1; 40 to 59 years: OR 2.80, 95% CI 1.98 to 3.96; 60 to 69 years: OR 4.43, 95% CI 3.04 to 6.44; and ≥70 years: OR 10.97, 95% CI 7.17 to 16.77). The odds were lower in female patients (OR 0.66, 95% CI 0.51 to 0.84), patients residing in rural areas (OR 0.75, 95% CI 0.59 to 0.95) and patients without health insurance (OR 0.62, 95% CI 0.46 to 0.83). The odds were higher in single/divorced/widowed patients compared with those in married patients (OR 1.95, 95% CI 1.21 to 3.12).

CONCLUSIONS

A large percentage of patients with T2DM in the tertiary care department in Ningbo, China, had comorbidities, and the factors associated with comorbidities were identified. The findings could be used in developing, evaluating and implementing interventions aimed at improving outcomes in patients with T2DM with comorbidities.

Association between mental health comorbidity and health outcomes in type 2 diabetes mellitus patients

Type 2 diabetes mellitus (T2D) is often accompanied by chronic diseases, including mental health problems. We aimed at studying mental health comorbidity prevalence in T2D patients and its association with T2D outcomes through a retrospective, observational study of individuals of the EpiChron Cohort (Aragón, Spain) with prevalent T2D in 2011 (n = 63,365). Participants were categorized as having or not mental health comorbidity (i.e., depression, anxiety, schizophrenia, and/or substance use disorder). We performed logistic regression models, controlled for age, sex and comorbidities, to analyse the likelihood of 4-year mortality, 1-year all-cause hospitalization, T2D-hospitalization, and emergency room visit. Mental health comorbidity was observed in 19% of patients. Depression was the most frequent condition, especially in women (20.7% vs. 7.57%). Mortality risk was higher in patients with mental health comorbidity (odds ratio 1.24; 95% confidence interval 1.16-1.31), especially in those with substance use disorder (2.18; 1.84-2.57) and schizophrenia (1.82; 1.50-2.21). Mental health comorbidity also increased the likelihood of all-cause hospitalization (1.16; 1.10-1.23), T2D-hospitalization (1.51; 1.18-1.93) and emergency room visit (1.26; 1.21-1.32). These results suggest that T2D healthcare management should include specific strategies for the early detection and treatment of mental health problems to reduce its impact on health outcomes.

Additive Manufacturing Technologies for Drug Delivery Applications

Patient to patient variability is one of the issues when administering medications to individuals with different health conditions, pharmacokinetic, age, fitness, gender, and race. This requires introducing smart and personalised drug delivery systems with controlled release profile manufactured using novel approaches. Additive manufacturing (AM) provides opportunities such as full customisation, design freedom, and on-site manufacturing, and materials recycling. As a result, the academic and industrial demand for additive manufacturing for drug delivery has been continuously increasing and showing impressive results for a wide range of products. This paper provides an extensive overview of AM technologies and their applications for drug delivery. The review discusses AM technologies including their working principles, processed materials, as well as current progress in drug delivery to produce personalized dosages for every patient with controlled release profile. AM potentials, industrial scale, and challenges are investigated with regards to practice and industrial applications. The paper covers novel possibilities of AM technologies and their pharmaceuticals applications, which indicate a promising healthcare future.

MorbiNet: multimorbidity networks in adult general population. Analysis of type 2 diabetes mellitus comorbidity

Multimorbidity has great impact on health care. We constructed multimorbidity networks in the general population, extracted subnets focused on common chronic conditions and analysed type 2 diabetes mellitus (T2DM) comorbidity network. We used electronic records from 3,135,948 adult people in Catalonia, Spain (539,909 with T2DM), with at least 2 coexistent chronic conditions within the study period (2006-2017). We constructed networks from odds-ratio estimates adjusted by age and sex and considered connections with OR > 1.2 and p-value < 1e-5. Directed networks and trajectories were derived from temporal associations. Interactive networks are freely available in a website with the option to customize characteristics and subnets. The more connected conditions in T2DM undirected network were: complicated hypertension and atherosclerosis/peripheral vascular disease (degree: 32), cholecystitis/cholelithiasis, retinopathy and peripheral neuritis/neuropathy (degree: 31). T2DM has moderate number of connections and centrality but is associated with conditions with high scores in the multimorbidity network (neuropathy, anaemia and digestive diseases), and severe conditions with poor prognosis. The strongest associations from T2DM directed networks were to retinopathy (OR: 23.8), glomerulonephritis/nephrosis (OR: 3.4), peripheral neuritis/neuropathy (OR: 2.7) and pancreas cancer (OR: 2.4). Temporal associations showed the relevance of retinopathy in the progression to complicated hypertension, cerebrovascular disease, ischemic heart disease and organ failure.

Patterns of multimorbid health conditions: a systematic review of analytical methods and comparison analysis

Background

The latest review of studies on multimorbidity patterns showed high heterogeneity in the methodology for identifying groups of multimorbid conditions. However, it is unclear how analytical methods used influence the identified multimorbidity patterns.

Methods

We undertook a systematic review of analytical methods used to identify multimorbidity patterns in PubMed and EMBASE from their inception to January 2017. We conducted a comparison analysis to assess the effect the analytical methods had on the multimorbidity patterns identified, using the Australian National Health Survey (NHS) 2007-08 data.

Results

We identified 13 194 studies and excluded 13 091 based on titles/abstracts. From the full-text reviews of the 103 remaining publications, we identified 41 studies that used five different analytical methods to identify multimorbid conditions in the studies. Thirty-seven studies (90%) adopted either the factor-analysis or hierarchical-clustering methods, but heterogeneity arises for the use of different proximity measures within each method to form clusters. Our comparison analysis showed the variation in identified groups of multimorbid conditions when applying the methods to the same NHS data. We extracted main similarities among the groupings obtained by the five methods: (i) cardiovascular and metabolic diseases, (ii) mental health problems and (iii) allergic diseases.

Conclusion

We showed the extent of effects for heterogeneous analytical methods on identification of multimorbidity patterns. However, more work is needed to guide investigators for choosing the best analytical method to improve the validity and generalizability of findings. Investigators should also attempt to compare results obtained by various methods for a consensus grouping of multimorbid conditions.

Exploring Different Strategies of Assessing the Economic Impact of Multiple Diabetes-Associated Complications and Their Interactions: A Large Claims-Based Study in Germany

BACKGROUND

In the context of an aging population with increasing diabetes prevalence, people are living longer with diabetes, which leads to increased multimorbidity and economic burden.

OBJECTIVE

The primary aim was to explore different strategies that address the economic impact of multiple type 2 diabetes-related complications and their interactions.

METHODS

We used a generalized estimating equations approach based on nationwide statutory health insurance data from 316,220 patients with type 2 diabetes (baseline year 2012, 3 years of follow-up). We estimated annual total costs (in 2015 euros) for type 2 diabetes-related complications and, in addition, explored different strategies to assess diabetes-related multimorbidity: number of prevalent complications, co-occurrence of micro- and macrovascular complications, disease-disease interactions of prevalent complications, and interactions between prevalent/incident complications.

RESULTS

The increased number of complications was significantly associated with higher total costs. Further assessment of interactions showed that macrovascular complications (e.g., chronic heart failure) and high-cost complications (e.g., end-stage renal disease, amputation) led to significant positive effects of interactions on costs, whereas early microvascular complications (e.g., retinopathy) caused negative interactions. The chronology of the onset of these complications turned out to have an additional impact on the interactions and their effect on total costs.

CONCLUSIONS

Health economic diabetes models and evaluations of interventions in patients with diabetes-related complications should pay more attention to the economic effect of specific disease interactions. Politically, our findings support the development of more integrated diabetes care programs that take better account of multimorbidity. Further observational studies are needed to elucidate the shared pathogenic mechanisms of diabetes complications.

The role of concordant and discordant comorbidities on performance of self-care behaviors in adults with type 2 diabetes: a systematic review

Background: Most patients with Type 2 diabetes (T2D) have high number of comorbid chronic conditions that can affect their self-care abilities. Guidelines for diabetes self-care behaviors are disease specific with little attention given to managing T2D with other comorbidities. Identifying comorbidities that either improve or potentially diminish the individual's capacity to perform effective self-care behaviors is essential to enhance clinical outcomes. One such framework conceptualizes comorbidities as concordant or discordant with diabetes pathophysiological pathways and care goals. Objective: The purpose of this systematic review was to examine the role of diabetes-concordant and discordant chronic conditions on the performance of self-care behaviors in adults with T2D. Methods: A comprehensive literature search was undertaken to identify published English language articles through the following five electronic databases: PubMed, CINAHL, PsycINFO, ISI Web of Science, and EMBASE. Quantitative studies published from March 2006 to April 2018 were included. Quality of evidence was evaluated using the Joanna Briggs Institutes Critical Appraisal Tools (JBI-CAT) and rated using Quality Assessment Tool for Quantitative Studies (QATQS). Results: The initial database search identified 1,136 articles but only 33 studies that met the inclusion criteria were included. The most common concordant comorbidity was hypertension while depression was the most common discordant condition. Adherence to medications was the most frequent diabetes self-care behavior reported and tended to be higher among concordant comorbidities. The findings showed mixed results concerning the effect of some concordant comorbidities such as hypertension, hyperlipidemia, retinopathy, and heart failure on diabetes self-care behaviors. But, there is agreement across studies that diabetes-discordant comorbidities have a more detrimental effect on self-care behaviors. Conclusions: Concordant comorbidities may improve diabetes self-care, but the evidence is inconclusive. Future research using well designed studies are needed to examine the complex relationship between diabetes self-care and comorbidities.

Impact of Hypoglycemia on Brain Metabolism During Diabetes

Diabetes is a metabolic disease afflicting millions of people worldwide. A substantial fraction of world's total healthcare expenditure is spent on treating diabetes. Hypoglycemia is a serious consequence of anti-diabetic drug therapy, because it induces metabolic alterations in the brain. Metabolic alterations are one of the central mechanisms mediating hypoglycemia-related functional changes in the brain. Acute, chronic, and/or recurrent hypoglycemia modulate multiple metabolic pathways, and exposure to hypoglycemia increases consumption of alternate respiratory substrates such as ketone bodies, glycogen, and monocarboxylates in the brain. The aim of this review is to discuss hypoglycemia-induced metabolic alterations in the brain in glucose counterregulation, uptake, utilization and metabolism, cellular respiration, amino acid and lipid metabolism, and the significance of other sources of energy. The present review summarizes information on hypoglycemia-induced metabolic changes in the brain of diabetic and non-diabetic subjects and the manner in which they may affect brain function.

Treatment variation related to comorbidity and complications in type 2 diabetes: A real world analysis

A complex comorbidity status may cause treatment variance interfering with type 2 diabetes (T2D) guideline-confirm therapy and influence the occurrence of complications but evidence on its relationships and alternative treatments are lacking. This study aimed to identify treatment variance and common T2D drug treatment related to comorbid status and the association with comorbidity and complications.Based on Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) databases, we conducted a retrospective, observational exploratory study including 7123 T2D patients without microvascular-, macrovascular complication. We explored patterns of comorbid status and drug treatment and its relation to the development of complications within 4-year period. Analysis was performed by two-step cluster analysis and nonlinear canonical correlation analysis.64.9% had at least one other chronic disease and 61.7% of T2D patients were treated with >1 glucose lowering drugs. 15.8% developed microvascular complications and 6.5% had ischemic heart disease or cerebrovascular complications. 82.2% of the treatment patterns were identified among T2D patients with 1 or no comorbidity while 14.4% was identified in patients with ≥2 comorbidities. Combination treatment such as, sulfonylurea or dipeptidyl peptidase-4 inhibitors combined with metformin were observed. Occurrence of microvascular- or/and macrovascular complication and its relation to comorbidity and treatment pattern was not identified.In conclusion, as number of comorbidity increased with both type of comorbidity (diabetes related-, unrelated) present, common treatment patterns were less or not identified. More treatment variance was observed in patient's groups that had developed complications.

Multimorbidity care model: Recommendations from the consensus meeting of the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS)

Patients with multimorbidity have complex health needs but, due to the current traditional disease-oriented approach, they face a highly fragmented form of care that leads to inefficient, ineffective, and possibly harmful clinical interventions. There is limited evidence on available integrated and multidimensional care pathways for multimorbid patients. An expert consensus meeting was held to develop a framework for care of multimorbid patients that can be applied across Europe, within a project funded by the European Union; the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS). The experts included a diverse group representing care providers and patients, and included general practitioners, family medicine physicians, neurologists, geriatricians, internists, cardiologists, endocrinologists, diabetologists, epidemiologists, psychologists, and representatives from patient organizations. Sixteen components across five domains were identified (Delivery of Care; Decision Support; Self Management Support; Information Systems and Technology; and Social and Community Resources). The description and aim of each component are described in these guidelines, along with a summary of key characteristics and relevance to multimorbid patients. Due to the lack of evidence-based recommendations specific to multimorbid patients, this care model needs to be assessed and validated in different European settings to examine specifically how multimorbid patients will benefit from this care model, and whether certain components have more importance than others.

Diabetic aggravation of stroke and animal models

Cerebral ischemia in diabetics results in severe brain damage. Different animal models of cerebral ischemia have been used to study the aggravation of ischemic brain damage in the diabetic condition. Since different disease conditions such as diabetes differently affect outcome following cerebral ischemia, the Stroke Therapy Academic Industry Roundtable (STAIR) guidelines recommends use of diseased animals for evaluating neuroprotective therapies targeted to reduce cerebral ischemic damage. The goal of this review is to discuss the technicalities and pros/cons of various animal models of cerebral ischemia currently being employed to study diabetes-related ischemic brain damage. The rational use of such animal systems in studying the disease condition may better help evaluate novel therapeutic approaches for diabetes related exacerbation of ischemic brain damage.

Cost-effectiveness of dipeptidyl peptidase-4 inhibitor monotherapy in elderly type 2 diabetes patients in Thailand

BACKGROUND

The management of type 2 diabetes mellitus (T2DM) in elderly population poses many challenges. Dipeptidyl peptidase-4 (DPP-4) inhibitors show particular promise due to excellent tolerability profiles, low risk of hypoglycemia, and little effect on body weight. This study evaluated, from the health care system's perspective, the long-term cost-effectiveness of DPP-4 inhibitor monotherapy vs metformin and sulfonylurea (SFU) monotherapy in Thai elderly T2DM patients.

METHODS

The clinical efficacy was estimated from a systematic review and meta-analysis. Baseline cohort characteristics and cost parameters were obtained from published studies and hospital databases in Thailand. A validated IMS CORE Diabetes Model version 8.5 was used to project clinical and economic outcomes over a lifetime horizon using a 3% annual discount rate. Costs were expressed in 2014 Thai Baht (THB) (US dollar value). Incremental cost-effectiveness ratios were calculated. Base-case assumptions were assessed through several sensitivity analyses.

RESULTS

For treating elderly T2DM patients, DPP-4 inhibitors were more expensive and less effective, ie, a dominated strategy, than the metformin monotherapy. Compared with SFU, treatment with DPP-4 inhibitors gained 0.031 more quality-adjusted life years (QALYs) at a total cost incurred over THB113,701 or US$3,449.67, resulting in an incremental cost-effectiveness ratio of THB3.63 million or US$110,133.50 per QALY. At the acceptable Thai ceiling threshold of THB160,000/QALY (US$4,854.37/QALY), DPP-4 inhibitors were not a cost-effective treatment.

CONCLUSION

DPP-4 inhibitor monotherapy is not a cost-effective treatment for elderly T2DM patients compared with metformin monotherapy and SFU monotherapy, given current resource constraints in Thailand.

Spatial Analysis of Case-Mix and Dialysis Modality Associations

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BACKGROUND

Health-care systems must attempt to provide appropriate, high-quality, and economically sustainable care that meets the needs and choices of patients with end-stage renal disease (ESRD). France offers 9 different modalities of dialysis, each characterized by dialysis technique, the extent of professional assistance, and the treatment site. The aim of this study was 1) to describe the various dialysis modalities in France and the patient characteristics associated with each of them, and 2) to analyze their regional patterns to identify possible unexpected associations between case-mixes and dialysis modalities. ♦

METHODS

The clinical characteristics of the 37,421 adult patients treated by dialysis were described according to their treatment modality. Agglomerative hierarchical cluster analysis was used to aggregate the regions into clusters according to their use of these modalities and the characteristics of their patients. ♦

RESULT

The gradient of patient characteristics was similar from home hemodialyis (HD) to in-center HD and from non-assisted automated peritoneal dialysis (APD) to assisted continuous ambulatory peritoneal dialysis (CAPD). Analyzing their spatial distribution, we found differences in the patient case-mix on dialysis across regions but also differences in the health-care provided for them. The classification of the regions into 6 different clusters allowed us to detect some unexpected associations between case-mixes and treatment modalities. ♦

CONCLUSIONS

The 9 modalities of treatment available make it theoretically possible to adapt treatment to patients' clinical characteristics and abilities. However, although we found an overall appropriate association of dialysis modalities to the case-mix, major inter-region heterogeneity and the low rate of peritoneal dialysis (PD) and home HD suggest that factors besides patients' clinical conditions impact the choice of dialysis modality. The French organization should now be evaluated in terms of patients' quality of life, satisfaction, survival, and global efficiency.

Time to face the challenge of multimorbidity. A European perspective from the joint action on chronic diseases and promoting healthy ageing across the life cycle (JA-CHRODIS)

Research on multimorbidity has rapidly increased in the last decade, but evidence on the effectiveness of interventions to improve outcomes in patients with multimorbidity is limited. The European Commission is co-funding a large collaborative project named Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS) in the context of the 2nd EU Health Programme 2008-2013. The present manuscript summarizes first results of the JA-CHRODIS, focuses on the identification of a population with multimorbidity who has a high or very high care demand. Identification of characteristics of multimorbid patients associated with a high rate of resource consumption and negative health outcomes is necessary to define a target population who can benefit from interventions. Indeed, multimorbidity alone cannot explain the complexity of care needs and further, stratification of the general population based on care needs is necessary for allocating resources and developing personalized, cost-efficient, and patient-centered care plans. Based on analyses of large databases from European countries a profile of the most care-demanding patients with multimorbidity is defined. Several factors associated with adverse health outcomes and resource consumption among patients with multimorbidity were identified in these analyses, including disease patterns, physical function, mental health, and socioeconomic status. These results underline that a global assessment is needed to identify patients with multimorbidity who are at risk of negative health outcomes and that a comprehensive approach, targeting not only diseases, but also social, cognitive, and functional problems should be adopted for these patients.