Effect of lifestyle intervention for people with diabetes or prediabetes in real-world primary care: propensity score analysis

<p>Abstract</p> <p>Background</p> <p>Many lifestyle interventions for patients with prediabetes or type 2 diabetes mellitus (T2DM) have been investigated in randomised clinical trial settings. However, the translation of these programmes into primary care seems challenging and the prevalence of T2DM is increasing. Therefore, there is an urgent need for lifestyle programmes, developed and shown to be effective in real-world primary care. We evaluated a lifestyle programme, commissioned by the Dutch government, for patients with prediabetes or type 2 diabetes in primary care.</p> <p>Methods</p> <p>We performed a retrospective comparative medical records analysis using propensity score matching. Patients with prediabetes or T2DM were selected from ten primary healthcare centres. Patients who received the lifestyle intervention (n = 186) were compared with a matched group of patients who received usual care (n = 2632). Data were extracted from the electronic primary care records. Propensity score matching was used to control for confounding by indication. Outcome measures were exercise level, BMI, HbA1c, fasting glucose, systolic and diastolic blood pressure, total cholesterol, HDL and LDL cholesterol and triglycerides and the follow-up period was one year.</p> <p>Results</p> <p>There was no significant difference at follow-up in any outcome measure between either group. The reduction at one year follow-up of HbA1c and fasting glucose was positive in the intervention group compared with controls, although not statistically significant (-0.12%, <it>P </it>= 0.07 and -0.17 mmol/l, <it>P </it>= 0.08 respectively).</p> <p>Conclusions</p> <p>The effects of the lifestyle programme in real-world primary care for patients with prediabetes or T2DM were small and not statistically significant. The attention of governments for lifestyle interventions is important, but from the available literature and the results of this study, it must be concluded that improving lifestyle in real-world primary care is still challenging.</p

The SMILE study: a study of medical information and lifestyles in Eindhoven, the rationale and contents of a large prospective dynamic cohort study

<p>Abstract</p> <p>Background</p> <p>Health problems, health behavior, and the consequences of bad health are often intertwined. There is a growing need among physicians, researchers and policy makers to obtain a comprehensive insight into the mutual influences of different health related, institutional and environmental concepts and their collective developmental processes over time.</p> <p>Methods/Design</p> <p>SMILE is a large prospective cohort study, focusing on a broad range of aspects of disease, health and lifestyles of people living in Eindhoven, the Netherlands. This study is unique in its kind, because two data collection strategies are combined: first data on morbidity, mortality, medication prescriptions, and use of care facilities are continuously registered using electronic medical records in nine primary health care centers. Data are extracted regularly on an anonymous basis. Secondly, information about lifestyles and the determinants of (ill) health, sociodemographic, psychological and sociological characteristics and consequences of chronic disease are gathered on a regular basis by means of extensive patient questionnaires. The target population consisted of over 30,000 patients aged 12 years and older enrolled in the participating primary health care centers.</p> <p>Discussion</p> <p>Despite our relatively low response rates, we trust that, because of the longitudinal character of the study and the high absolute number of participants, our database contains a valuable set of information.</p> <p>SMILE is a longitudinal cohort with a long follow-up period (15 years). The long follow-up and the unique combination of the two data collection strategies will enable us to disentangle causal relationships. Furthermore, patient-reported characteristics can be related to self-reported health, as well as to more validated physician registered morbidity. Finally, this population can be used as a sampling frame for intervention studies. Sampling can either be based on the presence of certain diseases, or on specific lifestyles or other patient characteristics.</p

Spuriously precise results from meta-analysis. Is better statistical correction or a more critical methodological assessment warranted?

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Patients with psychological ICPC codes in primary care; a case-control study investigating the decade before presenting with problems

<p><b>Background:</b> Recognizing patients with psychological problems can be difficult for general practitioners (GPs). Use of information collected in electronic medical records (EMR) could facilitate recognition.</p> <p><b>Objectives:</b> To assess relevant EMR parameters in the decade before patients present with psychological problems.</p> <p><b>Methods:</b> Exploratory case-control study assessing EMR parameters of 58 228 patients recorded between 2013 and 2015 by 54 GPs. We compared EMR parameters recorded before 2014 of patients who presented with psychological problems in 2014 with those who did not.</p> <p><b>Results:</b> In 2014, 2406 patients presented with psychological problems. Logistic regression analyses indicated that having registrations of the following statistically significant parameters increased the chances of presenting with psychological problems in 2014: prior administration of a depression severity questionnaire (odds ratio (OR): 3.3); fatigue/sleeping (OR: 1.6), neurological (OR: 1.5), rheumatic (OR: 1.5) and substance abuse problems (OR: 1.5); prescriptions of opioids (OR: 1.3), antimigraine preparations (OR: 1.5), antipsychotics (OR: 1.7), anxiolytics (OR: 1.4), hypnotics and sedatives (OR: 1.4), antidepressants (OR: 1.7), and antidementia drugs (OR: 2.1); treatment with minimal interventions (OR: 2.2) and physical exercise (OR: 3.3), referrals to psychology (OR: 1.5), psychiatry (OR: 1.6), and psychosocial care (OR: 2.1); double consultations (OR: 1.2), telephone consultations (OR: 1.1), and home visits (OR: 1.1).</p> <p><b>Conclusion:</b> This study demonstrates that possible indications of psychological problems can be identified in EMR. Many EMR parameters of patients presenting with psychological problems were different compared with patients who did not.</p

Phenotypic Variation in Patients with Chronic Obstructive Pulmonary Disease in Primary Care

Introduction. Despite the high number of inactive patients with COPD, not all inactive patients are referred to physical therapy, unlike recommendations of general practitioner (GP) guidelines. It is likely that GPs take other factors into account, determining a subpopulation that is treated by a physical therapist (PT). The aim of this study is to explore the phenotypic differences between inactive patients treated in GP practice and inactive patients treated in GP practice combined with PT. Additionally this study provides an overview of the phenotype of patients with COPD in PT practice. Methods. In a cross-sectional study, COPD patient characteristics were extracted from questionnaires. Differences regarding perceived health status, degree of airway obstruction, exacerbation frequency, and comorbidity were studied in a subgroup of 290 inactive patients and in all 438 patients. Results. Patients treated in GP practice combined with PT reported higher degree of airway obstruction, more exacerbations, more vascular comorbidity, and lower health status compared to patients who were not referred to and treated by a PT. Conclusion. Unequal patient phenotypes in different primary care settings have important clinical implications. It can be carefully concluded that other factors, besides the level of inactivity, play a role in referral to PT

Phenotypic Variation in Patients with Chronic Obstructive Pulmonary Disease in Primary Care

Introduction. Despite the high number of inactive patients with COPD, not all inactive patients are referred to physical therapy, unlike recommendations of general practitioner (GP) guidelines. It is likely that GPs take other factors into account, determining a subpopulation that is treated by a physical therapist (PT). The aim of this study is to explore the phenotypic differences between inactive patients treated in GP practice and inactive patients treated in GP practice combined with PT. Additionally this study provides an overview of the phenotype of patients with COPD in PT practice. Methods. In a cross-sectional study, COPD patient characteristics were extracted from questionnaires. Differences regarding perceived health status, degree of airway obstruction, exacerbation frequency, and comorbidity were studied in a subgroup of 290 inactive patients and in all 438 patients. Results. Patients treated in GP practice combined with PT reported higher degree of airway obstruction, more exacerbations, more vascular comorbidity, and lower health status compared to patients who were not referred to and treated by a PT. Conclusion. Unequal patient phenotypes in different primary care settings have important clinical implications. It can be carefully concluded that other factors, besides the level of inactivity, play a role in referral to PT.status: publishe