The effect of comorbidity on glycemic control and systolic blood pressure in type 2 diabetes: A cohort study with 5 year follow-up in primary care

To explore the longitudinal effect of chronic comorbid diseases on glycemic control (HbA1C) and systolic blood pressure (SBP) in type 2 diabetes patients. Methods In a representative primary care cohort of patients with newly diagnosed type 2 diabetes in The Netherlands (n = 610), we tested differences in the five year trend of HbA1C and SBP according to comorbidity profiles. In a mixed model analysis technique we corrected for relevant covariates. Influence of comorbidity (a chronic disease already present when diabetes was diagnosed) was tested as total number of comorbid diseases, and as presence of specific disease groups, i.e. cardiovascular, mental, and musculoskeletal disease, malignancies, and COPD. In subgroup effect analyses we tested if potential differences were modified by age, sex, socioeconomic status, and BMI. Results The number of comorbid diseases significantly influenced the SBP trend, with highest values after five years for diabetes patients without comorbidity (p = 0.005). The number of diseases did not influence the HbA1C trend (p = 0.075). Comorbid musculoskeletal disease resulted in lower HbA1C at the time of diabetes diagnosis, but in higher values after five years (p = 0.044). Patients with cardiovascular diseases had sustained elevated levels of SBP (p = 0.014). Effect modification by socioeconomic status was observed in some comorbidity subgroups. Conclusions Presence of comorbidity in type 2 diabetes patients affected the long-term course of HbA1C and SBP in this primary care cohort. Numbers and types of comorbidity showed differential effects: not the simple sum of diseases, but specific types of comorbid disease had a negative influence on long-term diabetes control parameters. The complex interactions between comorbidity, diabetes control and effect modifiers require further investigation and may help to personalize treatment goals

The health status of Q-fever patients after long-term follow-up

Contains fulltext : 96434.pdf (postprint version ) (Open Access)BACKGROUND: In the Netherlands, from 2007 to 2009, 3,522 Q-fever cases were notified from three outbreaks. These are the largest documented outbreaks in the world. Previous studies suggest that symptoms can persist for a long period of time, resulting in a reduced quality of life (QoL). The aim of this study was to qualify and quantify the health status of Q-fever patients after long-term follow-up. METHODS: 870 Q-fever patients of the 2007 and 2008 outbreaks were mailed a questionnaire 12 to 26 months after the onset of illness. We assessed demographic data and measured health status with the Nijmegen Clinical Screening Instrument (NCSI). The NCSI consists of three main domains of functional impairment, symptoms and QoL that are divided into eight sub-domains. The NCSI scores of Q-fever patients older than 50 years (N=277) were compared with patients younger than 50 years (N=238) and with norm data from healthy individuals (N=65) and patients with chronic obstructive pulmonary disease (N=128). RESULTS: The response rate was 65.7%. After applying exclusion criteria 515 Q-fever patients were included in this study. The long-term health status of two thirds of Q-fever patients (both younger and older than 50 years) was severely affected for at least one sub-domain. Patients scores were most severely affected on the sub-domains general QoL (44.9%) and fatigue (43.5%). Hospitalisation in the acute phase was significantly related to long-term behavioural impairment (OR 2.8, CI 1.5-5.1), poor health related QoL (OR 2.3,CI 1.5-4.0) and subjective symptoms (OR 1.9, CI 1.1-3.6). Lung or heart disease, depression and arthritis significantly affected the long-term health status of Q-fever patients. CONCLUSIONS: Q-fever patients presented 12 to 26 months after the onset of illness severe -clinically relevant- subjective symptoms, functional impairment and impaired QoL. All measured sub-domains of the health status were impaired. Hospitalisation and co-morbidity were predictors for worse scores. Our data emphasise that more attention is needed not only to prevent exposure to Q-fever but also for the prevention and treatment of the long-term consequences of this zoonosis