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BACKGROUND: Measurement of B-type natriuretic peptide (BNP) in plasma may have its greatest potential in primary care, as general practitioners need to rapidly identify patients who warrant further medical review. The aim of the present study was to examine the prognostic information of BNP measurement on all-cause mortality in a large Danish primary care cohort. METHODS: This study covered a cohort of Danish primary care patients (n = 61665) with a median follow-up period of 4.36 years (interquartile range, 2.29-6.62 years). BNP was measured in plasma using the ADVIA Centaur/ CentaurXP platform. The association of BNP with mortality was assessed with a hazard ratio for all-cause mortality from a multivariable Cox proportional hazards model. RESULTS: Kaplan-Meier curves showed decreasing survival probability with increasing BNP (P < 0.001). Each doubling of BNP increased mortality by 32.3% (95% CI, 30.8-33.8) when adjusted for sex and age, and by 25.3% (95% CI, 23.8-26.8) when further adjusted for Charlson comorbidity index, hemoglobin, estimated glomerular filtration rate, glycohemoglobin, and thyroid-stimulating hormone. Also, in a subcohort (n=10824) without biochemical signs of severe kidney failure, anemia, polycythemia, hypothyroidism or hyperthyroidism, or dysregulated diabetes, each doubling of BNP increased mortality by 28.6% (95% CI, 22.8-34.7). CONCLUSIONS: Our results show that even in a primary care population, BNP measurements contain prognostic information regarding all-cause mortality.

Objective: The aims of this study were to (1) quantify the development and composition of multimorbidity (MM) during 16 years following the diagnosis of type 2 diabetes and (2) evaluate whether the effectiveness of structured personal diabetes care differed between patients with and without MM.Research design and methods: One thousand three hundred eighty-one patients with newly diagnosed type 2 diabetes were randomized to receive either structured personal diabetes care or routine diabetes care. Patients were followed up for 19 years in Danish nationwide registries for the occurrence of outcomes. We analyzed the prevalence and degree of MM based on 10 well-defined disease groups. The effect of structured personal care in diabetes patients with and without MM was analyzed with Cox regression models.Results: The proportion of patients with MM increased from 31.6% at diabetes diagnosis to 80.4% after 16 years. The proportion of cardiovascular and gastrointestinal diseases in surviving patients decreased, while, for example, musculoskeletal, eye, and neurological diseases increased. The effect of the intervention was not different between type 2 diabetes patients with or without coexisting chronic disease.Conclusions: In general, the proportion of patients with MM increased after diabetes diagnosis, but the composition of chronic disease changed during the 16 years. We found cardiovascular and musculoskeletal disease to be the most prevalent disease groups during all 16 years of follow-up. The post hoc analysis of the intervention showed that its effectiveness was not different among patients who developed MM compared to those who continued to have diabetes alone.

Background: Knowledge about prevalent and deadly combinations of multimorbidity is needed. Objective: To determine the nationwide prevalence of multimorbidity and estimate mortality for the most prevalent combinations of 1-5 diagnosis groups. Furthermore, to assess the excess mortality of the combination of two groups compared to the product of mortality associated with the single groups. Design: A prospective cohort study using Danish registries and including 3 986 209 people aged ≥18 years on 1 January, 2000. Multimorbidity was defined as having diagnoses from at least two of ten diagnosis groups: lung, musculoskeletal, endocrine, mental, cancer, neurological, gastrointestinal, cardiovascular, kidney, and sensory organs. Logistic regression (odds ratios, OR) and Ratio of ORs (ROR) were used to study mortality and excess mortality. Results: Prevalence of multimorbidity was 7.1% in the Danish population. The most prevalent combination (0.4%) was the musculoskeletal-cardiovascular which had double the mortality (OR 2.03) compared to persons not belonging to any of the diagnosis groups but showed no excess mortality (ROR 0.97). The neurological-cancer combination had the highest mortality (OR 6.35), was less prevalent (0.07%), and had no excess mortality (ROR 0.94). Cardiovascular-lung was moderately prevalent (0.2%), had high mortality (OR 5.75), and had excess mortality (ROR 1.18). Endocrine-kidney had high excess mortality (ROR 1.81) and cancer-mental had low excess mortality (ROR 0.66). Mortality increased with the number of groups. Conclusions: All combinations had increased mortality risk with some of them having up to a six-fold increased risk. Mortality increased with the number of diagnosis groups. Most combinations did not increase mortality above that expected, i.e. were additive rather than synergistic.

Background: We investigated how four aspects of socio-demography influence the effectiveness of an intervention with structured personal diabetes care on long-term outcomes. Methods: The Diabetes Care in General Practice (DCGP) study is a cluster-randomized trial involving a population-based sample of 1381 patients with newly diagnosed type 2-diabetes mellitus. We investigated how education, employment, cohabitation status and residence influenced the effectiveness of 6 years of intervention with structured personal diabetes care, resembling present day recommendations. Outcomes were incidence of any diabetes-related endpoint and death during 19 years after diagnosis, and cardiovascular risk factors, behaviour, attitudes and process-of-care variables 6 years after diagnosis. Results: Structured personal care reduced the risk of any diabetes-related endpoint and the effect of the intervention was modified by geographical area (interaction p = 0.034) with HR of 0.71 (95%CI: 0.60–0.85) and of 1.07 (95%CI: 0.77–1.48), for patients in urban and rural areas, respectively. Otherwise, there was no effect modification of education, employment and civil status on the intervention for the final endpoints. There were no noticeable socio-demographic differences in the effect of the intervention on cardiovascular risk factors, behaviour, attitudes, and process-of-care. Conclusion: Structured personal care reduced the aggregate outcome of any diabetes-related endpoint and independent of socio-demographic factors similar effect on cardiovascular risk factors, behaviour, attitudes and process of care, but the intervention did not change the existing inequity in mortality and morbidity. Residence modified the uptake of the intervention with patients living in urban areas having more to gain of the intervention than rural patients, further investigations is warranted. Trial registration: ClinicalTrials.gov registration no. NCT01074762 (February 24

OBJECTIVE: This study examined the influence of weight loss on long-term morbidity and mortality in overweight (BMI≥25 kg/m2) patients with type 2 diabetes, and tested the hypothesis that therapeutic intentional weight loss supervised by a medical doctor prolongs life and reduces the risk for cardiovascular disease in these patients.METHODS: This is a 19 year cohort study of patients in the intervention arm of the randomized clinical trial Diabetes Care in General Practice. Weight and prospective intentions for weight loss were monitored every third month for six years in 761 consecutive patients (≥40 years) newly diagnosed with diabetes in general practices throughout Denmark in 1989-92. Multivariable Cox regression was used to estimate the association between weight change during the monitoring period (year 0 to 6) and the outcomes during the succeeding 13 years (year 6 to 19) in 444 patients who were overweight at diagnosis and alive at the end of the monitoring period (year 6). The analysis was adjusted for age, sex, education, BMI at diagnosis, change in smoking, change in physical activity, change in medication, and the Charlson comorbidity 6-year score. Outcomes were from national registers.RESULTS: Overall, weight loss regardless of intention was an independent risk factor for increased all-cause mortality (P<0.01). The adjusted hazard ratio for all-cause mortality, cardiovascular mortality, and cardiovascular morbidity attributable to an intentional weight loss of 1 kg/year was 1.20 (95%CI 0.97-1.50, P = 0.10), 1.26 (0.93-1.72, P = 0.14), and 1.06 (0.79-1.42, P = 0.71), respectively. Limiting the analysis to include only those patients who survived the first 2 years after the monitoring period did not substantially change these estimates. A non-linear spline estimate indicated a V-like association between weight change and all-cause mortality, suggesting the best prognosis for those who maintained their weight.CONCLUSIONS: In this

Aims/hypothesis: To assess gender differences in mortality and morbidity during 13 follow up years after 6 years of structured personal care in patients with type 2 diabetes mellitus. Methods: In the Diabetes Care in General Practice(DCGP) multicentre, cluster randomised, controlled trial(ClinicalTrials.gov, NCT01074762), 1,381 patients newly diagnosed with type 2 diabetes were randomized to six years of structured personal care or routine care. The intervention included regular follow up, individualized goal setting supported by continuing medical education of doctors. This observational analysis followed 970 patients, re-examined by the end of intervention, for 13 years using national registries. Outcomes were all-cause mortality, incidence of diabetes-related death, any diabetes-related endpoint, myocardial infarction, stroke, peripheral vascular disease, and microvascular disease. Results: In women, but not men, a lower hazard ratio for structured personal vs routine care emerged for any diabetes-related endpoint(0.65, P=0.004, adjusted; 73.4 vs 107.7 events per 1,000 patient-years), diabetes-related death(0.70, P=0.03; 34.6 vs 45.7), all-cause mortality(0.74, P=0.028; 55.5 vs 68.5), and stroke(0.59, P=0.038; 15.6 vs 28.9). This effect was different between genders for diabetes-related death(interaction P=0.015) and all-cause mortality(P=0.005). Conclusions/Interpretation: Compared to routine care, structured personal diabetes care reduced all-cause mortality, diabetes-related death, any diabetes-related outcome and stroke in women, but not in men. The gender difference was statistically significant for the first two outcomes. In this post hoc analysis of a randomized controlled trial, these observational gendered results cannot be explained by intermediate outcomes like haemoglobinA1c alone, but involves complex social and cultural issues of gender. There is a need to rethink treatment schemes for both genders to benefit from intensified treatment, Aims/hypothesis: The aim of this study was to assess gender differences in mortality and morbidity during 13 follow-up years after 6 years of structured personal care in patients with type 2 diabetes mellitus. Methods: In the Diabetes Care in General Practice (DCGP) multicentre, cluster-randomised, controlled trial (ClinicalTrials.gov registration no. NCT01074762), 1,381 patients newly diagnosed with type 2 diabetes were randomised to receive 6 years of either structured personal care or routine care. The intervention included regular follow-up, individualised goal setting and continuing medical education of general practitioners participating in the intervention. Patients were re-examined at the end of intervention. This observational analysis followed 970 patients for 13 years thereafter using national registries. Outcomes were all-cause mortality, incidence of diabetes-related death, any diabetes-related endpoint, myocardial infarction, stroke, peripheral vascular disease and microvascular disease. Results: In women, but not men, a lower HR for structured personal care vs routine care emerged for any diabetes-related endpoint (0.65, p = 0.004, adjusted; 73.4 vs 107.7 events per 1,000 patient-years), diabetes-related death (0.70, p = 0.031; 34.6 vs 45.7), all-cause mortality (0.74, p = 0.028; 55.5 vs 68.5) and stroke (0.59, p = 0.038; 15.6 vs 28.9). This effect was different between men and women for diabetes-related death (interaction p = 0.015) and all-cause mortality (interaction p = 0.005). Conclusions/interpretation: Compared with routine care, structured personal diabetes care reduced all-cause mortality and diabetes-related death in women but not in men. This gender difference was also observed for any diabetes-related outcome and stroke but was not statistically significant after extensive multivariate adjustment. These observational results from a post hoc analysis of a randomised controlled trial cannot be explained by intermed

Objective: Standard portions or substitution of missing portion sizes with medians may generate bias when quantifying the dietary intake from FFQ. The present study compared four different methods to include portion sizes in FFQ. Design: We evaluated three stochastic methods for imputation of portion sizes based on information about anthropometry, sex, physical activity and age. Energy intakes computed with standard portion sizes, defined as sex-specific medians (median), or with portion sizes estimated with multinomial logistic regression (MLR), ‘comparable categories’ (Coca) or k-nearest neighbours (KNN) were compared with a reference based on self-reported portion sizes (quantified by a photographic food atlas embedded in the FFQ). Setting: The Danish Health Examination Survey 2007–2008. Subjects: The study included 3728 adults with complete portion size data. Results: Compared with the reference, the root-mean-square errors of the mean daily total energy intake (in kJ) computed with portion sizes estimated by the four methods were (men; women): median (1118; 1061), MLR (1060; 1051), Coca (1230; 1146), KNN (1281; 1181). The equivalent biases (mean error) were (in kJ): median (579; 469), MLR (248; 178), Coca (234; 188), KNN (−340; 218). Conclusions: The methods MLR and Coca provided the best agreement with the reference. The stochastic methods allowed for estimation of meaningful portion sizes by conditioning on information about physiology and they were suitable for multiple imputation. We propose to use MLR or Coca to substitute missing portion size values or when portion sizes needs to be included in FFQ without portion size data.

Objective: Thrombocytosis has been associated with higher stage and mortality of cancer, however, the evidence is conflicting. We examined the stage distribution and prognosis of gynecologic cancer according to levels of prediagnostic platelet count. Methods: In a primary care resource with blood cell counts from more than 500,000 individuals, we identified 581 women with a primary diagnosis of gynecological cancer. We divided the pre-diagnostic mean platelet count derived from the 3-year period prior to cancer diagnosis into three categories of thrombocytosis (no, 150–400 × 109 /L; mild, N400–550 × 109 /L; severe, N550 × 109 /L). Logistic regression models were used to calculate odds ratios (ORs) for the association of prediagnostic platelet counts with stage at diagnosis. Subsequently, we estimated hazard ratios (HRs) for all-cause or gynecological cancer-specific mortality by level of thrombocytosis using Cox proportional hazard regression models. Results: Patients with non-localized disease had higher levels of prediagnostic platelet count [mild thrombocytosis: OR, 2.36 (95% CI, 1.33–4.19); severe thrombocytosis: 4.54 (95% CI, 1.55–13.3); compared with no prediagnostic thrombocytosis]. The median overall survival was 1.04 years among patients with severe prediagnostic thrombocytosis and 3.25 years among those with mild thrombocytosis, P b 0.0001. When adjusting for stage at diagnosis, elevated all-cause mortality remained with both mild (HR = 1.51; 95% CI, 1.08–2.12) and severe (HR = 3.15; 95% CI 1.95-5.08) prediagnostic thrombocytosis. Similar associations were found for cancer-specific mortality. Conclusions: Prediagnostic thrombocytosis was associated with advanced stage of gynecological cancer at diagnosis and increased all-cause and cancer-specific mortality. The platelet count may have an important role in diagnosis and post-diagnostic control of gynecological cancer.

Objective. To examine the impact of smoking cessation on body weight compared with normal long-termweight development. Methods. Of 1970 adults (20–69 years) in a rural town in Denmark invited to take part in the study in 1998–2000, 1374 (70%) participated. After 9 years, 1121 participated in the follow-up study. Weight changes werecompared using multivariable regression models. Results. The mean baseline weight of never-smokers was 76.4 kg (SD 16.0). The adjusted weight of smokersand ex-smokers differed by −4.2 kg (95% CI: −5.9, −2.6), and −0.7 kg (95% CI: −2.5, 1.1), respectively. Theadjusted weight gain rate (kg/year) of never-smokers, smokers, and ex-smokers was 0.213, 0.127, and 0.105,respectively. The absolute post cessation weight gain (PCWG) was 5.0 kg (SD 7.0), and the adjusted PCWGwas 2.8 kg (95% CI: 1.7, 3.9) compared with never-smokers, and 3.5 kg (95% CI: 2.3, 4.8) compared with smokers.The follow-up weight did not differ between quitters and never-smokers (0.1 kg; 95% CI: −2.4, 2.6). Conclusion. Smokers weigh less than never-smokers. By quitting, they gain weight and end up weighing thesame as comparable never-smokers. Weight gain rates differ by smoking status. Consequently, PCWG dependson the length of follow-up. Our graphical model indicates that smoking cessation results in a return to normalweight development.

Objective. To explore views and attitudes among general practitioners (GPs) and researchers in the field of general practicetowards problems and challenges related to treatment of patients with multimorbidity. Setting. A workshop entitled Patientswith multimorbidity in general practice held during the Nordic Congress of General Practice in Tampere, Finland, 2013.Subjects. A total of 180 GPs and researchers. Design. Data for this summary report originate from audio-recorded, transcribedverbatim plenary discussions as well as 76 short questionnaires answered by attendees during the workshop. Thedata were analysed using framework analysis. Results. (i) Complex care pathways and clinical guidelines developed forsingle diseases were identified as very challenging when handling patients with multimorbidity; (ii) insufficient cooperationbetween the professionals involved in the care of multimorbid patients underlined the GPs’ impression of a fragmentedhealth care system; (iii) GPs found it challenging to establish a good dialogue and prioritize problems with patients withinthe timeframe of a normal consultation; (iv) the future role of the GP was discussed in relation to diminishing healthinequality, and current payment systems were criticized for not matching the treatment patterns of patients with multimorbidity.Conclusion. The participants supported the development of a future research strategy to improve the treatment ofpatients with multimorbidity. Four main areas were identified, which need to be investigated further to improve care forthis steadily growing patient group.

Aims: The association between recent and more distant weight changes before and after the diagnosis of type 2 diabetes has been little researched. The aim of this study is to determine the influence of patients’ weight history before diabetes diagnosis on the observed 6-year weight changes after diagnosis. Methods: A clinical cohort study combined with self-reported past weight history. In total 885 patients aged ≥40 years and newly diagnosed with clinical type 2 diabetes were included. Body weight was measured immediately after diabetes diagnosis and again at the 6-year follow up examination (median, 5.7 years). At diagnosis patients reported their weight 1 year and 10 years previously, and also at the age of 20. Multivariate linear regression analyses controlled for 20 baseline patient characteristics. Results: The median (interquartile range) age at diagnosis was 63.2 (53.9; 71.4) years. Median body weight was 80.0 (72.0; 90.0) kg 10 years before diagnosis, 85.0 (75.0; 95.0) kg 1 year before diagnosis, 82.4 (72.0; 94.0) kg at diagnosis, and 80.0 (70.0; 91.1) kg at 6-year follow up. Each kg of weight gain during the year preceding the diagnosis was associated with a weight change (95% CI) of -0.20 (-0.28; -0.13) kg during the follow up period. In all models age and body mass index at diagnosis predicted future weight changes, while the weight at age 20 (-0.01 (-0.06; 0.03) kg/kg), and the weight change from 10 years to 1 year before diagnosis (-0.01 (-0.06; 0.04) kg/kg), did not predict weight change after diagnosis. Conclusions: During the first on average 5.7 years after diagnosis of type 2 diabetes, patients generally follow a course of declining average weight, and these weight developments are related primarily to recent weight changes, body mass index, and age, but not to the more distant weight history.

Objective. This study explored the impact of involvement in cooking on long-term morbidity and mortality among patients newly diagnosed with type 2 diabetes mellitus (T2DM). Design and subjects. Data are from the population-based study Diabetes Care in General Practice. In baseline questionnaires, 1348 patients newly diagnosed with T2DM gave information on how frequently they consumed a warm main meal and how often they cooked it themselves. The selected patients were followed up for 19 years in the Danish National Patient Registry and the Danish Register of Causes of Death. Main outcome measures. This study analysed the association between involvement in cooking and each of seven pre-specified outcomes was analysed in Cox regression models with stepwise adjustment for possible confounders and mediators. Results. 92% of the patients with T2DM consumed a warm main meal  five times per week. Among these, women who cooked for themselves less than once a week had a higher risk of diabetes-related deaths (HR 1.86 [95% CI 1.03–3.35], p = 0.039) and stroke (HR 2.47 [95% CI 1.08–5.65], p = 0.033), after adjustment for confounders. For men, infrequent cooking was not related to increased risk for the outcomes investigated. Conclusions. In patients newly diagnosed with T2DM and with a regular intake of warm main meals, infrequent involvement in cooking was associated with an increased risk of diabetes-related death and stroke for women, but not for men. General practitioners should pay special attention to managing diabetes treatment in female patients newly diagnosed with T2DM who report infrequent involvement in cooking.

Background Diabetic patients’ lifestyle adaptations to improve glycaemic control are not always followed by improvements in self-rated general health (SRH). The perceived impact of diabetes on patients’ daily lives may influence changes in their SRH. This paper examines the association of illness severity, treatment, behavioural, and coping-related factors with changes in SRH from diagnosis of type 2 diabetes until one year later, in a population-based sample of 599 patients aged 40 years or over who were treated in general practice. Methods Change in SRH was estimated by a cumulative probit model with the inclusion of covariates related to SRH (e.g. illness severity at diagnosis, behaviour, treatment, and the perceived impact of diabetes on patients’ daily lives one year later). Results At diagnosis, 11.6% of patients reported very good, 35.1% good, 44.6% fair and 8.5% poor SRH. Physical inactivity, many diabetes-related symptoms, and cardiovascular disease were related to lower SRH ratings. On average SRH improved by 0.46 (95% CI: 0.37; 0.55) during the first year after diagnosis without inclusion of covariates. Mental and practical illness burden was the only factor associated with change in SRH, independent of patients’ diabetes severity and medical treatment (p=0.03, multivariate analysis). Compared to otherwise similar patients without illness burden, increase in SRH was marginally smaller among patients who expressed minor illness burden, but much smaller among patients with more pronounced illness burden. Conclusions Much as one would expect, many patients increased their SRH during the first year after diabetes diagnosis. This increase in SRH was not associated with indicators of illness severity or factors reflecting socio-demographic circumstances, but patients experiencing illness burden had a smaller increase than those who reported no illness burden. We suggest that during the diabetes consultation, general practitioners exp, Background: iabetic patients’ lifestyle adaptations to improve glycaemic control are not always followed by improvements in self-rated general health (SRH). The perceived impact of diabetes on patients’ daily lives may influence changes in their SRH. This paper examines the association of illness severity, treatment, behavioural, and coping-related factors with changes in SRH from diagnosis of type 2 diabetes until one year later, in a population-based sample of 599 patients aged 40 years or over who were treated in general practice. Methods: Change in SRH was estimated by a cumulative probit model with the inclusion of covariates related to SRH (e.g. illness severity at diagnosis, behaviour, treatment, and the perceived impact of diabetes on patients’ daily lives one year later). Results: At diagnosis, 11.6% of patients reported very good, 35.1% good, 44.6% fair and 8.5% poor SRH. Physical inactivity, many diabetes-related symptoms, and cardiovascular disease were related to lower SRH ratings. On average SRH improved by 0.46 (95% CI: 0.37; 0.55) during the first year after diagnosis without inclusion of covariates. Mental and practical illness burden was the only factor associated with change in SRH, independent of patients’ diabetes severity and medical treatment (p = 0.03, multivariate analysis). Compared to otherwise similar patients without illness burden, increase in SRH was marginally smaller among patients who expressed minor illness burden, but much smaller among patients with more pronounced illness burden. Conclusions: Much as one would expect, many patients increased their SRH during the first year after diabetes diagnosis. This increase in SRH was not associated with indicators of illness severity or factors reflecting socio-demographic circumstances, but patients experiencing illness burden had a smaller increase than those who reported no illness burden. We suggest that during the diabetes consultation, general practitioners

Blood eosinophilia (≥0.5 × 109/l) may be an early sign of hematological malignancy. We investigated associations between levels of blood eosinophils and risks of hematological malignancies and mortality in order to provide clinically derived cut-offs for referral to specialist hematology care. From the Copenhagen Primary Care Differential Count (CopDiff) Database, we identified 356,196 individuals with at least one differential cell count encompassing the eosinophil count during 2000–2007 and matched these laboratory data with Danish nationwide health registers. We used multivariable logistic regression to calculate odds ratios (ORs) for the 4-year incidences of hematological malignancies and mortality between the eosinophil counts and a reference count of 0.16 × 109/l which was the median eosinophil count in our data. Risks of hematological malignancies and mortality increased above the median eosinophil count. At the 99th percentile, corresponding to an eosinophil count of 0.75 × 109/l, risks of hematological malignancies were increased more than twofold with OR (95% C.I.) of 2.39 (1.91–2.99). Interestingly, risks reached a plateau around an eosinophil count of 1.0 × 109/l. Risks also increased when the eosinophil count approached zero. Here, counts associated relatively more with acute myeloid leukemia and myelodysplastic syndromes whereas counts above 0.16 × 109/l associated more with myeloproliferative neoplasms. Eosinophil counts associate with hematological malignancies and mortality even below the definition of eosinophilia. The observed plateau of risks around 1.0 × 109/l is important for physicians encountering patients with eosinophilia since even mild-to-moderate eosinophilia according to traditional definitions confers maximally increased risks of subsequent/subclinical hematological malignancy