Different abdominal symptoms may signal cancer, but their role is unclear.
To examine associations between abdominal symptoms and subsequent cancer diagnosed in the abdominal region.
Prospective cohort study comprising 493 GPs from surgeries in Norway, Denmark, Sweden, Scotland, Belgium, and the Netherlands.
Over a 10-day period, the GPs recorded consecutive consultations and noted: patients who presented with abdominal symptoms pre-specified on the registration form; additional data on non-specific symptoms; and features of the consultation. Eight months later, data on all cancer diagnoses among all study patients in the participating general practices were requested from the GPs.
Consultations with 61 802 patients were recorded and abdominal symptoms were documented in 6264 (10.1%) patients. Malignancy, both abdominal and non-abdominal, was subsequently diagnosed in 511 patients (0.8%). Among patients with a new cancer in the abdomen (n = 251), 175 (69.7%) were diagnosed within 180 days after consultation. In a multivariate model, the highest sex- and age-adjusted hazard ratio (HR) was for the single symptom of rectal bleeding (HR 19.1, 95% confidence interval = 8.7 to 41.7). Positive predictive values of >3% were found for macroscopic haematuria, rectal bleeding, and involuntary weight loss, with variations according to age and sex. The three symptoms relating to irregular bleeding had particularly high specificity in terms of colorectal, uterine, and bladder cancer.
A patient with undiagnosed cancer may present with symptoms or no symptoms. Irregular bleeding must always be explained. Abdominal pain occurs with all types of abdominal cancer and several symptoms may signal colorectal cancer. The findings are important as they influence how GPs think and act, and how they can contribute to an earlier diagnosis of cancer.
The APHEA 2 project investigated short-term health effects of particles in eight European cities. In each city associations between particles with an aerodynamic diameter of less than 10 microm (PM(10)) and black smoke and daily counts of emergency hospital admissions for asthma (0-14 and 15-64 yr), chronic obstructive pulmonary disease (COPD), and all-respiratory disease (65+ yr) controlling for environmental factors and temporal patterns were investigated. Summary PM(10) effect estimates (percentage change in mean number of daily admissions per 10 microg/m(3) increase) were asthma (0-14 yr) 1.2% (95% CI: 0.2, 2.3), asthma (15-64 yr) 1.1% (0.3, 1.8), and COPD plus asthma and all-respiratory (65+ yr) 1.0% (0.4, 1.5) and 0.9% (0.6, 1.3). The combined estimates for Black Smoke tended to be smaller and less precisely estimated than for PM(10). Variability in the sizes of the PM(10) effect estimates between cities was also investigated. In the 65+ groups PM(10) estimates were positively associated with annual mean concentrations of ozone in the cities. For asthma admissions (0-14 yr) a number of city-specific factors, including smoking prevalence, explained some of their variability. This study confirms that particle concentrations in European cities are positively associated with increased numbers of admissions for respiratory diseases and that some of the variation in PM(10) effect estimates between cities can be explained by city characteristics.
OBJECTIVE: The overall aims of the ADDITION study are to evaluate whether screening for prevalent undiagnosed Type 2 diabetes is feasible, and whether subsequent optimised intensive treatment of diabetes, and associated risk factors, is feasible and beneficial. DESIGN: Population-based screening in three European countries followed by an open, randomised controlled trial. SUBJECTS AND METHODS: People aged 40-69 y in the community, without known diabetes, will be offered a random capillary blood glucose screening test by their primary care physicians, followed, if equal to or greater than 5.5 mmol/l, by fasting and 2-h post-glucose-challenge blood glucose measurements. Three thousand newly diagnosed patients will subsequently receive conventional treatment (according to current national guidelines) or intensive multifactorial treatment (lifestyle advice, prescription of aspirin and ACE-inhibitors, in addition to protocol-driven tight control of blood glucose, blood pressure and cholesterol). Patients allocated to intensive treatment will be further randomised to centre-specific interventions to motivate adherence to lifestyle changes and medication. Duration of follow-up is planned for 5 y. Endpoints will include mortality, macrovascular and microvascular complications, patient health status and satisfaction, process-of-care indicators and costs.
Authors investigated, cross-nationally, the factors, including demographic, psychiatric (including cognitive), physical, and behavioral, determining whether older people take their prescribed medication. Older adults are prescribed more medication than any other group, and poor adherence is a common reason for non-response to medication.
Researchers interviewed 3,881 people over age 65 who receive home care services in 11 countries, administering a structured interview in participants' homes. The main outcome measure was the percentage of participants not adherent to medication.
In all, 12.5% of people (N=456) reported that they were not fully adherent to medication. Non-adherence was predicted by problem drinking (OR=3.6), not having a doctor review their medication (OR=3.3), greater cognitive impairment (OR=1.4 for every one-point increase in impairment), good physical health (OR=1.2), resisting care (OR=2.1), being unmarried (OR=2.3), and living in the Czech Republic (OR=4.7) or Germany (OR=1.4).
People who screen positive for problem drinking and who have dementia (often undiagnosed) are less likely to adhere to medication. Therefore, doctors should consider dementia and problem drinking when prescribing for older adults. Interventions to improve adherence in older adults might be more effective if targeted at these groups. It is possible that medication-review enhances adherence by improving the doctor-patient relationship or by emphasizing the need for medications.
Admission hyperglycemia is associated with poor clinical outcome in ischemic and hemorrhagic stroke. Admission hyperglycemia has not been investigated in patients with cerebral venous thrombosis.
Consecutive adult patients with cerebral venous thrombosis were included at the Academic Medical Center, The Netherlands (2000-2014) and the Helsinki University Central Hospital, Finland (1998-2014). We excluded patients with known diabetes mellitus and patients without known admission blood glucose. We defined admission hyperglycemia as blood glucose =7.8 mmol/L (141 mg/dL) and severe hyperglycemia as blood glucose =11.1 mmol/L (200 mg/dL). We used logistic regression analysis to determine if admission hyperglycemia was associated with modified Rankin Scale (mRS) score of 3 to 6 or mortality at last follow-up. We adjusted for: age, sex, coma, malignancy, infection, intracerebral hemorrhage, deep cerebral venous thrombosis, and location of recruitment.
Of 380 patients with cerebral venous thrombosis, 308 were eligible. Of these, 66 (21.4%) had admission hyperglycemia with 8 (2.6%) having severe admission hyperglycemia. Coma (31.3% versus 5.0%, P
BACKGROUND: It is unclear if objective selection of employees, for an intervention to prevent sickness absence, is more effective than subjective 'personal enlistment'. We hypothesize that objectively selected employees are 'at risk' for sickness absence and eligible to participate in the intervention program. METHODS: The dispatch of 8603 screening instruments forms the starting point of the objective selection process. Different stages of this process, throughout which employees either dropped out or were excluded, were described and compared with the subjective selection process. Characteristics of ineligible and ultimately selected employees, for a randomized trial, were described and quantified using sickness absence data. RESULTS: Overall response rate on the screening instrument was 42.0%. Response bias was found for the parameters sex and age, but not for sickness absence. Sickness absence was higher in the 'at risk' (N = 212) group (42%) compared to the 'not at risk' (N = 2503) group (25%) (OR 2.17 CI 1.63-2.89; p = 0.000). The selection process ended with the successful inclusion of 151 eligible, i.e. 2% of the approached employees in the trial. CONCLUSION: The study shows that objective selection of employees for early intervention is effective. Despite methodological and practical problems, selected employees are actually those at risk for sickness absence, who will probably benefit more from the intervention program than others.
The aims were (1) to compare all cause mortality in population samples of different cultures; and (2) to cross predict fatal event by risk functions involving risk factors usually measured in cardiovascular epidemiology.
The study was a 25 year prospective cohort study. The prediction of all cause mortality was made using the multiple logistic equation as a function of 12 risk factors; the prediction of months lived after entry examination was made by the multiple linear regression using the same factors. POPULATION SAMPLES: There were five cohorts of men aged 40-59 years, from Finland (two cohorts, 1677 men), from The Netherlands (one cohort, 878 men), and from Italy (two cohorts, 1712 men).
The Finnish cohorts came from geographically defined rural areas, the Dutch cohort from a small town in central Holland, and the Italian cohorts from rural villages in northern and central Italy.
All cause mortality was highest in Finland (557 per 1000), and lower in The Netherlands (477) and in Italy (475). The solutions of the multiple logistic function showed the significant and almost universal predictive role of certain factors, with rare exceptions. These were age, blood pressure, cigarette smoking, and arm circumference (the latter with a negative relationship). Similar results were obtained when solving a multiple linear regression equation predicting the number of months lived after entry examination as a function of the same factors. The prediction of fatal events in each country, using the risk functions of the others, produced limited errors, the smallest one being -2% and the largest +11%. When solving the logistic model in the pool of all the cohorts with the addition of dummy variables for the identification of nationality, it also appeared that only a small part of the mortality differences between countries is not explained by 12 available risk factors.
A small set of risk factors seems to explain the intercohort differences of 25 year all cause mortality in population samples of three rather different cultures.
Cites: Circulation. 1972 Apr;45(4):815-285016014
Cites: Clin Chem. 1956 Jun;2(3):145-5913317101
Cites: Am J Epidemiol. 1981 Apr;113(4):371-77211822
Cites: Lancet. 1981 Jul 11;2(8237):58-616113438
Cites: Int J Epidemiol. 1981 Jun;10(2):187-977287279
The breast-ovary cancer-family syndrome is a dominant predisposition to cancer of the breast and ovaries which has been mapped to chromosome region 17q12-q21. The majority, but not all, of breast-ovary cancer families show linkage to this susceptibility locus, designated BRCA1. We report here the results of a linkage analysis of 145 families with both breast and ovarian cancer. These families contain either a total of three or more cases of early-onset (before age 60 years) breast cancer or ovarian cancer. All families contained at least one case of ovarian cancer. Overall, an estimated 76% of the 145 families are linked to the BRCA1 locus. None of the 13 families with cases of male breast cancer appear to be linked, but it is estimated that 92% (95% confidence interval 76%-100%) of families with no male breast cancer and with two or more ovarian cancers are linked to BRCA1. These data suggest that the breast-ovarian cancer-family syndrome is genetically heterogeneous. However, the large majority of families with early-onset breast cancer and with two or more cases of ovarian cancer are likely to be due to BRCA1 mutations.
This study concerns a comparative analysis of hospital readmission rates and related utilization in six areas, including three European countries (Finland, Scotland and the Netherlands) and three states in the USA (New York, California, Washington State). It includes a data analysis on six major causes of hospitalization across these areas. Its main focus is on two questions. (1) Do hospital readmission rates vary among the causes of hospitalization and the study populations? (2) Are hospital inpatient lengths of stay inversely related to readmissions rates? The study demonstrated that diagnoses such as chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF) were the major causes of hospital readmission rates. The data showed that (initial) hospital stays were generally longer for patients who were readmitted than for those who were not. As a result, short stays were not associated with a higher risk of readmission, meaning that hospital readmissions were not produced by premature hospital discharges in the study population. Furthermore, the spatial variation in readmission rates within 7 versus 8-30 days showed to be identical. Finally, it was found that countries or states with relatively shorter stays showed higher readmission rates and vice versa. Since patients with readmissions in all of the areas had on average longer initial stays, this finding at country level does illustrate that there seems to be a country specific trade off between length of stay and rate of readmission. An explanation should be sought in differences in health care arrangements per area, including factors that determine length of stay levels and readmission rates in individual countries (e.g. managed care penetration, after care by GP's or home care).