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1.
Mil Med ; 181(11): e1644-e1649, 2016 11.
Article in English | MEDLINE | ID: mdl-27849501

ABSTRACT

OBJECTIVE: To examine the assumption that postdeployment incidence of sickness and other absence from work are higher among Gulf War Veterans compared with nonveterans. METHODS: A prospective registry study including a cohort of 721 Danish Gulf War Veterans and a control cohort of 3,629 nonveterans selected from the general Danish population. Outcome measures were up to 23 years postdeployment incidence of (1) long-term sickness absence and (2) long-term all types of absence from work. Long term with regard to sickness and other absence was defined as exceeding 8 weeks. The association between outcomes and information on deployment history was studied using time-to-event analysis. The index date was the return date from the last deployment to the Gulf. The follow-up period was the time from index date until April 27, 2014. RESULTS: As the main finding, no difference was found between veterans and nonveterans in the incidence rate of long-term sickness absence. After an initial short period (3 months) with elevated incidence rate of long-term absence from work among veterans, there was no difference between the cohorts. CONCLUSION: Among Danish Gulf War Veterans, no postdeployment increased risk of long-term sickness absence or long-term absence from work was found as compared with nonveterans.


Subject(s)
Absenteeism , Veterans/statistics & numerical data , Warfare , Adult , Cohort Studies , Denmark , Female , Humans , Indian Ocean , Male , Middle Aged , Prospective Studies , Registries
2.
Eur J Gen Pract ; 21(2): 118-23, 2015 Jun.
Article in English | MEDLINE | ID: mdl-25712495

ABSTRACT

BACKGROUND: Unnecessary prescribing of antibiotics is a major public health concern. General practitioners (GPs) prescribe most antibiotics, often for upper respiratory tract infections (URTIs), and have in general been shown to prescribe antibiotics more often to women. No studies have examined the influence of patient gender on unnecessary antibiotic prescribing. OBJECTIVES: To study a possible gender difference in unnecessary antibiotic prescriptions for URTIs in general practice; to assess whether a possible difference is explained by patient demand for antibiotics. METHODS: Post-hoc analysis of a cross-sectional study including 15,022 patients with URTI (acute rhinitis, acute otitis media, acute sinusitis, acute pharyngotonsillitis) from Argentina, Denmark, Lithuania, Russia, Spain and Sweden (HAPPY AUDIT Project). The association between gender and unnecessary antibiotic prescriptions, unadjusted and adjusted for treatment demand, was analysed using logistic regression models. RESULTS: A total of 25% of patients with URTI received antibiotics; in 45% of the cases, antibiotics were unnecessary. Overall, no gender difference for unnecessary prescribing of antibiotics for URTIs was found. Women with acute otitis media received an unnecessary antibiotic twice as often as men (14.4% versus 7.1%). In Danish patients with acute pharyngotonsillitis, there was a gender difference in unnecessary prescriptions for antibiotics (women 29.1% versus men 48.6%). Some 14% of patients receiving unnecessary antibiotics demonstrated a demand for antibiotics, but no gender difference was found in this group. CONCLUSION: This study indicated a high rate of unnecessary antibiotic prescribing for URTIs in general practice, but overall found no gender differences in receiving unnecessary antibiotic prescriptions.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Inappropriate Prescribing/statistics & numerical data , Patient Acceptance of Health Care/statistics & numerical data , Primary Health Care/statistics & numerical data , Respiratory Tract Infections/drug therapy , Sex Factors , Argentina , Cross-Sectional Studies , Denmark , Female , Humans , Lithuania , Male , Otitis Media/drug therapy , Pharyngitis/drug therapy , Russia , Spain , Sweden , Tonsillitis/drug therapy
3.
Diabetologia ; 57(6): 1119-23, 2014 Jun.
Article in English | MEDLINE | ID: mdl-24599111

ABSTRACT

AIMS/HYPOTHESIS: The estimation of effect size in clinical trials commonly disregards recurrent outcomes. We investigated the effectiveness of a complex intervention on recurrent outcomes in patients with type 2 diabetes. METHODS: In the Diabetes Care in General Practice (DCGP) randomised controlled trial, 1,381 patients newly diagnosed with type 2 diabetes were randomised to 6 years of structured personal care or routine care (ClinicalTrials.gov NCT01074762). The trial had 19 years of registry-based follow-up and was analysed with Cox regression models. Repeated occurrences in the same patient of outcomes (any diabetes-related endpoint, myocardial infarction [MI], stroke, peripheral vascular disease and microvascular disease) were accounted for with the Wei, Lin and Weissfeld method. RESULTS: As previously shown, the intervention reduced the rates of first occurrence of both MI and any diabetes-related endpoint. However, for all outcomes, the HR for a second event showed a statistically non-significant tendency to be increased. We estimated a combined HR for all marginal failure times, regardless of whether they were first, second or later events. This showed that the intervention had no effect on the rate of any of the outcomes, including MI (HR 0.89, 95% CI 0.76, 1.05) and any diabetes-related endpoint (HR 0.98, 95% CI 0.87, 1.09). CONCLUSIONS/INTERPRETATION: In the DCGP study, a smaller proportion of patients who received structured care experienced a first occurrence of MI or any diabetes-related endpoint compared with patients who received routine care. However, the patients who received structured care tended to experience more recurrent outcomes, so the total outcome rate was not affected by the intervention.


Subject(s)
Diabetes Mellitus, Type 2/drug therapy , Cardiovascular Diseases/etiology , Cardiovascular Diseases/prevention & control , Diabetes Mellitus, Type 2/complications , Female , Follow-Up Studies , Humans , Hypoglycemic Agents/therapeutic use , Male , Proportional Hazards Models
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