ObjectivesThe present study investigated (1) trends in the prevalence and incidence of knee osteoarthritis over a 20-year period (1996–2015); (2) trends in multimorbidity and (3) trends in drug prescriptions.DesignRegistry-based study.SettingPrimary healthcare, Flanders, Belgium.ParticipantsData were collected from Intego, a general practice-based morbidity registration network. In the study period between 1996 and 2015, data from 440 140 unique patients were available.Outcome measuresTrends in prevalence and incidence rate of knee osteoarthritis were computed using joinpoint regression analysis. The mean disease count was calculated to assess trends in multimorbidity. In addition, the number of drug prescriptions was identified by the Anatomical Therapeutic Chemical Classification code and trends were equally recorded with joinpoint regression.ResultsThe total age-standardised prevalence of knee osteoarthritis increased from 2.0% in 1996 to 3.6% in 2015. An upward trend was observed with an average annual percentage change (AAPC) of 2.5 (95% CI 2.2 to 2.9). In 2015, the prevalence rates in the 10 year age groups from the 45–54 years age group onwards were 3.1%, 5.6%, 9.0% and 13.9%, to reach 15.0% in people aged 85 years and older. The incidence remained stable with 3.75‰ in 2015 (AAPC=−0.5, 95% CI −1.4 to 0.5). The mean disease count significantly increased from 1.63 to 2.34 (p<0.001) for incident cases with knee osteoarthritis. Finally, we observed a significantly positive trend in the overall prescription of acetaminophen (AAPC=6.7, 95% CI 5.6 to 7.7), weak opioids (AAPC=4.0, 95% CI 0.9 to 7.3) and glucosamine (AAPC=8.6, 95% CI 2.4 to 15.1). Oral non-steroidal anti-inflammatory drugs were most prescribed, with a prevalence rate of 29.8% in 2015, but remained stable during the study period (AAPC=0.0, 95% CI −1.1 to 1.1).ConclusionsIncreased prevalence, multimorbidity, and number of drug prescriptions confirm an increased burden of knee osteoarthritis. In future, these trends can be used to prioritise initiatives for improvement in care.

ObjectivesTo assess the prevalence and incidence of heart failure (HF) stages A to C/D and their evolution over a 16-year period. Additionally, trends in comorbidities and cardiovascular (CV) treatment in patients with HF were studied in the same period.DesignRegistry-based study.SettingPrimary care, Flanders, Belgium.ParticipantsData were obtained from Intego, a morbidity registration network in which 111 general practitioners of 48 practices collaborate. In the study period between 2000 and 2015, data from 165 796 unique patients aged 45 years and older were available.Outcome measuresPrevalence and incidence were calculated for HF stage A, B and C/D by gender. Additionally, the trend in age-standardised prevalence and incidence rates between 2000 and 2015 was analysed with joint-point regression. The same model was used to study trends in comorbidity profiles in incident HF cases and trends in cardiovascular medication in prevalent HF cases.ResultsWe found a downward trend in the incidence and prevalence of HF stage C/D in Flemish general practice between 2000 and 2015, whereas the prevalence and incidence of stage A and B increased. The burden of comorbidities in incident HF cases increased during the study period, as shown by an increasing disease count (p<0.001). The prescription of cardiovascular medication such as renin-angiotensin-aldosterone system blockade, β-blockers and statins showed a sharp increase in the first part of the study period (2000–2008).ConclusionAge-standardised incidence and prevalence of HF stage C/D showed a slightly downward trend over the past 16 years, probably due to the sharp increase in cardiovascular treatment. However, the increasing age-standardised incidence and prevalence of stage A and B, as precursors of symptomatic HF, together with a rising comorbid burden, highlights the challenges we are still facing.

Aim To examine how the development of cardiovascular and renal disease (CVRD) translates to hospital healthcare costs in individuals with type 2 diabetes (T2D) initially free from CVRD. Methods Data were obtained from the digital healthcare systems of 12 nations using a prespecified protocol. A fixed country‐specific index date of 1 January was chosen to secure sufficient cohort disease history and maximal follow‐up, varying between each nation from 2006 to 2017. At index, all individuals were free from any diagnoses of CVRD (including heart failure [HF], chronic kidney disease [CKD], coronary ischaemic disease, stroke, myocardial infarction [MI], or peripheral artery disease [PAD]). Outcomes during follow‐up were hospital visits for CKD, HF, MI, stroke, and PAD. Hospital healthcare costs obtained from six countries, representing 68% of the total study population, were cumulatively summarized for CVRD events occurring during follow‐up. Results In total, 1.2 million CVRD‐free individuals with T2D were identified and followed for 4.5 years (mean), that is, 4.9 million patient‐years. The proportion of individuals indexed before 2010 was 18% (n = 207 137); 2010‐2015, 31% (361 175); and after 2015, 52% (609 095). Overall, 184 420 (15.7%) developed CVRD, of which cardiorenal disease was most frequently the first disease to develop (59.7%), consisting of 23.0% HF and 36.7% CKD, and more common than stroke (16.9%), MI (13.7%), and PAD (9.7%). The total cumulative cost for CVRD was US$1 billion, of which 59.0% was attributed to cardiorenal disease, 3‐, 5‐, and 6‐fold times greater than the costs for stroke, MI, and PAD, respectively. Conclusion Across all nations, HF or CKD was the most frequent CVRD manifestation to develop in a low‐risk population with T2D, accounting for the highest proportion of hospital healthcare costs. These novel findings highlight the importance of cardiorenal awareness when planning healthcare.

Background In case-control studies most algorithms allow the controls to be sampled several times, which is not always optimal. If many controls are available and adjustment for several covariates is necessary, matching without replacement might increase statistical efficiency. Comparing similar units when having observational data is of utter importance, since confounding and selection bias is present. The aim was twofold, firstly to create a method that accommodates the option that a control is not resampled, and second, to display several scenarios that identify changes of Odds Ratios (ORs) while increasing the balance of the matched sample. Methods The algorithm was derived in an iterative way starting from the pre-processing steps to derive the data until its application in a study to investigate the risk of antibiotics on colorectal cancer in the INTEGO registry (Flanders, Belgium). Different scenarios were developed to investigate the fluctuation of ORs using the combination of exact and varying variables with or without replacement of controls. To achieve balance in the population, we introduced the Comorbidity Index (CI) variable, which is the sum of chronic diseases as a means to have comparable units for drawing valid associations. Results This algorithm is fast and optimal. We simulated data and demonstrated that the run-time of matching even with millions of patients is minimal. Optimal, since the closest controls is always captured (using the appropriate ordering and by creating some auxiliary variables), and in the scenario that a case has only one control, we assure that this control will be matched to this case, thus maximizing the cases to be used in the analysis. In total, 72 different scenarios were displayed indicating the fluctuation of ORs, and revealing patterns, especially a drop when balancing the population. Conclusions We created an optimal and computationally efficient algorithm to derive a matched case-control sample with and without replacement of controls. The code and the functions are publicly available as an open source in an R package. Finally, we emphasize the importance of displaying several scenarios and assess the difference of ORs while using an index to balance population in observational data.

ObjectivesTo examine if the estimated glomerular filtration rate (eGFR) slope over a 5-year period is related to incident cardiovascular (CV) events in the following 5 years.DesignRetrospective cohort study.SettingPrimary care.ParticipantsAll patients aged ≥50 years with at least four eGFR measurements between 01 January 2006 and 31 December 2010 were included in the study.Outcome measuresDuring the follow-up period (01 January 2011 until 31 December 2015), CV events (acute myocardial infarction, stroke (cerebrovascular accident (CVA)/transient ischemic attack (TIA)), peripheral arterial disease and acute heart failure) were identified.MethodsThe slope was calculated by the least square method (in mL/min/year). The following slope categories were considered: (−1 to 1), (−3 to −1) (−5 to −3), ≤−5, (1 to 3), (3 to 5) and ≥5.00 mL/min/year. Cox proportional hazards model was used to assess the association between eGFR slope and incidence of CV events. Survival probability from CV events was estimated per slope category.Results19 567 patients had at least four eGFR measurements, of whom 52% was female. 12% of the ≤−5 slope category developed a new CV event in comparison to 7.8% of the reference group and 5.4% of the ≥5 slope category. Survival rates were worst in those with a slope ≤−5. Patients with a slope of (−5 to −3) and ≤−5 had an adjusted HR of 1.37 and 1.55, respectively. Most patients with a slope <−3 mL/min had an eGFR still >60 mL/min.ConclusionsNegative eGFR slopes of at least 3 mL/min/year give irrespectively of the eGFR itself a higher risk of CV events compared with patient groups with stable or improved kidney function. So the eGFR slope identifies an easy to define group of patients with a high risk for developing CV events.