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.
Objectives
To evaluate the predictive value of muscle strength and physical performance in the oldest old for all‐cause mortality; hospitalization; and the onset of disability, defined as a decline ...in activities of daily living (ADLs), independent of muscle mass, inflammatory markers, and comorbidities.
Design
A prospective, observational, population‐based follow‐up study.
Setting
Three well‐circumscribed areas of Belgium.
Participants
Five hundred sixty participants aged 80 and older were followed for 33.5 months (interquartile range 31.1–35.6 months).
Measurements
Grip strength, Short Physical Performance Battery (SPPB) score, and muscle mass were measured at baseline; ADLs at baseline and after 20 months; and all‐cause mortality and time to first hospitalization from inclusion onward. Kaplan‐Meier curves and Cox proportional hazards models were calculated for all‐cause mortality and hospitalization. Logistic regression analysis was used to determine predictors of decline in ADLs.
Results
Kaplan–Meier curves showed significantly higher all‐cause mortality and hospitalization in subjects in the lowest tertile of grip strength and SPPB score. The adjusted Cox proportional hazards model showed that participants with high grip strength or a high SPPB score had a lower risk of mortality and hospitalization, independent of muscle mass, inflammatory markers, and comorbidity. A relationship was found between SPPB score and decline in ADLs, independent of muscle mass, inflammation, and comorbidity.
Conclusion
In people aged 80 and older, physical performance is a strong predictor of mortality, hospitalization, and disability, and muscle strength is a strong predictor of mortality and hospitalization. All of these relationships were independent of muscle mass, inflammatory markers, and comorbidity.
The Short Physical Performance Battery (SPPB) is a well-established tool to assess lower extremity physical performance status. Its predictive ability for all-cause mortality has been sparsely ...reported, but with conflicting results in different subsets of participants. The aim of this study was to perform a meta-analysis investigating the relationship between SPPB score and all-cause mortality.
Articles were searched in MEDLINE, the Cochrane Library, Google Scholar, and BioMed Central between July and September 2015 and updated in January 2016. Inclusion criteria were observational studies; >50 participants; stratification of population according to SPPB value; data on all-cause mortality; English language publications. Twenty-four articles were selected from available evidence. Data of interest (i.e., clinical characteristics, information after stratification of the sample into four SPPB groups 0-3, 4-6, 7-9, 10-12) were retrieved from the articles and/or obtained by the study authors. The odds ratio (OR) and/or hazard ratio (HR) was obtained for all-cause mortality according to SPPB category (with SPPB scores 10-12 considered as reference) with adjustment for age, sex, and body mass index.
Standardized data were obtained for 17 studies (n = 16,534, mean age 76 ± 3 years). As compared to SPPB scores 10-12, values of 0-3 (OR 3.25, 95%CI 2.86-3.79), 4-6 (OR 2.14, 95%CI 1.92-2.39), and 7-9 (OR 1.50, 95%CI 1.32-1.71) were each associated with an increased risk of all-cause mortality. The association between poor performance on SPPB and all-cause mortality remained highly consistent independent of follow-up length, subsets of participants, geographic area, and age of the population. Random effects meta-regression showed that OR for all-cause mortality with SPPB values 7-9 was higher in the younger population, diabetics, and men.
An SPPB score lower than 10 is predictive of all-cause mortality. The systematic implementation of the SPPB in clinical practice settings may provide useful prognostic information about the risk of all-cause mortality. Moreover, the SPPB could be used as a surrogate endpoint of all-cause mortality in trials needing to quantify benefit and health improvements of specific treatments or rehabilitation programs. The study protocol was published on PROSPERO (CRD42015024916).
Aims
Little is known about the impact of inappropriate prescribing (IP) in community‐dwelling adults, aged 80 years and older. The prevalence at baseline (November 2008September 2009) and impact of ...IP (misuse and underuse) after 18 months on mortality and hospitalization in a cohort of community‐dwelling adults, aged 80 years and older (n = 503) was studied.
Methods
Screening Tool of Older People's Prescriptions (STOPP‐2, misuse) and Screening Tool to Alert to Right Treatment (START‐2, underuse) criteria were cross‐referenced and linked to the medication use (in Anatomical Therapeutic Chemical coding) and clinical problems. Survival analysis until death or first hospitalization was performed at 18 months after inclusion using Kaplan–Meier, with Cox regression to control for covariates.
Results
Mean age was 84.4 (range 80–102) years. Mean number of medications prescribed was 5 (range 0–16). Polypharmacy (≥5 medications, 58%), underuse (67%) and misuse (56%) were high. Underuse and misuse coexisted in 40% and were absent in 17% of the population. A higher number of prescribed medications was correlated with more misused medications (rs = .51, P < 0.001) and underused medications (rs = .26, P < 0.001).
Mortality and hospitalization rate were 8.9%, and 31.0%, respectively. After adjustment for number of medications and misused medications, there was an increased risk of mortality (HR 1.39, 95% CI 1.10, 1.76) and hospitalization (HR 1.26, 95% CI 1.10, 1.45) for every additional underused medication. Associations with misuse were less clear.
Conclusion
IP (polypharmacy, underuse and misuse) was highly prevalent in adults, aged 80 years and older. Surprisingly, underuse and not misuse had strong associations with mortality and hospitalization.
The aim of this paper was to describe the time trends in the prevalence of multimorbidity and polypharmacy in Flanders (Belgium) between 2000 and 2015, while controlling for age and sex.
Data were ...available from Intego, a Flemish-Belgian general practice-based morbidity registration network. The practice population between 2000 and 2015 was used as the denominator, representing a mean of 159,946 people per year. Age and gender-standardised prevalence rates were used for the trends of multimorbidity and polypharmacy in the total population and for subgroups. Joinpoint regression analyses were used to analyse the time trends and breaks in trends, for the entire population as well as for specific age and sex groups.
Overall, in 2015, 22.7% of the population had multimorbidity, while the overall prevalence of polypharmacy was 20%. Throughout the study period the standardised prevalence rate of multimorbidity rose for both sexes and in all age groups. The largest relative increase in multimorbidity was observed in the younger age groups (up to the age of 50 years). The prevalence of polypharmacy showed a significant increase between 2000 and 2015 for all age groups except the youngest (0-25 years).
For all adult age groups multimorbidity and polypharmacy are frequent, dynamic over time and increasing. This asks for both epidemiological and interventional studies to improve the management of the resulting complex care.
the prevalence of sarcopenia varies widely between studies. The objective of this study was to assess the prevalence of sarcopenia in a representative sample of persons aged 80 years and older ...according to the European Working Group on Sarcopenia in Older People (EWGSOP) algorithm and the proposed cut-off values. A secondary aim was to investigate the relationship between different individual criteria and low physical performance capacity.
baseline data of the prospective BELFRAIL study (BFC80+) were analysed. Sarcopenia status was determined according to the EWGSOP guidelines. The skeletal muscle mass index (SMI) was assessed according to bioelectrical impedance. Muscle strength and muscle performance were evaluated according to grip strength and the modified short physical performance battery (SPPBm). A logistic regression analysis was performed.
according to the EWGSOP algorithm, 12.5% of the participants were classified in the sarcopenia group. Sixty percent of the female participants had muscle strength values below the cut-off and 70% had low SPPBm values. In males, these prevalence values were 49.5% for grip strength and 39.7% for SPPB. The logistic regression analysis showed that low SPPBm was associated with grip strength (OR: 0.88, 95% CI: 0.84-0.92) independent of SMI.
in a population-based sample of the very old the prevalence of sarcopenia according to the EWGSOP algorithm is similar to the prevalence of sarcopenia with SMI as a single criterion. A large number of participants with a sufficient SMI value showed low muscle strength and/or a poor SPPBm score. A low SPPBm was associated with grip strength but not with SMI.
The Covid-19 pandemic had a tremendous impact on healthcare but uncertainty remains about the extent to which primary care provision was affected. Therefore, this paper aims to assess the impact on ...primary care provision and the evolution of the incidence of disease during the first year of the Covid-19 pandemic in Flanders (Belgium). Care provision was defined as the number of new entries added to a patient's medical history. Pre-pandemic care provision (February 1, 2018-January 31, 2020) was compared with care provision during the pandemic (February 1, 2020-January 31, 2021). A large morbidity registry (Intego) was used. Regression models compared the effect of demographic characteristics on care provision and on acute and chronic diagnoses incidence both prior and during the pandemic. During the first year of the Covid-19 pandemic, overall care provision increased with 9.1% (95%CI 8.5%;9.6%). There was an increase in acute diagnoses of 5.1% (95%CI 4.2%;6.0%) and a decrease in the selected chronic diagnoses of 12.8% (95% CI 7.0%;18.4%). Obesity was an exception with an overall incidence increase. The pandemic led to strong fluctuations in care provision that were not the same for all types of care and all demographic groups in Flanders. Relative to other groups in the population, the pandemic caused a reduction in care provision for children aged 0-17 year and patients from a lower socio-economic situation. This paper strengthened the claim that Covid-19 should be considered as a syndemic instead of a pandemic. During the first Covid-19 year, overall care provision and the incidence of acute diagnoses increased, whereas chronic diseases' incidence decreased, except for obesity diagnoses which increased. More granular, care provision and chronic diseases' incidence decreased during the lockdowns, especially for people with a lower socio-economic status. After the lockdowns they both returned to baseline.
Objectives
To investigate whether an observed association between cytomegalovirus (CMV) exposure and functional impairment and frailty in older adults is reproducible in a cohort of individuals aged ...80 and older.
Design
The baseline results of the BELFRAIL study, a prospective observational cohort study, were analyzed.
Setting
Three well‐circumscribed areas of Belgium.
Participants
Five hundred sixty‐seven persons aged 80 and older recruited by 29 general practitioners.
Measurements
Serum samples were assayed for levels of CMV immunoglobulin (Ig)G antibodies, interleukin (IL)‐6, and C‐reactive protein. Measures of functional impairment were the Physical Performance Battery, Activities of Daily Living, and the Mini‐Mental State Examination. Frailty was assessed using the Fried criteria.
Results
Positive CMV serology was found in 74% of the population, 61% of whom had a high anti‐CMV IgG titer (>250 IU/mL). CMV infection was not associated with functional or cognitive impairment. Positive CMV serology was negatively associated with prevalent frailty after adjusting for age, sex, level of education, comorbidity, smoking status, body mass index, and IL‐6 level. High levels of anti‐CMV IgG were associated with functional impairment. In the adjusted models, this relationship was no longer statistically significant. There was no association between prevalent frailty or cognitive impairment and high anti‐CMV IgG titers.
Conclusion
The findings of previous studies could not be confirmed. Moreover, positive CMV serology was found to be negatively associated with frailty. These apparently contradictory results may reflect a survival effect because the current study population was considerably older than the populations of older adults in previous studies.
Audit and feedback (A&F) is a widely used implementation strategy to evaluate and improve medical practice. The optimal design of an A&F system is uncertain and structured process evaluations are ...currently lacking. This study aimed to develop and validate a questionnaire to evaluate the use of automated A&F systems.
Based on the Clinical Performance Feedback Intervention Theory (CP-FIT) and the REFLECT-52 (REassessing audit & Feedback interventions: a tooL for Evaluating Compliance with suggested besT practices) evaluation tool a questionnaire was designed for the purpose of evaluating automated A&F systems. A Rand-modified Delphi method was used to develop the process evaluation and obtain validation. Fourteen experts from different domains in primary care consented to participate and individually scored the questions on a 9-point Likert scale. Afterwards, the questions were discussed in a consensus meeting. After approval, the final questionnaire was compiled.
A 34-question questionnaire composed of 57 items was developed and presented to the expert panel. The consensus meeting resulted in a selection of 31 questions, subdivided into 43 items. A final list of 30 questions consisting of 42 items was obtained.
A questionnaire consisting of 30 questions was drawn up for the assessment and improvement of automated A&F systems, based on CP-FIT and REFLECT-52 theory and approved by experts. Next steps will be piloting and implementation of the questionnaire.
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.
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.
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.
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.
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