Explore the vast range of titles available.

Targeted fracture prevention strategies among late‐life adults should balance fracture risk versus competing mortality risk. Models have previously been constructed using Fine‐Gray subdistribution methods. We used a machine learning method adapted for competing risk survival time to evaluate candidate risk factors and create models for hip fractures and competing mortality among men and women aged 80 years and older using data from three prospective cohorts (Study of Osteoporotic Fractures [SOF], Osteoporotic Fracture in Men study [MrOS], Health Aging and Body Composition study [HABC]). Random forest competing risk models were used to estimate absolute 5‐year risk of hip fracture and absolute 5‐year risk of competing mortality (excluding post–hip fracture deaths). Models were constructed for both outcomes simultaneously; minimal depth was used to rank and select variables for smaller models. Outcome specific models were constructed; variable importance was used to rank and select variables for inclusion in smaller random forest models. Random forest models were compared to simple Fine‐Gray models with six variables selected a priori. Top variables for competing risk random forests were frailty and related components in men while top variables were age, bone mineral density (BMD) (total hip, femoral neck), and frailty components in women. In both men and women, outcome specific rankings strongly favored BMD variables for hip fracture prediction while frailty and components were strongly associated with competing mortality. Model discrimination for random forest models varied from 0.65 for mortality in women to 0.81 for hip fracture in men and depended on model choice and variables included. Random models performed slightly better than simple Fine‐Gray model for prediction of competing mortality, but similarly for prediction of hip fractures. Random forests can be used to estimate risk of hip fracture and competing mortality among the oldest old. Modest gains in performance for mortality without hip fracture compared to Fine‐Gray models must be weighed against increased complexity. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Provision of non-invasive vascular imaging results to individuals has been shown to improve cardiovascular disease risk factor control: its impact on diet remains uncertain. In this two-arm, single-blind, parallel, 12-week randomized controlled trial, 240 participants, 57.5% females aged 60–80 y had abdominal aortic calcification and clinical assessments performed at a hospital clinic. Participants were randomized 1:1 to receive (intervention n  = 121) or not (control n  = 119) their calcification results. Both groups received educational resources on cardiovascular disease risk control and were unblinded to the intervention. Outcome measures were performed at baseline and 12 weeks. The primary outcomes of the study were changes in fruit and vegetable intake measures over 12 weeks assessed using plasma carotenoid concentrations (biomarkers of FV intake) and a food frequency questionnaire. Secondary outcomes included 12-week changes in other aspects of the diet, physical activity, body weight, blood pressure, heart rate, lipid profile, glucose concentrations, estimated cardiovascular disease risk score, and medication use. Between-group differences were tested using linear mixed-effects regression. There were no between-group differences in the primary outcomes at 12 weeks: plasma carotenoids (mean difference +0.03 µg/mL [95%CI −0.06, 0.13]) and fruit and vegetable intakes (+18 g/d [−37, 72]). However, the provision of calcification results led to between-group differences in serum total (−0.22 mmol/L [−0.41, −0.04]) and non-HDL (−0.19 mmol/L [−0.35, −0.03]) cholesterol, and estimated cardiovascular disease risk score (−0.24% [−0.47, −0.02]). No between-group differences were seen for other secondary outcomes. In this work, providing vascular imaging results did not improve diet but did improve some cardiovascular disease risk factors (Australian and New Zealand Clinical Trials Registry ACTRN12618001087246). It is unclear whether providing the results of abdominal aortic calcification imaging to patients improves diet parameters. This randomized trial shows that this intervention does not lead to improvements in fruit and vegetable intake, while showing an effect on some cardiovascular disease risk factors used as secondary outcomes.

Cardiovascular disease is the most common cause of mortality among post-menopausal women. Our objective was to determine whether or not lateral spine images obtained on a bone densitometer to detect prevalent vertebral fracture can also accurately detect radiographic abdominal aortic calcification (AAC), an important risk factor for cardiovascular disease independent of clinical risk factors. One hundred seventy four postmenopausal women had bone densitometry, lateral spine densitometry imaging (called vertebral fracture assessment, or VFA), and lateral spine digital radiographs. Radiographs and VFA images were scored for AAC using a previously validated 24 point scale and a simplified, new 8 point scale (AAC-8). One hundred fifty six (90%) of the VFA images were evaluable for AAC. The non-parametric intraclass correlation coefficient between VFA and radiographic 24 point and AAC-8 readings, respectively, were 0.80 (95% C.I. 0.68-0.87) and 0.76 (95% C.I. 0.65-0.84). Areas under receiver operating characteristics (ROC) curves for VFA to detect those with a radiographic 24-point AAC score >or=5 were 0.86 (95% C.I. 0.77-0.94) using the 24 point scale and 0.84 (95% C.I. 0.76-0.92) using the AAC-8 scale. VFA imaging intended to detect prevalent vertebral fracture can also detect radiographic AAC, an important cardiovascular disease risk factor. Since bone densitometry is recommended for all women age 65 and older, VFA imaging at the time of bone densitometry offers an opportunity to assess this risk factor in the post-menopausal female population at very little incremental time and expense.

The association of weight loss with health care costs among older women is uncertain. Our study aim was to examine the association of objectively measured weight change with subsequent total health care (THC) costs and other health care utilization among older women. Our study population included 2,083 women (mean age 80.2 years) enrolled in the Study of Osteoporotic Fractures and U.S. Medicare Fee for Service. Weight loss and gain were defined, respectively, as ≥5% decrease and ≥5% increase in body weight, and weight maintenance as <5% change in body weight over a period of 4.5 years. THC costs, outpatient costs, hospitalizations, and skilled nursing facility [SNF] utilization were estimated from Medicare claims for 1 year after the period during which weight change was measured. The associations of weight change with THC and outpatient costs were estimated using generalized linear models with gamma variance and log link functions, and with hospitalizations and SNF utilization using logistic models. Adjusted for age and current body mass index (BMI), weight loss compared with weight maintenance was associated with a 35% increase in THC costs ($2148 [95% CI, 745 to 3552], 2014 U.S. dollars), a 15% increase in outpatient costs ($329 [95% C.I. -1 to 660]), and odds ratios of 1.42 (95% CI, 1.14 to 1.76) for ≥1 hospital stay and 1.45 (95% CI, 1.03 to 2.03) for ≥1 SNF stay. These associations did not vary by BMI category. After additional adjustment for multi-morbidity and functional status, associations of weight loss with all four outcomes were no longer significant. In conclusion, ≥5% weight loss among older women is not associated with increased THC and outpatient costs, hospitalization, and SNF utilization, irrespective of BMI category after accounting for multi-morbidity and impaired functional status that accompany weight loss.

The ability of the fracture risk assessment tool (FRAX) to discriminate between women who do and do not experience major osteoporotic fractures (MOFs) is suboptimal. Adding common clinical risk factors may improve discrimination. We used data from the Women's Health Initiative, a prospective study of women aged 50 to 79 years at baseline (n = 99,413; n = 5722 in BMD subset) enrolled at 40 US clinical centers. The primary outcome was incident MOFs assessed annually during 10 years' follow‐up. For prediction of incident MOF, we examined the area under the receiver operatic characteristic curve (AUC) and net reclassification index (NRI) of the FRAX model alone and FRAX plus additional risk factors (singly or together: type 2 diabetes mellitus, frequent falls [≥2 falls in the past year], vasomotor symptoms, self‐reported physical function score [RAND 36‐item Health Survey subscale), and lumbar spine BMD). For NRI calculations, high risk was defined as predicted MOF risk ≥20%. We also assessed calibration as observed MOF events/expected MOF events. The AUC value for FRAX without BMD information was 0.65 (95% CI, 0.65 to 0.66). Compared with the FRAX model (without BMD), the AUC value was not improved by the addition of vasomotor symptoms, diabetes, or frequent falls, but was minimally increased by adding physical function score (AUC 0.66, 95% CI, 0.66 to 0.67). FRAX was well‐calibrated for MOF prediction. The NRI of FRAX + additional variables versus FRAX alone was 5.7% (p < 0.001) among MOF cases and −1.7% among noncases (p > 0.99). Additional variables (diabetes, frequent falls, vasomotor symptoms, physical function score, or lumbar spine BMD) did not yield meaningful improvements in NRI or discrimination of FRAX for MOFs. Future studies should assess whether tools other than FRAX provide superior discrimination for prediction of MOFs. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Objective Metabolic dysregulation frequently co‐occurs with obesity, which has been shown to be a risk factor for lower extremity osteoarthritis (OA). We evaluated the association between metabolic syndrome (MetS), alone and in combination with obesity, and hip OA. Methods In two parallel cross‐sectional analyses, we studied 403 women from the Study of Osteoporotic Fractures (SOF) and 2354 men from the Osteoporotic Fractures in Men (MrOS) study. We used multivariable logistic regression to evaluate associations of obesity (body mass index ≥30 kg/m2) and/or MetS (three of five National Cholesterol Education Program Adult Treatment Panel III criteria) with clinical hip OA, defined as a modified Croft score of 2 or more or total hip replacement, and pain or limited range of motion. Our analysis adjusted for demographics. Results Approximately 3.5% of SOF women and 5.4% of MrOS men had clinical hip OA. Among women, obesity was not associated with hip OA, yet those with MetS had a 365% higher odds of hip OA (95% CI: 1.37‐15.83). Among men, those who had obesity had a 115% higher odds of hip OA (95% CI: 1.39‐3.32), yet MetS was not associated with hip OA. There was no interaction between MetS, obesity, and hip OA in either women or men. Conclusion In women, but not in men, MetS was associated with hip OA. In men, but not in women, obesity was associated with hip OA. These findings suggest that mechanical effects of obesity may predominate in the pathogenesis of hip OA in men, whereas metabolic effects predominate in women.

Summary Among those who use of liver-enzyme inducing anticonvulsant medication for more than 2 years, 27% have a prevalent vertebral fracture on vertebral fracture assessment (VFA) lateral spine imaging. VFA imaging at the time of bone densitometry may be appropriate for older individuals who are chronic users of these medications. Purpose It is unclear whether prevalent vertebral fractures are associated with use of anticonvulsant drugs, especially those that induce liver enzymes (LEI) that metabolize drugs and vitamin D. Our purpose was to estimate the prevalence of vertebral fracture on densitometric lateral spine images according to duration of prior anticonvulsant medication use. Methods Our study population was 11,822 individuals (mean [sd] age 76.1 [6.8] years, 94% female) who had bone densitometry with VFA between 2010 and 2018. Cumulative prior exposure to LEI anticonvulsants (carbamazepine, phenobarbital, phenytoin, valproic acid, n  = 538), non-LEI anticonvulsants (clonazepam, gabapentin, levetiracetam, others, n  = 2786), and other non-clonazepam benzodiazepines ( n  = 5082) was determined using linked pharmacy records. Prevalent vertebral fractures were identified on VFA images using the modified ABQ method. Logistic regression models were used to estimate the association of anticonvulsant drug exposure with prevalent vertebral fractures. Results Prevalence of one or more vertebral fractures was 16.1% for the entire analytic cohort, and 27.0%, 19.0%, and 18.5% for those with ≥ 2 years of prior LEI anticonvulsant use, non-LEI anticonvulsant use, and other benzodiazepine use, respectively. Adjusted for multiple covariates, use of prior LEI anticonvulsant medication for ≥ 2 years was associated with prevalent fracture on VFA (OR 1.48 [95% CI 1.04, 2.10]). Conclusion LEI anticonvulsant use for ≥ 2 years is associated with higher vertebral fracture prevalence. Lateral spine VFA imaging at the time of bone densitometry may be appropriate for older individuals who have used LEI anticonvulsant medications for ≥ 2 years.

INTRODUCTION Little is known regarding the relationship between anticholinergic medications and frailty in dementia with Lewy bodies (DLB). METHODS Anticholinergic Cognitive Burden Scale (ACB) and Claims‐based Frailty Index scores were calculated for 12 months prior to the dementia diagnosis using electronic medical record and claims data. Logistic regression was used to estimate the association between ACB and odds of frailty. RESULTS Compared to controls (n = 525), a diagnosis of DLB (n = 175; adjusted odds ratio [aOR]: 15.1, 95% confidence interval [CI]: 7.0–33.9) or Alzheimer's disease (AD: n = 525; aOR = 7.7, 95% CI: 4.4–13.7) was associated with an increased odds of frailty. Patients with DLB had greater prescriptions for anticholinergic medications than patients with AD (pB < 0.001; 23%  vs 9.7%). ACB was positively correlated with frailty for all groups (r = 0.30 to 0.47, p < 0.001). DISCUSSION Cumulative anticholinergic burden may be a modifiable predictor of frailty among older adults, including those newly diagnosed with dementia. Highlights Patients with newly diagnosed dementia with Lewy bodies (DLB) are more likely to have prescriptions for anticholinergic medications relative to patients newly diagnosed with Alzheimer's disease (AD) and older adults without documented cognitive impairment. In the year prior to a documented dementia diagnosis, 74% of patients with DLB and 66% of patients with AD had evidence of frailty. Anticholinergic medication burden was associated with frailty among all older adults in the study, including those without a dementia diagnosis.

This article reviews the implications of documentation of vertebral fracture for subsequent fracture risk and its role as an adjunct to bone-density assessment. Strategies for the management of vertebral fractures are also discussed. Foreword This Journal feature begins with a case vignette highlighting a common clinical problem. Evidence supporting various strategies is then presented, followed by a review of formal guidelines, when they exist. The article ends with the authors' clinical recommendations. Stage A 72-year-old woman presents with a 2-month history of increasing pain in her lower back, which has not improved with ibuprofen and is causing difficulty with walking and dressing. On questioning, she reports having lost about 5 cm (2 in.) of height since she was a young woman. On examination, there is mild kyphosis in her lower thoracic spine but no point tenderness. A lateral spine radiograph reveals that the L2 vertebra is biconcave in appearance, a finding that is consistent with a vertebral fracture (Figure 1). How should this case be managed? The Clinical Problem Vertebral fractures — . . .

ABSTRACT Objective: Non-adherence to oral bisphosphonate medications is a pervasive problem that blunts their potential to prevent fractures. Using multivariate modeling, we assessed the unique contribution of six classes of variables as drivers of non-adherence to bisphosphonates: (1) beliefs about osteoporosis and its prescription drug treatment, (2) ratings of the affordability of the prescription osteoporosis medications, (3) evaluations of the convenience of the bisphosphonate dosing frequency, (4) reports of troublesome side effects, (5) ratings of aspects of the bisphosphonate dosing regimen, and (6) risk factors for fracture. These categories of predictor variables were selected for investigation because they have been suggested by clinical-trial, survey, and observational studies in osteoporosis as reasons for non-adherence among patients taking prescription osteoporosis therapy. Methods: Women aged 45 or older who filled a prescription for an oral bisphosphonate in January or February of 2006 were identified through a dispensing database of 3300 US retail pharmacies. Subjects received a mailed pre-notification letter from the retail pharmacy chain informing them that someone would be calling them to invite them to participate in a telephone survey about osteoporosis medications. Trained interviewers used a standardized telephone script to recruit patients. Our definition of adherence was provisionally based on database records across a 7-month period and then cross-validated using patient self-report during the telephone recruitment. We measured beliefs regarding bisphosphonate effectiveness and safety, osteoporosis health concerns, concerns regarding drug costs, dosing frequency convenience, and experienced side effects using multi-item scales. Data were collected by telephone interview. Bivariate analyses were conducted using χ2 and t-tests, and multivariate analyses were conducted using logistic regression. Results: Of the 3274 women contacted for study participation, 1092 (33%) completed the interview and 1015 had analyzable data. Multivariate analyses showed that those most symptomatic in terms of side effects and those with the most skeptical beliefs in drug effectiveness and drug safety had odds ratios for non-adherence of 6.78 (95% CI 4.67–9.86), 5.70 (95% CI 3.65–8.92), and 2.26 (95% CI 1.49–3.42), respectively. In multivariate models, osteoporosis health concerns, dosing frequency convenience, and concerns regarding medication costs were not statistically associated with non-adherence to bisphosphonate therapy. Conclusions: The experience of troublesome side effects and patient beliefs regarding the effectiveness and safety of oral bisphosphonate medications prescribed for them are strongly associated with bisphosphonate non-adherence. Improving adherence to oral bisphosphonates may require providers to solicit and address patients’ medication beliefs and to proactively address side effects. Limitations of our study include: (1) the study sample is not likely to be a national random sample of bisphosphonate users, and (2) some evidence of non-response bias was observed.