INTRODUCTION: This service improvement project aimed to improve detection of incidental vertebral fractures on routine imaging. It embedded a vertebral fracture identification service (Optasia Medical, OM) on routine computerised tomography (CT) scans performed in this hospital as part of its Fracture Liaison Service (FLS).
METHODS: The service was integrated into the hospital's CT workstream. Scans of patients aged ≥ 50 years for 3 months were prospectively retrieved, alongside their clinical history and the CT report. Fractures were identified via OM's machine learning algorithm and cross-checked by the OM radiologist. Fractures identified were then added as an addendum to the original CT report and the hospital FLS informed. The FLS made recommendations based on an agreed algorithm.
RESULTS: In total, 4461 patients with CT scans were retrieved over the 3-month period of which 850 patients had vertebra fractures identified (19.1%). Only 49% had the fractures described on hospital radiology report. On average, 61 patients were identified each week with a median of two fractures. Thirty-six percent were identified by the FLS for further action and recommendations were made to either primary care or the community osteoporosis team within 3 months of fracture detection. Of the 64% not identified for further action, almost half was because the CT was part of cancer assessment or treatment. The remaining were due to a combination of only ≤ 2 mild fractures; already known to a bone health specialist; in the terminal stages of any chronic illness; significant dependency for activities of daily living; or a life expectancy of less than 12 months CONCLUSION: It was feasible to integrate a commercial vertebral fracture identification service into the daily working of a FLS. There was a significant increase in workload which needs to be considered by any future FLS planning to incorporate such a service into their clinical practice.
Methods: The medical records of 95 older patients (age ≥ 65) who attended the GMC from 16 December 2019 to 10 January 2020 were reviewed. Frailty was identified using the FRAIL scale and the CFS. Patient characteristics were investigated for their association with frailty and their difference in the prevalence of frailty by the FRAIL scale and CFS.
Results: The CFS identified nonsignificant higher prevalence of frailty compared to the FRAIL scale (21/95; 22.1% vs. 17/95; 17.9%, ratio of prevalence = 1.235, p=0.481). Minimal agreement was found between the FRAIL scale and the CFS (Kappa = 0.272, p < 0.001). Three out of 5 components of the FRAIL scale (resistance, ambulation, and loss of weight) were associated with frailty by the CFS. Higher prevalence of frailty was identified by the CFS in those above 70 years of age. The FRAIL scale identified more patients with frailty in ischaemic heart disease patients.
Conclusion: Patient characteristics influenced the choice of the frailty assessment tool. The FRAIL scale and the CFS may complement each other in providing optimized care to older patients who attended the GMC.
AIM: To develop a list of medications to facilitate appropriate prescribing among older adults.
METHODS: A preliminary list of PIM and potential prescribing omission (PPO) were generated from systematic review, supplemented with local pharmacovigilance data of adverse reaction incidents among older people. Twenty-one experts from nine specialties participated in two Delphi to determine the list of PIM and PPO in February and March 2023. Items that did not reach consensus after the second Delphi round were adjudicated by six geriatricians.
RESULTS: The preliminary list included 406 potential candidates, categorised into three sections: PIM independent of diseases, disease dependent PIM and omitted drugs that could be restarted. At the end of Delphi, 92 items were decided as PIM, including medication classes, such as antacids, laxatives, antithrombotics, antihypertensives, hormones, analgesics, antipsychotics, antidepressants, and antihistamines. Forty-two disease-specific PIM criteria were included, covering circulatory system, nervous system, gastrointestinal system, genitourinary system, and respiratory system. Consensus to start potentially omitted treatment was achieved in 35 statements across nine domains.
CONCLUSIONS: The newly developed PIM criteria can serve as a useful tool to guide clinicians and pharmacists in identifying PIMs and PPOs during medication review and facilitating informed decision-making for appropriate prescribing.