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•AI tools can assist risk stratification of older people who have fallen and are living with frailty.•AI models designed for the care of falls and frailty often lack strong external validation.•Digital bias can exaggerate healthcare inequities if AI is under poor governance.•AI’s role should be to synergise, not replace, CGA and multidisciplinary team-based care.•Clinicians require clear guidelines and policies to appraise and use AI appropriately. Older people living with falls and frailty are common in emergency attendances, admissions and functional decline. Artificial intelligence (AI) and machine learning (ML) are increasingly incorporated in risk prediction, service streamlining and re-engineering, yet their roles in healthcare practice remain unclear. This CME article provides a practical overview for clinicians of acute care and internal medicine with a special interest in older people’s care. We summarise emerging applications of AI and AI-assisted tools across the falls and frailty care pathway, from community support through the emergency department, orthogeriatrics and post-acute rehabilitation. We highlight potential benefits: enhanced risk stratification, facilitation of comprehensive geriatric assessment (CGA), rehabilitation and delivery of care transition programmes. We then discuss challenges and ethical concerns, for instance, ‘digital ageism’, automation bias and weak evidence for impact. Finally, we outline pragmatic questions and steps that clinicians can adopt when using AI-enabled tools in clinical settings.

Purpose Minimum training recommendations to become a specialist geriatrician in the EU have been published and in this study we compared these recommendations with content from the post-graduate training scheme in Geriatric Medicine in Ireland. Methods We examined the content of didactic study-day lectures delivered during Geriatric medicine training in Ireland. We compared how both the formal Irish curriculum and the content of the study days match up with the 36 items that are identified as core knowledge content areas. Results The Irish geriatric medicine curriculum outlined that 30 of the 36 knowledge areas from the European curriculum should be covered. Formal teaching was delivered on 33 of the 36 knowledge components that are outlined in the European curriculum. 24 of 36 topics were covered at least twice. Conclusion There was a high concordance between the content of the Irish and European post-graduate curriculum in Geriatric medicine.

Introduction Acutely hospitalised older patients often live with frailty and have an increased risk of impaired physical function. Previous studies suggest that exercise might mitigate the risk of physical impairment; however, further research is needed to compare the effect of different types of exercise interventions. In this paper, we report a protocol for a trial that aims to examine (1) if multicomponent exercise interventions (interventions that include both mobility and strengthening exercises) have effects on physical function compared with usual care in older adults and (2) if a comprehensive multicomponent exercise programme is more effective than a simple multicomponent exercise programme that only include walking and sit-to-stand exercises.Methods and analysis This is a three-armed randomised controlled trial, with two intervention groups (comprehensive and simple exercise programme) and a control group receiving usual care. We will include 320 participants aged ≥75 years from geriatric medical departments of four hospitals in Stockholm, Sweden. Assessments will be conducted at hospital admission, discharge and 3 months thereafter concerning physical function (primary outcome), activities of daily living, health-related quality of life, sarcopenia and falls. The number of readmissions will be registered up to 1 year after discharge. Data will be analysed with linear mixed effects models, according to the intention-to-treat approach.Ethics and dissemination Ethical approval for this trial has been granted by the Swedish Ethical Review Authority (approval number 2022-03032-01). Data collection will consider the information requirement, the requirement of consent, confidentiality obligations and the utilisation requirement. Trial findings will be disseminated through multiple channels, including scientific publications and conferences, and workshops with healthcare professionals and the public.Trial registration number NCT05366075

The European Cooperation in Science and Technology (COST) Action 21122, PROmoting GeRiAtric Medicine in countries where it is still eMergING (PROGRAMMING) developed an online open survey to assess the educational interests and needs of health care professionals and final-year medical students across participating countries. This survey aims to establish a current baseline for developing educational content on geriatric medicine for nongeriatricians and a framework for its delivery. This paper describes the aim, development, structure, content, and dissemination of this survey. The mixed methods electronic survey, initially developed in English through a cocreation process with key stakeholders, was subsequently translated into 24 languages. It received ethics approval from multiple participating countries. Within- and cross-country analyses of the survey data will be conducted using descriptive and inferential statistics for quantitative data and content analyses for qualitative data. National and international teams will conduct analyses in parallel exploring responses within a specific country or region, professional category (or among medical students), or setting of work. Basic descriptive statistics and chi-square tests will evaluate differences in knowledge, relevance, and interest in geriatric topics across countries, professions, and settings of work. The effectiveness of formal education in geriatric medicine and clinical rotations in geriatric settings versus the lack thereof in promoting higher self-perceived knowledge on geriatric medicine topics will be explored using binary logistic regression. We will provide basic descriptive statistics (frequencies) of reported barriers to receiving further training in geriatric medicine and the effectiveness of various teaching methods as rated by the respondents and explore differences across countries, professions, and settings using chi-square tests. We will conduct qualitative content analyses of free-text responses to the questions exploring professionals' and medical students' thoughts on caring for older people and medical students' thoughts on becoming geriatricians. The survey included the following sections: Informed Consent, Demographics, Topics and Skills, Medical Students vs. Professionals, Current Profession (for professionals), Previous Education in Geriatric Medicine (for professionals), Education in Geriatric Medicine (for medical students), Interest in Care of Older People or Geriatric Medicine, Suggestions for Courses in Care for Older People or Geriatric Medicine, and Closure. The survey was disseminated between October 9, 2023, and June 5, 2024, and received 6099 responses; after cleaning, there were 5922 (97.1%) responses (n=5474, 92.43% from professionals and n=448, 7.57% from medical students). This survey's findings will inform educational projects across the PROGRAMMING countries. We will share these findings with national and international stakeholders, including professional societies, medical schools, and other relevant organizations. We will advocate for professional educational curricula to include geriatric topics rated as relevant by the survey respondents and promote clinical rotations in geriatric settings and teaching methods rated as effective by the survey respondents. DERR1-10.2196/64985.

Although the current low workforce availability of care of the elderly (COE) physicians, geriatric medicine specialists, and geriatric psychiatrists is undeniable, the ongoing demographic shift means this situation will only worsen. This evolving crisis is outlined clearly in the article “Updated Inventory and Projected Requirements for Specialist Physicians in Geriatrics” by Basu et al. found in this issue of the Canadian Geriatrics Journal.

A woman in her 80s with known metastatic small-cell oropharyngeal cancer was admitted after a fall. There was proximal limb weakness with hypertension, metabolic alkalosis, hypokalaemia and hyperglycaemia. CT scans revealed progression of her cancer with enlarging liver and lung metastases. Her admission was complicated by delirium and progressive dysphagia relating to her primary oropharyngeal malignancy. Cortisol and adrenocorticotropic hormone (ACTH) were markedly raised and were not suppressed after overnight and high-dose dexamethasone tests. Typical clinical features of Cushing’s syndrome were absent. She was diagnosed with ectopic ACTH syndrome secondary to small-cell oropharyngeal cancer. Metyrapone and spironolactone were commenced; however, the patient deteriorated, and a decision was made to prioritise her comfort over escalating treatment.

Life-sustaining and life-improving surgical interventions are increasingly available to older, frailer patients, many of whom have multimorbidity. Physicians can help support perioperative multidisciplinary teams with assessment and preoperative optimisation of physiological reserve, comorbidities and associated geriatric syndromes. Similar structured support can be useful in the postoperative period where older patients are at increased risk of delirium, medical complications, increased functional dependency and where discharge planning can prove more difficult than in younger cohorts. Comprehensive geriatric assessment has been shown to improve outcomes and is now embedded in most UK-based services for traumatic hip fracture. Perioperative comprehensive geriatric assessment has been explored in other surgical disciplines and procedures and, where evaluated, has been associated with improved outcomes. The need to support older patients with frailty undergoing surgery exceeds the capacity of specialist geriatricians. Other groups of healthcare professionals need to nurture the core competencies to support this group perioperatively.

The increasing access to health data worldwide is driving a resurgence in machine learning research, including data-hungry deep learning algorithms. More computationally efficient algorithms now offer unique opportunities to enhance diagnosis, risk stratification, and individualised approaches to patient management. Such opportunities are particularly relevant for the management of older patients, a group that is characterised by complex multimorbidity patterns and significant interindividual variability in homeostatic capacity, organ function, and response to treatment. Clinical tools that utilise machine learning algorithms to determine the optimal choice of treatment are slowly gaining the necessary approval from governing bodies and being implemented into healthcare, with significant implications for virtually all medical disciplines during the next phase of digital medicine. Beyond obtaining regulatory approval, a crucial element in implementing these tools is the trust and support of the people that use them. In this context, an increased understanding by clinicians of artificial intelligence and machine learning algorithms provides an appreciation of the possible benefits, risks, and uncertainties, and improves the chances for successful adoption. This review provides a broad taxonomy of machine learning algorithms, followed by a more detailed description of each algorithm class, their purpose and capabilities, and examples of their applications, particularly in geriatric medicine. Additional focus is given on the clinical implications and challenges involved in relying on devices with reduced interpretability and the progress made in counteracting the latter via the development of explainable machine learning.

ObjectivesThe objective was to describe the prevalence of geriatric conditions among older medical patients in the emergency department (ED) and the association with admission, mortality, reattendance and loss of independency.DesignPopulation-based prospective cohort study.SettingED of a large university hospital.ParticipantsAll medical patients ≥65 years of age from a single municipality with a first attendance to the ED during a 1-year period (November 2013 to November 2014).Primary and secondary outcome measuresBased on information from healthcare registers, we defined geriatric conditions as disability, recently increased disability, polypharmacy and comorbidity. Outcomes were admission, length of admission, 30 days postdischarge mortality, 30 days hospital reattendance and home care dependency 0–360 days following ED contact.ResultsTotally, 3775 patients (55% women) were included, age 78 (71–85) years (median (IQR)). No patients were lost to follow-up. The prevalence of 0–4 geriatric conditions was 14.9%, 27.3%, 25.2%, 22.3% and 10.3%, respectively. The number of conditions was significantly associated with hospital admission, length of admission, 30 days postdischarge mortality and 30 days hospital reattendance. Among patients with no geriatric conditions, 70% lived independent all 360 days after discharge, whereas all patients with ≥3 conditions had some dependency or were dead within 360 days following discharge.ConclusionAmong older medical patients in the ED, 50% had two or more geriatric conditions which were associated with poor health outcomes. This highlights the need for studies of the effect of geriatric awareness and competences in the ED.

Purpose The heterogeneity of very old patients (age ≥ 80 years) and the prevalence of complex geriatric syndromes in this cohort constitute major challenges for the classical methods of evidence-based medicine to inform clinical practice. The lack of robust guidance for the management of critical conditions in these patients contributes to considerable uncertainty among practitioners and unwarranted variations of care. The European Society of Intensive Care Medicine (ESICM) initiated a Delphi study to translate the empirical knowledge of experts in this field into consensus-based recommendations for clinical practice. Methods A multi-national group of specialists in intensive care, emergency, and geriatric medicine provided opinions on managing very old patients with critical conditions. Strong or moderate consensus was defined as having at least 90% or 80% of experts, respectively, expressing agreement or disagreement on the three highest or lowest levels of a 9-points Likert scale. Results Twenty-eight members of the expert steering group and 82 additional experts completed two Delphi rounds. After discussing the results, the steering group issued recommendations for 48 statements and 2 checklists for which consensus was achieved. In addition to determining fundamental principles, they include advice on goals of care and the decision-making about admission to and treatment of patients in intensive care and the management after discharge. Conclusion A multi-disciplinary group of experts achieved consensus on recommendations concerning intensive care for very old patients, which were approved and endorsed by ESICM. The implementation requires a careful analysis of available healthcare resources and should proceed in a stepwise fashion.