Mihai Grecu

Introduction and Objective: Monitoring short-term changes in functional and neuromotor performance among older adults during a two-week hospital stay remains challenging in everyday geriatric practice. In this context, the present exploratory observational study aims at investigating the potential of the Clock Drawing Test, evaluated by means of quantitative geometric and kinematic parameters, as a method for capturing short-term fluctuations in visuomotor performance in routine multimodal inpatient care. The aim of the study is not to identify the isolated causal effects of single pharmacological or physical interventions, but to formulate hypotheses on the evolution of graphomotor trajectories within the framework of the usual clinical management. Methods: We conducted a prospective observational study involving 90 older adults hospitalized with chronic medical comorbidities and receiving multimodal inpatient care, including pharmacological treatments and physical rehabilitation techniques such as kinesiotherapy and TECAR therapy. Participants were classified into three diagnostic groups according to their cognitive status: no cognitive impairment (n = 40), mild cognitive impairment (n = 25), and dementia (n = 25). Results of the Clock Drawing Test performed at admission (T0) were compared with those performed at discharge (T14), focusing on contour integrity, numeral spacing, hand placement precision, and digital kinematic parameters. As the primary longitudinal outcome, paired T0 and T14 drawings were compared to evaluate short-term visuomotor changes. As a secondary exploratory analysis, baseline (T0) cognitive status classification was evaluated using Random Forest and Multilayer Perceptron models through participant-level 5-fold stratified cross-validation to determine how baseline neurocognitive and vascular profiles frame short-term graphomotor trajectories. Additionally, a binary (two-way) classification experiment (no cognitive impairment, n = 40, vs. cognitive impairment combining MCI and dementia, n = 50) was conducted, and the Structural Similarity Index (SSIM) was employed to objectively quantify whole-image morphological differences between CDT images obtained at admission (T0) and discharge (T14) using a standardized clock as ground truth. Results: Across the 90 complete pairs, significant Time × Regimen Cluster interactions were observed (p < 0.001). In Cluster 1 (multimodal physical and neurotrophic rehabilitation, n = 55), discharge evaluations showed significant improvements in contour closure gap (from 9.12 ± 2.45 mm to 1.78 ± 0.64 mm, p < 0.001), angular hand placement error (from 27.9° ± 6.8° to 4.1° ± 1.9°, p < 0.001), air-to-paper time ratio (from 1.84 ± 0.42 to 1.36 ± 0.31, p < 0.001), and Z-axis pressure stability (p < 0.001), whereas conceptual time-representation errors remained unchanged. Conversely, the small exploratory Cluster 2 subgroup that was treated with central nervous system depressants for acute inpatient insomnia or agitation showed a decline in graphomotor parameters (contour gap 2.15 ± 0.70 mm to 7.85 ± 2.30 mm, p = 0.016). This pattern could be a marker of either the pharmacodynamic sedation or the underlying acute neuropsychiatric conditions that warranted treatment. Conversely, Cluster 3 (standard medical maintenance, n = 27) remained stable (p > 0.20). For the secondary baseline classification task, the regularized Random Forest and Multilayer Perceptron models achieved promising internal cross-validation (out-of-fold) balanced accuracies of 86.00% and 88.13%, respectively. When reformulated as a two-way classification task (no impairment vs. MCI + dementia), out-of-fold overall accuracies increased to 92.22% (balanced accuracy 92.00%) for Random Forest and 94.44% (balanced accuracy 94.25%) for Multilayer Perceptron. Across 83 paired image sets, mean SSIM between T0 and T14 was 0.7494 ± 0.1016, while mean SSIM relative to the ground-truth clock changed from 0.7527 ± 0.0609 at T0 to 0.7352 ± 0.0687 at T14 (p < 0.001). Conclusions: Quantitative geometric and kinematic CDT parameters captured short-term changes in visuomotor execution over a 14-day hospitalization, while conceptual clock-drawing deficits remained associated with baseline diagnostic status in this exploratory observational cohort. Confounding by indication, practice effects and relief of pain or fatigue may also contribute to the observed trajectories in non-randomized multimodal care. Controlled trials and external multi-center validation cohorts are needed to confirm broader model generalizability and establish the independent effects of specific therapies.

Frailty is a dynamic state of reduced reserve whose expression reflects clinical, functional, cognitive, psychological, social, and environmental factors. This structured narrative review examines its conceptual models, determinants, consequences, multidimensional assessment, holistic interventions, and coordination across hospital, community, and home care. The literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, and Embase up to September 2026, supplemented by World Health Organization (WHO) documents, Google Scholar, and citation tracking. Physical phenotype, deficit-accumulation, multidimensional, judgement-based, and electronic approaches address different clinical questions and should not be treated as interchangeable. Brief case finding is most useful when it leads to assessment of modifiable contributors and a care plan aligned with the older person’s goals. Evidence most consistently supports progressive multicomponent exercise; nutritional support, medication review, falls prevention, and cognitive or social interventions should target identified needs. Hospital geriatric care, structured discharge, community follow-up, and home-based services require coordination, shared information, and reassessment, although evidence for particular models remains heterogeneous. Under-recognition, fragmented services, limited multidisciplinary capacity, caregiver burden, and unequal access constrain implementation. Frailty care is best understood as a longitudinal, person-centred process. Future research should test clinically meaningful outcomes, reproducible pathways, and equity in digital and non-digital delivery.

Cognitive disorders, from mild cognitive impairment to more serious dementia, are becoming more common and are directly related to the increased longevity and quality of life throughout the world. This demographic dynamic places a tremendous pressure on health care systems and fosters vigorous research in the international medical community, with the aim of identifying disease-modifying treatments able to stop or slow the progression of these neurodegenerative diseases. In total, 28 molecules are presently under development in this therapeutic portfolio at various phases of clinical studies. The main purpose of this research is to conduct a detailed analysis of therapeutic agents in Phase III clinical trials, a key phase for evaluating efficacy and safety. Another section describes monoclonal antibodies, a class of drugs that has already demonstrated impressive results as DMTs by specifically targeting pathogenic processes. Besides DMTs, there are several innovative approaches under research for treating acute exacerbations and symptom relief in neurodegenerative diseases. This review aims to critically synthesize the therapeutic landscape in dementia, pointing to promising directions for future clinical research. Of the 28 candidates evaluated, 7.1% met the primary efficacy endpoints in Phase III, 50.0% showed minimal or no efficacy, and 42.9% await definitive results. While monoclonal antibodies demonstrate a modest slowing of clinical progression in early-stage disease, many candidate compounds have failed, underscoring the ongoing difficulties of late-stage pharmaceutical development.

Frailty syndrome and Alzheimer’s disease are prevalent conditions in the elderly that are associated with aging, decreased quality of life, and a significant healthcare burden. Evidence for a relationship between physical frailty and neurodegenerative decline is accumulating. This study analyzed two independent datasets, a frailty dataset based on gait and mobility parameters and an AD dataset with clinical, functional and lifestyle variables, in order to evaluate and compare their classification performance using machine learning. Features were optimized using dimensionality reduction techniques to keep predictors of clinical significance and hyperparameter optimized Random Forest models were built to develop the best model. Evaluation was performed with Accuracy, F1-score, Matthews Correlation Coefficient and Area Under the Curve. The results showed that the models constructed on the whole AD dataset achieved maximum predictive power with an accuracy of 0.946, which was slightly increased to an accuracy of 0.948 after the selection of significant features. Diagnostic models based on frailty were able to demonstrate an ACC predictive capacity of 0.6418, and in terms of feature selection, improvements appeared in all indicators. Regarding the features derived from Alzheimer’s disease associated with geriatric frailty, they managed to surpass the ACC frailty features of 0.741 alone, suggesting some intercalation mechanisms between neurodegeneration and physical vulnerability. These findings show that machine learning algorithms accompanied by feature selection improve clinical discrimination and prediction of frailty and neurodegenerative disorders, which offers a promising aspect for geriatric assessment. The frailty models analyzed demonstrated an ACC predictive capacity of 0.6418, even though feature selection improved all indicators. Alzheimer’s disease-derived features associated with frailty outperformed features in the frailty dataset with an ACC of 0.741, suggesting the mechanism of overlap between neurodegeneration and physical vulnerability. These results support the theory of a motor-cognitive aging continuum, indicating that algorithmic machine learning techniques coupled with feature selection mainly provide computational validation for the biological intersection of neurodegeneration and physical frailty, rather than forming an independent predictive clinical model. Using these algorithms the study highlights shared pathophysiological mechanisms, providing a significant insight into systemic geriatric deterioration.

Background: Syncope in older adults is a frequent and diagnostically challenging presentation in prehospital emergency care, particularly in geographically remote areas with limited access to advanced cardiac services. While many syncopal episodes are benign, some are caused by life-threatening conduction disorders such as complete atrioventricular block (CAVB), which may manifest with seizure-like activity due to severe cerebral hypoperfusion. Case Presentation: We report the case of a 70-year-old man with a history of hypertension, residing in a remote rural area, who experienced a nocturnal tonic–clonic episode followed by recurrent loss of consciousness. Due to difficult ground access, a helicopter emergency medical service (HEMS) team was deployed. On arrival, the patient was hypotensive and severely bradycardic, with recurrent syncopal episodes. Electrocardiography (ECG) confirmed CAVB with a slow escape rhythm. Temporary transvenous pacing was initiated but required progressively higher output, up to approximately 80 mV, with intermittent loss of capture, indicating a high risk of pacing failure and asystole. The patient was transported by helicopter to a tertiary interventional cardiology center, where he experienced additional syncopal episodes before undergoing emergent implantation of a permanent single-chamber ventricular pacemaker (VVI). Permanent pacing resulted in immediate hemodynamic stabilization, and no further syncopal or seizure-like episodes were observed. Conclusions: In geriatric patients presenting with convulsive syncope, cardiac causes such as CAVB must be rapidly identified. Unstable temporary pacing with high capture thresholds represents a life-threatening condition requiring urgent permanent pacemaker implantation. HEMS plays a critical role in ensuring timely access to definitive cardiac care in geographically isolated regions.