Journal of Personalized Medicine最新文献

Clinical research aims to answer questions that are of importance to daily clinical practice in order to improve and optimize disease diagnosis and therapy, which ultimately impacts patients' well-being [...].

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that poses critical challenges in global healthcare due to its increasing prevalence and severity. Diagnosing AD and other dementias, such as frontotemporal dementia (FTD), is slow and resource-intensive, underscoring the need for automated approaches. Methods: To address this gap, this study proposes a novel deep learning methodology for EEG classification of AD, FTD, and control (CN) signals. The approach incorporates advanced preprocessing techniques and CNN classification of FFT-based spectrograms and is evaluated using the leave-N-subjects-out validation, ensuring robust cross-subject generalizability. Results: The results indicate that the proposed methodology outperforms state-of-the-art machine learning and EEG-specific neural network models, achieving an accuracy of 79.45% for AD/CN classification and 80.69% for AD+FTD/CN classification. Conclusions: These results highlight the potential of EEG-based deep learning models for early dementia screening, enabling more efficient, scalable, and accessible diagnostic tools.

Introduction: Artificial intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy, treatment, and patient monitoring, benefiting older adults by offering personalized care plans. AI-powered tools help manage chronic conditions and maintain independence, making them a valuable asset in addressing aging challenges. Objectives: The objectives are as follows: 1. To identify and describe AI-power-based exercise programs for older adults. 2. To highlight primary evidence gaps in AI interventions for functional improvement and mobility. 3. To evaluate the quality of existing reviews on this topic. Methods: The evidence gap map (EGM) will follow the five-step method, adhering to the Campbell Collaboration guidelines and, if available at the time of reporting, PRISMA-AI standards. Guided by the Metaverse Equitable Rehabilitation Therapy framework, this study will categorize findings across domains like equity, health service integration, interoperability, governance, and humanization. The study will include systematic reviews, randomized controlled trials, and pre-and post-intervention designs. Results will be reported following PRISMA-AI guidelines. We will use AMSTAR-2 Checklist for Analyzing Systematic Reviews on AI Interventions for Improving mobility and function in Older Adults to evaluate the reliability of systematic reviews and focus on internal validity. Conclusions: This comprehensive analysis will act as a critical resource for guiding future research, refining clinical interventions, and influencing policy decisions to enhance AI-driven solutions for aging populations. The EGM aims to bridge existing evidence gaps, fostering a more informed, equitable, and effective approach to AI solutions for older adults.

Sensory evoked potentials (EPs), namely, somatosensory, visual, and brainstem acoustic EPs, are used in neurosurgery to monitor the corresponding functions with the aim of preventing iatrogenic neurological complications. Functional deficiency usually precedes structural defect, being initially reversible, and prompt alarms may help surgeons achieve this aim. However, sensory EP registration requires presenting multiple stimuli and averaging of responses, which significantly lengthen this procedure. As delays can make intraoperative neuromonitoring (IONM) ineffective, it is important to reduce EP recording time. The possibility of speeding up EP recording relies on differences between IONM and outpatient clinical neurophysiology (CN). Namely, in IONM, the patient is her/his own control, and the neurophysiologist is less constrained by norms and standards than in outpatient CN. Therefore, neurophysiologists can perform a personalized selection of optimal locations of recording electrodes, frequency filter passbands, and stimulation rates. Varying some or all of these parameters, it is often possible to significantly improve the signal-to-noise ratio (SNR) for EPs and accelerate EP recording by up to several times. The aim of this paper is to review how this personalized approach is or may be applied during IONM for recording sensory EPs of each of the abovementioned modalities. Also, the problems hindering the implementation and dissemination of this approach and options for overcoming them are discussed here, as well as possible future developments.

Objective. To investigate the relationships among neuropathic pain (NP), pain catastrophizing (PC), and central sensitization (CS) in relation to functional status and radiological damage in patients with knee osteoarthritis (OA). Methods. This cross-sectional study included knee OA patients derived from an observational cohort. The Spearman correlation test was used to analyze the relationship between the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the PainDetect Questionnaire (PDQ), Central Sensitization Inventory (CSI), and Pain Catastrophizing Scale (PCS). The Kruskal-Wallis test was employed to compare WOMAC scores according to CSI categories. A multivariate analysis was conducted to identify predictors of functional ability, with the WOMAC score as the dependent variable and the independent variables including pain-related indices such as PCS, PDQ, and CSI, along with Kellgren-Lawrence (K-L) grading and demographic characteristics. Results. This study included 149 patients (76.5% female; mean age 71.5 years; mean duration of pain 8.1 years). In total, 23.5% exhibited NP, 30.9% showed PC, and 33.6% had CS. Higher mean values of WOMAC were correlated with CSI categories (p < 0.0001). WOMAC showed a significant relationship with CSI (rho = 0.791; p < 0.0001), PDQ (rho = 0.766; p < 0.0001), and PCS (rho = 0.536; p < 0.0001). In the multiple regression analysis, WOMAC was independently associated with CSI (p < 0.0001), PDQ (p < 0.0001), and PC (p = 0.0001). No association was observed between the K-L grading and the other variables. Conclusions. A reduced functional capacity in patients with knee OA is correlated with the presence of NP, PC and CS, without being significantly associated with radiological damage.

Background: Periprosthetic joint infection (PJI) following knee arthroplasty can significantly compromise patient mobility and quality of life. The newly proposed TNM classification system, adapted from oncology, categorizes PJI severity but has not yet been correlated with both subjective and objective outcomes post PJI treatment. Objective: This study evaluates the applicability of the TNM classification system for predicting outcomes in knee PJI revision surgeries. Methods: We conducted a retrospective analysis of 108 patients who underwent revision surgeries for knee PJI at our institution from January 2012 to January 2023. We assessed the correlation between the TNM classification and postoperative outcomes using the Knee Society Score (KSS) function and knee score, as well as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Results: The TNM classification demonstrated that higher 'T' stages were significantly associated with worse functional and subjective outcomes. The 'N' classification had limited predictive value, likely due to treatment adjustments based on pathogen type. The 'M' classification correlated with functional outcomes but not with subjective scores, suggesting that patients with more severe preoperative comorbidities might adjust their expectations. Conclusions: While the TNM classification shows potential, its current form as a prognostic tool in PJI management is limited. Enhancing the 'T' component, coupled with the integration of a validated morbidity score such as the CCI could improve its prognostic value. Despite its shortcomings, the TNM system may still provide valuable prognostic insights for both patients and surgeons in tackling complex PJI.

Background: This study aims to evaluate the safety and efficacy of prostatic artery embolization (PAE) in elderly, multimorbid patients with benign prostatic hyperplasia (BPH). Additionally, it seeks to identify technical and clinical factors that predict clinical failure at the mid-term follow-up. Methods: We analyzed the clinical records of 175 consecutive patients who underwent PAE. Technical success was defined as achieving embolization on at least one side. Safety was assessed using the Clavien-Dindo classification. The pre-procedural international prostate symptom score (IPSS), quality of life (QoL) score, prostate volume (PV), prostate-specific antigen (PSA), maximum urinary flow rate (Qmax), and post-void residual urine (PVR) were compared with values assessed at the follow-up evaluation. Clinical failure was defined as no improvement or worsening of lower urinary tract symptoms (LUTS) based on the IPSS at the follow-up evaluation. Univariate and multivariate regression models were applied to identify predictors of clinical failure. Results: 158 patients met the inclusion criteria. The median age was 74 years (68, 79), with a median ASA score of 2 (2, 3) and a Charlson comorbidity index (CCI) of 5 (4, 7). Follow-up assessments were carried out at a median of 12 months (0, 1). IPSS decreased by -5 points (-8, 0), QoL by -1 point (-1, 0), PV by -19 cc (-26, -8), PVR by -45 cc (-25 to -80), and PSA by -1.1 ng/mL (-2.5, -0.2) (p < 0.01); while Qmax improved by 4 mL/s (2, 6) (p < 0.01). A total of 44 patients (30.3%) experienced clinical failure, which was significantly correlated with unilateral embolization (p < 0.01). Multivariate regression analysis indicated that higher CCI, elevated PVR, and the use of larger microspheres were associated with poorer clinical outcomes, with odds ratios of 2.17 (95% CI: 1.4-3.38), 1.02 (95% CI: 1.01-1.03), and 26.83 (95% CI: 4.81-149.8), respectively (p < 0.01). Conclusions: PAE is a safe and effective treatment for elderly multimorbid patients with BPH. Comprehensive pre-procedural clinical assessment, incorporating the CCI and PVR, is essential to optimize treatment outcomes.

Background/Objectives: Next-generation sequencing (NGS) can explain how genetics influence morbidity and mortality in children. However, it is unclear whether health providers will perceive and use such treatments. We conducted a discrete choice experiment (DCE) to understand Italian health professionals' preferences for NGS to improve the diagnosis of paediatric genetic diseases. Methods: The DCE was administered online to 125 health professionals in Italy. We documented attributes influencing professionals' decisions of NGS, including higher diagnostic yield, shorter counselling periods, cost, turnaround time, and the identification of fewer variants of unknown significance. Results: Results show that factors such as higher diagnostic yield, shorter counselling periods, lower costs, and faster turnaround times positively influenced the adoption of NGS tests. Willingness to pay (WTP) estimates varied from EUR 387 (95% CI, 271.8-502.9) for 7% increase in the diagnostic yield to EUR 469 (95% CI, 287.2-744.9) for a decrease of one week in the turnaround time. Responders would reduce diagnostic yield by 7% to decrease the turnaround time by one week in both the preference and the willingness to trade (WTT) spaces. Respondents prioritised diagnostic yield (RI = 50.36%; 95% CI 40.2-67.2%) compared to other attributes. Conclusions: therefore, health professionals value NGS for allowing earlier, more accurate genetic diagnoses.

Total hip arthroplasty (THA) is a widely performed surgical procedure that has evolved significantly due to advancements in artificial intelligence (AI) and robotics. As demand for THA grows, reliable tools are essential to enhance diagnosis, preoperative planning, surgical precision, and postoperative rehabilitation. AI applications in orthopedic surgery offer innovative solutions, including automated hip osteoarthritis (OA) diagnosis, precise implant positioning, and personalized risk stratification, thereby improving patient outcomes. Deep learning models have transformed OA severity grading and implant identification by automating traditionally manual processes with high accuracy. Additionally, AI-powered systems optimize preoperative planning by predicting the hip joint center and identifying complications using multimodal data. Robotic-assisted THA enhances surgical precision with real-time feedback, reducing complications such as dislocations and leg length discrepancies while accelerating recovery. Despite these advancements, barriers such as cost, accessibility, and the steep learning curve for surgeons hinder widespread adoption. Postoperative rehabilitation benefits from technologies like virtual and augmented reality and telemedicine, which enhance patient engagement and adherence. However, limitations, particularly among elderly populations with lower adaptability to technology, underscore the need for user-friendly platforms. To ensure comprehensiveness, a structured literature search was conducted using PubMed, Scopus, and Web of Science. Keywords included "artificial intelligence", "machine learning", "robotics", and "total hip arthroplasty". Inclusion criteria emphasized peer-reviewed studies published in English within the last decade focusing on technological advancements and clinical outcomes. This review evaluates AI and robotics' role in THA, highlighting opportunities and challenges and emphasizing further research and real-world validation to integrate these technologies into clinical practice effectively.

Introduction: Maintenance therapy is crucial in managing and preventing symptom relapse in gastroesophageal reflux disease (GERD), with continuous and on-demand therapy being the common approaches. However, maintenance therapy using potassium-competitive acid blockers (P-CABs), such as fexuprazan, remains incompletely evaluated. Methods: This single-center, single-arm, prospective cohort study enrolled individuals with weekly heartburn or acid regurgitation and confirmed erosive esophagitis. The participants received 40 mg fexuprazan daily for 4 weeks as initial therapy, followed by 4 weeks of maintenance therapy. Patients chose either continuous or on-demand therapy for maintenance, according to their preference. The primary endpoint was the proportion of patients selecting on-demand therapy. The symptom scores were assessed using the GERD questionnaire (GERD-Q) and patient assessment of upper-gastrointestinal-disorders symptoms questionnaire (PAGI-SYM). Results: The 31 included participants showed a significant reduction in symptom scores after initial treatment (baseline vs. 4-week: GERD-Q, 9.0 vs. 6.5, p < 0.001; PAGI-SYM, 29.0 vs. 10.8, p < 0.001). Twenty-one (67.7%) patients chose on-demand therapy after initial treatment. The symptom scores did not differ significantly before and after maintenance therapy (4-week vs. 8-week: GERD-Q, 6.5 vs. 6.0, p = 0.225; PAGI-SYM, 10.8 vs. 9.0, p = 0.354). Although this relation was not significant, patients experiencing larger decreases in symptom scores tended to prefer on-demand therapy. After maintenance therapy, the symptom scores did not differ between continuous and on-demand therapy (GERD-Q, 5.3 vs. 6.3, p = 0.342; PAGI-SYM, 9.4 vs. 8.8, p = 0.611). Conclusions: Fexuprazan was effective as an initial and maintenance therapy in patients with GERD who showed typical symptoms. Approximately 68% of the patients preferred on-demand therapy as a maintenance treatment. Based on the patient's preference for maintenance therapy, symptom control did not differ between continuous and on-demand therapy.