Journal of Personalized Medicine最新文献

Background: the present multicenter retrospective study aimed to evaluate the efficacy and safety of intra-class switching between interleukin-17A (IL-17A) inhibitors, specifically from ixekizumab to secukinumab, in patients with plaque psoriasis. Methods: this study included 11 patients (6 male, 5 female) who had previously received ixekizumab and then were switched to secukinumab. Patients' PASI, DLQI, and pain VAS (in those with psoriatic arthritis) were evaluated at weeks 16, 24, 54, and 98. Results: PASI-90 was reached in 10 (91%) cases at week 24. One patient experienced secondary failure to secukinumab at week 98. No adverse events were reported. Conclusions: overall, the majority of patients experienced a favorable response to secukinumab, suggesting that it may be an effective treatment option for patients with an inadequate response or loss of efficacy to ixekizumab.

Background/Objectives: This study aimed to develop a machine learning (ML) algorithm that can predict unplanned reoperations and surgical/medical complications after vestibular schwannoma (VS) surgery. Methods: All pre- and peri-operative variables available in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (n = 110), except those directly related to our outcome variables, were used as input variables. A deep neural network model consisting of seven layers was developed using the Keras open-source library, with a 70:30 breakdown for training and testing. The feature importance of input variables was measured to elucidate their relative permutation effect in the ML model. Results: Of the 1783 patients with VS undergoing surgery, unplanned reoperation, surgical complications, and medical complications were seen in 8.5%, 5.2%, and 6.2% of patients, respectively. The deep neural network model had area under the curve of receiver operating characteristics (ROC-AUC) of 0.6315 (reoperation), 0.7939 (medical complications), and 0.719 (surgical complications). Accuracy, specificity, and negative predictive values of the model for all outcome variables ranged from 82.1 to 96.6%, while positive predictive values and sensitivity ranged from 16.7 to 51.5%. Variables such as the length of stay post-operation until discharge, days from operation to discharge, and the total hospital length of stay had the highest permutation importance. Conclusions: We developed an effective ML algorithm predicting unplanned reoperation and surgical/medical complications post-VS surgery. This may offer physicians guidance into potential post-surgical outcomes to allow for personalized medical care plans for VS patients.

Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements in machine learning, deep learning, robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible and are driven by AI-based large language models (LLMs). These chatbots have facilitated new research avenues and have gained traction in both clinical and surgical applications in ophthalmology. They are also increasingly being utilized in studies on ophthalmology-related exams, particularly those containing multiple-choice questions (MCQs). This narrative review evaluates both the opportunities and the challenges of integrating chatbots into ophthalmology research, with separate assessments of studies involving open- and close-ended questions. While chatbots have demonstrated sufficient accuracy in handling MCQ-based studies, supporting their use in education, additional exam security measures are necessary. The research on open-ended question responses suggests that AI-based LLM chatbots could be applied across nearly all areas of ophthalmology. They have shown promise for addressing patient inquiries, offering medical advice, patient education, supporting triage, facilitating diagnosis and differential diagnosis, and aiding in surgical planning. However, the ethical implications, confidentiality concerns, physician liability, and issues surrounding patient privacy remain pressing challenges. Although AI has demonstrated significant promise in clinical patient care, it is currently most effective as a supportive tool rather than as a replacement for human physicians.

Background: Blunt thoracic trauma possesses unique physiopathological traits due to the complex interaction of immune and coagulation systems in the lung tissue. Hemogram-based ratios such as neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), neutrophil-to-lymphocyte × platelet (NLPR) ratios have been studied as proxies for immune dysregulation and survival in trauma. We hypothesized that blunt thoracic trauma patients exhibit distinct patterns of coagulation and inflammation abnormalities identifiable by the use of readily available hemogram-derived markers. Methods: The present study represents a retrospective observational analysis that included 86 patients with blunt thoracic trauma from a single high-volume level one trauma center. The primary outcome was mortality prediction in blunt thoracic trauma patients using these derived biomarkers. Secondary outcomes included phenotypes of the immune response and coagulopathy and the prediction of non-fatal adverse events. Results: A U-shaped distribution of mortality was found, with high rates of early deaths in patients with an NLPR value of <3.1 and high rates of late deaths in patients with NLPR > 9.5. A subgroup of blunt thoracic trauma patients expressing moderate inflammation and inflammation-induced hypercoagulation objectified as NLPR between 3.1 and 9.5 may have a survival benefit (p < 0.0001). The NLPR cut-off for predicting early deaths and the need for massive transfusion was 3.1 (sensitivity = 80.00% and specificity = 71.05%). Conclusions: These findings suggest that blunt thoracic trauma patients exhibit distinct phenotypes of the immune response and coagulopathy from the early stages. A controlled, balanced interaction of immune, coagulation, and fibrinolytic systems might effectively achieve tissue repair and increase survival in thoracic trauma patients and should be subject to further research.

Background: The aim of this study was to determine whether the oral parameter reflecting the total number of remaining permanent teeth (NRT) on both arches represents a predictability factor for a certain type of cardiovascular condition. Methods: This study included 84 subjects (40 males and 44 females) with ages between 50 and 89 years old, hospitalized in the Cardiology Department, who required dental examinations and specialized therapeutic interventions within the Emergency Dental Department of the same medical facility. Results: The study participant's data were statically analyzed. An unadjusted oral parameter NRT < 21 may represent a statistically significant predictor of developing cardiomyopathy (OR = 8.00, 95%CI = 2.78-23.06, p < 0.0005), heart valve disease and arterial hypertension, in association with other comorbidities (except for metabolic or pulmonary comorbidities). The regression analyses revealed a borderline-significant association between the adjusted NRT and metabolic comorbidities or coronary disease (OR = 0.37, 95%CI = 0.13-1.01, p = 0.052). Conclusions: Overall, the NRT may be considered a predictive marker that is relative to the risk of exhibiting cardiovascular conditions.

Musculoskeletal image-guided interventional radiology plays a key role in diagnosing and treating a range of conditions. Recent advances have yielded a wide variety of procedures that can be applied selectively and enable the personalisation of patient care. This review aims to outline the indications, applications, and techniques of subspecialist musculoskeletal oncology interventional procedures that were used at our tertiary referral centre with a focus on how these may be used to personalise patient management. The applications of a range of diagnostic and therapeutic image-guided interventional procedures including different methods of bone and soft tissue sampling, ablation, and augmentation procedures across different types of patients and pathologies are reviewed. To supplement the reviewed literature, we included our own experience and radiology images retrospectively collected from our Picture Archiving and Communication System (PACS). We demonstrate how the range of musculoskeletal image-guided interventions provide flexibility in the diagnosis and management of different tumours across different patient populations. This study provides the musculoskeletal interventional radiologist with insight into how to appropriately utlilise different techniques to optimise the diagnosis, treatment and palliation of tumours.

Background: Elderly patients with severe aortic stenosis (AS) need individualized decision-making in their management in order to benefit in terms of survival and improvement of quality of life. Frailty, a common condition in elderly patients, needs to be considered when weighing treatment options. Aim: We aimed to evaluate outcomes including survival and functional parameters according to disability criteria at six years of follow-up in an older population treated for severe AS using a frailty-based management. Methods: We evaluated data derived from a pilot clinical project involving elderly patients with severe AS referred to a tailored management based on classification by Fried's score into pre-frail, early frail, and frail and a multidimensional geriatric assessment. A Frailty, Inflammation, Malnutrition, and Sarcopenia (FIMS) score was used to predict the risk of mortality at six years of follow-up. Functional status was evaluated by telephonic interview. Results: At six years of follow-up, we found a survival rate of 40%. It was higher in the pre-frail patients (long rank < 0.001) and in the patients who underwent TAVR treatment (long rank < 0.001). The cut-off FIMS score value of ≥1.28 was an independent determinant associated with a higher risk of mortality at six years of follow-up (HR 2.91; CI 95% 1.7-5.1; p-value 0.001). We found a moderate increase of disability levels, malnutrition status, comorbidities, and number of drugs, but none of them self-reported advanced NYHA class III-IV heart failure. Conclusion: An accurate clinical-instrumental and functional geriatric evaluation in an elderly population with AS is required for a non-futile interventional treatment in terms of survival and functional status even in long-term follow-up.

The clinical relevance of musculoskeletal disorders (MSDs) continues to rise due to an ageing population and changes in lifestyle, and consequently this wide range of diseases and injuries remains a leading contributor to disability on a global scale [...].

Background/Objectives: Prostate cancer (PCa) outcomes vary significantly across risk groups. In early-stage localized PCa, the functional outcomes following radical prostatectomy (RP) can be severe, prompting increased interest in focal therapy, particularly High-Intensity Focused Ultrasound (HIFU). This study is to summarize the current clinical trials of HIFU on PCa. Methods: We reviewed clinical trials from major databases, including PubMed, MEDLINE, Scopus, and EMBASE, to summarize the current research on HIFU in PCa treatment. Results: The literature highlights that HIFU may offer superior functional outcomes, particularly in continence recovery, compared to RP and radiation therapy. However, the oncological efficacy of HIFU remains inadequately supported by high-quality studies. Focal and hemigland ablations carry a risk of residual significant cancer, necessitating comprehensive patient counseling before treatment. For post-HIFU monitoring, we recommend 3T magnetic resonance imaging (MRI) with biopsy at 6 to 12 months to reassess the cancer status. Biochemical recurrence should be defined using the Phoenix criteria, and PSMA PET/CT can be considered for identifying recurrence in biopsy-negative patients. Conclusions: Whole-gland ablation is recommended as the general approach, as it provides a lower PSA nadir and avoids the higher positive biopsy rates observed after focal and hemigland ablation in both treated and untreated lobes. Future study designs should address heterogeneity, including variations in recurrence definitions and surveillance strategies, to provide more robust evidence for HIFU's oncological outcomes.

Chronic kidney disease (CKD) is a major worldwide health concern because of its progressive nature and complex biology. Traditional diagnostic and therapeutic approaches usually fail to account for disease heterogeneity, resulting in low efficacy. Precision medicine offers a novel approach to studying kidney disease by combining omics technologies such as genomics, transcriptomics, proteomics, metabolomics, and epigenomics. By identifying discrete disease subtypes, molecular biomarkers, and therapeutic targets, these technologies pave the way for personalized treatment approaches. Multi-omics integration has enhanced our understanding of CKD by revealing intricate molecular linkages and pathways that contribute to treatment resistance and disease progression. While pharmacogenomics offers insights into expected responses to personalized treatments, single-cell and spatial transcriptomics can be utilized to investigate biological heterogeneity. Despite significant development, challenges persist, including data integration concerns, high costs, and ethical quandaries. Standardized data protocols, collaborative data-sharing frameworks, and advanced computational tools such as machine learning and causal inference models are required to address these challenges. With the advancement of omics technology, nephrology may benefit from improved diagnostic accuracy, risk assessment, and personalized care. By overcoming these barriers, precision medicine has the potential to develop novel techniques for improving patient outcomes in kidney disease treatment.