Journal of Personalized Medicine最新文献

Background: Hip osteoarthritis (HOA) is a disease with globally rising incidence that leads to disability and morbidity, overall, in older populations, and might be primary or secondary to numerous risk factors. The most common idiopathic HOA is generally a diagnosis of exclusion, with pathogenetic mechanisms largely still misunderstood. We aimed to investigate the correlation between femoral-acetabular and spinopelvic anatomical and computed tomography (CT) characteristics, and the presence of primary OA.

Methods: We retrospectively analyzed CT scans from 2019 to 2021, excluding patients under 45 years or with conditions affecting the pelvis, sacrum, or lower limbs. Femoral, acetabular, and spinopelvic parameters were measured; signs of OA were analyzed in the hip and knee joints. Patients were categorized into two groups: A (isolated hip OA) and B (no OA); patients with hip OA, also presenting knee OA, were excluded from this study.

Results: In total, 232 cases were examined; statistical analyses compared CT parameters between 129 subjects from Group A and 103 patients of Group B. Group A showed a mean femoral version of 16 ± 4.53 degrees, significantly higher than Group B's 13.16 ± 4.37 degrees (p = 0.0001). Other parameters showed no significant differences.

Conclusion: This study highlights an association between femoral version and primary hip OA.

Background/objectives: Non-vitamin K antagonist oral anticoagulants (NOACs) have demonstrated similar effectiveness and safety profiles to vitamin K antagonists (VKAs) in treating nonvalvular atrial fibrillation (AF). Given their favorable pharmacological profile, including the rapid onset and offset of action, fixed dosing, and predictable pharmacokinetics with a consistent dose-response relationship, reducing the need for frequent blood tests, researchers have investigated the potential of NOACs in patients with AF and valvular heart disease (VHD).

Methods: Clinical trials, excluding patients with mechanical prosthetic valves or moderate/severe mitral stenosis, have shown the benefits of NOACs over VKAs in this population. However, there is a need for further research to determine if these findings apply to mechanical valve prostheses and NOACs.

Results: Several ongoing randomized controlled trials are underway to provide more definitive evidence regarding NOAC treatment in moderate to severe rheumatic mitral stenosis. Importantly, recent trials that included patients with atrial fibrillation and bioprosthetic valves (also transcatheter heart valves) have provided evidence supporting the safety of NOACs in this specific patient population. Ongoing research aims to clearly define the specific scenarios where NOACs can be safely and effectively prescribed for various types of VHD, including moderate/severe mitral stenosis and mechanical valves.

Conclusions: The aim of this review is to accurately identify the specific situations in which NOACs can be prescribed in patients with VHD, with a focus centered on each type of valvulopathy.

Background: The most commonly used method for low-density lipoprotein cholesterol (LDL-C) estimation is the Friedewald equation, which has notable limitations. However, more accurate methods have been proposed. This study investigates the advantages and limitations of these methods and identifies the contexts in which each equation is the most or least applicable.

Methods: A cohort of 222 individuals underwent a standard lipid profile assessment, including directly measuring their LDL-C (dLDL-C). LDL-C was also estimated using the Friedewald, Martin-Hopkins, and Sampson equations. The differences (%Delta) between the estimated and measured LDL-C were analyzed in relation to dLDL-C, high-density lipoprotein cholesterol (HDL-C), and triglyceride levels.

Results: The %Delta was significantly lower (p < 0.0001) for the Martin-Hopkins (-8.8 ± 9.8) and Sampson (-9.5 ± 9.2) equations compared to Friedewald (-12.2 ± 9.2). All equations increasingly underestimated LDL-C as the dLDL-C levels decreased. The %Delta of the Martin-Hopkins equation showed significant positive correlations with dLDL-C (≤130 mg/dL) and triglycerides and a significant negative correlation with HDL-C. In a subgroup of 30 individuals with extreme %Delta values, patterns of gross underestimation were observed, particularly when low LDL-C, low triglycerides, and high HDL-C coincided.

Conclusions: The Martin-Hopkins equation is a superior method for LDL-C estimation and a valuable tool in precision medicine. However, clinicians and laboratory professionals must be aware of its limitations and recognize patterns that could lead to significant LDL-C underestimation. We propose an algorithm for clinical laboratories to provide personalized LDL-C assessments.

Background: While adoption of personalized medicine (PM) continues to increase in clinical oncology, there is limited data connecting the level of PM adoption at a given institution to improved clinical outcomes for patients. The purpose of this study was to analyze the correlation between health care providers' scores on a previously described PM integration framework and two outcome measures: the use of targeted therapy and clinical trial enrollment.

Methods: This study was conducted using real-world data (RWD) from the Syapse^® Learning Health Network (LHN). The PM integration score for six community hospital systems in the LHN was calculated and subsequently correlated with the two outcome measures.

Results: Across six institutions, a strong correlation between PM integration score and targeted therapy use was observed in metastatic non-small cell lung cancer (mNSCLC) (R² = 0.81), an indication with a significant number of approved targeted agents. Conversely, a strong correlation between PM integration score and clinical trial enrollment was observed in metastatic triple-negative breast cancer (TNBC) (R² = 0.63), an indication with fewer marketed targeted therapies but an active targeted therapy pipeline.

Conclusion: The results in these cases suggest that PM integration is a strong indicator of high-quality care practices for both utilization of targeted therapy in more mature PM indications (e.g., mNSCLC) and clinical trial enrollment in more emerging PM indications (e.g., TNBC).

Objectives: We evaluated the effect of preoperative chest computed tomography (CT) screening on the perioperative stroke rate in cardiosurgical patients at risk of aortic calcification.

Methods: Between May 2019 and April 2020, 129 patients at risk of aortic calcification underwent non-contrast chest CT screening before their procedure. They were assigned to Group 1 and compared with a historical Group 2, who were treated the previous year without a preoperative CT scan. The primary endpoint was to determine postoperative stroke occurrence. The secondary outcomes were the rate reintubation/tracheostomy, the length of hospital stay, and any change in surgical strategy based on the CT findings.

Results: Groups 1 and 2 comprised 129 and 261 patients, respectively. Group 1 had a lower left ventricular ejection fraction, less carotid stenosis, a history of carotid endarterectomy, and a longer cross-clamp time. The surgical strategy was changed for 6 patients in Group 1. Group 1 had a significantly lower stroke rate. No significant differences were observed in reintubation and tracheostomy rates, or length of hospital stay. Lack of CT screening, age, aortic valve surgery, aortic surgery, and rethoracotomy were identified as independent risk factors for a stroke.

Conclusions: Preoperative non-contrast chest CT screening of patients at risk of aortic calcification reduces postoperative stroke through adaptation of the surgical approach and should be used routinely in these patients.

Objectives: Our aim was to study how hemodialysis patients with varying levels of literacy would use a diet and fluid intake monitoring mobile application (DIMA-P) and what would be its impact on their dietary behaviors.

Materials and methods: We developed a mobile application using user-centered methods and informed by the Integrated Theory of Health Behavior Change (ITHBC). Eight hemodialysis patients were recruited to use the application to record and monitor their diet and fluid intakes for a 6-week study. Overall, the participants had low literacy, numeracy, and technical skills. We collected the data on application usage and administered usability and context-of-use questionnaires to gain insights into the participants' interaction with the application. The participants' portion estimation skills and dietary self-regulation self-efficacy were assessed using various tests. In addition, interdialytic weight gain data were collected to assess the impact of app usage on the participants' health outcomes.

Results: The application usage patterns varied, with a general trend towards frequent use (n = 5) correlating with engagement in self-monitoring. The participants gave high comprehensibility, user-friendliness, satisfaction, and usefulness ratings, suggesting that the app was well designed and the target users could easily navigate and interact with the features. While the participants improved in estimating portion sizes, the impact on measuring skills was variable. There was also an improvement in the participants' dietary self-regulation self-efficacy post-study. The interdialytic weight gain trends indicated a slight improvement in fluid and diet management.

Conclusion: People with different literacy skills can effectively use icon-based interfaces for portion size estimation and develop personalized usage patterns to self-regulate their fluid and dietary intakes. Moreover, they can experience an enhancement in their dietary self-efficacy skills by using a mobile application aimed at providing nutritional feedback. Furthermore, this research shows that the constructs of the ITHBC are effective in promoting dietary behavior change in a population with varying literacy skills. The target users can benefit from explicitly visualizing the relationship between their health outcomes and the factors influencing those outcomes. These user ambitions could be supported by developing machine learning models. Future research should also focus on enhancing the mechanisms by which technology can further enhance each component of the ITHBC framework.

Objective: In this study, we aimed to determine post-traumatic growth and depression levels in renal transplant recipients and the relationship between these two variables. Design and Methods: The study was conducted with a descriptive, cross-sectional, and correlational design. The data for the study were collected at the organ transplant unit of a research and training hospital located in the west of Turkey. The sample of the study included 122 kidney transplant recipients (n = 122). A Sociodemographic Information Form, the Post-Traumatic Growth (PTG) Inventory, and the Beck Depression Inventory (BDI) were employed to collect data. In the analyses of the data, descriptive statistics, ANOVA, an independent-samples t-test, post hoc tests, and Pearson correlation tests were used. Results: As the ages of the renal transplant recipients increased, their depression scores decreased, while their PTG scores increased. Higher depression levels were identified in the female participants compared to the male participants and in those with a low income compared to other income groups. The lowest PTG levels were found in the recipients who received their kidney transplants from third-degree relatives. Age, gender, economic status, and time of transplant were predictors of depression. The identity of the donor was the most significant predictor of PTG (62% explanation rate). A strong and inverse correlation was found between depression and PTG (p < 0.05). Conclusions: Post-traumatic growth was found to decrease depression. However, while poor economic status led to depression, high economic status did not lead to a significant change in PTG. As education levels increased, PTG decreased, but education status did not have any significant effect on depression. On the other hand, there was a negative correlation between PTG and depression. The results obtained in this study are valuable and important in terms of understanding depression better and determining PTG as a significant factor that could alleviate it.

Background: Aseptic meningitis comprises meningeal inflammation and cerebrospinal fluid (CSF) pleocytosis without positive Gram stain and culture. Regional differences exist in the prevalence of viral etiologies of aseptic meningitis. We aimed to assess the etiologies of aseptic meningitis in immunocompetent adults, focusing on herpes simplex virus type 2 (HSV-2).

Methods: This study retrospectively analyzed immunocompetent adults diagnosed with meningitis at a Korean tertiary care hospital from 2016 to 2018. Aseptic meningitis was defined through clinical and CSF analysis. We compared clinical and laboratory characteristics across viral etiologies and investigated predictors of HSV-2 meningitis.

Results: A total of 98 patients (46.9% female) with aseptic meningitis were finally enrolled. The etiologies of aseptic meningitis were identified in 62 patients (63.3%), including enterovirus (28.5%), HSV-2 (16.3%), and varicella zoster virus (VZV, 15.3%). HSV-2 showed female predominance, with shorter admission times with longer hospital stays and a recurrent meningitis history. Compared to other viral etiologies, HSV-2 showed higher CSF white blood cell (WBC) counts and protein levels but lower C-reactive protein (CRP) levels. A random forest model identified previous meningitis history and serum CRP level as key predictors of HSV-2 meningitis.

Conclusions: This study provides insights into the etiologies of aseptic meningitis in a specific Korean region, identifying HSV-2 as a notable cause. The prediction model suggested that the clinical history of previous meningitis and serum CRP level may guide clinical assessment of meningitis.

Glioblastoma (GBM) is the most common and most malignant primary brain tumor, presenting significant treatment challenges due to its heterogeneity, invasiveness, and resistance to conventional therapies. Despite aggressive treatment protocols, the prognosis remains poor, with a median survival time of approximately 15 months. Recent advancements in mRNA vaccine technology, particularly the development of lipid nanoparticles (LNPs), have revitalized interest in mRNA-based therapies. These vaccines offer unique advantages, including rapid production, personalization based on tumor-specific mutations, and a strong induction of both humoral and cellular immune responses. mRNA vaccines have demonstrated potential in preclinical models, showing significant tumor regression and improved survival rates. Early-phase clinical trials have indicated that mRNA vaccines are safe and can induce robust immune responses in GBM patients. Combining mRNA vaccines with other immunotherapeutic approaches, such as checkpoint inhibitors, has shown synergistic effects, further enhancing their efficacy. However, challenges such as optimizing delivery systems and overcoming the immunosuppressive tumor microenvironment remain. Future research should focus on addressing these challenges and exploring combination therapies to maximize therapeutic benefits. Large-scale, randomized clinical trials are essential to validate the efficacy and safety of mRNA vaccines in GBM therapy. The potential to reshape the tumor microenvironment and establish long-term immunological memory underscores the transformative potential of mRNA vaccines in cancer immunotherapy.

Background: Out-of-hospital cardiac arrest (OHCA) is associated with high mortality and cerebral disability in survivors. Current models of risk prediction and survival are mainly based on resuscitation duration. We examined the prognostic value of circulating biomarkers in predicting mortality and severe cerebral disability for OHCA survivors, alongside traditional clinical risk indicators.

Methods: Biomarkers including BNP, troponin I, and galectin-3 were measured at hospital admission in resuscitated OHCA patients. Prognostic significance for mortality and cerebral disability involving circulating biomarkers, resuscitation duration, demographics, and laboratory and clinical characteristics was examined via univariate and multivariate Cox proportional hazards regression models. The incremental prognostic value of the index covariates was examined through model diagnostics, focusing on the Akaike information criterion (AIC) and Harrell's concordance statistic (c-statistic).

Results: In a combinatorial analysis of 144 OHCA survivors (median follow-up 5.7 years (IQR 2.9-6.6)), BNP, galectin-3, arterial pH, and resuscitation time were significant predictors of all-cause death and severe cerebral disability, whereas troponin I levels were not. Multivariate regression, adjusting for BNP, arterial pH, and resuscitation time, identified galectin-3 as an independent predictor of long-term mortality. Multiple linear regression models also confirmed galectin-3 as the strongest predictor of cerebral disability. The incorporation of galectin-3 into models for predicting mortality and cerebral disability enhanced fit and discrimination, demonstrating the incremental value of galectin-3 beyond traditional risk predictors.

Conclusions: Galectin-3 is a significant, independent long-term risk predictor of cerebral disability and mortality in OHCA survivors. Incorporating galectin-3 into current risk stratification models may enhance early prognostication and guide targeted clinical interventions.