Anatomic versus Low Tibial Tunnel in Double-Bundle Posterior Cruciate Ligament Reconstruction: Clinical and Radiologic Outcomes with a Minimum 2-Year Follow-Up.

There is currently no consensus on the optimal placement of the tibial tunnel for double-bundle posterior cruciate ligament (PCL) reconstruction. The purpose of this study was to compare the clinical and radiologic outcomes of double-bundle PCL reconstruction utilizing anatomic versus low tibial tunnels. We conducted a retrospective cohort study involving patients who underwent double-bundle PCL reconstruction between Jan 2019 and Jan 2022, with a minimum follow-up of 2 years (n = 36). Based on the tibial tunnel position on postoperative computed tomography, patients were categorized into two groups: anatomic placement (group A; n = 18) and low tunnel placement (group L; n = 18). We compared the range of motion, stability test, complications, and side-to-side differences in tibial posterior translation using kneeling stress radiography between the two groups. There were no significant differences between the groups regarding clinical outcomes or complication rates. No significant differences in the posterior drawer test and side-to-side difference on kneeling stress radiography (2.5 ± 1.2 mm in group A vs. 3.7 ± 2.0 mm in group L; p = 0.346). In conclusion, the main findings of this study indicate that both anatomic tunnel and low tibial tunnel placements in double-bundle PCL reconstruction demonstrated comparable and satisfactory clinical and radiologic outcomes, with similar overall complication rates at the 2-year follow-up.

PD-L1 and AKT Overexpressing Adipose-Derived Mesenchymal Stem Cells Enhance Myocardial Protection by Upregulating CD25+ T Cells in Acute Myocardial Infarction Rat Model.

This study explores the synergistic impact of Programmed Death Ligand 1 (PD-L1) and Protein Kinase B (Akt) overexpression in adipose-derived mesenchymal stem cells (AdMSCs) for ameliorating cardiac dysfunction after myocardial infarction (MI). Post-MI adult Wistar rats were allocated into four groups: sham, MI, ADMSC treatment, and ADMSCs overexpressed with PD-L1 and Akt (AdMSC-PDL1-Akt) treatment. MI was induced via left anterior descending coronary artery ligation, followed by intramyocardial AdMSC injections. Over four weeks, cardiac functionality and structural integrity were assessed using pressure-volume analysis, infarct size measurement, and immunohistochemistry. AdMSC-PDL1-Akt exhibited enhanced resistance to reactive oxygen species (ROS) in vitro and ameliorated MI-induced contractile dysfunction in vivo by improving the end-systolic pressure-volume relationship and preload-recruitable stroke work, together with attenuating infarct size. Molecular analyses revealed substantial mitigation in caspase3 and nuclear factor-κB upregulation in MI hearts within the AdMSC-PDL1-Akt group. Mechanistically, AdMSC-PDL1-Akt fostered the differentiation of normal T cells into CD25+ regulatory T cells in vitro, aligning with in vivo upregulation of CD25 in AdMSC-PDL1-Akt-treated rats. Collectively, PD-L1 and Akt overexpression in AdMSCs bolsters resistance to ROS-mediated apoptosis in vitro and enhances myocardial protective efficacy against MI-induced dysfunction, potentially via T-cell modulation, underscoring a promising therapeutic strategy for myocardial ischemic injuries.

Prescribing cascades of antigout medications from thiazide diuretics in gout-naïve hypertensive adults receiving first-line pharmacological management.

Prescribing cascade is a significant clinical problem but is often overlooked. We explore the incidence of the prescribing cascades of antigout medications related to thiazide treatment in gout-naïve hypertensive adults newly exposed to the pharmacological treatment. This population-based, retrospective cohort study used the Taiwan National Health Insurance Registry Database. Gout-naïve hypertensive adults who were newly dispensed first-line antihypertensive drugs between January 1, 2000, and December 31, 2016, were enrolled. Patients were divided into the thiazide group (n = 4192) and the non-thiazide group (n = 81,083). The non-thiazide group included patients who received an angiotensin-converting enzyme inhibitor, angiotensin II receptor blocker, calcium channel blocker, or beta-blocker. The study utilized propensity score matching and multivariable Cox regression models to investigate the prescribing cascade of antigout agents following antihypertensive treatment, adjusting for factors like age, sex, comorbidities, and concurrent medications. After propensity score matching, each group consisted of 4045 patients, with the thiazide group exhibiting a higher risk of being prescribed antigout medications across different time intervals post-treatment initiation. Specifically, adjusted hazard ratios (aHRs) for the thiazide group were 2.23, 2.07, and 2.41 for < 30 days, 31-180 days, and > 180 days, respectively, indicating a sustained and significant risk over time. Comparative analyses revealed thiazide diuretics were associated with a higher risk of antigout medication prescriptions compared to other antihypertensive classes, particularly evident after 180 days. Subgroup analyses across various demographics and comorbidities consistently showed an increased risk in the thiazide cohort. Gout-naïve hypertensive adults newly dispensed thiazide had a higher risk of subsequently adding antigout agents than those taking other first-line antihypertensive medications. The awareness and interruption of these prescribing cascades are critical to improving patient safety.

Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images.

Automated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice.

Extracorporeal cardiopulmonary resuscitation for patients with refractory out-of-hospital cardiac arrest: a propensity score matching, observational study.

Extracorporeal cardiopulmonary resuscitation (ECPR) is increasingly performed as an adjunct to conventional cardiopulmonary resuscitation (CCPR) for refractory out-of-hospital cardiac arrest (OHCA). However, the specific benefits of ECPR concerning survival with favorable neurological outcomes remain uncertain. This study aimed to investigate the potential advantages of ECPR in the management of refractory OHCA. We conducted a retrospective cohort study involved OHCA patients between January 2016 and May 2021. Patients were categorized into ECPR or CCPR groups. The primary endpoint assessed was survival with favorable neurological outcomes, and the secondary outcome was survival rate. Multivariate logistic regression analyses, with and without 1:2 propensity score matching, were employed to assess ECPR's effect. In total, 1193 patients were included: 85underwent ECPR, and 1108 received CCPR. Compared to the CCPR group, the ECPR group exhibited notably higher survival rate (29.4% vs. 2.4%; p < 0.001). The ECPR group also exhibited a higher proportion of survival with favorable neurological outcome than CCPR group (17.6% vs. 0.7%; p < 0.001). Multivariate logistic regression analysis demonstrated that ECPR correlated with increased odds of survival with favorable neurological outcome (adjusted odds ratio: 13.57; 95% confidence interval (CI) 4.60-40.06). Following propensity score matching, the ECPR group showed significantly elevated odds of survival with favorable neurological outcomes (adjusted odds ratio: 13.31; 95% CI 1.61-109.9). This study demonstrated that in comparison to CCPR, ECPR may provide survival benefit and increase the odds of favorable neurological outcomes in selected OHCA patients.

Novel Genes Associated with Atrial Fibrillation and the Predictive Models for AF Incorporating Polygenic Risk Scores and PheWAS-Derived Risk Factors.

BACKGROUND: Atrial fibrillation (AF), the most common atrial arrhythmia, presents varied clinical manifestations. Despite the identification of genetic loci associated with AF, particularly in specific populations, research within Asian ethnicities remains limited. This study aimed to develop predictive models for AF using AF-associated single-nucleotide polymorphisms (SNPs) from a Genome-Wide Association Study (GWAS) on a substantial cohort of Taiwanese individuals, evaluating the models' predictive efficacy. METHODS: Involving 75,121 subjects, including 5,694 AF patients and 69,427 normal controls with GWAS data, the study merged polygenic risk scores (PRS) from AF-associated SNPs with Phenome-wide association study (PheWAS)-derived risk factors. Advanced statistical and machine learning techniques were employed to develop and evaluate AF predictive models for discrimination and calibration. RESULTS: The study identified the top 30 significant SNPs associated with AF, predominantly on chromosomes 10 and 16, implicating genes like NEURL1, SH3PXD2A, INA, NT5C2, STN1, and ZFHX3. Notably, INA, NT5C2, and STN1 were newly linked to AF. The GWAS predictive power using PRS-CS analysis for AF exhibited an area under the curve (AUC) of 0.600 (P < 0.001), improving to 0.855 (P < 0.001) after adjusting for age and gender. PheWAS analysis showed the top 10 diseases associated with these genes were circulatory system diseases. CONCLUSIONS: Integrating genetic and phenotypic data enhanced the accuracy and clinical relevance of AF predictive models. The findings suggest promise for refining AF risk assessment, enabling personalized interventions, and reducing AF-related morbidity and mortality burdens.