Investigation of the variants at the binding site of inflammatory transcription factor NF-κB in patients with end-stage renal disease.

BACKGROUND: A chronic inflammatory state is a prominent feature in patients with end-stage renal disease (ESRD). Nuclear factor-kappa B (NF-κB) is a transcription factor that regulates the expression of genes involved in inflammation. Some genetic studies have demonstrated that the NF-κB genetic mutation could cause kidney injury and kidney disease progression. However, the association of a gene polymorphism in the transcription factor binding site of NF-κB with kidney disease is not clear. METHODS: We used the Taiwan Biobank database, the University of California, Santa Cruz, reference genome, and a chromatin immunoprecipitation sequencing database to find single nucleotide polymorphisms (SNPs) at potential binding sites of NF-κB. In addition, we performed a case-control study and genotyped 847 patients with ESRD and 846 healthy controls at Tri-Service General Hospital from 2015 to 2016. Furthermore, we used the ChIP assay to identify the binding activity of different genotypes and used Luciferase reporter assay to examine the function of the rs9395890 polymorphism. RESULT: The results of biometric screening in the databases revealed 15 SNPs with the potential binding site of NF-κB. Genotype distributions of rs9395890 were significantly different in ESRD cases and healthy controls (P = 0.049). The ChIP assay revealed an approximately 1.49-fold enrichment of NF-κB of the variant type TT when compared to that of the wild-type GG in rs9395890 (P = 0.027; TT = 3.20 ± 0.16, GT = 2.81 ± 0.20, GG = 1.71 ± 0.18). The luciferase reporter assay showed that the NF-κB binding site activity in T allele was slightly higher than that in G allele, though it is not significant. CONCLUSIONS: Our findings indicate that rs9395890 is associated with susceptibility to ESRD in Taiwan population.

Dexamethasone Down-regulates Osteocalcin in Bone Cells through Leptin Pathway.

Glucocorticoid therapy, especially at higher doses, is associated with significant adverse side effects including osteoporosis. Leptin, secreted from adipose tissue, has diverse effects on bone tissue regulation. As glucocorticoids stimulate leptin synthesis and secretion directly in adipose tissue we hypothesised that dexamethasone (DEX) induced osteoporosis may, in part, be mediated by an osteoblast dependent leptin-leptin receptor pathway. Human bone cells expressed leptin and leptin receptors (Ob-Ra and Ob-Rb). DEX increased leptin, Ob-Ra and Ob-Rb expression in a dose-dependent manner while decreasing expression of osteocalcin. In the presence of leptin, Cbfa1 and osteonectin expression showed no significant change, whereas osteocalcin expression was decreased. Recombinant human quadruple antagonist leptin suppressed DEX-induced osteocalcin downregulation. The signaling pathway involved up-regulation of JAK2. In conclusion, upregulation of leptin and Ob-Rb in human bone cells by DEX is associated with down-regulation of osteocalcin expression. The down regulation of osteocalcin by DEX was partially through a leptin autocrine/paracrine loop. Adverse effects of DEX on the skeleton may be modified by targeting leptin signaling pathways.

No difference in the functional improvements between unilateral and bilateral total knee replacements.

BACKGROUND: Differences between staged bilateral total knee replacement (TKR) and simultaneous bilateral TKR have been investigated, but few studies have investigated differences in the functional improvements resulting from these methods. Therefore, this study investigates the different functional improvements between staged bilateral total knee TKR and simultaneous bilateral TKR. METHODS: Among 144 potential bilateral TKR patients who were included in this study, 93 (64.6%) patients selected unilateral TKR and 51 (35.4%) selected bilateral TKR. Functional improvements were assessed using the Western Ontario and McMaster University osteoarthritis index (WOMAC) and the Medical Outcomes Trust Short Form-36 (SF-36), and patients were interviewed pre-operatively and after 6 months. A generalized equation was used to test for differences in functional improvements. RESULTS: After TKR, pain, stiffness, function and total WOMAC scores were significantly reduced in both groups, with mean changes from - 26.6 to - 41.4 and from - 27.5 to - 42.2.The mean health change of SF-36 scores, physical component and mental component scores changed to 45.2 ± 18.2, 74.0 ± 15.4 and 77.0 ± 9.6, respectively, in Group 1 and 47.1 ± 17.1, 74.0 ± 15.2 and 75.5 ± 12.1, respectively, in Group 2. Unilateral and simultaneous bilateral TKR produce similar functional improvements, although current work status may be a novel impact factor. CONCLUSION: No differences in functional improvements were identified between patients who selected unilateral versus bilateral TKR, indicating no recommendation for one procedure over the other.

Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.

BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). OBJECTIVE: Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes. METHODS: We used 2 classification methods: (1) extracting from discharge notes some features (terms, n-gram phrases, and SNOMED CT categories) that we used to train a set of supervised machine learning models (support vector machine, random forests, and gradient boosting machine), and (2) building a feature matrix, by a pretrained word embedding model, that we used to train a CNN. We used these methods to identify the chapter-level ICD-10-CM diagnosis codes in a set of discharge notes. We conducted the evaluation using 103,390 discharge notes covering patients hospitalized from June 1, 2015 to January 31, 2017 in the Tri-Service General Hospital in Taipei, Taiwan. We used the receiver operating characteristic curve as an evaluation measure, and calculated the area under the curve (AUC) and F-measure as the global measure of effectiveness. RESULTS: In 5-fold cross-validation tests, our method had a higher testing accuracy (mean AUC 0.9696; mean F-measure 0.9086) than traditional NLP-based approaches (mean AUC range 0.8183-0.9571; mean F-measure range 0.5050-0.8739). A real-world simulation that split the training sample and the testing sample by date verified this result (mean AUC 0.9645; mean F-measure 0.9003 using the proposed method). Further analysis showed that the convolutional layers of the CNN effectively identified a large number of keywords and automatically extracted enough concepts to predict the diagnosis codes. CONCLUSIONS: Word embedding combined with a CNN showed outstanding performance compared with traditional methods, needing very little data preprocessing. This shows that future studies will not be limited by incomplete dictionaries. A large amount of unstructured information from free-text medical writing will be extracted by automated approaches in the future, and we believe that the health care field is about to enter the age of big data.

[Precision Nursing: Individual-Based Knowledge Translation].

U.S. President Obama announced a new era of precision medicine in the Precision Medicine Initiative (PMI). This initiative aims to accelerate the progress of personalized medicine in light of individual requirements for prevention and treatment in order to improve the state of individual and public health. The recent and dramatic development of large-scale biologic databases (such as the human genome sequence), powerful methods for characterizing patients (such as genomics, microbiome, diverse biomarkers, and even pharmacogenomics), and computational tools for analyzing big data are maximizing the potential benefits of precision medicine. Nursing science should follow and keep pace with this trend in order to develop empirical knowledge and expertise in the area of personalized nursing care. Nursing scientists must encourage, examine, and put into practice innovative research on precision nursing in order to provide evidence-based guidance to clinical practice. The applications in personalized precision nursing care include: explanations of personalized information such as the results of genetic testing; patient advocacy and support; anticipation of results and treatment; ongoing chronic monitoring; and support for shared decision-making throughout the disease trajectory. Further, attention must focus on the family and the ethical implications of taking a personalized approach to care. Nurses will need to embrace the paradigm shift to precision nursing and work collaboratively across disciplines to provide the optimal personalized care to patients. If realized, the full potential of precision nursing will provide the best chance for good health for all.

Risk factors and their interaction on chronic kidney disease: A multi-centre case control study in Taiwan.

BACKGROUND: Chronic kidney disease (CKD) is highly prevalent in Taiwan. More than two-thirds of end-stage renal disease is associated with diabetes mellitus (DM) or hypertension (HTN). Therefore, the formulation of a special preventative policy of CKD in these patients is essential. This study surveyed 14 traditional risk factors and identified their effects on CKD in patients with HTN/DM and compared these with their effects in the general population. METHODS: This study included 5328 cases and 5135 controls in the CKD/HTN/DM outpatient and health centres of 10 hospitals from 2008 to 2010. Fourteen common effect factors were surveyed (four demographic, five disease and five lifestyle), and their effects on CKD were tested. Significance tests were adjusted by the Bonferroni method. Results of the stratified analyses in the variables were presented with significant heterogeneity between patients with different comorbidities. RESULTS: Male, ageing, low income, hyperuricemia and lack of exercise habits were risk factors for CKD, and their effects in people with different comorbidities were identical. Anaemia was a risk factor, and there was an additive effect between anaemia and HTN on CKD. Patients with anaemia had a higher risk when associated with HTN [odds ratio (OR) = 6.75, 95% confidence limit (95% CI) 4.76-9.68] but had a smaller effect in people without HTN (OR 2.83, 95% CI 2.16-3.67). The association between hyperlipidaemia-related factors and CKD was also moderated by HTN. It was a significant risk factor in people without HTN (OR = 1.67, 95% CI 1.38-2.01) but not in patients with HTN (OR =1.03, 95% CI 0.89-1.19). Hepatitis B, hepatitis C, betel nut chewing, smoking, alcohol intake and groundwater use were not associated with CKD in multivariate analysis. CONCLUSIONS: We considered that patients with HTN and anaemia were a high CKD risk population. Physicians with anaemic patients in outpatient clinics need to recognise that patients who also have HTN might be latent CKD cases.

A functional polymorphism in the promoter region of TLR3 is associated with susceptibility to end-stage renal disease.

BACKGROUND/AIMS: End-stage renal disease (ESRD) is simultaneously associated with immune activation, systemic inflammation and immune deficiency. Toll-like receptor 3 (TLR3), a receptor for viral double-stranded RNA, is involved in immune cell activation in renal diseases and may contribute to chronic inflammatory disease progression. To date, effects of TLR3 polymorphisms on ESRD remain unknown. Therefore, we determined the predictive value of TLR3 polymorphisms and further functionally studied ESRD. METHODS: We performed a case-control association study and genotyped 616 ESRD patients and 813 healthy controls. Patients were genotyped for -7C/A, 1377C/T and 1234C/T polymorphisms of TLR3 using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. The Haplotype association analysis was performed using the Haploview package. A luciferase reporter assay and real-time PCR were used to test the function of the -7C/A promoter polymorphism in TLR3 expression in human embryonic kidney 293 (HEK293) cells. RESULTS: Genotype distributions of -7C/A and 1377C/T in TLR3 were significantly different in ESRD patients and healthy controls. The ATC haplotype of TLR3 was associated with a decreased risk of ESRD. We also found significant differences in TLR3 expression by dexamethasone treatment between various genotypes of -7C/A (p = 0.02). TLR3 transcriptional activity of the variant -7 C allele was higher than that of the -7 A allele after dexamethasone treatment. CONCLUSION: RESULTS indicate that, in our population, the presence of the C allele of -7C/A in TLR3 increases the susceptibility to ESRD. In vitro studies demonstrated that -7C/A may be involved in ESRD development through transcriptional modulation of TLR3.

An intron polymorphism of the fibronectin gene is associated with end-stage knee osteoarthritis in a Han Chinese population: two independent case-control studies.

BACKGROUND: Knee osteoarthritis (OA) is a complex disease involving both biomechanical and metabolic factors that alter the tissue homeostasis of articular cartilage and subchondral bone. The catabolic activities of extracellular matrix degradation products, especially fibronectin (FN), have been implicated in mediating cartilage degradation. Chondrocytes express several members of the integrin family which can serve as receptors for FN including integrins α5ß1, αvß3, and αvß5. The purpose of this study was to determine whether polymorphisms in the FN (FN-1) and integrin genes are markers of susceptibility to, or severity of, knee OA in a Han Chinese population. METHODS: Two independent case-control studies were conducted on 928 patients with knee OA and 693 healthy controls. Ten single nucleotide polymorphisms (SNPs) of FN-1 and the integrin αV gene (ITGAV) were detected using the ABI 7500 real-time PCR system. RESULTS: The AT heterozygote in FN-1 (rs940739A/T) was found to be significantly associated with knee OA (adjusted OR = 1.44; 95% CI = 1.16-1.80) in both stages of the study. FN-1 rs6725958C/A and ITGAV rs10174098A/G SNPs were only associated with knee OA when both study groups were combined. Stratifying the participants by Kellgren-Lawrence (KL) score identified significant differences in the FN-1 rs6725958C/A and rs940739 A/T genotypes between patients with grade 4 OA and controls. Haplotype analyses revealed that TGA and TAA were associated with a higher risk of OA, and that TAG conferred a lower risk of knee OA in the combined population. CONCLUSIONS: Our study suggests that the FN-1 rs940739A/T polymorphism may be an important risk factor of genetic susceptibility to knee OA in the Han Chinese population.

Gene-gene interactions in renin-angiotensin-aldosterone system contributes to end-stage renal disease susceptibility in a Han Chinese population.

OBJECTIVE: In this study, we investigated whether RAAS gene single nucleotide polymorphisms (SNPs) and their interactions were associated with end-stage renal stage (ESRD). METHODOLOGY AND RESULTS: This was a case-control study for 647 ESRD cases and 644 controls. AGT (M235T (rs699) and T174M (rs4762)), AGTR1 (A1166C (rs5186) and C573T (rs5182)), ACE (I/D (rs1799752) and G2350A (rs4343)), and CYP11B2 C-344T (rs1799998) were genotyped and compared between cases and controls to identify SNPs associated with ESRD susceptibility. Multifactor dimensionality reduction (MDR) was used to identify gene-gene interactions. Several RAAS genes were associated with ESRD: AGT M235T, ACE I/D, ACE G2350A, and CYP11B2 C-344T. By MDR analysis, a three-locus model (ACE ID/ACE G2350A/CYP11B2 C-344T) of gene-gene interaction was the best for predicting ESRD risk, and its maximum testing accuracy was 56.08% and maximum cross-validation consistency was 9/10. ESRD risk was higher with the simultaneous occurrence of ACE I/D DD-ACE G2350A AA. AGT, ACE, and CYP11B2 gene polymorphisms are associated with ESRD. CONCLUSIONS: The gene-gene interaction effects of ACE I/D, ACE G2350A, and CYP11B2 C-344T polymorphisms are more important than individual factors for ESRD development among Han Chinese.

Simplified Assessment of Radioiodine Biokinetics for Thyroid Cancer Patients: A Practical Approach Using Continuous External Radiation Monitoring.

INTRODUCTION: The biokinetics of radioiodine (RAI) in thyroid cancer patients are complex. This study aims to develop a practical approach for assessing RAI biokinetics to predict patient discharge time and estimate radiation exposure to caregivers. METHODS: We retrospectively reviewed data from patients with differentiated thyroid carcinoma undergoing RAI treatment. Serial radiation dose rates were dynamically collected during hospitalization and fitted to a biexponential model to assess the biokinetic features: RAI uptake fraction of thyroid tissue (Ft) and effective half-life of extra-thyroid tissue (Tet). Correlations with 99mTc thyroid uptake ratio (TcUR), radiation retention ratio (RR), renal function, and body mass index (BMI) were analyzed. RESULTS: Thirty-five patients were enrolled. The derived Ft was 0.08 ± 0.06 and Tet was 7.57 ± 1.45 h. Pearson's correlation analysis revealed a significant association between Ft and both TcUR and RR (p < 0.05), while Tet correlated with renal function and BMI (p < 0.05). CONCLUSION: This novel and practical method assessing RAI biokinetics demonstrates consistency with other parameters and related studies, enhancing the model reliability. It shows promise in predicting an appropriate discharge time and estimating radiation exposure to caregivers, allowing for modifications to radiation protection precautions to follow ALARA principle and minimize the potential risks from radiation exposure.

A case-control study coupling with meta-analysis elaborates decisive association between IGF-1 rs35767 and osteoporosis in Asian postmenopausal females.

BACKGROUND: Osteoporosis (OP) is prevalent in postmenopausal women. Several studies investigated the association between IGF-1 polymorphisms and OP among postmenopausal females with conflicting outcomes. OBJECTIVE: To investigate whether the IGF-1 (rs35767, rs2288377, rs5742612) were associated with OP in postmenopausal females. METHODS: In case-control study, 95 OP cases and 222 healthy controls were recruited between March 2015 and July 2019. OP was diagnosed based on WHO criteria for diagnosis of OP as T score of bone mineral density (BMD) ≤-2.5; normal, as T score of BMD ≥-1. IGF-1 SNPs were genotyped by iPLEX Gold SNP genotyping. To be solid, related studies from PubMed, Embase, Cochrane, Web of science, and previous meta-analysis up until November 2020, along with our case-control study, were incorporated into a meta-analysis with criteria of significance using odds ratios (ORs) with corresponding 95% confidence intervals (CI) to evaluate risk factor of SNPs on OP. TSA was used to estimate the sample sizes required to achieve a conclusion. RESULTS: In dominant model of our case-control study, we found nonsignificant association of rs35767 [Adj-OR: 0.95 (95% CI: 0.56-1.60)], rs2288377 [Adj-OR: 1.15 (95% CI: 0.67-1.97)], and rs5742612 [Adj-OR: 1.07 (95% CI: 0.62-1.83)] with OP in postmenopausal females. However, integration of our case-control study and 3 published studies, rs35767 [OR: 1.24 (95% CI: 1.05-1.47)] showed a conclusively risk association with OP in postmenopausal females judged by TSA with 2267 Asians. CONCLUSIONS: This study demonstrates a crucial sample to conclude that IGF-1 rs35767 is significantly associated with OP in postmenopausal women.

Gender difference in appendicular muscle strength: determinant of the quality of life in the older Taiwanese.

BACKGROUND: The loss of skeletal muscle mass by aging determines the health status and the quality of life (QoL). OBJECTIVE: To examine the relationships between appendicular muscle strength and the QoL of elderly adults in gender difference. METHODS: This was a cross-sectional study, in which 690 subjects who participated in older adults health examination in the health management center of Tri-Service General Hospital from 2018 to 2021. A structured questionnaire was used to collect basic demographic data. The 12-Item Short Form Survey (SF-12) was used to evaluate the QoL of subjects. Their grip strength and gait speed were measured, and Dual-energy X-ray absorptiometry was used to measure muscle mass and other body composition data. Multivariate regression analysis was used to examine the relationships between upper and lower limb muscle strength and the QoL of older adults. RESULTS: In men, legs muscle mass percentage (LegsMM%) (ß = 3.67; 95% CI: 0.64-6.69; p = 0.018) and gait speed (ß = 6.09; 95% CI: 3.88-8.30; p < 0.001) were positively associated with physical component summary (PCS) scores, and gait speed (ß = 4.63; 95% CI: 2.66-6.60; p < 0.001) was also related to an improvement mental component summary (MCS) scores. In women, arms muscle mass percentage (ArmsMM%) (ß = 6.50; 95% CI: 2.34-10.66; p = 0.002) and grip strength (ß = 10.54; 95% CI: 6.27-14.81; p < 0.001) had the greatest effect on improving PCS scores, whereas grip strength (ß = 7.58; 95% CI 4.00-11.17; p < 0.001) was also found to help improve MCS scores. CONCLUSIONS: Men should focus on lower limb training, whereas females should focus on upper limb training to effectively improve their QoL. Appropriate exercise interventions should be designed for different genders for the promotion of the healthy aging policy.

Decisive gene strategy on osteoporosis: a comprehensive whole-literature-based approach for conclusive candidate gene targets.

PURPOSE: Previous meta-analyses only examined the association between single gene polymorphisms and osteoporosis; there is no compilation of all gene loci that correlate with osteoporosis in the literature. In this study, we develop a new literature-based approach, a decisive gene strategy (DGS), to examine the sufficiency of the cumulative sample size for each gene locus and to assess whether a definite conclusion of the association between the gene locus and osteoporosis can be drawn. METHODS: The DGS was used to search PubMed, Embase, and Cochrane databases for all meta-analyses that correlated gene polymorphisms with osteoporosis. Trial sequential analysis was employed to examine the sufficiency of the cumulative sample size. Finally, we assessed the importance of gene loci in osteoporosis based on whether there were enough sample sizes and the heterogeneity of the literature with the I2 value. RESULTS: After excluding 169 irrelevant publications, 39 meta-analysis papers were obtained. Among Caucasians, in 17 gene loci, there were eight gene loci (e.g., vitamin D Receptor ApaI rs7975232) with sufficient cumulative sample size to confirm that they were unrelated to the disease. Among Asians, in 15 gene loci, four gene loci that had sufficient sample sizes were risk factors: VDR FokI rs2228570 (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.22-1.70), TGF ß1 rs1800470 (OR = 1.35, 95% CI = 1.10-1.65), IGF1 rs2288377 (OR = 1.44, 95% CI = 1.28-1.62), and IGF1 rs35767 (OR = 1.20, 95% CI = 1.06-1.36), respectively, whereas one gene locus, ESR2 RsaI rs1256049 (OR = 0.69, 95% CI = 0.59-0.81), was a protective factor. CONCLUSIONS: The DGS successfully identified five gene loci in osteoporosis that will apply to other diseases to find causal genes, which may contribute to further genetic therapy.

Differential gene expression orchestrated by transcription factors in osteoporosis: bioinformatics analysis of associated polymorphism elaborating functional relationships.

BACKGROUND: Identification of candidate SNPs from transcription factors (TFs) is a novel concept, while systematic large-scale studies on these SNPs are scarce. PURPOSE: This study aimed to identify the SNPs of six TF binding sites (TFBSs) and examine the association between candidate SNPs and osteoporosis. METHODS: We used the Taiwan BioBank database; University of California, Santa Cruz, reference genome; and a chromatin immunoprecipitation sequencing database to detect 14 SNPs at the potential binding sites of six TFs. Moreover, we performed a case-control study and genotyped 109 patients with osteoporosis (T-score ≤ -2.5 evaluated by dual-energy X-ray absorptiometry) and 262 healthy individuals (T-score ≥ -1) at Tri-Service General Hospital from 2015 to 2019. Furthermore, we used the expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression database to identify downstream gene expression as a criterion for the function of candidate SNPs. RESULTS: Bioinformatic analysis identified 14 SNPs of TFBSs influencing osteoporosis. Of these SNPs, the rs130347 CC + TC genotype had 0.57 times higher risk than the TT genotype (OR = 0.57, p = 0.031). Validation of eQTL analysis revealed that rs130347 T allele influences mRNA expression of downstream A4GALT in whole blood (p = 0.0041) and skeletal tissues (p = 0.011). CONCLUSIONS: We successfully identified the unique osteoporosis locus rs130347 in the Taiwanese and functionally validated this finding. In the future, this strategy can be expanded to other diseases to identify susceptible loci and achieve personalized precision medicine.

Novel and Efficient Quantitative Posterior-Circulation-Structure-Based Scale via Noncontrast CT to Predict Ischemic Stroke Prognosis: A Retrospective Study.

(1) Background: Posterior circulation ischemic stroke has high mortality and disability rates and requires an early prediction prognosis to provide the basis for an interventional approach. Current quantitative measures are only able to accurately assess the prognosis of patients using magnetic resonance imaging (MRI). However, it is difficult to obtain MRI images in critically urgent cases. Therefore, the development of a noncontrast CT-based rapid-assist tool is needed to enhance the value of the clinical application. (2) Objective: This study aimed to develop an auxiliary-annotating noncontrast CT-efficient tool, which is based on a deep learning model, to provide a quantitative scale and the prognosis of posterior circulation ischemic stroke patients. (3) Methods: A total of 31 patients with posterior circulation ischemic stroke, diagnosed in the stroke registry at the Tri-Service General Hospital from November 2019 to July 2020, were included in the study, with a total of 578 CT images collected from noncontrast CT and MRI that were ≤ 3 days apart. A 5-fold cross validation was used to develop an image segmentation model to identify nine posterior circulation structures, and intersection over union (IoU) was used to assess the ability of the model to identify each structure. A quantitative score was integrated to assess the importance of the proportion of ischemic lesions in each posterior circulation structure, and the ROC curve was compared with the semiquantitative score for prognostic power. The prognoses of the patients were defined into two groups of 18 patients. An mRS score of 0-2 at discharge was defined as a good prognosis, while an mRS score of 3-6 was deemed to be a poor prognosis. (4) Results: The performance of the image segmentation model for identifying the nine posterior circulation structures in noncontrast CT images was evaluated. The IoU of the left cerebellum was 0.78, the IoU of the right cerebellum was 0.79, the IoU of the left occipital lobe was 0.74, the IoU of the right occipital lobe was 0.68, the IoU of the left thalamus was 0.73, the IoU of the right thalamus was 0.75, the IoU of the medulla oblongata was 0.82, and the IoU of the midbrain was 0.83. The prognostic AUC of posterior circulation patients predicted using a quantitative integrated score was 0.74, which was significantly higher than that of the pc-ASPECTS (AUC = 0.63, p = 0.035), with a sensitivity of 0.67 and a specificity of 0.72. (5) Conclusions: In this study, a deep learning model was used to develop a noncontrast CT-based quantitative integrated score tool, which is an effective tool for clinicians to assess the prognosis of posterior circulation ischemic stroke.

A Simple Algorithm Using Ventilator Parameters to Predict Successfully Rapid Weaning Program in Cardiac Intensive Care Unit Patients.

BACKGROUND: Ventilator weaning is one of the most significant challenges in the intensive care unit (ICU). Approximately 30% of patients fail to wean, resulting in prolonged use of ventilators and increased mortality. There are numerous high-performance prediction models available today, but they require a large number of parameters to predict and are thus impractical in clinical practice. OBJECTIVES: This study aims to create an artificial intelligence (AI) model for predicting weaning time and to identify the most simplified key predictors that will allow the model to achieve adequate accuracy with as few parameters as possible. METHODS: This is a retrospective study of to-be-weaned patients (n = 1439) hospitalized in the cardiac ICU of Cheng Hsin General Hospital's Department of Cardiac Surgery from November 2018 to August 2020. The patients were divided into two groups based on whether they could be weaned within 24 h (i.e., "patients weaned within 24 h" (n = 1042) and "patients not weaned within 24 h" (n = 397)). Twenty-eight variables were collected including demographic characteristics, arterial blood gas readings, and ventilation set parameters. We created a prediction model using logistic regression and compared it to other machine learning techniques such as decision tree, random forest, support vector machine (SVM), extreme gradient boosting, and artificial neural network. Forward, backward, and stepwise selection methods were used to identify significant variables, and the receiver operating characteristic curve was used to assess the accuracy of each AI model. RESULTS: The SVM [receiver operating characteristic curve (ROC-AUC) = 88%], logistic regression (ROC-AUC = 86%), and XGBoost (ROC-AUC = 85%) models outperformed the other five machine learning models in predicting weaning time. The accuracies in predicting patient weaning within 24 h using seven variables (i.e., expiratory minute ventilation, expiratory tidal volume, ventilation rate set, heart rate, peak pressure, pH, and age) were close to those using 28 variables. CONCLUSIONS: The model developed in this research successfully predicted the weaning success of ICU patients using a few and easily accessible parameters such as age. Therefore, it can be used in clinical practice to identify difficult-to-wean patients to improve their treatment.

The Effect of PPARγ rs1801282 Variant on Mortality Risk Among Asians With Chronic Kidney Disease: A Cohort Study and Meta-Analysis.

Background: Chronic kidney disease (CKD) is a public health issue, and an independent risk factor for cardiovascular disease. The peroxisome proliferator-activated receptor gamma (PPARG) plays an important role in the cardiovascular system. Previous studies have examined one important exon polymorphism, Pro12Ala, in PPARG with respect to mortality of CKD patients, but the results were inconsistent and current evidence is insufficient to support a strong conclusion. This study aimed to examine the correlation between Pro12Ala gene polymorphism and mortality among Asians with CKD by trial sequential analysis (TSA). Methods: The research was divided into observational research and meta-analysis. For the cohort study, 767 subjects from dialysis centers in Taipei were selected as samples, and tracked from December 2015 to February 2017. For the meta-analysis, relevant literature from "PubMed" and "Embase" databases (until December 2016), was searched and TSA was used to verify the results. In order to achieve the best evidence hierarchies, our retrospective cohort study was added to the meta-analysis and the TSA. Results: The combined sample size for Asian was 1,685 after adding our cohort study, and there was no significant correlation between PPARG Pro12Ala and mortality by the allele model (RR: 0.85, 95% CI: 0.39-1.83, I2 = 79.3%). Under the parameter setting with the RR value of 1.5, TSA estimation presented that the cumulative sample size entered into the futility area, and it confirmed the conclusion in this study. Conclusion: We found that PPARG Pro12Ala gene polymorphism was not related to mortality in CKD Asians patients, and validated our conclusion using TSA after adding our sample.

The T-1237C polymorphism of the Toll-like receptor-9 gene is associated with chronic kidney disease in a Han Chinese population.

Chronic kidney disease (CKD) is increasingly recognized as a global public health problem. As inflammatory processes and genetic factors are involved in the pathogenesis of CKD, we have investigated the potential genetic contribution of Toll-like receptor (TLR) gene polymorphisms in CKD. In a case-control association study, 149 CKD patients and 429 healthy controls were genotyped by real-time polymerase chain reaction. CKD patients were defined as kidney damage (albuminuria, proteinuria or hematuria) or glomerular filtration rate < 60 ml/min/1.73 m(2) for 3 months or more. Single nucleotide polymorphisms (SNPs) at TLR-2 G2408A, TLR-4 A12874G and C13174T, and TLR-9 T-1237C, T-1486C, and G1635A were assessed, and linkage disequilibrium calculations and haplotype association analysis were undertaken. The functions of TLR-9 have been documented to recognize the viral and bacterial CpG DNA sequences, whereas detects microbe-derived peptidoglycan and lipopeptides and TLR-4 binds lipopolysaccharides. SNPs within the TLR genes may influence promoter activity, mRNA conformation and subcellular localization, and/or protein structure and function. Our results show that only the TLR-9 T-1237C and G1635A gene polymorphisms demonstrate an association with CKD (p = 0.002 and p = 0.04, respectively). The TLR-9 TCA haplotype at T-1237C, T-1486C, and G1635A was associated with a lower risk of CKD, whereas the TTA haplotype was associated with a higher risk of CKD. In the Han Chinese population, those who carry the C and A alleles at SNPs T-1237C and G1635A in the TLR-9 gene appear to be more susceptible to the development of CKD.

Genetic association between TNF-α G-308A and osteoarthritis in Asians: A case-control study and meta-analysis.

BACKGROUND: Osteoarthritis (OA) is an important health issue in elderly people. Many studies have suggested that genetic factors are important risk factors for OA, of which tumor necrosis factor-α (TNF-α) is one of the most examined genes. Moreover, several studies have investigated the relationship between TNF-α G-308A polymorphisms and OA risk, but consistent results have not been obtained. OBJECTIVE: This study examines the association between TNF-α G-308A polymorphisms and knee OA. Moreover, meta-analysis and trial sequential analysis (TSA) was used to determine whether this is a susceptibility gene for knee OA. METHODS: Between 2015 and 2019, 591 knee OA cases and 536 healthy controls were recruited. The Kellgren-Lawrence grading system was used to identify the knee OA cases. A meta-analysis was conducted including related studies published until 2020 from PubMed, Embase, and previous meta-analysis to improve the evidence level of the current study. The results were expressed as odds ratios (ORs) with corresponding 95% confidence intervals (CI) to evaluate the effect of this polymorphism on knee OA risk. The TSA was used to estimate the sample sizes required in this issue. RESULTS: A nonsignificant association was found between the AA genotype and knee OA [adjusted OR, 0.84; 95% CI, 0.62-1.15) in the recessive model] in the present case-control study, and analysis of other genetic models showed a similar trend. After adding the critical case-control samples for Asians, the TNF-α G-308A, AA genotype exhibited 2.57 times more risk of developing arthritis when compared with the GG + GA genotype (95% CI, 1.56-4.23), and the cumulative samples for TSA (n = 2182) were sufficient to obtain a definite conclusion. CONCLUSIONS: The results of this meta-analysis revealed that the TNF-α G-308A, AA genotype is a susceptible genotype for OA in the Asian population. This study integrated all current evidence to arrive at this conclusion, suggesting that future studies on Asians are not required.

Prognostic Analysis of Patients with Acute Myocardial Infarction Undergoing Implantation of Different Stents for the First Time.

For patients with acute myocardial infarction scheduled to undergo percutaneous coronary stent implantation, in most cases a drug-eluting stent is recommended as the first choice for treatment. However, there is a lack of research on the effectiveness of bare-metal stents and drug-eluting stents on patients with different types of myocardial infarction. Our objective was to explore the effects of bare-metal stents and drug-eluting stents on patients with different types of myocardial infarction in terms of major cardiovascular incidents. This retrospective cohort study included 934 patients with myocardial infarction undergoing coronary artery stent implantation for the first time at the cardiac catheter room of the Tri-Service General Hospital in the Neihu District between 2014 and 2018. Patients' information, including demographic data, laboratory data, cardiac echocardiography results, and angiocardiography results, was collected by reviewing medical records. Cox proportional hazards regression was used to adjust the potential confounding factors, and the adjusted data were then used to compare the correlation between different types of stents and major cardiovascular incidents in patients with ST-elevation myocardial infarction and non-ST-elevation myocardial infarction. After the confounding factors were adjusted, in patients with ST-elevation myocardial infarction receiving a drug-eluting stent compared with those receiving a bare-metal stent, it was found that the mortality risk was lower in terms of all causes of death (Adj-HR = 0.26, 95% CI = 0.14-0.48, p < 0.001) and cardiogenic death (Adj-HR = 0.20, 95% CI = 0.08-0.55, p = 0.002), the risk of non-fatal myocardial infarction was lower (Adj-HR = 0.17, 95% CI = 0.04-0.73, p = 0.017), and there was no difference in the risk of revascularization at the lesion site (Adj-HR = 0.59, 95% CI = 0.24-1.43, p = 0.243). It terms of the findings in patients with non-ST-elevation myocardial infarction, those receiving a drug-eluting stent had a lower risk of revascularization at the lesion site (Adj-HR = 0.48, 95% CI = 0.24-0.97, p = 0.04); however, there was no difference in the mortality risk in terms of all causes of death (Adj-HR = 0.71, 95% CI = 0.37-1.35, p = 0.296) or cardiogenic death (Adj-HR = 0.59, 95% CI = 0.18-1.90, p = 0.379),or in the risk of non-fatal myocardial infarction (Adj-HR = 0.27, 95% CI = 0.06-1.25, p = 0.093). Compared with bare-metal stents, drug-eluting stents provide better protection against death to receivers with ST-elevation myocardial infarction; however, this protection is decreased in receivers with non-ST-elevation myocardial infarction. It is recommended that for patients with non-ST-elevation myocardial infarction who are indicated to receive a drug-eluting stent, the clinical effectiveness of the treatment must be considered.