Effectiveness of a standardized quality control management procedure for COVID-19 RT-PCR testing: a large-scale diagnostic accuracy study in China.

BACKGROUND: The study aimed to construct a standardized quality control management procedure (QCMP) and access its accuracy in the quality control of COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR). METHODS: Considering the initial RT-PCR results without applying QCMP as the gold standard, a large-scale diagnostic accuracy study including 4,385,925 participants at three COVID-19 RT-PCR testing sites in China, Foshan (as a pilot test), Guangzhou and Shenyang (as validation sites), was conducted from May 21, 2021, to December 15, 2022. RESULTS: In the pilot test, the RT-PCR with QCMP had a high accuracy of 99.18% with 100% specificity, 100% positive predictive value (PPV), and 99.17% negative predictive value (NPV). The rate of retesting was reduced from 1.98% to 1.16%. Its accuracy was then consistently validated in Guangzhou and Shenyang. CONCLUSIONS: The RT-PCR with QCMP showed excellent accuracy in identifying true negative COVID-19 and relieved the labor and time spent on retesting.

Air Pollutants and Mortality Risk in Patients with Aortic Dissection: Evidence from a Clinical Cohort, Single-Cell Sequencing, and Proteomics.

We aimed to evaluate the association between air pollutants and mortality risk in patients with acute aortic dissection (AAD) in a longitudinal cohort and to explore the potential mechanisms of adverse prognosis induced by fine particulate matter (PM2.5). Air pollutants data, including PM2.5, PM10.0, nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were collected from official monitoring stations, and multivariable Cox regression models were applied. Single-cell sequencing and proteomics of aortic tissue were conducted to explore the potential mechanisms. In total, 1,267 patients with AAD were included. Exposure to higher concentrations of air pollutants was independently associated with an increased mortality risk. The high-PM2.5 group carried approximately 2 times increased mortality risk. There were linear associations of PM10, NO2, CO, and SO2 exposures with long-term mortality risk. Single-cell sequencing revealed an increase in mast cells in aortic tissue in the high-PM2.5 exposure group. Enrichment analysis of the differentially expressed genes identified the inflammatory response as one of the main pathways, with IL-17 and TNF signaling pathways being among the top pathways. Analysis of proteomics also identified these pathways. This study suggests that exposure to higher PM2.5, PM10, NO2, CO, and SO2 are associated with increased mortality risk in patients with AAD. PM2.5-related activation and degranulation of mast cells may be involved in this process.

Myricetin alleviates diabetic cardiomyopathy by regulating gut microbiota and their metabolites.

BACKGROUND: The gut microbiota is involved in the pathogenesis of diabetic cardiomyopathy (DCM). Myricetin protects cardiac function in DCM. However, the low bioavailability of myricetin fails to explain its pharmacological mechanisms thoroughly. Research has shown that myricetin has a positive effect on the gut microbiota. We hypothesize that myricetin improves the development of DCM via regulating gut microbiota. METHODS: DCM mice were induced with streptozotocin and fed a high-fat diet, and then treated with myricetin by gavage and high-fat diet for 16 weeks. Indexes related to gut microbiota composition, cardiac structure, cardiac function, intestinal barrier function, and inflammation were detected. Moreover, the gut contents were transplanted to DCM mice, and the effect of fecal microbiota transplantation (FMT) on DCM mice was assessed. RESULTS: Myricetin could improve cardiac function in DCM mice by decreasing cardiomyocyte hypertrophy and interstitial fibrosis. The composition of gut microbiota, especially for short-chain fatty acid-producing bacteria involving Roseburia, Faecalibaculum, and Bifidobacterium, was more abundant by myricetin treatment in DCM mice. Myricetin increased occludin expression and the number of goblet cells in DCM mice. Compared with DCM mice unfed with gut content, the cardiac function, number of goblet cells, and expression of occludin in DCM mice fed by gut contents were elevated, while cardiomyocyte hypertrophy and TLR4/MyD88 pathway-related proteins were decreased. CONCLUSIONS: Myricetin can prevent DCM development by increasing the abundance of beneficial gut microbiota and restoring the gut barrier function.

Preeclampsia/eclampsia impacts the structure and function of neonatal hearts probably by reducing myocardial compaction.

PURPOSE: Preeclampsia/Eclampsia (PE/E) poses significant risks to neonatal cardiac health. Traditional echocardiographic methods have limitations in detailing these impacts. This study hypothesized that echocardiographic radiomics could provide a more comprehensive assessment of the cardiac changes in neonates affected by PE/E. METHOD: In a comprehensive analysis, 2594 neonates underwent echocardiographic screening. From these, 556 were selected for detailed radiomics analysis, focusing on cardiac shape, movement, and texture features. A multiblock sparse partial least squares (sPLS) model integrated these features to assess their association with PE/E. RESULTS: Newborns from PE/E-affected pregnancies displayed lower left ventricular ejection fractions compared to the control group (61.1 % vs. 66.2 %). Our radiomics approach extracted 15,494 features per neonate, with the sPLS model identifying 17 features significantly correlated with PE/E. Among these, texture features representing myocardial non-compaction were most strongly correlated with PE/E (correlation coefficient r = 0.63). Detailed visualization of these texture features suggested that PE/E might lead to more pronounced myocardial non-compaction, characterized by a thicker non-compaction layer and increased cardiac trabeculation. CONCLUSIONS: Our findings demonstrate the potential of echocardiographic radiomics as a tool for assessing the impact of PE/E on neonatal cardiac function. The correlation between PE/E and myocardial non-compaction underlines the need for enhanced cardiac monitoring in neonates born to PE/E-affected mothers. This study contributes to a better understanding of PE/E's cardiac implications, potentially guiding future clinical practices.

Upregulation of NF-κB by USP24 aggravates ferroptosis in diabetic cardiomyopathy.

BACKGROUND: Recent investigations have proposed a potential causal association between the occurrence of ferroptosis, nuclear factor kappa B (NF-κB) and ubiquitin-specific protease 24 (USP24). Nevertheless, the mechanism of USP24 and NF-κB regulation of ferroptosis in the context of diabetic cardiomyopathy (DCM) remain unclear. METHODS: In this study, a high-fat diet and a streptozotocin-induced mouse DCM model were established, and high glucose and palmitic acid treatment of H9c2 cells and neonatal mouse primary cardiomyocytes (NMPCs) was used as an in vitro DCM models. Utilizing both the in vivo and in vitro DCM models, we assessed of USP24, NF-κB, and ferroptosis levels, and explored the relationship among them. RESULTS: In in vivo and in vitro DCM models, increased expression of USP24, NF-κB, phosphorylated NF-κB (p-NF-κB) and fatty acid-CoA ligase 4 (FACL4) were detected, along with accumulated iron, as well as reduced ferritin heavy chain 1 (FTH1), solute carrier family 7 member 11 (SLC7A11) and antioxidant capacity. Knockdown of USP24 resulted in a reduction of NF-κB levels, while knockdown of NF-κB did not lead to a decrease in USP24 expression. Moreover, in H9c2 cells, knockdown of USP24 and NF-κB separately resulted in reduced levels of FACL4, increased levels of SLC7A11 and FTH1, as well as improved antioxidant capacity and cell viability. In shUSP24 knockdown H9c2 cells, administration of phorbol 12-myristate 13-acetate (PMA) activated NF-κB, subsequently reversing the previously observed effect caused by USP24 knockdown. CONCLUSIONS: These findings show that USP24 upregulates NF-κB to promote ferroptosis in DCM.

Abnormal adiposity indices are associated with an increased risk of diabetes in a non-obese Asian population.

OBJECTIVES: The aim of this study was to evaluate the association between adiposity indices and the risk of incident diabetes and to compare their predictive ability in non-obese healthy individuals. STUDY DESIGN: Population-based cohort study. METHODS: Data were taken from the NAGALA research study, which enrolled Japanese adults aged 18-79 years. Cox regression was used to evaluate the association between adiposity indices (including waist circumference [WC], waist-to-height ratio [WHtR], lipid accumulation product index [LAP], body roundness index [BRI], visceral adiposity index [VAI] and Chinese visceral adiposity index [CVAI]) and diabetes risk. The performance of the indices for predicting diabetes was explored using area under the receiver operating characteristic curve (AUC). A Chinese community-based population was used for validation. RESULTS: A total of 12,940 healthy Japanese individuals with normal body mass index and glycaemic levels were included and were followed up for a median of 6 years. Multivariable Cox models revealed a positive and significant association between all indices and incident diabetes, with the hazard ratios for the highest quartile of the indices ranging from 1.89 to 2.90 (all P-values < 0.01). A non-linear association between WC, BRI and VAI and a linear association between WHtR, LAP and CVAI and diabetes risk were observed. CVAI, VAI and LAP had comparable ability in predicting diabetes, with the highest AUC being 0.733 for CVAI. Data from 10,830 Chinese individuals confirmed these results. CONCLUSIONS: Adiposity indices are associated with incident diabetes in healthy non-obese individuals. Participants in the highest quartile of WC, WHtR, LAP, BRI, VAI and CVAI had an increased risk of developing diabetes.

Differentiating Origins of Outflow Tract Ventricular Arrhythmias: The Correction of Transitional Zone Index Is Not Superior to the Original One.

INTRODUCTION: Our team once proposed a correction of transitional zone index (CTZI) based on the transitional zone index (TZI) in view of achieving a more precise prediction of outflow tract ventricular arrhythmia (OTVA). The predictive accuracy of these two electrocardiogram (ECG) algorithms has not been validated and compared. The purpose of this study was to compare the predictive accuracy of TZI and CTZI in a much larger population with idiopathic OTVA. METHODS: The predictive accuracy of TZI and CTZI was compared in 695 individuals with idiopathic premature ventricular complex or ventricular tachycardia which exhibited a left bundle branch block pattern and inferior axis QRS morphology. Receiver operating characteristic curve analysis, decision curve analysis, and calibration curve were used to compare the predictive accuracy of TZI and CTZI. RESULTS: TZI and CTZI manifested the similar area under the curve. While a TZI of <0 predicted a left ventricular outflow tract (LVOT) origin with a high specificity of 88.2% but a low sensitivity of 67.1%, a CTZI of <0 yielded a high sensitivity of 84.3% but a low specificity of 59.5% in the overall analysis. Similar results were yielded in the sub-analysis of participants with a precordial transition occurring at lead V3. In the sub-analysis of participants with a TZI = 0, CTZI demonstrated a bit higher but not satisfactory predictive accuracy than TZI. CONCLUSION: Based on the scientific spirit of self-criticism and seeking truth from facts, our team disproves the correction of TZI proposed previously.

Predicting 1-, 3-, 5-, and 8-year all-cause mortality in a community-dwelling older adult cohort: relevance for predictive, preventive, and personalized medicine.

Background: Population aging is a global public health issue involving increased prevalence of age-related diseases, and concomitant burden on medical resources and the economy. Ninety-two diseases have been identified as age-related, accounting for 51.3% of the global adult disease burden. The economic cost per capita for older people over 60 years is 10 times that of the younger population. From the aspects of predictive, preventive, and personalized medicine (PPPM), developing a risk-prediction model can help identify individuals at high risk for all-cause mortality and provide an opportunity for targeted prevention through personalized intervention at an early stage. However, there is still a lack of predictive models to help community-dwelling older adults do well in healthcare. Objectives: This study aims to develop an accurate 1-, 3-, 5-, and 8-year all-cause mortality risk-prediction model by using clinical multidimensional variables, and investigate risk factors for 1-, 3-, 5-, and 8-year all-cause mortality in community-dwelling older adults to guide primary prevention. Methods: This is a two-center cohort study. Inclusion criteria: (1) community-dwelling adult, (2) resided in the districts of Chaonan or Haojiang for more than 6 months in the past 12 months, and (3) completed a health examination. Exclusion criteria: (1) age less than 60 years, (2) more than 30 incomplete variables, (3) no signed informed consent. The primary outcome of the study was all-cause mortality obtained from face-to-face interviews, telephone interviews, and the medical death database from 2012 to 2021. Finally, we enrolled 5085 community-dwelling adults, 60 years and older, who underwent routine health screening in the Chaonan and Haojiang districts, southern China, from 2012 to 2021. Of them, 3091 participants from Chaonan were recruited as the primary training and internal validation study cohort, while 1994 participants from Haojiang were recruited as the external validation cohort. A total of 95 clinical multidimensional variables, including demographics, lifestyle behaviors, symptoms, medical history, family history, physical examination, laboratory tests, and electrocardiogram (ECG) data were collected to identify candidate risk factors and characteristics. Risk factors were identified using least absolute shrinkage and selection operator (LASSO) models and multivariable Cox proportional hazards regression analysis. A nomogram predictive model for 1-, 3-, 5- and 8-year all-cause mortality was constructed. The accuracy and calibration of the nomogram prediction model were assessed using the concordance index (C-index), integrated Brier score (IBS), receiver operating characteristic (ROC), and calibration curves. The clinical validity of the model was assessed using decision curve analysis (DCA). Results: Nine independent risk factors for 1-, 3-, 5-, and 8-year all-cause mortality were identified, including increased age, male, alcohol status, higher daily liquor consumption, history of cancer, elevated fasting glucose, lower hemoglobin, higher heart rate, and the occurrence of heart block. The acquisition of risk factor criteria is low cost, easily obtained, convenient for clinical application, and provides new insights and targets for the development of personalized prevention and interventions for high-risk individuals. The areas under the curve (AUC) of the nomogram model were 0.767, 0.776, and 0.806, and the C-indexes were 0.765, 0.775, and 0.797, in the training, internal validation, and external validation sets, respectively. The IBS was less than 0.25, which indicates good calibration. Calibration and decision curves showed that the predicted probabilities were in good agreement with the actual probabilities and had good clinical predictive value for PPPM. Conclusion: The personalized risk prediction model can identify individuals at high risk of all-cause mortality, help offer primary care to prevent all-cause mortality, and provide personalized medical treatment for these high-risk individuals from the PPPM perspective. Strict control of daily liquor consumption, lowering fasting glucose, raising hemoglobin, controlling heart rate, and treatment of heart block could be beneficial for improving survival in elderly populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00342-4.

Genetic and immunological insights into COVID-19 with acute myocardial infarction: integrated analysis of mendelian randomization, transcriptomics, and clinical samples.

Background: Globally, most deaths result from cardiovascular diseases, particularly ischemic heart disease. COVID-19 affects the heart, worsening existing heart conditions and causing myocardial injury. The mechanistic link between COVID-19 and acute myocardial infarction (AMI) is still being investigated to elucidate the underlying molecular perspectives. Methods: Genetic risk assessment was conducted using two-sample Mendelian randomization (TSMR) to determine the causality between COVID-19 and AMI. Weighted gene co-expression network analysis (WGCNA) and machine learning were used to discover and validate shared hub genes for the two diseases using bulk RNA sequencing (RNA-seq) datasets. Additionally, gene set enrichment analysis (GSEA) and single-cell RNA-seq (scRNA-seq) analyses were performed to characterize immune cell infiltration, communication, and immune correlation of the hub genes. To validate the findings, the expression patterns of hub genes were confirmed in clinical blood samples collected from COVID-19 patients with AMI. Results: TSMR did not find evidence supporting a causal association between COVID-19 or severe COVID-19 and AMI. In the bulk RNA-seq discovery cohorts for both COVID-19 and AMI, WGCNA's intersection analysis and machine learning identified TLR4 and ABCA1 as significant hub genes, demonstrating high diagnostic and predictive value in the RNA-seq validation cohort. Single-gene GSEA and single-sample GSEA (ssGSEA) revealed immune and inflammatory roles for TLR4 and ABCA1, linked to various immune cell infiltrations. Furthermore, scRNA-seq analysis unveiled significant immune dysregulation in COVID-19 patients, characterized by altered immune cell proportions, phenotypic shifts, enhanced cell-cell communication, and elevated TLR4 and ABCA1 in CD16 monocytes. Lastly, the increased expression of TLR4, but not ABCA1, was validated in clinical blood samples from COVID-19 patients with AMI. Conclusion: No genetic causal link between COVID-19 and AMI and dysregulated TLR4 and ABCA1 may be responsible for the development of immune and inflammatory responses in COVID-19 patients with AMI.

Visceral fat and its dynamic change are associated with renal damage: Evidence from two cohorts.

BACKGROUND AND AIMS: To evaluate the association of Chinese visceral adiposity index (CVAI) and its dynamic trends with risk of renal damage, and to compare its prediction performance with that of other obesity indices. METHODS AND RESULTS: A community-based population with 23 905 participants from Shantou city was included in the cross-sectional analysis. A total of 9,778 individuals from two separated cohort were included in the longitudinal portion. Five patterns of CVAI change were predefined (low-stable, decreasing, moderate, increasing, and persistent-high). Logistic and Cox regressions were used to evaluate the association between CVAI and renal damage. We explored potential mechanisms using the mediating effect method, and the prediction performance was determined by receiver operating characteristic curve analysis. Results from both cross-sectional and longitudinal data revealed a positive and linear association between CVAI and risk of renal damage. Pooled analysis of the two cohorts showed that per unit increase in Z score of CVAI induced 18% increased risk of renal damage (P = .008). Longitudinal trends of CVAI were also associated with renal damage, and the moderate, increasing, and persistent-high patterns showing a higher risk. Blood pressure and glucose had a mediating effect on renal damage induced by CVAI. Among several obesity indices, CVAI was the optimal for predicting renal damage. CONCLUSION: A higher level of immediate CVAI and longitudinal increasing and persistent-high patterns of CVAI were independently associated with increased risk of renal damage. Monitoring immediate level and long-term trend of CVAI may contribute to the prevention of renal damage.

COVID-19 lessons to protect populations against future pandemics by implementing PPPM principles in healthcare.

The coronavirus disease 2019 (COVID-19) pandemic has continued for more than 3 years, placing a huge burden on society worldwide. Although the World Health Organization (WHO) has declared an end to COVID-19 as a Public Health Emergency of International Concern (PHEIC), it is still considered a global threat. Previously, there has been a long debate as to whether the COVID-19 emergency will eventually end or transform into a more common infectious disease from a PHEIC, and how should countries respond to similar pandemics in the future more time-efficiently and cost-effectively. We reviewed the past, middle and current situation of COVID-19 based on bibliometric analysis and epidemiological data. Thereby, the necessity is indicated to change the paradigm from reactive healthcare services to predictive, preventive and personalised medicine (PPPM) approach, in order to effectively protect populations against COVID-19 and any future pandemics. Corresponding measures are detailed in the article including the involvement of multi-professional expertise, application of artificial intelligence, rapid diagnostics and patient stratification, and effective protection, amongst other to be considered by advanced health policy.

Maternal High Fat Diet and its expressions in the Heart and Liver in the Mice Embryogenesis.

BACKGROUND: The developmental biology for the nonalcoholic fatty liver disease and coronary heart disease are known but elaborative ideas of triglycerides phenomenon in the embryo-genesis of the liver and the heart are still not clear. OBJECTIVE: The aim of the study was to relate different triglycerides like LXRα, LPL, LDL R, PPARG-, and SREBP-1C expression in the high fat-fed mice with the normal-fed diet mice in the process of developmen-tal and embryo-genesis biology. METHODS: Tissue preparation was done by RIPA lysis. Different protein content was obtained via western blot for the 6 samples namely A.3 months embryo B.4 months embryo C.Birth day embryo D.3 days infant E. 2 weeks infant F. 4 weeks infant. Protein lysates from the heart tissues of the mice were obtained via ho-mogenization and centrifugation. Hematoxylin and Eosin staining (H and E) were done to see the fat droplets in the liver tissues at the different developmental stages. RESULT: LXRα,SREBP-1C expression in 3 months embryo and 4 months embryo is highly expressed in the high-fat diet. LDL-R in the high-fat diet mice is increased in 3 days infant heart but in 3 months and 4 months embryo it has low expression but from the 0th day to the 4 weeks the expression is in a decreasing trend. Similarly, LPL is highly expressed in 3 months embryo and 0th day(Birthday) and thus low expression indecreasing order until 4 weeks infant. Thus, these results collectively show that a maternal HF diet in-creases the expression of proteins such as LPL, and LDLr in the embryo phase and thus getting normal ex-pressions in the adult phase that facilitate Triglycerides (TAG) hydrolysis across the liver and the heart. Also, maternal high-fat diet increases the SREBP1c expression, leading to stimulation of LPL Expression. CONCLUSION: In summary, using a pregnant mice model, we found that a maternal high-fat diet increases fe-tal fat accumulation. Elevated placental LPL activity and expression of genes that facilitate placental lipid transport suggest that enhanced placental lipid transport may play a key role in maternal nutrition and obesi-ty-induced fetal fat accumulation.

Effect of probiotic supplementation on in-hospital mortality in patients with acute myocardial infarction: a study protocol for an open-label, randomized, controlled, superiority clinical trial.

BACKGROUND: Recent studies have demonstrated a correlation between intestinal flora and the severity of myocardial infarction as well as post-myocardial infarction repair. However, few studies have investigated whether probiotics reduce mortality and improve cardiovascular outcomes in patients with acute myocardial infarction. In this study, we will conduct a randomized controlled trial (RCT) to evaluate the effect of probiotics on in-hospital mortality and the incidence of major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI). METHODS: This is an open-label, randomized, controlled, superiority clinical trial involving 2594 adult patients who were diagnosed with acute myocardial infarction. Patients will be randomized to (1) receive bifidobacteria triple viable capsule (Bifidobacterium longum, Lactobacillus acidophilus, and Enterococcus faecalis) 840 mg, twice a day, plus standard treatment strategy during the hospital stay, for a maximum of 30 days, or (2) receive the standard treatment strategy and will not take the bifidobacterium triple live capsule. The primary outcome was in-hospital all-cause mortality. DISCUSSION: The purpose of this clinical trial is to determine whether probiotics can reduce in-hospital mortality and improve prognosis in patients with AMI, and the results will provide evidence for probiotics as a complementary treatment for AMI. TRIAL REGISTRATION: Chinese Clinical Trials Registry ChiCTR2000038797. Registered on 2 October 2020.

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (LASSO logistic regression, random forest, backpropagation neural network, and support vector machines) to predict the occurrence of PIH in a prospective cohort. Candidate features for predicting the occurrence of middle and late PIH were acquired using a LASSO algorithm. The performance of predictive models was assessed using receiver operating characteristic analysis. Finally, a nomogram was established with the model scores, age, and nulliparity. Calibration, clinical usefulness, and internal validation were used to assess the performance of the nomogram. In the training set (2258 pregnant women), eleven candidate factors in the first trimester were significantly associated with the occurrence of PIH (P < 0.001 in the training set). Four models showed AUCs from 0.780 to 0.816 in the training set. For the validation set (939 pregnant women), AUCs varied from 0.516 to 0.795. The nomogram showed good discrimination, with an AUC of 0.847 (95% CI: 0.805-0.889) in the training set and 0.753 (95% CI: 0.653-0.853) in the validation set. Decision curve analysis suggested that the model was clinically useful. The model developed using LASSO logistic regression achieved the best performance in predicting the occurrence of PIH. The derived nomogram, which incorporates the model score and maternal risk factors, can be used to predict PIH in clinical practice. We develop a model with good performance for clinical prediction of PIH in the first trimester.

Deciphering HERG mutation in long QT syndrome type 2 using antisense oligonucleotide-mediated techniques: Lessons from cystic fibrosis.

Long QT syndrome type 2 (LQT2) is a genetic disorder caused by mutations in the KCNH2 gene, also known as the human ether-a-go-go-related gene (HERG). More than 30% of HERG mutations result in a premature termination codon that triggers a process called nonsense-mediated messenger RNA (mRNA) decay (NMD), where the mRNA transcript is degraded. NMD is a quality control mechanism that removes faulty mRNA to prevent the translation of truncated proteins. Recent advances in antisense oligonucleotide (ASO) technology in the field of cystic fibrosis (CF) have yielded significant progress, including the ASO-mediated comprehensive characterization of key NMD factors and exon-skipping therapy. These advances have contributed to our understanding of the role of premature termination codon-containing mutations in disease phenotypes and have also led to the development of potentially useful therapeutic strategies. Historically, studies of CF have provided valuable insights for the research on LQT2, particularly concerning increasing the expression of HERG. In this article, we outline the current state of knowledge regarding ASO, NMD, and HERG and discuss the introduction of ASO technology in the CF to elucidate the pathogenic mechanisms through targeting NMD. We also discuss the potential clinical therapeutic benefits and limitations of ASO for the management of LQT2. By drawing on lessons learned from CF research, we explore the potential translational values of these advances into LQT2 studies.

Diagnostic accuracy of autoverification and guidance system for COVID-19 RT-PCR results.

Background: To date, most countries worldwide have declared that the pandemic of COVID-19 is over, while the WHO has not officially ended the COVID-19 pandemic, and China still insists on the personalized dynamic COVID-free policy. Large-scale nucleic acid testing in Chinese communities and the manual interpretation for SARS-CoV-2 nucleic acid detection results pose a huge challenge for labour, quality and turnaround time (TAT) requirements. To solve this specific issue while increase the efficiency and accuracy of interpretation, we created an autoverification and guidance system (AGS) that can automatically interpret and report the COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) results relaying on computer-based autoverification procedure and then validated its performance in real-world environments. This would be conductive to transmission risk prediction, COVID-19 prevention and control and timely medical treatment for positive patients in the context of the predictive, preventive and personalized medicine (PPPM). Methods: A diagnostic accuracy test was conducted with 380,693 participants from two COVID-19 test sites in China, the Hong Kong Hybribio Medical Laboratory (n = 266,035) and the mobile medical shelter at a Shanghai airport (n = 114,658). These participants underwent SARS-CoV-2 RT-PCR from March 28 to April 10, 2022. All RT-PCR results were interpreted by laboratorians and by using AGS simultaneously. Considering the manual interpretation as gold standard, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were applied to evaluate the diagnostic value of the AGS on the interpretation of RT-PCR results. Results: Among the 266,035 samples in Hong Kong, there were 16,356 (6.15%) positive, 231,073 (86.86%) negative, 18,606 (6.99%) indefinite, 231,073 (86.86%, negative) no retest required and 34,962 (13.14%, positive and indefinite) retest required; the 114,658 samples in Shanghai consisted of 76 (0.07%) positive, 109,956 (95.90%) negative, 4626 (4.03%) indefinite, 109,956 (95.90%, negative) no retest required and 4702 (4.10%, positive and indefinite) retest required. Compared to the fashioned manual interpretation, the AGS is a procedure of high accuracy [99.96% (95%CI, 99.95-99.97%) in Hong Kong and 100% (95%CI, 100-100%) in Shanghai] with perfect sensitivity [99.98% (95%CI, 99.97-99.98%) in Hong Kong and 100% (95%CI, 100-100%) in Shanghai], specificity [99.87% (95%CI, 99.82-99.90%) in Hong Kong and 100% (95%CI, 99.92-100%) in Shanghai], PPV [99.98% (95%CI, 99.97-99.99%) in Hong Kong and 100% (95%CI, 99.99-100%) in Shanghai] and NPV [99.85% (95%CI, 99.80-99.88%) in Hong Kong and 100% (95%CI, 99.90-100%) in Shanghai]. The need for manual interpretation of total samples was dramatically reduced from 100% to 13.1% and the interpretation time fell from 53 h to 26 min in Hong Kong; while the manual interpretation of total samples was decreased from 100% to 4.1% and the interpretation time dropped from 20 h to 16 min at Shanghai. Conclusions: The AGS is a procedure of high accuracy and significantly relieves both labour and time from the challenge of large-scale screening of SARS-CoV-2 using RT-PCR. It should be recommended as a powerful screening, diagnostic and predictive system for SARS-CoV-2 to contribute timely the ending of the COVID-19 pandemic following the concept of PPPM.

Dysnatremia is associated with increased risk of all-cause mortality within 365 days post-discharge in patients with atrial fibrillation without heart failure: A prospective cohort study.

Aim: The aim of this study is to evaluate the association between serum sodium concentrations at hospital admission and all-cause mortality within 365 days post-discharge in patients with atrial fibrillation (AF) without heart failure (HF). Methods: The prospective cohort study enrolled 1,446 patients with AF without HF between November 2018 and October 2020. A follow-up was performed 30, 90, 180, and 365 days after enrollment through outpatient visits or telephone interviews. All-cause mortality was estimated in three groups according to serum sodium concentrations: hyponatremia (< 135 mmol/L), normonatremia (135-145 mmol/L), and hypernatremia (> 145 mmol/L). We estimated the risk of all-cause mortalities using univariable and multivariable Cox proportional hazards models with normonatremia as the reference. Results: The all-cause mortalities of hyponatremia, normonatremia, and hypernatremia were 20.6, 9.4, and 33.3% within 365 days post-discharge, respectively. In the univariable analysis, hyponatremia (HR: 2.19, CI 1.5-3.2) and hypernatremia (HR: 4.03, CI 2.32-7.02) increased the risk of all-cause mortality. The HRs for hyponatremia and hypernatremia were 1.55 (CI 1.05-2.28) and 2.55 (CI 1.45-4.46) after adjustment for age, diabetes mellitus, loop diuretics, antisterone, antiplatelet drugs, and anticoagulants in the patients with AF without HF. The association between serum sodium concentrations and the HRs of all-cause mortality was U-shaped. Conclusion: Dysnatremia at hospital admission was an independent factor for all-cause mortality in patients with AF without HF within 365 days post-discharge.

Translation and cross-cultural validation of a precision health tool, the Suboptimal Health Status Questionnaire-25, in Korean.

Background: Suboptimal health status (SHS) is a reversible stage between health and illness that is characterized by health complaints, low energy, general weakness, and chronic fatigue. The Suboptimal Health Status Questionnaire-25 (SHSQ-25) has been validated in three major populations (African, Asian, and Caucasian) and is internationally recognized as a reliable and robust tool for health estimation in general populations. This study focused on the development of K-SHSQ-25, a Korean version of the SHSQ-25, from its English version. Methods: The SHSQ-25 was translated from English to Korean according to international guidelines set forth by the World Health Organization (WHO) for health instrument translation between different languages. A subsequent cross-sectional survey involved 460 healthy South Korean participants (aged 18-83 years; 65.4% females) to answer the 25 questions focusing on the health perspectives of 5 domains, 1) fatigue, 2) cardiovascular health, 3) digestive tract, 4) immune system and 5) mental health. The K-SHSQ-25 was further validated using tests for reliability, internal consistency, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). Results: The version of K-SHSQ-25 achieved linguistic, cultural, and conceptual equivalence to the English version. The intraclass correlation coefficient (ICC) of test-retest reliability for individual items ranged from 0.88 to 0.99. Reliability estimates based on internal consistency reached a Cronbach's α of 0.953; the Cronbach's α for each domain ranged from 0.76 to 0.94. Regarding construct validity, the EFA of the K-SHSQ-25 generally replicated the multidimensional structure (fatigue, cardiovascular, digestive, immune system, and mental health) and 25 questions. The CFA revealed that the root mean square error of approximation (RMSEA), goodness-of-fit index (GFI) and adjusted goodness of fit index (AGFI) were excellent (RMSEA = 0.069<0.08, GFI = 0.929>0.90, AGFI = 0.907>0.90). The five domains of the K-SHSQ-25 showed significant correlations with each other (r = 0.59-0.81, P<0.001). The cut-off point of K-SHSQ-25 for SHS was determined as an SHS score of 25. The prevalence of SHS in this study was 60.0% (276/460), with 47.8% (76/159) for males and 58.5% for females (176/301). Conclusions: Our results indicate that the Korean version of SHSQ-25, K-SHSQ-25, is a transcultural equivalent, robust, valid, and reliable assessment tool for evaluating SHS in the Korean-speaking population.