Association between ambient PM1 and the prevalence of chronic kidney disease in China: A nationwide study

Particulate of diameter ≤ 1 µm (PM1) presents a novel risk factor of adverse health effects. Nevertheless, the association of PM1 with the risk of chronic kidney disease (CKD) in the general population is not well understood, particularly in regions with high PM1 levels like China. Based on a nationwide representative survey involving 47,204 adults and multi-source ambient air pollution inversion data, the present study evaluated the association of PM1 with CKD prevalence in China. The two-year average PM1, particulate of diameter ≤ 2.5 µm (PM2.5), and PM1-2.5 values were accessed using a satellite-based random forest approach. CKD was defined as estimated glomerular filtration rate < 60 ml/min/1.73 m2 or albuminuria. The results suggested that a 10 μg/m3 rise in PM1 was related to a higher CKD risk (odds ratio [OR], 1.13; 95% confidence interval [CI] 1.08-1.18) and albuminuria (OR, 1.11; 95% CI, 1.05-1.17). The association between PM1 and CKD was more evident among urban populations, older adults, and those without comorbidities such as diabetes or hypertension. Every 1% increase in the PM1/PM2.5 ratio was related to the prevalence of CKD (OR, 1.03; 95% CI, 1.03-1.04), but no significant relationship was found for PM1-2.5. In conclusion, the present study demonstrated long-term exposure to PM1 was associated with an increased risk of CKD in the general population and PM1 might play a leading role in the observed relationship of PM2.5 with the risk of CKD. These findings provide crucial evidence for developing air pollution control strategies to reduce the burden of CKD.

Graph-guided deep hashing networks for similar patient retrieval

With the rapid growth and widespread application of electronic health records (EHRs), similar patient retrieval has become an important task for downstream clinical decision support such as diagnostic reference, treatment planning, etc. However, the high dimensionality, large volume, and heterogeneity of EHRs pose challenges to the efficient and accurate retrieval of patients with similar medical conditions to the current case. Several previous studies have attempted to alleviate these issues by using hash coding techniques, improving retrieval efficiency but merely exploring underlying characteristics among instances to preserve retrieval accuracy. In this paper, drug categories of instances recorded in EHRs are regarded as the ground truth to determine the pairwise similarity, and we consider the abundant semantic information within such multi-labels and propose a novel framework named Graph-guided Deep Hashing Networks (GDHN). To capture correlation dependencies among the multi-labels, we first construct a label graph where each node represents a drug category, then a graph convolution network (GCN) is employed to derive the multi-label embedding of each instance. Thus, we can utilize the learned multi-label embeddings to guide the patient hashing process to obtain more informative and discriminative hash codes. Extensive experiments have been conducted on two datasets, including a real-world dataset concerning IgA nephropathy from Peking University First Hospital, and a publicly available dataset from MIMIC-III, compared with traditional hashing methods and state-of-the-art deep hashing methods using three evaluation metrics. The results demonstrate that GDHN outperforms the competitors at different hash code lengths, validating the superiority of our proposal.

Hospitalizations of Chronic Dialysis Patients: A National Study in China

Background

Patients receiving chronic dialysis are usually with multiple comorbidities and at high risk for hospitalization, which lead to tremendous health care resource utilization. This study aims to explore the characteristics of hospitalizations among chronic dialysis patients in China.

Methods

Hospital admissions from January 2013 to December 2015 were extracted from a national inpatient database in China. Chronic dialysis, including hemodialysis and peritoneal dialysis, was identified according to inpatient discharge records and International Classification of Diseases-10 (ICD-10) codes. The primary kidney disease, causes of admissions, modalities of dialysis, and comorbidities were analyzed. Multivariable logistic regression model was used to assess the association of patient characteristics with multiple hospitalizations per year.

Results

Altogether, 266,636 hospitalizations from 124,721 chronic dialysis patients were included in the study. The mean age was 54.46 ± 15.63 years and 78.29% of them were receiving hemodialysis. The leading cause of hospitalizations was dialysis access-related, including dialysis access creation (25.06%) and complications of access (21.09%). The following causes were nonaccess surgery (1.89%), cardiovascular disease (1.66%), and infectious diseases (1.43%). One-fourth of the patients were hospitalized more than once per year. Multivariate logistic regression models indicated that the primary kidney disease of diabetic kidney disease (odds ratio [OR]: 1.16, 95% confidence interval [CI]: 1.11-1.22) or hypertensive nephropathy (OR: 1.33, 95% CI: 1.27-1.40), coronary heart disease (OR: 1.09, 95% CI: 1.05-1.14), cancer (OR: 1.21, 95% CI: 1.13-1.30), or modality of peritoneal dialysis (OR: 2.67, 95% CI: 2.59-2.75) was risk factors for multiple hospitalizations.

Conclusion

Our study described characteristics and revealed the burden of hospitalizations of chronic dialysis patients in China. These findings highlight the importance of effective and efficient management strategies to reduce the high burden of hospitalization in dialysis population.

The relationship between tumour dosimetry, response, and overall survival in patients with unresectable Neuroendocrine Neoplasms (NEN) treated with 177Lu DOTATATE (LuTate)

Peptide Receptor Radionuclide Therapy (PRRT) delivers targeted radiation to Somatostatin Receptor (SSR) expressing Neuroendocrine Neoplasms (NEN). We sought to assess the predictive and prognostic implications of tumour dosimetry with respect to response by 68 Ga DOTATATE (GaTate) PET/CT molecular imaging tumour volume of SSR (MITVSSR) change and RECIST 1.1, and overall survival (OS).

METHODS

Patients with gastro-entero-pancreatic (GEP) NEN who received LuTate followed by quantitative SPECT/CT (Q-SPECT/CT) the next day (Jul 2010 to Jan 2019) were retrospectively reviewed. Single time-point (STP) lesional dosimetry was performed for each cycle using population-based pharmacokinetic modelling. MITVSSR and RECIST 1.1 were measured at 3-months post PRRT.

RESULTS

Median of 4 PRRT cycles were administered to 90 patients (range 2-5 cycles; mean 27.4 GBq cumulative activity; mean 7.6 GBq per cycle). 68% received at least one cycle with radiosensitising chemotherapy (RSC). RECIST 1.1 partial response was 24%, with 70% stable and 7% progressive disease. Cycle 1 radiation dose in measurable lesions was associated with local response (odds ratio 1.5 per 50 Gy [95% CI: 1.1-2.0], p = 0.002) when adjusted by tumour grade and RSC. Median change in MITVSSR was -63% (interquartile range -84 to -29), with no correlation with radiation dose to the most avid lesion on univariable or multivariant analyses (5.6 per 10 Gy [95% CI: -1.6, 12.8], p = 0.133). OS at 5-years was 68% (95% CI: 56-78%). Neither baseline MITVSSR (hazard ratio 1.1 [95% CI: 1.0, 1.2], p = 0.128) nor change in baseline MITVSSR (hazard ratio 1.0 [95% CI: 1.0, 1.1], p = 0.223) were associated with OS when adjusted by tumour grade and RSC but RSC was (95% CI: 0.2, 0.8, p = 0.012).

CONCLUSION

Radiation dose to tumour during PRRT was predictive of radiologic response but not survival. Survival outcomes may relate to other biological factors. There was no evidence that MITVSSR change was associated with OS, but a larger study is needed.

The global syndemic of metabolic diseases in the young adult population: a consortium from the Global Burden of Disease 2000-2019

Funding Acknowledgements

Type of funding sources: None.

Background

A large proportion of premature deaths are related to metabolic diseases in the young adult population. We examined the global trends and mortality of metabolic diseases using estimates from the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019 in individuals aged below 40 years.

Methods

From 2000-2019, global estimates of prevalence, deaths, and disability-adjusted life years (DALYs) were described for metabolic diseases (type 2 diabetes mellitus [T2DM], hypertension, non-alcoholic fatty liver disease [NAFLD]). Global estimates were limited to mortality and DALYs for risk factors (hyperlipidemia and obesity). Subgroup analyses were performed based on sex, geographical regions and Socio-Demographic Index (SDI). Age-standardized prevalence, death, and DALYs were presented per 100,000 population with 95% uncertainty intervals (UI).

Findings

The prevalence for all metabolic diseases increased from 2000-2019, with the most pronounced increase in males and high SDI countries. In 2019, the highest age-standardised death rates were observed in hypertension (133·88 [121·25-155·73]; males, 160·13 [138·91-180·79]; females, 119·66 [102·33-136·86]), followed by obesity (62·59 [39·92-89·13]; males, 66·55 [39·76-97·21]; females, 58·14 [38·53-81·39]), hyperlipidemia (56·51 [41·83-73·62]; males, 67·33 [50·78-86·43]; females, 46·50 [32·70-62·38]), T2DM (18·49 [17·18-19·66]; males, 19·94 [18·50-21·32]; females, 17·30 [15·62-18·70]) and NAFLD (2·09 [1·61-2·60]; males, 2·38 [1·82-3·02]; females, 1·82 [1·41-2·27]). Similarly, obesity (1932·54 [1276·61-2639·74]) had the highest age-standardised DALYs, followed by hypertension (2885·57 [2580·75-3201·05]), hyperlipidemia (1207·15 [975·07-1461·11]), T2DM (801·55 [670·58-954·43]) and NAFLD (53·33 [40·73-68·29]). Mortality rates decreased over time in hyperlipidemia (-60%), hypertension (-47%), NAFLD (-31%) and T2DM (-20%), but not in obesity (107% increase). The highest metabolic-related mortality was observed in the Eastern Mediterranean and low SDI countries.

Conclusion

The growing prevalence of metabolic diseases, increasing obesity-related mortality trends, and the sex-regional-socioeconomic disparities evident in young adulthood, present the concerning global burden of metabolic diseases now and in the years ahead.

Higher risk of adverse cardiovascular outcomes in women with type 2 diabetes mellitus: an umbrella review of systematic reviews

Funding Acknowledgements

Type of funding sources: None.

Background

Previous studies have shown that females with type 2 diabetes mellitus (T2DM) may have an excess mortality risk compared to males. Furthermore, other studies have reported sex differences in managing cardiovascular risk factors, such as controlling hypertension and hypercholesterolemia.

Purpose

With the growing evidence from systematic reviews examining the sex differences in cardiovascular outcomes for patients with T2DM, an umbrella review is an essential next step to synthesising and assessing the strength of the available evidence.

Methods

Medline and Embase were searched from inception till 7th August 2022 for systematic reviews and meta-analyses studying the effects of sex on cardiovascular outcomes in T2DM patients. Results from reviews were synthesised with a narrative synthesis, with a tabular presentation of findings and forest plots for reviews that performed a meta-analysis. AMSTAR 2 tool was used to assess the methodological quality of included reviews, while the GRADE assessment was used to assess the quality of evidence for outcomes.

Results

A total of 28 studies evaluating sex differences in cardiovascular outcomes were included. Females with T2DM had a higher risk of developing coronary heart disease (CHD; RRR 1.52, 95%CI 1.32–1.76, p&lt;0.001), acute coronary syndrome (ACS; RRR 1.38, 95%CI 1.25–1.52, p&lt;0.001), and heart failure (RRR 1.09, 95%CI 1.05–1.13, p&lt;0.001) than males. In terms of mortality outcomes, females had a higher risk of all-cause mortality (RRR 1.13, 95%CI 1.07–1.19, p&lt;0.001), cardiac mortality (RRR 1.49, 95%CI 1.11–2.00, p=0.009) and CHD mortality (RRR 1.44, 95%CI 1.20–1.73, p&lt;0.001) as compared to males. In patients undergoing percutaneous coronary intervention, females reported higher odds of MACE (OR 1.49, 95%CI 1.07–2.07, p=0.020) and all-cause mortality (OR 1.71, 95%CI 1.46–2.00, p&lt;0.001) compared to males. Females in Asia (RRR 1.12, 95%CI 1.03–1.21, p=0.006) and North America (RRR 1.10, 95%CI 1.08–1.12, p&lt;0.001) were at increased risk of all-cause mortality while females in Western countries had an increased risk for cardiac death (RRR 1.84, 95%CI 1.45–2.32, p&lt;0.001) compared to males. Six reviews were rated as high in quality; eight reviews were rated as moderate, and fourteen reviews were rated as low in quality. Regarding the quality of outcomes, all outcomes in non-interventional studies had a moderate quality of evidence, while all outcomes in interventional studies achieved a high quality of evidence.

Conclusions

This umbrella review evaluated the quality of meta-analyses and demonstrated that females with T2DM have a higher risk of cardiovascular outcomes than their male counterparts. Future studies examining the sex differences in outcomes should attempt to address the heterogeneity and epidemiological factors for a better quality of evidence. Policymakers should consider sex-specific differences in implementing effective tailored strategies to tackle T2DM.

Effects of epicardial adipose tissue volume and thickness assessed by computed tomography and echocardiography on cardiovascular and cerebrovascular outcomes: a systematic review and meta-analysis

Funding Acknowledgements

Type of funding sources: None.

Background

Epicardial adipose tissue (EAT) has garnered attention as a potential imaging biomarker for the risk stratification of cardiovascular diseases (CVD). However, the prognostic utility of EAT due to inter-ethnic differences and imaging modality (computed tomography (CT) or transthoracic echocardiography (TTE)) remains undetermined.

Purpose

To evaluate the effect of EAT volume and thickness on cardiovascular and cerebrovascular outcomes. We also aim to compare the prognostic utility between CT volumetric and TTE thickness quantification; and provide consolidated data on the heterogeneity in EAT measurements across different ethnic groups.

Methods

Medline and Embase databases were searched from inception till 16 May 2022 for studies that measured EAT volume or thickness of adult patients at baseline and reported follow-up data on outcomes of interest. Outcomes included MACE, all-cause mortality, cardiac death, myocardial infarction (MI), coronary revascularisation, atrial fibrillation (AF), and stroke. Statistical analyses were conducted on Review Manager 5.4.1 to obtain unadjusted and adjusted hazard ratios (HR) and odds ratios (OR) with the results presented on forest plots.

Results

Twenty-nine studies comprising 19709 patients were included in our analysis. Increased EAT thickness and volume were associated with higher risks of MACE (adjusted HR [aHR] 1.46, 95%CI 1.25–1.71, p&lt;0.001), cardiac death (OR 2.53, 95%CI 1.17–5.44, p=0.020), MI (OR 2.63, 95%CI 1.39–4.96, p=0.003), coronary revascularisation (OR 2.99, 95%CI 1.64–5.44, p&lt;0.001), AF (aOR 4.04, 95%CI 3.06–5.32, p&lt;0.001), and stroke (HR 1.02, 95%CI 1.01–1.03, p&lt;0.001). CT-volumetric quantification of EAT conferred a larger MACE risk (aHR 1.79, 95%CI 1.47–2.17, p&lt;0.001) compared to TTE thickness quantification (aHR 1.20, 95%CI 1.09–1.32, p&lt;0.001). Studies originating from North America (HR 1.91, 95%CI 1.26–2.89, p=0.002) and Asia (HR 1.60, 95%CI 1.09–2.36, p=0.020) demonstrated a significantly higher risk of MACE with increased EAT thickness and volume. However, this significance was not seen in European studies (HR 1.48, 95%CI 0.99–2.20, p=0.060). Subgroup differences were also noted across the studies’ countries of origin when analysing the association of EAT and MI (p=0.020). European studies reported a higher magnitude of MI risk associated with higher EAT thickness and volume (OR 5.28, 95%CI 2.34–11.95, p&lt;0.001) as compared to Asian studies (OR 1.75, 95%CI 1.05–2.92, p=0.030). No differences were noted across other outcomes in the subgroup comparisons by geographical region and between CT and TTE quantification of EAT.

Conclusion

The utility of EAT as an imaging biomarker for predicting and prognosticating CVD is promising. Future efforts to harmonise the EAT parameter thresholds, based on the type of imaging modality and the target population’s ethnic characteristics, will be the next important step before including EAT in CVD prediction models.

Global burden of metabolic diseases: data from Global Burden of Disease 2000-2019. A cosortium of metabolic disease

Funding Acknowledgements

Type of funding sources: None.

Background

The growing prevalence of metabolic diseases is a major concern. We sought to examine the global trends and mortality of metabolic diseases using estimates from the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019.

Methods

Global estimates of prevalence, deaths, and disability-adjusted life year (DALYs) from 2000-2019 were examined for metabolic diseases (type 2 diabetes mellitus [T2DM], hypertension, and nonalcoholic fatty liver disease [NAFLD]). For metabolic risk factors (hyperlipidemia and obesity), estimates were limited to mortality and DALYs. Death rates was compared across sex, World Health Organisation regions and Socio-demographic Index (SDI) quintiles. Age-standardised prevalence and death rates were presented per 100,000 population with 95% uncertainty intervals (UI).

Findings

From 2000 to 2019, prevalence rates increased for all metabolic diseases, with the most pronounced increase in high SDI countries. In 2019, the mean (95%UI) age-standardised prevalence per 100,000 population was estimated to be 15,023 (13,493-16,764) for NAFLD, 5,283 (4,864–5,720) for T2DM and 234 (171-313) for hypertension. The highest age-standardised death rates were observed in obesity (62·59 [39·92-89·13]; males, 66·55 [39·76-97·21]; females. 58·14 [38·53-81·39]), followed by hyperlipidemia (56·51 [41·83-73·62]; males, 67·33 [50·78-86·43]; females, 46·50 [32·70-62·38]), T2DM (18·49 [17·18-19·66], males, 67·33 [50·78-86·43]; females, 46·50 [32·70-62·38]), hypertension (15·16 [11·20-16·75]; males, 14·95 [10·32-16·75]; females, 15·05 [11·51-17·09]) and NAFLD (2·09 [1·61-2·60]; males, 2·38 [1·82-3·02]; females, 1·82 [1·41-2·27]). Mortality rates decreased over time in hyperlipidemia (-154%), hypertension (-52%) and NAFLD (-52%), but not in T2DM and obesity. The highest mortality for metabolic diseases was found in Eastern Mediterranean, and low to low-middle SDI countries.

Conclusion

The global prevalence of metabolic diseases has risen over the past two decades regardless of SDI. Attention is needed to address the unchanging mortality rates attributed to metabolic disease and the regional, socioeconomic, and sex disparities in mortality from metabolic disease.

Prevalence of psychological symptoms and associated risk factors among nurses in 30 provinces during the COVID-19 pandemic in China

BACKGROUND

With the outbreak of the coronavirus disease 2019 (COVID-19), nurses have won well-deserved recognition for their indispensable roles in providing humane and professional healthcare for patients. However, by the nature of their role working at the forefront of patient care, nurses are prone to experiencing mental health consequences. Therefore, we pay attention to measuring the magnitude of psychological symptoms and identifying associated factors among nurses in China.

METHODS

We launched a nationwide, cross-sectional survey of nurses who worked in secondary or tertiary hospitals and public or private hospitals from 30 provinces in China. The prevalence and severity of symptoms of burnout, depression, and anxiety were investigated, respectively. Multivariable logistic regression analyses were performed to identify factors associated with each psychological symptom.

FINDINGS

A total of 138 279 respondents who worked in 243 hospitals completed this survey. A substantial proportion of nurses reported symptoms of burnout (34%), depression (55·5%), and anxiety (41·8%). In line with the disproportionality of economic development, we noted that the middle or western region was an independent risk factor for depression and anxiety. Compared with those working in the secondary hospital, nurses who worked in tertiary hospitals were associated with a higher likelihood of burnout and depression.

INTERPRETATION

Nurses are experiencing emotional, physical, and mental exhaustion during the COVID-19 epidemic. Governments and health policymakers need to draw attention to reinforcing prevention and ameliorating countermeasures to safeguard nurses' health.

FUNDING

The strategic consulting project of the Chinese Academy of Engineering [2021-32-5]. Advanced Institute of Infomation Technology, Peking University, Zhejiang Province [2020-Z-17].

China trauma treatment statistics 2019: A national retrospective study based on hospitalized cases

Objective

Trauma is China's fifth leading cause of death and ranked first among youths. Trauma databases have been well-established in many countries to announce the current state of trauma rescue, treatment and care. Nevertheless, China hasn't yet established a comparable database. This paper included two national-level databases in China to describe the current situation of trauma treatment and the epidemiological characteristics of trauma incidence, which sought to provide data support for decision-making, resource allocation, trauma prevention, trauma management, and other aspects.

Methods

This study used the diagnosis and treatment data from the Hospital Quality Monitoring System (HQMS) and the China Trauma Rescue and Treatment Association (CTRTA) in 2019. A descriptive analysis was conducted to explore the demographic characteristics, trauma causes, injury degrees of trauma patients, disease burden and mortality rates in the abstracted hospitalized cases.

Results

A total of 4,532,029 trauma patients were included, of which 4,436,653 were from HQMS and 95,376 from CTRTA respectively. The age group with the highest proportion is 50-54 years old (493,320 [11.12%] in HQMS and 12,025 [12.61%] in CTRTA). Fall was the most frequent cause of trauma hospitalization, accounting for 40.51% of all cases, followed by traffic injuries, accounting for 25.22%. However, for trauma patients aged between 20 and 24 years old, the most common cause of injury was traffic accidents (28.20%). Hospital expenses for trauma patients in 2019 exceeded 100.30 billion yuan, which increases significantly with age, and fall costs the most. The mortality rate of trauma inpatients was 0.77%, which gradually increased with age after 30-year-old, and was the highest in the age group above 85 (1.86%).

Conclusion

This paper summarizes the demographic characteristics, trauma causes distribution, disease burden, mortality rate, and other relative data of inpatients in 2019, which can now be used as an up-to-date clinical evidence base for national healthcare prevention and management in China.

Disparity in female and Asian representation amongst cardiology journal editorial boards members: a call for empowerment

BACKGROUND

While progress is evident in gender and ethnic representation in the workplace, this disparity remains prevalent in academic positions.

OBJECTIVES

We examined gender and Asian ethnic representation in editorial boards of cardiology journals.

METHODS

A cross-sectional analysis was conducted using publicly available data on Cardiology and Cardiovascular medicine journals in the first quartile of the 2020 Scimago Journal & Country Rank indicator. The proportions of female and Asian editorial board members, associate editors and editors-in-chief were assessed. Subgroup analyses were conducted based on the journal's geographical origin, subspecialty and demographic of the editor-in-chief.

RESULTS

Seventy-six cardiology journals, involving 8915 editorial board members, were included. Only 19.6% of editorial board members were female, 20.8% Asians and 4.0% Asian females. There were less female representation amongst editors-in-chief (9.9%) compared to associate editors (22.3%). European (18.1%) and North American-based journals (21.1%) had higher female representation compared to Asian-based journals (8.7%). There was lower Asian representation in European (18.1%) and North American-based journals (19.9%) compared to Asian-based journals (72.3%). Females were underrepresented in interventional (14.5%) journals, while Asians were underrepresented in general cardiology (18.3%) and heart failure (18.3%) journals. Journals led by female editors-in-chief had significantly higher female representation compared to male-led ones, while journals with Asian editors-in-chief had greater Asian representation compared to non-Asian led ones.

CONCLUSION

This study highlights the female and Asian ethnic underrepresentation in academic roles in cardiology journal editorial boards. Further analysis is needed for other ethnicities, while the community pushes towards gender-balanced and ethnic diversity across editorial boards.

Metabolic associated fatty liver disease increases risk of adverse events after acute coronary syndrome

 

Metabolic Associated Fatty Liver Disease (MAFLD) was recently introduced as an alternative definition for fatty liver, that has been linked to an increased risk of systemic end-organ damage. However, current studies have not examined the impact of MAFLD on patients presenting with acute coronary syndrome (ACS). Here, we present a retrospective analysis on the short and long-term outcomes of ACS patients with MAFLD.

Methods

A retrospective analysis was conducted in a tertiary care centre. Hepatic steatosis and fibrosis was examined with hepatic steatosis index and fibrosis-4 (FIB-4) index. The primary and secondary outcomes of the analysis were long term all-cause mortality, and in-hospital all-cause mortality, stroke, heart failure and cardiogenic shock respectively. Adjusted analysis was conducted for primary and secondary outcomes with covariates including age, sex, race, type of ACS and previous myocardial infarction.

Results

A total of 5770 patients were included in the analysis, and 21% of ACS patients had concomitant MAFLD. MAFLD resulted in a 23% increase in long-term all-cause mortality compared to non-MAFLD (HR: 1.230, CI: 1.065 to 1.420, p=0.005). MAFLD increased the risk of in-hospital mortality, stroke, heart failure and cardiogenic shock compared to non-MAFLD. A sensitivity analysis conducted based on MAFLD with advance fibrosis, chronic kidney disease and diabetes also demonstrated significantly increased effect size magnitude of all-cause mortality, compared to non-MAFLD.

Conclusion

MAFLD represents an encapsulation of metabolism dysregulation and has been associated with increased risk of systematic disease. The present study shows that MAFLD is associated with significantly increased adverse prognostic outcomes after ACS compared to non-MAFLD. An increase in awareness of MAFLD is required beyond the field of hepatology for improvements in multidisciplinary care and management.

Funding Acknowledgement

Type of funding sources: None.

Reconstructed meta-analysis of percutaneous coronary intervention versus coronary artery bypass grafting for left main disease

Background

Randomized controlled trials (RCTs) comparing percutaneous coronary intervention (PCI) with drug-eluting stents and coronary artery bypass grafting (CABG) for patients with left main coronary artery disease (LMCAD) have reported conflicting results.

Objectives

We performed a systematic review from inception to 23 May 2021 and one-stage reconstructed individual-patient data meta-analysis (IPDMA) that included 10-year mortality outcomes.

Methods

The primary outcome was 10-year all-cause mortality. Secondary outcomes included myocardial infarction (MI), stroke and unplanned revascularization at 5 years. We did IPDMA using published Kaplan-Meier curves to provide individual data points in coordinates and numbers at risk were used to increase the calibration accuracy of the reconstructed data. Shared frailty model or, when proportionality assumptions were not met, a restricted mean survival time model were fitted to compare outcomes between treatment groups.

Results

Of 583 articles retrieved, 5 RCTs were included. A total of 4595 patients from these 5 RCTs were randomly assigned to PCI (N=2297) or CABG (N=2298). The cumulative 10-year all-cause mortality after PCI and CABG was 12.0% versus 10.6% respectively (HR 1.093, 95% CI: 0.925–1.292; p=0.296). PCI conferred similar time-to-MI (RMST ratio 1.006, 95% CI: 0.992–1.021, p=0.391) and stroke (RMST ratio 1.005, 95% CI: 0.998–1.013, p=0.133) at 5 years. Unplanned revascularization was more frequent following PCI compared with CABG (HR 1.807, 95% CI: 1.524–2.144, p&lt;0.001) at 5 years.

Conclusion

This meta-analysis using reconstructed participant-level time-to-event data showed no statistically significant difference in cumulative 10-year all-cause mortality between PCI versus CABG in the treatment of LMCAD.

Funding Acknowledgement

Type of funding sources: None.

A 10-year cohort on prognostic outcomes in patients presenting with acute myocardial infarction complicated by cardiogenic shock and/or cardiac arrest

Background

Cardiogenic shock (CS) and cardiac arrest (CA) complicating acute myocardial infarction (AMI) portend unfavourable outcomes. This study examined the prognosis of patients presenting with AMI complicated by CS and/or CA.

Methods

Consecutive patients presented with AMI to a percutaneous coronary intervention-capable tertiary institution between 2011 and 2021 were studied. Patients were stratified based on the presence or absence of CS (CS+ or CS−) and CA (CA+ or CA−). The primary outcome was 30-day cardiovascular-related mortality. Subgroup analyses based on AMI-type and sex were conducted. Kaplan-Meier curves for cardiovascular-related mortality based on the AMI-type and sex were constructed.

Results

The study included 11,608 AMI patients, 283 of whom had CS+/CA+, 1,068 had CS+/CA−, 54 had CS−/CA+ and 10,203 had CS−/CA−. Cardiovascular-related mortality was significantly higher for CS+/CA+ (57.6%), followed by CS+/CA− (41.6%), CS−/CA+ (20.4%) and CS−/CA− (2.4%). Kaplan-Meier curves demonstrated CS+/CA+ group had the highest mortality (HR=36.26; 95% CI: 29.71–44.25, p&lt;0.001), followed by CS+/CA− (HR=21.59; 95% CI: 18.47–25.24, p&lt;0.001) and CS−/CA+ (HR=9.18; 95% CI: 5.02–16.80, p&lt;0.001), with CS−/CA− as the reference. Those with NSTEMI had consistently higher cardiovascular-related mortality rates than their STEMI counterparts for all groups, apart from the CS+/CA+ group. The sex-specific analysis demonstrated that the survival curves for females with CS+/CA+, CS+/CA− and CS−/CA+ converged, whilst the survival curves for males diverged over time. The multivariable Cox regression revealed the presence of CS and CA are independent predictors of cardiovascular-related mortality, but not NSTEMI, when adjusted for age, gender, diabetes, left ventricular ejection fraction, chronic renal failure, and culprit vessel.

Conclusions

AMI associated with CA and CS portends the least favourable survival, followed by those with CS or CA alone. Excess mortality was observed in the traditionally perceived lower-risk groups, particularly in women. This calls for increased awareness amongst clinicians when managing this subset of high-risk patients.

Funding Acknowledgement

Type of funding sources: None.

Higher long-term mortality in patients with concomitant acute coronary syndrome and aortic stenosis

Background

Aortic stenosis (AS) and acute coronary syndrome (ACS) share similar cardiovascular risk factors, and their concomitant presentation is increasing in incidence with the aging population. Yet literature regarding the prognosis of patients with concomitant ACS and AS remains scarce.

Methods

This retrospective cohort study examined consecutive patients presenting with ACS (ST-segment elevation myocardial infarction [STEMI] and non-STEMI [NSTEMI]) and concomitant AS between 1 January 2011 and 31 March 2021 in a tertiary hospital. The cohort was divided into mild, moderate and severe AS based on index echocardiogram. The primary outcome was all-cause mortality. Kaplan-Meier curves were constructed to compare all-cause mortality among the three groups of patients, based on ACS type and left ventricular ejection fraction (LVEF). Multivariable Cox regression was performed to identify independent predictors of all-cause mortality.

Results

Of a total of 563 patients, 264 had mild (46.9%), 193 moderate (34.3%) and 106 severe AS (18.8%). The mean follow-up duration was 2.5 (± 2.4) years. Majority of patients (72.5%) presented with NSTEMI. Patients with moderate and severe AS had higher rates of all-cause mortality compared to those with mild AS (49.7% vs. 51.4% vs. 35.6% respectively, p=0.002). Concomitant moderate (HR 1.439, 95% CI 1.012–2.048, p=0.043) and severe AS (HR 1.844, 95% CI 1.159–2.933, p=0.010) were independent predictors of all-cause mortality after adjusting for age, gender, LVEF, ACS type, chronic kidney disease, diabetes, hypertension, coronary artery bypass grafting and aortic valve replacement as a time-dependent variable. The Kaplan-Meier curves demonstrated excess mortality in moderate and severe AS, compared to the mild AS group (p&lt;0.001), with similar survival trends observed in the STEMI and the NSTEMI groups, as well as those with preserved LVEF.

Conclusion

Regardless of the ACS presentation type, long-term excess mortality in those with concomitant moderate or severe AS was observed. The adverse prognosis typically observed in patients with concomitant severe AS, in the setting of ACS, extends to patients with moderate AS.

Funding Acknowledgement

Type of funding sources: None.

Prognostically distinct phenotypes of metabolic health beyond obesity in aortic stenosis

Background

Whilst current evidence are in favour of metabolic health and non-obesity in the reduction of incident cardiovascular disease, little is known regarding the prognosis across the metabolic phenotypes once cardiovascular disease occurs. This study examined the prognosis of patients with significant aortic stenosis (AS) based on the presence of metabolic health and obesity.

Methods

This retrospective cohort on consecutive patients presenting with moderate-to-severe AS to a tertiary hospital between 2010 and 2015. Patients were allocated into 4 groups based on obesity and metabolic health: metabolically healthy obese (MHO), metabolically healthy non-obese (MHNO), metabolically unhealthy obese (MUO) and metabolically unhealthy non-obese (MUNO). Metabolic health was defined in accordance to Program Adult Treatment Panel III criteria. The primary outcome was all-cause mortality. Cox regression examined independent associations between mortality and metabolic phenotypes, adjusting for aortic valve area, ejection fraction, age, sex, chronic kidney disease and AVR as a time-dependent covariate.

Results

Of 727 patients, the majority (51.6%) were MUNO, followed by MUO (32.7%), MHNO (11.4%), and MHO (4.3%). MHNO had the highest mortality (43.0%), followed by the MUNO (37.5%), MUO (30.0%) and MHO (6.9%) groups (p=0.001). Compared to MHNO, MHO (HR 0.159, 95% CI 0.038–0.668, p=0.012) and MUO (HR 0.614, 95% CI 0.403–0.937, p=0.024) were independently associated with lower all-cause mortality rates, after adjusting for confounders. In obese patients, metabolic health had favourable survival compared to metabolically unhealthy (p=0.015), but this protective impact of metabolic health was not observed in overweight or normal weight individuals. Obesity had favourable survival compared to overweight and normal weight, in both metabolically health (p=0.002) and unhealthy (p=0.007) patients,

Conclusion

MHO patients with AS have the most favourable prognosis whilst the seemingly healthy MHNO group had the worst survival. There should be a paradigm shift towards prioritising metabolic health rather than weight reduction in patients with significant AS.

Funding Acknowledgement

Type of funding sources: None.

The prognostic outcomes of acute myocardial infarction stratified according to metabolic health and obesity status

Background

There has been emerging evidence on the favourable cardiovascular disease incidence in non-obese subjects with healthy metabolism. However, little is known regarding the prognosis across the metabolic phenotypes once cardiovascular disease is established. This study examines the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status.

Methods

A retrospective study conducted in a tertiary hospital between 2014–2021. Consecutive patients with AMI were allocated into 4 groups based on metabolic and obesity profile: metabolically healthy obesity (MHO), metabolically healthy non-obesity (MHNO), metabolically unhealthy obesity (MUO) and metabolically unhealthy non-obesity (MUNO). The primary outcome was all-cause mortality. Cox regression examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type and ejection fraction.

Results

A total of 9958 patients were studied with majority (68.5%) in the MUNO group, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO patients had lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%) and MUNO (22.6%, p&lt;0.001). Relative to MHNO, MUO (HR 1.610, 95% CI 1.198–2.163, p=0.002) and MUNO (HR 1.383, 95% CI 1.043–1.835, p=0.024) had significantly higher mortality risk, but not MHO (HR 1.514, 95% CI 0.649–3.534, p=0.337), after adjusting for confounders. Kaplan-Meier curves showed favourable survival in metabolically healthy groups with clear divergence from metabolically unhealthy groups (p&lt;0.001). There were stepwise increments in mortality with increasing number of metabolic risk factors regardless of obesity status (p&lt;0.001). Favourable survival was observed in overweight and obese versus normal weight patients regardless of metabolic health.

Conclusion

Metabolically healthy AMI patients had favourable prognosis compared to metabolically unhealthy patients. The obesity paradox was observed in the AMI cohort, but the beneficial effects of obesity appeared not as pronounced in magnitude as in metabolically healthy groups.

Funding Acknowledgement

Type of funding sources: None.

Bidirectional associations of vision loss, hearing loss, and dual sensory loss with depressive symptoms among the middle-aged and older adults in China

BACKGROUND

Most studies on the relationship between sensory loss and depression focus on the unidirectional association between sensory loss and the risk of depression based on cross-sectional designs. The present study aimed to explore the bidirectional longitudinal associations of vison loss (VL), ¹ hearing loss (HL), ² and dual sensory loss (DSL)³ with depressive symptoms among Chinese population.

METHODS

A longitudinal study was conducted among 13,690 participants aged 45 years and older over four years. VL, HL, and DSL were identified through self-reporting, and depressive symptoms were assessed using a 10-item Center for Epidemiologic Studies Depression Scale. Multivariable Cox proportional hazards regression models were constructed to estimate the bidirectional associations of VL, HL, and DSL with depressive symptoms.

RESULTS

Participants with self-reported VL (HR: 1.14, 95%CI: 1.04-1.24), HL (HR: 1.22, 95%CI: 1.07-1.37), and DSL (HR: 1.27, 95%CI: 1.08-1.49) were associated with higher risk of developing depressive symptoms, compared with those without VL, HL, and DSL, respectively. In comparison with those without depressive symptoms, participants with depressive symptoms in the baseline had higher risk of developing VL (HR: 1.43, 95%CI: 1.33-1.54), HL (HR: 1.49, 95%CI: 1.36-1.63), and DSL (HR: 1.76, 95%CI: 1.59-1.95).

LIMITATIONS

Sensory loss was defined only based on participants' self-report.

CONCLUSIONS

Significant bidirectional associations exist between self-reported VL, HL, or DSL and depressive symptoms. The mental health of people with VL and HL should be focused on, and regular assessments of vision and hearing in people with depressive symptoms are recommended.

Structure-Aware Siamese Graph Neural Networks for Encounter-Level Patient Similarity Learning

Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given patient and patient records in the database could contribute to clinical references for diagnosis and medication. The sparsity of underlying relationships between patients poses difficulties for similarity learning, which becomes more challenging when considering real-world Electronic Health Records (EHRs) with a large number of missing values. In the paper, we organize EHRs as a graph and propose a novel deep learning framework, Structure-aware Siamese Graph neural Networks (SSGNet), to perform robust encounter-level patient similarity learning while capturing the intrinsic graph structure and mitigating the influence from missing values. The proposed SSGNet regards each patient encounter as a node, and learns the node embeddings and the similarity between nodes simultaneously via Graph Neural Networks (GNNs) with siamese architecture. Further, SSGNet employs a low-rank and contrastive objective to optimize the structure of the patient graph and enhance model capacity. The extensive experiments were conducted on two publicly available datasets and a real-world dataset regarding IgA nephropathy from Peking University First Hospital, in comparison with multiple baseline and state-of-the-art methods. The significant improvement in Accuracy, Precision, Recall and F1 score on the patient encounter pairwise similarity classification task demonstrates the superiority of SSGNet. The mean average precision (mAP) of SSGNet on the similar encounter retrieval task is also better than other competitors. Furthermore, SSGNet's stable similarity classification accuracies at different missing rates of data validate the effectiveness and robustness of our proposal.

Association between pulse pressure, systolic blood pressure and the risk of rapid decline of kidney function among general population without hypertension: results from the China health and retirement longitudinal study (CHARLS)

BACKGROUND

Association between blood pressure (BP) and kidney function among the middle and old aged general population without hypertension remains unclear.

METHODS

Participants aged ≥ 45 years, with complete data in 2011 and 2015 interviews of the China Health and Retirement Longitudinal Study(CHARLS), and without pre-existing hypertension were included. Systolic BP (SBP) was categorized as low (< 120 mmHg), medium (120-129 mmHg), and high (120-139 mmHg). Diastolic BP (DBP) was categorized as low (< 60 mmHg), medium (60-74 mmHg), and high (75-89 mmHg). Pulse pressure (PP) was categorized as normal (< 60 mmHg) and high (≥ 60 mmHg). The outcome was defined as rapid decline of estimated glomerular filtration rate(eGFR, decline ≥ 4 ml/min/1.73 m2/year). BP combination was designed according to the category of SBP and PP. The association between BP components, types of BP combination, and the risk of rapid decline of eGFR was analyzed using multivariate logistic regression models, respectively. Age-stratified analyses were conducted.

RESULTS

Of 4,534 participants included, 695(15.3%) individuals were recognized as having rapid decline of eGFR. High PP[odds ratio(OR) = 1.34, 95%confidence interval(CI) 1.02-1.75], low SBP (OR = 1.28, 95%CI 1.03-1.59), and high SBP (OR = 1.32, 95% CI 1.02-1.71) were significantly associated with the risk of eGFR decline. Low SBP were associated with 65% increment of the risk of eGFR decline among participants aged < 55 years. The combination of high SBP and high PP (OR = 1.79, 95% CI 1.27-2.54) and the combination of low SBP and high PP (OR = 3.07, 95% CI 1.24-7.58) were associated with the increased risk of eGFR decline among the middle and old aged general population.

CONCLUSION

Single and combination of high PP and high SBP could be the risk indicators of eGFR decline among the middle and old aged general population.

Predicting Prolonged Length of ICU Stay through Machine Learning

This study aimed to construct machine learning (ML) models for predicting prolonged length of stay (pLOS) in intensive care units (ICU) among general ICU patients. A multicenter database called eICU (Collaborative Research Database) was used for model derivation and internal validation, and the Medical Information Mart for Intensive Care (MIMIC) III database was used for external validation. We used four different ML methods (random forest, support vector machine, deep learning, and gradient boosting decision tree (GBDT)) to develop prediction models. The prediction performance of the four models were compared with the customized simplified acute physiology score (SAPS) II. The area under the receiver operation characteristic curve (AUROC), area under the precision-recall curve (AUPRC), estimated calibration index (ECI), and Brier score were used to measure performance. In internal validation, the GBDT model achieved the best overall performance (Brier score, 0.164), discrimination (AUROC, 0.742; AUPRC, 0.537), and calibration (ECI, 8.224). In external validation, the GBDT model also achieved the best overall performance (Brier score, 0.166), discrimination (AUROC, 0.747; AUPRC, 0.536), and calibration (ECI, 8.294). External validation showed that the calibration curve of the GBDT model was an optimal fit, and four ML models outperformed the customized SAPS II model. The GBDT-based pLOS-ICU prediction model had the best prediction performance among the five models on both internal and external datasets. Furthermore, it has the potential to assist ICU physicians to identify patients with pLOS-ICU risk and provide appropriate clinical interventions to improve patient outcomes.

Incidence, prevalence, and survival trends for neuroendocrine neoplasms in Victoria, Australia, from 1982 to 2019: Based on site, grade, and region

AIMS

Neuroendorcine neoplasms (NENs) are rare tumors characterised by variable biology and delayed diagnosis. Several population studies have reported a marked increased incidence over time. The objectives of this analysis were to describe within Victoria (the second largest Australian state, 6.4 Million) the trends for NENs incidence/survival over nearly 38 years (1982-2019), and regional differences in survival.

METHODS

All NEN cases were identified from the Victorian Cancer Registry over four time periods: 1982-1989, 1990-1999, 2000-2009, and 2010-2019. Data collected included primary tumor site, histological grade, gender, overall survival (OS), and place of residence. Incidence data were analyzed with the generation of annual standardized rates (ASR). OS was assessed for the entire cohort and between geographical regions.

RESULTS

The overall NEN population (1982-2019) included 8,106 patients: over 60% grade 1/2 NENs, especially small bowel and colorectal. The number of new diagnoses increased over three-fold over time for the overall cohort and by tumoral categories. The ASR increased similarly, especially pancreatic NENs (4.3-fold) and differed between genders. The 5-year OS rates and median OS increased over time for the overall cohort: from 52% to 67% (p < 0.001). OS was greater for NEN patients residing in major cities relative to regional/remote areas (p = 0.01).

CONCLUSION

This population-wide analysis with over 38 years of data has confirmed the international trends of the increased incidence, prevalence, and OS of NEN patients regardless of primary site or histological grade. The analysis also observed a difference in survival outcome in rural/remote versus urban areas.

Influence of doctors' perception on the diagnostic status of chronic kidney disease: results from 976 409 individuals with electronic health records in China

Background

The diagnostic status of chronic kidney disease (CKD) and its underlying reasons provide evidence that can improve CKD management. However, the situation in developing countries remains under-investigated.

Methods

Adults with electronic health records (EHRs; 2008-19) in Yinzhou, China were included. The gold standard for CKD was defined as having persistently reduced estimated glomerular filtration rate (eGFR), albuminuria/proteinuria, haematuria or a history of CKD. CKD stages (G1-G5) were defined by eGFR. Clinical diagnosis of CKD in the real world setting was evaluated using International Classification of Diseases (ICD)-10 codes related to primary cause or stages of CKD. The specialty of doctors who administered the serum creatinine (SCr) tests and who made the primary-cause/CKD-staging diagnoses was analysed. The accuracy of CKD-staging codes was assessed.

Results

Altogether, 85 519 CKD patients were identified from 976 409 individuals with EHRs. Of them, 10 287 (12.0%) having persistent urinary abnormalities or labelled with CKD-related ICD codes did not receive SCr tests within 12 months before or after the urine tests. Among 75 147 patients who received SCr tests, 46 150 (61.4%) missed any CKD-related codes, 6857 (35.7%) were merely labelled with primary-cause codes, and only 2140 (2.9%) were labelled with CKD-staging codes. The majority of CKD patients (51.6-91.1%) received SCr tests from non-nephrologists, whereas CKD-staging diagnoses were mainly from nephrologists (52.3-64.8%). Only 3 of 42 general hospitals had nephrologists. The CKD-staging codes had high specificity (>99.0%) but low sensitivity (G3-G4: <10.0%).

Conclusions

Under-perception of CKD among doctors, rather than unsatisfactory health-seeking behaviour or low detection rates, was the main cause of under-diagnosis of CKD in China. Intensification of CKD education among doctors with different specialties might bring about immediate effective improvement in the diagnosis and awareness of CKD.

Age- and Gender-Specific Prevalence of Frailty and Its Outcomes in the Longevous Population: The Chinese Longitudinal Healthy Longevity Study

Background: Frailty is an epidemic age-related syndrome addressing heavy burden to the healthcare system. Subject to the rarity, age-, and gender-specific prevalence of frailty and its prognosis among the longevous population remains under-investigated.

Methods: Based on the Chinese Longitudinal Healthy Longevity Study (CLHLS, 2008–2018), individuals aged ≥ 65 years having complete data of frailty were recruited. Modified Fried criteria (exhaustion, shrink, weakness, low mobility, and inactivity) were adopted to define pre-frailty (1–2 domains) and frailty (≥3 domains), respectively. The association between pre-frailty/frailty and adverse outcomes (frequent hospitalization, limited physical performance, cognitive decline, multimorbidity, and dependence) was analyzed using logistic regression models. The association between pre-frailty/frailty and mortality was analyzed using Cox proportional hazards models. Age- and gender-stratified analyses were performed.

Results: Totally, 13,859 participants aged 85.8 ± 11.1 years, including 2,056 centenarians, were recruited. The overall prevalence of pre-frailty and frailty were 54.1 and 26.3%, respectively. Only 5.0% of centenarians were non-frailty whereas 59.9% of the young-old (65–79 years) showed pre-frailty. Both pre-frailty and frailty were associated with the increased risk of multiple adverse outcomes, such as incident limited physical performance, cognitive decline and dependence, respectively (P < 0.05). Frail males were more vulnerable to the risk of mortality (hazard ratio [HR] = 2.3, 95% confidence interval [CI], 2.1–2.6) compared with frail females (HR = 1.9, 95%CI, 1.7–2.1). The strongest association between frailty and mortality was observed among the young-old (HR = 3.6, 95%CI, 2.8–4.5). Exhaustion was the most common domain among patients with pre-frailty (74.8%) or frailty (83.2%), followed by shrink (32.3%) in pre-frailty and low mobility (83.0%) in frailty. Inactivity among females aged 65–79 years showed the strongest association with the risk of mortality (HR = 3.50, 95%CI, 2.52–4.87).

Conclusion: A huge gap exists between longer life and healthy aging in China. According to the age- and gender-specific prevalence and prognosis of frailty, the strategy of frailty prevention and intervention should be further individualized.

Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis-Treated Patients Using Stacked Generalization: Model Development and Validation Study

Background

The increasing number of patients treated with peritoneal dialysis (PD) and their consistently high rate of hospital admissions have placed a large burden on the health care system. Early clinical interventions and optimal management of patients at a high risk of prolonged length of stay (pLOS) may help improve the medical efficiency and prognosis of PD-treated patients. If timely clinical interventions are not provided, patients at a high risk of pLOS may face a poor prognosis and high medical expenses, which will also be a burden on hospitals. Therefore, physicians need an effective pLOS prediction model for PD-treated patients.

Objective

This study aimed to develop an optimal data-driven model for predicting the pLOS risk of PD-treated patients using basic admission data.

Methods

Patient data collected using the Hospital Quality Monitoring System (HQMS) in China were used to develop pLOS prediction models. A stacking model was constructed with support vector machine, random forest (RF), and K-nearest neighbor algorithms as its base models and traditional logistic regression (LR) as its meta-model. The meta-model used the outputs of all 3 base models as input and generated the output of the stacking model. Another LR-based pLOS prediction model was built as the benchmark model. The prediction performance of the stacking model was compared with that of its base models and the benchmark model. Five-fold cross-validation was employed to develop and validate the models. Performance measures included the Brier score, area under the receiver operating characteristic curve (AUROC), estimated calibration index (ECI), accuracy, sensitivity, specificity, and geometric mean (Gm). In addition, a calibration plot was employed to visually demonstrate the calibration power of each model.

Results

The final cohort extracted from the HQMS database consisted of 23,992 eligible PD-treated patients, among whom 30.3% had a pLOS (ie, longer than the average LOS, which was 16 days in our study). Among the models, the stacking model achieved the best calibration (ECI 8.691), balanced accuracy (Gm 0.690), accuracy (0.695), and specificity (0.701). Meanwhile, the stacking and RF models had the best overall performance (Brier score 0.174 for both) and discrimination (AUROC 0.757 for the stacking model and 0.756 for the RF model). Compared with the benchmark LR model, the stacking model was superior in all performance measures except sensitivity, but there was no significant difference in sensitivity between the 2 models. The 2-sided t tests revealed significant performance differences between the stacking and LR models in overall performance, discrimination, calibration, balanced accuracy, and accuracy.

Conclusions

This study is the first to develop data-driven pLOS prediction models for PD-treated patients using basic admission data from a national database. The results indicate the feasibility of utilizing a stacking-based pLOS prediction model for PD-treated patients. The pLOS prediction tools developed in this study have the potential to assist clinicians in identifying patients at a high risk of pLOS and to allocate resources optimally for PD-treated patients.

Association of cardiovascular disease with 30-day hospital readmission in Chinese patients receiving maintenance dialysis

Background

Previous studies have shown cardiovascular disease (CVD) to be a risk factor in the prediction of 30-day hospital readmission among patients receiving dialysis. However, studies of Asian populations are limited. In the present study, we examined the association between CVD and 30-day hospital readmission in Chinese patients receiving maintenance dialysis.

Methods

Patients receiving maintenance dialysis were identified by searching a national claims database, the China Health Insurance Research Association (CHIRA) database, using the International Classification of Diseases revision 10 (ICD-10) and items of medical service claims. Patients aged ≥18 years who were discharged after index hospitalization between January 2015 and December 2015 were included in our retrospective analysis. CVD-related diagnoses were divided into three categories: coronary heart disease (CHD), heart failure (HF), and stroke. Thirty-day hospital readmission was defined as any hospital readmission within the 30 days following discharge. Logistic regression models adjusted for logit of propensity scores (PS) were used to assess the association of CVD with 30-day hospital readmission.

Results

Of 4,700 patients receiving dialysis, the 30-day hospital readmission rate was 10.4%. Compared with patients without CVD, there was an increased risk of 30-day hospital readmission among maintenance dialysis patients with total CVD [odds ratio (OR): 1.33, 95% confidence interval (CI): 1.06–1.66]. Patients with HF (OR: 1.77, CI: 1.27–2.47) and stroke (OR: 2.14, 95% CI: 1.53–2.98) had a greater risk of 30-day hospital readmission. The fully adjusted OR of CHD for the risk of 30-day hospital readmission was 1.22 (95% CI: 0.97–1.55).

Conclusions

CVDs, especially stroke and HF, are independent predictors of 30-day hospital readmission in Chinese patients receiving dialysis, and could help to guide interventions to improve the quality of care for these patients.

The gene NtMYC2a acts as a 'master switch' in the regulation of JA-induced nicotine accumulation in tobacco

The biosynthesis and transport of nicotine has been shown to be coordinately upregulated by jasmonate (JA). MYC2, a member of basic helix-loop-helix (bHLH) transcription factor family, is well-documented as the core player in the JA signalling pathway to regulate diverse plant development processes. Four MYC2 genes were found in the tobacco genome, NtMYC2a/2b and 1a/1b. In this study, we tested whether one of them, NtMYC2a, acts as a 'master switch' in the regulation of nicotine biosynthesis and transport in tobacco. We generated NtMYC2a knockout tobacco plants using the CRISPR-Cas9 technique and analysed the effect of NtMYC2a knockout on expression of the nicotine biosynthesis genes (NtAO, NtQS, NtPMT1a, NtQPT2, NtODC2, NtMPO1, NtA622 and NtBBLa) and transport genes (NtMATE2 and NtJAT1), as well as leaf accumulation of nicotine in the NtMYC2a knockout plants. We found that all the nicotine biosynthesis and transport genes tested in this study were significantly downregulated (>50% reduction compared with wild-type control) in the NtMYC2a knockout plants. Moreover, the leaf nicotine content in knockout plants was dramatically reduced by ca 80% compared with the wild-type control. These results clearly show that NtMYC2a acts as a 'master switch' to coordinate JA-induced nicotine accumulation in tobacco and suggests that NtMYC2a might play an important role in tobacco nicotine-mediated defence against herbivory.

Long-Term Exposure to Ambient PM2.5, Sunlight, and Obesity: A Nationwide Study in China

BACKGROUND

Accumulated researches revealed that both fine particulate matter (PM_2.5) and sunlight exposure may be a risk factor for obesity, while researches regarding the potential effect modification by sunlight exposure on the relationship between PM_2.5 and obesity are limited. We aim to investigate whether the effect of PM_2.5 on obesity is affected by sunlight exposure among the general population in China.

METHODS

A sample of 47,204 adults in China was included. Obesity and abdominal obesity were assessed based on body mass index, waist circumference and waist-to-hip ratio, respectively. The five-year exposure to PM_2.5 and sunlight were accessed using the multi-source satellite products and a geochemical transport model. The relationship between PM_2.5, sunshine duration, and the obesity or abdominal obesity risk was evaluated using the general additive model.

RESULTS

The proportion of obesity and abdominal obesity was 12.6% and 26.8%, respectively. Levels of long-term PM_2.5 ranged from 13.2 to 72.1 μg/m³ with the mean of 46.6 μg/m³. Each 10 μg/m³ rise in PM_2.5 was related to a higher obesity risk [OR 1.12 (95% CI 1.09-1.14)] and abdominal obesity [OR 1.10 (95% CI 1.07-1.13)]. The association between PM_2.5 and obesity varied according to sunshine duration, with the highest ORs of 1.56 (95% CI 1.28-1.91) for obesity and 1.66 (95% CI 1.34-2.07) for abdominal obesity in the bottom quartile of sunlight exposure (3.21-5.34 hours/day).

CONCLUSION

Long-term PM_2.5 effect on obesity risk among the general Chinese population are influenced by sunlight exposure. More attention might be paid to reduce the adverse impacts of exposure to air pollution under short sunshine duration conditions.

Development of a scoring tool for predicting prolonged length of hospital stay in peritoneal dialysis patients through data mining

Background

The hospital admission rate is high in patients treated with peritoneal dialysis (PD), and the length of stay (LOS) in the hospital is a key indicator of medical resource allocation. This study aimed to develop a scoring tool for predicting prolonged LOS (pLOS) in PD patients by combining machine learning and traditional logistic regression (LR).

Methods

This study was based on patient data collected using the Hospital Quality Monitoring System (HQMS) in China. Three machine learning methods, classification and regression tree (CART), random forest (RF), and gradient boosting decision tree (GBDT), were used to develop models to predict pLOS, which is longer than the average LOS, in PD patients. The model with the best prediction performance was used to identify predictive factors contributing to the outcome. A multivariate LR model based on the identified predictors was then built to derive the score assigned to each predictor. Finally, a scoring tool was developed, and it was tested by stratifying PD patients into different pLOS risk groups.

Results

A total of 22,859 PD patients were included in our study, with 25.2% having pLOS. Among the three machine learning models, the RF model achieved the best prediction performance and thus was used to identify the 10 most predictive variables for building the scoring system. The multivariate LR model based on the identified predictors showed good discrimination power with an AUROC of 0.721 in the test dataset, and its coefficients were used as a basis for scoring tool development. On the basis of the developed scoring tool, PD patients were divided into three groups: low risk (≤5), median risk [5–10], and high risk (>10). The observed pLOS proportions in the low-risk, median-risk, and high-risk groups in the test dataset were 11.4%, 29.5%, and 54.7%, respectively.

Conclusions

This study developed a scoring tool to predict pLOS in PD patients. The scoring tool can effectively discriminate patients with different pLOS risks and be easily implemented in clinical practice. The pLOS scoring tool has a great potential to help physicians allocate medical resources optimally and achieve improved clinical outcomes.

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU

Background

Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predict the risk of hospital death of patients with sepsis in ICUs.

Methods

The source database used for model development and validation is the medical information mart for intensive care (MIMIC) III. We identified adult sepsis patients using the new sepsis definition Sepsis-3. A total of 86 predictor variables consisting of demographics, laboratory tests and comorbidities were used. We employed the least absolute shrinkage and selection operator (LASSO), random forest (RF), gradient boosting machine (GBM) and the traditional logistic regression (LR) method to develop prediction models. In addition, the prediction performance of the four developed models was evaluated and compared with that of an existent scoring tool – simplified acute physiology score (SAPS) II – using five different performance measures: the area under the receiver operating characteristic curve (AUROC), Brier score, sensitivity, specificity and calibration plot.

Results

The records of 16,688 sepsis patients in MIMIC III were used for model training and test. Amongst them, 2949 (17.7%) patients had in-hospital death. The average AUROCs of the LASSO, RF, GBM, LR and SAPS II models were 0.829, 0.829, 0.845, 0.833 and 0.77, respectively. The Brier scores of the LASSO, RF, GBM, LR and SAPS II models were 0.108, 0.109, 0.104, 0.107 and 0.146, respectively. The calibration plots showed that the GBM, LASSO and LR models had good calibration; the RF model underestimated high-risk patients; and SAPS II had the poorest calibration.

Conclusion

The machine learning-based models developed in this study had good prediction performance. Amongst them, the GBM model showed the best performance in predicting the risk of in-hospital death. It has the potential to assist physicians in the ICU to perform appropriate clinical interventions for critically ill sepsis patients and thus may help improve the prognoses of sepsis patients in the ICU.

The association between reduced kidney function and hearing loss: a cross-sectional study

Background

The relationship between kidney function and hearing loss has long been recognized, but evidence of this association mostly comes from small observational studies or other populations. The aim of this study is to explore the association between reduced kidney function and hearing loss in a large population-based study among the middle-aged and elderly Chinese.

Methods

Data collected from the Chinese Health and Retirement Longitudinal Study (CHARLS) in 2015 were used for analysis. A cross-sectional study was conducted among 12,508 participants aged 45 years and older. Hearing loss, the outcome of this study, was defined according to interviewees’ responses to three survey questions related to hearing in the CHARLS. Estimated glomerular filtration rate (eGFR) was employed to assess kidney function, and participants were classified into three categories based on eGFR: ≥90, 60–89 and < 60 mL/min/1.73 m². Multivariable logistic regression was employed to adjust for potential confounders, including demographics, health-related behaviors, and cardiovascular risk factors.

Results

The overall prevalence of self-reported hearing loss in the study population was 23.6%. Compared with participants with eGFR ≥90 mL/min/1.73 m², participants with eGFR of 60–89 mL/min/1.73 m² (odds ratio [OR]: 1.11, 95% confidence interval [CI]: 1.00–1.23) and eGFR < 60 mL/min/1.73 m² (OR: 1.25, 95% CI: 1.04–1.49) showed increased risk of hearing loss after adjusting for potential confounders.

Conclusions

Reduced kidney function is independently associated with hearing loss. Testing for hearing should be included in the integrated management of patients with chronic kidney disease.

[Letrozole versus gonadotropin-releasing hormone antagonist during luteal phase in the prevention of ovarian hyperstimulation syndrome: a randomized controlled trial]

Objective: To explore and compare the preventive effect of using letrozole and gonadotropin-releasing hormone (GnRH) antagonist during luteal phase of patients at high risk for ovarian hyperstimulation syndrome (OHSS). Methods: A total of 99 infertile women undergoing in vitro fertilization and embryo transfer or intracytoplasmic sperm injection with high risk for OHSS were enrolled in this randomized controlled trial.The letrozole group (n=51) received letrozole of 7.5 mg daily for 3 days;the GnRH antagonist group (n=48) were given cetrorelix of 0.25 mg subcutaneously daily for 3 days. Both groups received support therapy combined with embryo cryopreservation. The incidence of OHSS was surveyed. And the serum concentration of estradiol, LH and progesterone on days 3, 5 and 8 after oocytes retrieval were measured. Results: There were no statistical differences in terms of baseline characteristics of patients and outcomes of controlled ovarian hyperstimulation between the two groups.The incidence of moderate and severe OHSS was found no significantly difference between letrozole group [11.8%(6/51)] and GnRH antagonist group [10.4%(5/48);P>0.05]. The estradiol concentration of the indicated days on days 3,5 and 8 after oocytes retrieval in letrozole group and GnRH antagonist group were (1 417±3 543) versus (15 210±9 921) pmol/L, (1 692±4 330) versus (18 680±11 567) pmol/L, (239±336) versus (3 582±5 427) pmol/L, respectively;compared with GnRH antagonist group, the estradiol level was significantly lower in the letrozole group (all P<0.01). The luteinizing hormone level in the letrozole group were (0.46±0.40), (0.56±0.55)and (0.67±0.58) U/L on days 3,5 and 8 after oocytes retrieval, which were significantly higher than those of GnRH antagonist group [(0.28±0.28), (0.30±0.19) and (0.45±0.37) U/L, respectively; all P<0.05]. There was no obvious differences on progesterone levels between letrozole group and GnRH antagonist group (all P>0.05),and on days 8 after oocytes retrieval,the level of progesterone in each group were significantly lower than those on day 3 and 5 after oocytes retrieval (P<0.05). Conclusion: Letrozole has the same efficiency as GnRH antagonist for the prevention of OHSS, faster and cheaper to use, but its efficacy seems not to be related to the suppression of steroidogenic during the luteal phase.

The contributor roles for randomized controlled trials and the proposal for a novel CRediT-RCT

Background

The past decade has witnessed a rapid increase in the number of contributors per article, which has made explicitly defining the roles of each contributor even more challenging. The Contributor Roles Taxonomy (CRediT) was developed to explicitly define author roles, but there is a lack of empirical data on how CRediT is used in clinical trials. This study aimed to provide empirical data on the use of CRediT in randomized controlled trials (RCTs) and discuss some limitations of CRediT. A new taxonomy (CRediT-RCT) is proposed to explicitly define the author roles in RCTs.

Methods

The electronic database of PubMed was searched from July 2017 to October 2019 to identify component trials with a randomized controlled design. Publications from the Public Library of Science (PLoS) were included because they embed the CRediT roles within the authors' metadata rather than solely as a separate paragraph of text.

Results

A total of 446 articles involving 4,185 authors were included in the study. Most authors participated in the study's conceptualization (44.9%) and investigation (48.8%), but only a fraction of the authors participated in software management (7.4%). Many CRediT roles were correlated with each other: the strongest correlation was the one between funding acquisition and conceptualization (correlation metric =0.39), followed by the one between conceptualization and methodology (0.37). The authors who acquired funding (OR: 2.06; 95% CI: 1.54-2.76; P<0.001), did project administration (OR: 1.54; 95% CI: 1.17-2.03; P=0.002), performed supervision (OR: 2. 60; 95% CI: 1.93-3.52; P<0.001), wrote the original draft (OR: 4.83; 95% CI: 3.54-6.60; P<0.001), or were the first author (OR: 7.85; 95% CI: 5.71-10.87; P<0.001), were more likely to be the corresponding author. Also, while the original draft writing was significantly associated with the designation of the first author (OR: 37.49; 95% CI: 25.29-57.57; P<0.001), the first author did not perform review and editing (OR: 0.55; 95% CI: 0.40-0.75; P<0.001), supervision (OR: 0.49; 95% CI: 0.36-0.67; P<0.001), or resource management (OR: 0.71; 95% CI: 0.50-1.00; P=0.053). We further propose a novel Contributor Roles Taxonomy for Randomized Controlled Trials (CRediT-RCT) which includes 10 roles.

Conclusions

The present study provides empirical data on the use of CRediT for RCTs, and some limitations of the taxonomy are discussed. We further propose a new CRediT-RCT which includes 10 roles.

Effect of lncRNA LET on proliferation and invasion of osteosarcoma cells

OBJECTIVE

To investigate the expression of long non-coding RNA (LncRNA) LET in osteosarcoma and its effect on the proliferation, apoptosis, migration and invasion of osteosarcoma cells.

PATIENTS AND METHODS

The expression of lncRNA LET was detected in osteosarcoma tissues and cell lines (MG63 and hFOB1.19). MG63 cells stably overexpressing lncRNA LET were constructed by lentiviral. The effects of lncRNA LET overexpression on the proliferation, apoptosis, migration and invasion of osteosarcoma cells were detected by cell counting kit-8 (CCK-8), flow cytometry and transwell chamber assay.

RESULTS

The expression of lncRNA LET in osteosarcoma tissues and MG63 cells was significantly down-regulated. Overexpression of lncRNA LET significantly inhibited the proliferation, migration, invasion, and induced apoptosis of MG63 cells.

CONCLUSIONS

LncRNA LET was participated in the development of osteosarcoma, and may be used as a potential molecular target for the treatment of osteosarcoma.

Association between the Charlson Comorbidity Index and the risk of 30-day unplanned readmission in patients receiving maintenance dialysis

Background

Patients receiving maintenance hemodialysis (HD) and peritoneal dialysis (PD) are frequently hospitalized. Reducing unplanned 30-day hospital readmissions is a key priority for improving the quality of health care. The purpose of this study was to assess the association between the Charlson Comorbidity Index (CCI), which has been used to evaluate multi-comorbidities status, and 30-day readmission in patients on HD and PD therapy.

Methods

The Hospital Quality Monitoring System (HQMS), a national administrative database for hospitalized patients in China was used to extract dialysis patients admitted from January 2013 to December 2015. The outcome was the unplanned readmission following the hospital discharge within 30 days. For patients with multiple hospitalizations, a single hospitalization was randomly selected as the index hospitalization. A cause-specific Cox proportional hazard model was utilized to assess the association of CCI with readmission within 30 days.

Results

Of the 124,721 patients included in the study, 19,893 patients (16.0%) were identified as experiencing unplanned readmissions within 30 days. Compared with patients without comorbidity (CCI = 2, scored for dialysis), the risk of 30-day readmission increased with elevated CCI score. The hazards ratio (HR) for those with CCI 3–4, 5–6 and > 6 was 1.01 (95% confidence interval [CI] 0.98–1.05), 1.09 (95% CI 1.05–1.14), and 1.14 (95% CI 1.09–1.20), respectively.

Conclusions

Our study indicated that CCI was independently associated with the risk of 30-day readmission for patients receiving dialysis including HD and PD, and could be used for risk-stratification.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1538-0) contains supplementary material, which is available to authorized users.

Using electronic health record data to establish a chronic kidney disease surveillance system in China: protocol for the China Kidney Disease Network (CK-NET)-Yinzhou Study

INTRODUCTION

Chronic kidney disease (CKD) is an important public health problem worldwide. However, there are few active disease surveillance systems for it. The China Kidney Disease Network (CK-NET) was established as a comprehensive surveillance system for CKD using various data sources. As part of this, the proposed CK-NET-Yinzhou study aims to build a regional surveillance system in a developed coastal area in China to obtain detailed dynamic information about kidney disease and to improve the ability to manage the disease effectively.

METHODS AND ANALYSIS

Yinzhou is a district of Ningbo city, Zhejiang province. The district has a population of more than 1 million. By 2016, 98% were registered in a regional health information system that started in 2009. This system includes administrative databases containing general demographic characteristics, health check information, inpatient and outpatient electronic medical records, health insurance information, disease surveillance and management information, and death certificates. We will use longitudinal individual electronic health record data to identify people with CKD by repeated laboratory measurements and diagnostic codes. We will also evaluate the associated risk factors, prognosis and disease management. An intelligent clinical decision support system (CDSS) will be developed based on clinical guidelines, domain expert knowledge and real-world data, and will be integrated into the hospital information system.

ETHICS AND DISSEMINATION

The CK-NET-Yinzhou study has been reviewed and approved by the Peking University First Hospital Ethics Committee. Privacy of local residents registered with the health information system will be tightly protected through the study process. The findings of the study will be disseminated through peer-reviewed journal articles, posters and presentations in national and international scientific conferences, as well as among local practitioners through the CDSS.

Big data in nephrology: Are we ready for the change?

Chronic kidney disease (CKD) is a major public health issue worldwide. However, the status of kidney health care needs to be strengthened globally and research evidence in nephrology is relatively limited. The unmet needs in nephrology leave ample space for imagination regarding leveraging big data and artificial intelligence (AI). Big data has potential to drive medical innovation, reduce medical costs and improve health care quality. Compared with other specialties such as cardiology, the scopes of utilizing big data in nephrology need to be enhanced. We reviewed the studies on the application of big data in nephrology, such as disease surveillance, risk prediction and clinical decision support systems (CDSS), and proposed several potential directions of utilizing big data and AI. The efforts including building a CKD surveillance system and collaborative network, implementing a real-world cohort in a cost-effective manner, strengthening the application and transformation of AI and CDSS, and stimulating the activeness of medical imaging in nephrology, could be considered. In the era of big data, a nephrologist would be stronger and smarter if he or she could get intelligent assistance from knowledge or big data-driven CDSS.

Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model

OBJECTIVES

We aimed to construct a mortality prediction model using the random forest (RF) algorithm for acute kidney injury (AKI) patients in the intensive care unit (ICU), and compared its performance with that of two other machine learning models and the customized simplified acute physiology score (SAPS) II model.

METHODS

We used medical information mart for intensive care (MIMIC) III database for model development and performance comparison. The RF model uses the same predictor variable set as that of the SAPS II model. We also developed three other models and compared the RF model with the other three models in prediction performance. Three other models include support vector machine (SVM) model, artificial neural network (ANN) model and customized SAPS II model. In model comparison, the prediction performance of each model was assessed by the Brier score, the area under the receiver operating characteristic curve (AUROC), accuracy and F₁ score.

RESULTS

The final cohort consisted of 19044 patients with AKI in the ICU. The observed in-hospital mortality of AKI patients is 13.6% in the final cohort. The results of model performance comparison show that the Brier score of the RF model is 0.085 (95%CI: 0.084-0.086) and AUROC of the RF model is 0.866 (95%CI: 0.862-0.870). The accuracy of the RF model is 0.728 (95%CI: 0.715-0.741). The F₁ score of the RF model is 0.459 (95%CI: 0.449-0.470). The calibration plots show that the RF model slightly overestimates mortality in patients with low risk of death and underestimates mortality in patients with high risk of death.

CONCLUSION

There is great potential for the RF model in mortality prediction for AKI patients in ICU. The RF model may be helpful to aid ICU clinicians to make timely clinical intervention decisions for AKI patients, which is critical to help reduce the in-hospital mortality of AKI patients. A prospective study is necessary to evaluate the clinical utility of the RF model.

JAK1/2 Inhibitors AZD1480 and CYT387 Inhibit Canine B-Cell Lymphoma Growth by Increasing Apoptosis and Disrupting Cell Proliferation

Background

Canine diffuse large B‐cell lymphoma (DLBCL) is a common and aggressive hematologic malignancy. The lack of conventional therapies with sustainable efficacy warrants further investigation of novel therapeutics. The Janus kinase (JAK) and signal transducer and activator of transcription (STAT) pathways play important roles in the pathogenesis of hematologic malignancies in humans including DLBCLs. AZD1480 and CYT387 are novel JAK1/2 inhibitors that have been used in clinical trials for treating various hematologic cancers in humans. No studies have characterized the antitumor effects of JAK inhibitors on DLBCL in dogs.

Hypothesis/Objectives

We hypothesize that JAK1/2 inhibitors AZD1480 and CYT387 can effectively inhibit growth of canine DLBCL in vitro. We aim to assess the antitumor activity of AZD1480 and CYT387 in canine DLBCL and to determine the underlying mechanisms of action.

Methods

In vitro study of canine lymphoma cell growth, proliferation, and apoptosis by viability, proliferation and apoptosis assays.

Results

A significant decrease in viable canine lymphoma cells was observed after AZD1480 and CYT387 treatments. In addition, AZD1480 and CYT387 treatment resulted in decreased lymphoma cell proliferation and increased early apoptosis.

Conclusion and Clinical Importance

AZD1480 and CYT387 inhibit canine lymphoma cell growth in a dose‐dependent manner. Our findings justify further phase I/II clinical investigations of the safety and efficacy of JAK1/2 inhibitors in canine DLBCL and suggest new opportunities for novel anticancer therapies.

LSD1 demethylates HIF1α to inhibit hydroxylation and ubiquitin-mediated degradation in tumor angiogenesis

Lysine-specific demethylase 1 (LSD1), which has been considered as a potential therapeutic target in human cancer, has been known to regulate many biological functions through its non-histone substrates. Although LSD1-induced hypoxia-inducible factor alpha (HIF1α) demethylation has recently been proposed, the effect of LSD1 on the relationship between HIF1α post-translational modifications (PTMs) and HIF1α-induced tumor angiogenesis remains to be elucidated. Here, we identify a new methylation site of the HIF1α protein antagonized by LSD1 and the interplay between HIF1α protein methylation and other PTMs in regulating tumor angiogenesis. LSD1 demethylates HIF1α at lysine (K) 391, which protects HIF1α against ubiquitin-mediated protein degradation. LSD1 also directly suppresses PHD2-induced HIF1α hydroxylation, which has a mutually dependent interplay with Set9-mediated HIF1α methylation. Moreover, the HIF1α acetylation that occurs in a HIF1α methylation-dependent manner is inhibited by the LSD1/NuRD complex. HIF1α stabilized by LSD1 cooperates with CBP and MTA1 to enhance vascular endothelial growth factor (VEGF)-induced tumor angiogenesis. Thus, LSD1 is a key regulator of HIF1α/VEGF-mediated tumor angiogenesis by antagonizing the crosstalk between PTMs involving HIF1α protein degradation.

Association of blood pressure in the supine position with target organ damage in subjects over 60 years old

Objective Toexplore the correlation between blood pressure in the supine position and target organ damage in subjects over 60 years of age. Methods In 2444 individuals, we investigated the association of systolic blood pressure (SBP) in the supine position with the target organ damage indices microalbuminuria (ALBU), brachial-ankle pulse wave velocity (baPWV), and carotid intima-media thickness (IMT). Supine hypertension (SH) is defined as systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg. Subjects were assigned to either the SH group (1275 cases) or the non-SH group (1169 cases). Results The levels of ALBU, baPWV, and IMT, as well as the percentage of participants with ALBU > 30 mg/L, baPWV ≥ 1400 cm/s, and IMT ≥ 1 mm, were significantly higher in the SH group than in the non-SH group. Multivariate logistic regression analysis showed that SH was an independent risk factor for baPWV and IMT, but the relationship with ALBU was not statistically significant after correction for confounding factors. Conclusions SH is a risk factor for target organ damage, as expressed by the indices baPWV and IMT. The association of SH with kidney damage requires further study.

Influence of pelvic postural angle change on acetabulum implantation in total hip arthroplasty

The current study investigated the relationship between the implantation angle of the acetabular component and the change in the pelvic postural angle during hip arthroplasty surgery. One pelvis with a left lower limb prosthesis was used. Total hip arthroplasty on the left pelvis was simulated with the help of a computer-assisted navigation system. The pelvis revolved around the horizontal, longitudinal and sagittal axes at different angles, and the anteversion and abduction of the acetabular component were measured. The changing angle of the pelvis rotating around the horizontal and longitudinal axes greatly influenced acetabular component anteversion. The changing angle of the pelvis rotating around the sagittal axis had a relatively great influence on the acetabular component abduction angle. The change in the postural angle of the pelvis had a great influence on the installation angle of the acetabular component. It is important to standardize posture prior to the operation.