Early prediction of cerebral-cardiac syndrome after ischemic stroke: the PANSCAN scale.

BACKGROUND: Cerebral-cardiac syndrome, newly developed cardiac damage manifestations subsequent to cerebral injuries, is a common complication of stroke and leads to increased morbidity and mortality. The current study is aimed to develop a risk prediction scale to stratify high-risk population of CCS among ischemic stroke patients. METHODS: The study included 410 cases from four tertiary medical centers from June 2018 to April 2019. The risk prediction model was established via logistic regression from the derivation cohort including 250 cases admitted between June 2018 and December 2018. Another 160 cases admitted from January 2019 to April 2019 were included as the validation cohort for external validation. The performance of the model was determined by the area under curve of the receiver operating characteristic curve. A rating scale was developed based on the magnitude of the logistic regression coefficient. RESULTS: The prevalence of CCS was 55.2% in our study. The predictive model derived from the derivation cohort showed good calibration by Hosmer-Lemeshow test (P = 0.492), and showed sensitivity of 0.935, specificity of 0.720, and Youden index of 0.655. The C-statistic for derivation and validation cohort were 0.888 and 0.813, respectively. Our PANSCAN score (0 to 10 points) was then established, which consists of the following independent risk factors: PT(12 s-14 s = 0; otherwise = 1), APTT(30s-45s = 0, otherwise = 1), Neutrophils(50-70% = 0; otherwise = 1), Sex(female = 1), Carotid artery stenosis(normal or mild = 0; moderate to severe = 2), Age(≥65 years = 1), NIHSS score(1 to 4 = 2; ≥5 = 3). Patients scored 3 or more points were stratified as high risk. CONCLUSION: The risk prediction model showed satisfactory prediction effects. The PANSCAN scale provides convenient reference for preventative treatment and early management for high-risk patients. TRIAL REGISTRATION: The study was retrospectively registered in Chinese Trial Registry. The date of registration is April 17, 2019. TRIAL REGISTRATION NUMBER: ChiCTR1900022587 .

Mast cell specific immunological biomarkers and metabolic syndrome among middle-aged and older Chinese adults.

The main aim of this study is to explore whether these mast cell specific immunological biomarkers [immunoglobulin E (IgE), chymase and tryptase] is an independent risk factor of MetS and whether the combined action of these biomarkers increased the associations with MetS. Three mast cell-specific immunological biomarkers were measured using enzyme linked immunosorbent assay (ELISA). One-way analysis of covariance and logistic regression models were used for analyzing the associations between immunological biomarkers with MetS. A total of 340 participants, 82 (24.1%) individuals had diabetes mellitus, 31 (9.1%) had MetS (without diabetes mellitus) and 110 had MetS plus diabetes mellitus. After adjusting by multivariable (age, gender, smoking, and family history for hypertension), compared with no diabetes mellitus or MetS group (reference group), hs-CRP was associated with diabetes mellitus [OR (odds ratio): 2.29 (1.15-4.57, 95% CI (confidence interval), p=0.019] and MetS plus diabetes mellitus [OR: 2.20 (1.05-4.61, 95% CI), p=0.036], IgE was associated with MetS plus diabetes mellitus [OR: 2.38 (1.13-5.02, 95% CI), p=0.023]. After adjusting by multivariable, compared with reference group, most of combined elevated inflammatory or immunological biomarkers were significantly associated with diabetes mellitus or MetS with or without diabetes mellitus. Patients with established diabetes mellitus or MetS had different inflammatory or immunological cytokine profile (such as hs-CRP, IgE, chymase, tryptase), which indicated that there is an alteration in the function of the immune system in diabetes mellitus or MetS patient. But these results are requested to be further demonstrated for large sample population-based cohort study.

Significance of serum potassium level monitoring during the course of post-operative rehabilitation in patients with hypokalemia.

OBJECTIVE: Our objective was to evaluate the significance of pre-hospital and post-operative serum potassium level monitoring and hypokalemia intervention in laparotomy patients with hypokalemia. METHOD: A total of 118 laparotomy patients with hypokalemia were randomly divided into an intervention group (N = 60) and a control group (N = 58). Blood samples were collected for measurement of potassium levels at various time points (pre-admission, admission, 24 h and 48 h post-operation) for both groups. Hypokalemia interventions were administered to patients in the intervention group in the pre-admission period and the post-operative period. Visceral dynamics were assessed after laparotomy in both groups. RESULT: Average serum potassium levels at admission, time period of drinking, and time of first bowel sound after laparotomy differed significantly (p < 0.001) between the two groups. Average serum potassium levels, first time of defecation, urination, and ambulation at 24 h and 48 h post-operation differed significantly (p < 0.05) between the two groups. CONCLUSION: An optimal pathway of serum potassium monitoring not only saves limited ward space but also allows for early correction of hypokalemia in patients undergoing laparotomy.

Development and validation of fall risk perception scale for patients with Parkinson's disease.

Background: Perception assessment plays an important role in fall risk awareness and fall prevention. Parkinson's disease patients with motor dysfunction are at high risk of falling. Currently, no instrument has been explicitly crafted to assess the risk perception of fall in PD patients. The purpose of this study was to develop and validate the fall risk perception scale for PD patients (FRPS-PD), providing healthcare professionals with a effective assessment tool to enhance proactive fall prevention initiatives. Method: Based on the Proactive Health theory and Risk Perception Attitude (RPA) Framework, the questionnaire was developed through literature review, semi-structure interview, expert consultation and pilot testing. A total of 428 patients with PD from Grade A tertiary hospitals in Shanghai, Hangzhou and Anhui from January 2023 to July 2023 were recruited. The items and dimensions in the scale were explored and confirmed using item-analysis, content validity, exploratory factor analytical (EFA), confirmatory factor analytical (CFA), internal consistency and test-retest reliability analysis. Results: A total of 16-items, 2-dimensions structure were identified, including 12 items of risk perception and 4 items of self-efficacy dimension. The cumulative variance of EFA model was 73.669%, further CFA showed that acceptable model fit (χ2/df = 2.226, RMSEA = 0.074, NF = 0.928, TLI = 0.951, CFI = 0.959, GFI = 0.887 and AGFI = 0.848). The content validity index was 0.956. The reliability of the scale was 0.952 using Cronbach's α coefficient method. The test-retest reliability was 0.944. Conclusion: The FRPS-PD is a valid and reliable measurement for evaluating fall risk perception level for individuals with PD in mainland China.

A dataset of endorheic basins on detailed delineation and classification for the Qinghai-Tibet Plateau.

Endorheic basins are important geomorphological and ecological units on the Qinghai-Tibet Plateau (QTP), which is undergoing a rapid evolution of its lake system structure and drainage reorganization that is threatening local ecology, infrastructures and residuals owing to climate change. This dataset provides a detailed delineation and classification of endorheic basins on the QTP for understanding the complex dynamics under climate changes. A newly-developed algorithm, namely the Joint Elevation-Area Threshold (JEAT) algorithm (Liu et al, 2024), is applied for delineating endorheic basins based on digital elevation model (DEM). A total of 184 endorheic basins were divided, of which the permanent divide lines were characterized. All the endorheic basins were further categorized into five groups based on the hydraulic connectivity attributes, which have been commonly observed since 2000. The dataset also includes basic information such as drainage area, water surface area, and water storage volume of each endorheic basin. It is particularly beneficial for digital watershed analysis towards ecological restoration and water resource management on the environmentally vulnerable QTP.

Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China.

Carbonaceous particles are an important chemical component of atmospheric fine particles. In this study, a single particle aerosol mass spectrometer was used to continuously measure the carbonaceous particles in Chengdu, one of the megacities most affected by haze in China, from January 22 to March 3, 2021. During the observation period, the average mass concentration of PM2.5 was 62.3 ± 37.2 µg m-3, and the emissions from mobile sources were more prominent. Carbonaceous particles accounted for 68.6% of the total particles and could be classified into 10 categories, with elemental carbon (EC) mixed with sulfate (EC-S) particles making the highest contribution (33.1%). EC particles rich in secondary components and organic carbon (OC) particles rich in secondary component exhibited different diurnal variations, suggesting different sources and mixing mechanisms. From "excellent" to "polluted" days, the contributions of EC-S, EC mixed with sulfate and nitrate (EC-SN) and OC mixed with EC (OC-EC) particles increased by 9.8%, 4.5% and 6.6%, respectively, and thus these particles are key targets for future pollution control. The potential source contribution of the southwest area was stronger than that of other areas, and the potential contribution of regional transport to EC-related particles was stronger than to OC-related particles. Most particles were highly mixed with sulfate or nitrate, and the level of secondary mixing further enhanced as pollution worsened.

Whole-genome sequencing for surveillance of fluoroquinolone resistance in rifampicin-susceptible tuberculosis in a rural district of Shanghai: A 10-year retrospective study.

Background: Fluoroquinolones (FQs) are the most important second-line anti-tuberculosis (anti-TB) drugs, primarily used for the treatment of multidrug- or rifampicin-resistant TB (MDR/RR-TB). However, FQs are also commonly used to treat other bacterial infections. There are few published data on the rates of FQ resistance among rifampicin-susceptible TB. Methods: We used whole-genome sequencing (WGS) to determine the prevalence of FQ resistance among rifampicin-susceptible TB in a rural district of Shanghai. This was a population-based retrospective study of all culture-positive pulmonary TB patients diagnosed in the Chongming district of Shanghai, China during 2009-2018. Results: The rate of FQ resistance was 8.4% (29/345) among TB, 6.2% (20/324) among rifampicin-susceptible TB, and 42.9% (9/21) among MDR/RR-TB. Transmission of FQ-resistant strains was defined as strains differing within 12 single-nucleotide polymorphisms (SNPs) based on WGS. Among the rifampicin-susceptible TB, 20% (4/20) of FQ resistance was caused by the transmission of FQ-resistant strains and 45% (9/20) of FQ resistance was identified as hetero-resistance. Conclusions: The prevalence of FQ resistance in rifampicin-susceptible TB was higher than expected in Shanghai. Both the transmission and the selection of drug-resistant strains drive the emergence of FQ resistance in rifampicin-susceptible TB isolates. Therefore, the WGS-based surveillance system for TB should be urgently established and the clinical awareness of the rational use of FQs for respiratory infections should be enhanced to prevent the premature occurrence of FQ resistance.

The mechanisms and clinical application of Traditional Chinese Medicine Lianhua-Qingwen capsule.

Lianhua-Qingwen capsule (LQC) is a commonly used Traditional Chinese Medicine (TCM) in China and has 11 herb components. The main active ingredient can target specific molecules and perform many clinic treatment roles. LQC has been authorized by National Medical Products Administration (NMPA) of China to treat severe acute respiratory syndrome (SARS) in 2002-2003, type A influenza virus HIN1 pandemic in 2009, H7N9, H3N2 and coronavirus disease-19 (COVID19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) in 2020. It is also widely used to treat common cold with wind-heat syndrome, chronic rhinosinusitis (CRS), amygdalitis and chronic obstructive pulmonary disease. This article summarizes the advanced research progress of LQC in clinical application, mechanisms and provides new clues in the clinical application of LQC.

Influence of the Integrated Delivery System on the Medical Serviceability of Primary Hospitals.

OBJECTIVE: To explore the change in the medical serviceability of primary hospitals since the establishment of the Huzhou No. 1 People's Hospital medical care group incorporating the integrated delivery system. METHODS: With reference to the "Grade Evaluation Standard of General Hospitals in Zhejiang Province" and the "Guidelines for Service Capacity Evaluation of Township Hospitals (2019 Edition)," we analyzed the influence of the integrated delivery system on the capacity of primary medical services and selected the targeted core indicators. From the four dimensions of diagnosis and treatment breadth, diagnosis and treatment efficiency, surgical ability, and patient satisfaction, an index evaluation system was established to explore the changes in the medical serviceability in primary hospitals. RESULTS: The measurements were aimed at four specific issues, that is, the low medical technology level of grassroots personnel, the poor information communication among medical institutions, the difficulty in recruiting people, and the imperfect training mechanism in primary hospitals. After establishing a series of measurements related to the problems faced by the primary healthcare sector in China, the score of breadth of diagnosis and treatment, efficiency of diagnosis and treatment ability, surgical ability, and patient satisfaction of the primary hospitals in our medical group have greatly increased. CONCLUSION: The integrated delivery system improved the primary hospitals' medical health ability obviously. Our study also provides various useful and operable suggestions for primary healthcare.

Towards advancing the earthquake forecasting by machine learning of satellite data.

Earthquakes have become one of the leading causes of death from natural hazards in the last fifty years. Continuous efforts have been made to understand the physical characteristics of earthquakes and the interaction between the physical hazards and the environments so that appropriate warnings may be generated before earthquakes strike. However, earthquake forecasting is not trivial at all. Reliable forecastings should include the analysis and the signals indicating the coming of a significant quake. Unfortunately, these signals are rarely evident before earthquakes occur, and therefore it is challenging to detect such precursors in seismic analysis. Among the available technologies for earthquake research, remote sensing has been commonly used due to its unique features such as fast imaging and wide image-acquisition range. Nevertheless, early studies on pre-earthquake and remote-sensing anomalies are mostly oriented towards anomaly identification and analysis of a single physical parameter. Many analyses are based on singular events, which provide a lack of understanding of this complex natural phenomenon because usually, the earthquake signals are hidden in the environmental noise. The universality of such analysis still is not being demonstrated on a worldwide scale. In this paper, we investigate physical and dynamic changes of seismic data and thereby develop a novel machine learning method, namely Inverse Boosting Pruning Trees (IBPT), to issue short-term forecast based on the satellite data of 1371 earthquakes of magnitude six or above due to their impact on the environment. We have analyzed and compared our proposed framework against several states of the art machine learning methods using ten different infrared and hyperspectral measurements collected between 2006 and 2013. Our proposed method outperforms all the six selected baselines and shows a strong capability in improving the likelihood of earthquake forecasting across different earthquake databases.

Lysophosphatidic acid enhances neointimal hyperplasia following vascular injury through modulating proliferation, autophagy, inflammation and oxidative stress.

Lysophosphatidic acid (LPA), which is one of the intermediate products of membrane phospholipid metabolism, is a bioactive phospholipid that possesses diverse activities. In the present study, the effects of LPA on neointimal formation following vascular injury were investigated. A carotid artery balloon injury model was employed in the present study, and following vascular injury, rats received an intraperitoneal injection of 1 mg/kg LPA. Subsequently, histopathological alterations were assessed by hematoxylin and eosin staining, the expression levels of proliferating cell nuclear antigen (PCNA) were detected by immunohistochemistry, apoptosis was assessed via a terminal deoxynucleotidyl transferase­mediated dUTP nick end labeling assay, and the expression levels of apoptosis­associated and autophagy­associated proteins were detected by western blotting. In addition, inflammatory and oxidative stress­associated factors were assessed by reverse transcription­quantitative polymerase chain reaction or corresponding kits. The results of the present study demonstrated that LPA enhanced vascular injury­induced neointimal hyperplasia. LPA further elevated the expression levels of PCNA in the injured carotid artery tissues. LPA exhibited no effect on apoptosis in carotid artery tissues, whereas it modulated autophagy in the injured carotid artery tissues. Furthermore, LPA enhanced vascular injury­induced inflammation and oxidative stress. The present study demonstrated that LPA may enhance neointimal hyperplasia following vascular injury by modulating proliferation, autophagy, inflammation and oxidative stress, but not apoptosis. Furthermore LPA may contribute to the pathology of atherosclerosis and may be considered a promising therapeutic target for the treatment of atherosclerosis.

Analysis of Inflammatory Mediators in Prediabetes and Newly Diagnosed Type 2 Diabetes Patients.

This study evaluated the inflammatory markers in prediabetes and newly diagnosed type 2 diabetes mellitus (T2DM). Inflammatory markers levels were analyzed using one-way analysis of covariance and the association with prediabetes or T2DM risks was examined by logistic regression models. Our data showed increased levels of hypersensitivity C-reactive protein (hs-CRP), interleukin (IL-4), IL-10, and tryptase in prediabetes subjects and hs-CRP, immunoglobulin E (IgE), IL-4, and IL-10 in T2DM subjects. We concluded that Hs-CRP, IgE, IL-4, IL-10, and tryptase were positively associated with prediabetes or T2DM. Further large prospective studies are warranted to assess a temporal relation between inflammatory biomarkers and incidence of prediabetes or T2DM and its associated chronic diseases.

Immunoglobulin E and mast cell proteases are potential risk factors of impaired fasting glucose and impaired glucose tolerance in humans.

AIM: Mast cells are important in experimental diabetes. Plasma levels of immunoglobulin E (IgE), tryptases, and chymases are inflammatory markers of human diabetes. Whether they also correlate with the risk of pre-diabetes, however, remains unknown. METHODS AND RESULTS: A total of 260 subjects 55-75 years of age were grouped as normal glucose tolerance (NGT), isolated impaired fasting glucose (I-IFG), isolated impaired glucose tolerance (I-IGT), and mixed IFG/IGT. There were significant differences in plasma levels of high-sensitivity C-reactive protein (hsCRP) (P < 0.001) and IgE (P = 0.003) among all subgroups of pre-diabetes, and chymase in I-IGT (P = 0.043) and mixed IFG/IGT (P = 0.037) subgroups compared with NGT group. High-sensitivity CRP was a risk factor in all subgroups of pre-diabetes; IgE was a risk factor of mixed IFG/IGT; and chymase was a risk factor of I-IGT and mixed IFG/IGT. Interactions between hsCRP and high waist circumference (WC), waist-to-hip ratio (WHR), or HOMA-ß index, and interactions between IgE and high WC or tryptase levels all increased further the risk of developing I-IFG, I-IGT, or mixed IFG/IGT. CONCLUSION: Plasma hsCRP, IgE, and chymase levels associate with pre-diabetes status. While hsCRP, IgE, and chymase are individual risk factors of pre-diabetes, interactions with metabolic parameters increased further the risk of pre-diabetes.

Immunoglobulin E and mast cell proteases are potential risk factors of human pre-diabetes and diabetes mellitus.

BACKGROUND: Recent studies have suggested that mast-cell activation and inflammation are important in obesity and diabetes. Plasma levels of mast cell proteases and the mast cell activator immunoglobulin E (IgE) may serve as novel inflammatory markers that associate with the risk of pre-diabetes and diabetes mellitus. METHODS AND RESULTS: A total of 340 subjects 55 to 75 years of age were grouped according to the American Diabetes Association 2003 criteria of normal glucose tolerance, pre-diabetes, and diabetes mellitus. The Kruskal-Wallis test demonstrated significant differences in plasma IgE levels (P = 0.008) among groups with different glucose tolerance status. Linear regression analysis revealed significant correlations between plasma levels of chymase (P = 0.030) or IgE (P = 0.022) and diabetes mellitus. Ordinal logistic regression analysis showed that IgE was a significant risk factor of pre-diabetes and diabetes mellitus (odds ratio [OR]: 1.674, P = 0.034). After adjustment for common diabetes risk factors, including age, sex, hypertension, body-mass index, cholesterol, homeostatic model assessment (HOMA) index, high-sensitivity C-reactive protein (hs-CRP), and mast cell chymase and tryptase, IgE remained a significant risk factor (OR: 1.866, P = 0.015). Two-variable ordinal logistic analysis indicated that interactions between hs-CRP and IgE, or between IgE and chymase, increased further the risks of developing pre-diabetes and diabetes mellitus before (OR: 2.204, P = 0.044; OR: 2.479, P = 0.033) and after (OR: 2.251, P = 0.040; OR: 2.594, P = 0.026) adjustment for common diabetes risk factors. CONCLUSIONS: Both IgE and chymase associate with diabetes status. While IgE and hs-CRP are individual risk factors of pre-diabetes and diabetes mellitus, interactions of IgE with hs-CRP or with chymase further increased the risk of pre-diabetes and diabetes mellitus.