Partial hypopituitarism with ACTH deficiency as the main manifestation as a complication of hemorrhagic fever with renal syndrome.

Hypopituitarism is a relatively rare complication of hemorrhagic fever with renal syndrome. However, almost all available reported cases were total anterior pituitary hypofunction, isolated growth-hormone deficiency, or isolated gonadotropin deficiency. Here, we firstly describe a patient with partial hypopituitarism with ACTH deficiency as the main manifestation as a complication of hemorrhagic fever with renal syndrome.

HTNV infection induces activation and deficiency of CD8+MAIT cells in HFRS patients.

Hantaan virus (HTNV) infection causes an epidemic of hemorrhagic fever with renal syndrome (HFRS) mainly in Asia. Mucosal-associated invariant T (MAIT) cells are innate-like T lymphocytes known to play an important role in innate host defense during virus infection. However, their roles and phenotypes during HTNV infection have not yet been explored. We characterized CD8+MAIT cells from HFRS patients based on scRNA-seq data combined with flow cytometry data. We showed that HTNV infection caused the loss and activation of CD8+MAIT cells in the peripheral blood, which were correlated with disease severity. The production of granzyme B and IFN-γ from CD8+MAIT cells and the limitation of HTNV replication in endothelia cells indicated the anti-viral property of CD8+MAIT cells. In addition, in vitro infection of MAIT cells by HTNV or HTNV-exposed monocytes showed that the activation of MAIT cells was IL-18 mediated. In conclusion, this study identified, for the first time, gene expression profiles of MAIT cells, provided underlying molecular mechanisms for activation of MAIT cells during HTNV infection, and suggested a potential anti-viral role of MAIT cells in HFRS.

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study.

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.

Potential clinical biomarkers in monitoring the severity of Hantaan virus infection.

Hantavirus, which causes hemorrhagic fever with renal syndrome (HFRS) is almost prevalent worldwide. While Hantaan virus (HTNV) causes the most severe form of HFRS with typical clinical manifestations of thrombocytopenia, increased vascular permeability, and acute kidney injury. Although the knowledge of the pathogenesis of HFRS is still limited, immune dysfunction and pathological damage caused by disorders of immune regulation are proposed to play a vital role in the development of the disorder, and the endothelium is considered to be the primary target of hantaviruses. Here, we reviewed the production and function of multiple molecules, mainly focusing on their role in immune response, endothelium, vascular permeability regulation, and platelet and coagulation activation which are closely related to the pathogenesis of HTNV infection. meanwhile, the relationship between these molecules and characteristics of HTNV infection including the hospital duration, immune dysfunction, thrombocytopenia, leukocytosis, and acute kidney injury are also presented, to provide a novel insight into the potential role of these molecules as monitoring markers for HTNV infection.

Hospital Frailty Risk Score (HFRS) Predicts Adverse Outcomes Among Hospitalized Patients with Chronic Pancreatitis.

INTRODUCTION: The prevalence of frailty among patients with chronic pancreatitis (CP) and its impact on clinical outcomes is unclear. We report the impact of frailty on mortality, readmission rates, and healthcare utilization among patients with chronic pancreatitis in the United States. METHODS: We extracted data on patients hospitalized with a primary or secondary diagnosis of CP from the Nationwide Readmissions Database 2019. We applied a previously validated hospital frailty risk scoring system to classify CP patients into frail and non-frail on index hospitalization and compared the characteristics of frail and non-frail patients. We studied the impact of frailty on mortality, readmission, and healthcare utilization. RESULTS: Of 56,072 patients with CP, 40.78% of patients were classified as frail. Frail patients experienced a higher rate of unplanned and preventable hospitalizations. Almost two-thirds of frail patients were younger than 65, and one-third had no or only single comorbidity. On multivariate analysis, frailty was independently associated with two times higher mortality risk (adjusted hazard ratio [aHR], 2.05; 95% CI 1.7-2.5). Frailty was also associated with a higher risk of all-cause readmission with an aHR of 1.07; (95% CI 1.03-1.1). Frail patients experienced a longer length of stay, higher hospitalization costs, and hospitalization charges. Infectious causes were the most common cause of readmission among frail patients compared to acute pancreatitis among non-frail patients. CONCLUSIONS: Frailty is independently associated with higher mortality, readmission rates, and healthcare utilization among patients with chronic pancreatitis in the US.

Validation of Frail Scale and comparison with hospital frailty risk score to predict hospital use in a cohort of older Australian women.

INTRODUCTION: With no standard frailty tool for clinical care, research and policymaking, identifying frail older people is a challenge. AIMS: This study aimed to compare two validated scales, which are the Frail Scale and Hospital Frailty Risk Score (HFRS) for their ability in identifying frailty in older Australian women and predicting hospital use. METHODS: This study included older Australian women aged 75-95 years, who had unplanned overnight hospital admission as an index admission between 2001 and 2016. Data from the Australian Longitudinal Study on Women's Health (ALSWH) were linked with administrative hospital data to calculate HFRS (using the International Statistical Classification of Diseases, Australia Modification (ICD-10-AM) diagnostic codes) and the Frail Scale (using the ALSWH self-reported survey). RESULTS: The Frail Scale identified a higher proportion of older frail women (30.54%) compared to the HFRS (23.0%). Frail older women, classified by Frail Scale, were at higher risk of long hospital stay (adjusted odds ratio = 1.28, 95% CI = 1.02-1.60), repeated admission (adjusted hazard ratio [AHR] = 1.30, 95% CI = 1.03-1.41) and death (AHR = 1.70, 95% CI = 1.45-2.01). HFRS was associated with longer hospital stay and mortality. CONCLUSIONS: The proportion of older women classified as frail by the Frail Scale tool was higher than women classified as frail by HFRS. The Frail Scale and HFRS were not significantly associated with each other. While both tools were associated with the risk of long hospital stay and mortality, only the Frail Scale predicted the risk of repeated admission.

Puumala Orthohantavirus Reassortant Genome Variants Likely Emerging in the Watershed Forests.

Hemorrhagic fever with renal syndrome (HFRS) remains a prevalent zoonosis in the Republic of Tatarstan (RT), Russian Federation. Puumala orthohantavirus (PUUV), carried by bank voles (Myodes glareolus), is the principal zoonotic pathogen of HFRS in the RT. In this study, we sought to demonstrate the similarity of the PUUV genetic sequences detected in HFRS case patients and bank vole samples previously collected in some areas of the RT. Furthermore, we intended to identify the reassortant PUUV genomes and locate a potential site for their emergence. During 2019 outbreaks, the PUUV genome sequences of the S and M segments from 42 HFRS cases were analysed and compared with the corresponding sequences from bank voles previously trapped in the RT. Most of the PUUV strains from HFRS patients turned out to be closely related to those isolated from bank voles captured near the site of the human infection. We also found possible reassortant PUUV genomes in five patients while they were absent in bank voles. The location of the corresponding HFRS infection sites suggests that reassortant PUUV genomes could emerge in the bank voles that inhabit the forests on the watershed between the Kazanka River and Myosha River. These findings could facilitate the search for the naturally occurring reassortants of PUUV in bank vole populations.

Comparison of the predictive ability of clinical frailty scale and hospital frailty risk score to determine long-term survival in critically ill patients: a multicentre retrospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is the most commonly used frailty measure in intensive care unit (ICU) patients. The hospital frailty risk score (HFRS) was recently proposed for the quantification of frailty. We aimed to compare the HFRS with the CFS in critically ill patients in predicting long-term survival up to one year following ICU admission. METHODS: In this retrospective multicentre cohort study from 16 public ICUs in the state of Victoria, Australia between 1st January 2017 and 30th June 2018, ICU admission episodes listed in the Australian and New Zealand Intensive Care Society Adult Patient Database registry with a documented CFS, which had been linked with the Victorian Admitted Episode Dataset and the Victorian Death Index were examined. The HFRS was calculated for each patient using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes that represented pre-existing conditions at the time of index hospital admission. Descriptive methods, Cox proportional hazards and area under the receiver operating characteristic (AUROC) were used to investigate the association between each frailty score and long-term survival up to 1 year, after adjusting for confounders including sex and baseline severity of illness on admission to ICU (Australia New Zealand risk-of-death, ANZROD). RESULTS: 7001 ICU patients with both frailty measures were analysed. The overall median (IQR) age was 63.7 (49.1-74.0) years; 59.5% (n = 4166) were male; the median (IQR) APACHE II score 14 (10-20). Almost half (46.7%, n = 3266) were mechanically ventilated. The hospital mortality was 9.5% (n = 642) and 1-year mortality was 14.4% (n = 1005). HFRS correlated weakly with CFS (Spearman's rho 0.13 (95% CI 0.10-0.15) and had a poor agreement (kappa = 0.12, 95% CI 0.10-0.15). Both frailty measures predicted 1-year survival after adjusting for confounders, CFS (HR 1.26, 95% CI 1.21-1.31) and HFRS (HR 1.08, 95% CI 1.02-1.15). The CFS had better discrimination of 1-year mortality than HFRS (AUROC 0.66 vs 0.63 p < 0.0001). CONCLUSION: Both HFRS and CFS independently predicted up to 1-year survival following an ICU admission with moderate discrimination. The CFS was a better predictor of 1-year survival than the HFRS.

Hospital frailty risk score predicts adverse events in spine surgery.

PURPOSE: The Hospital Frailty Risk Score (HFRS) is derived from routinely collected data and validated as a geriatric risk stratification tool. This study aimed to evaluate the utility of the HFRS as a predictor for postoperative adverse events in spine surgery. METHODS: In this retrospective analysis of 2042 patients undergoing spine surgery at a university spine center between 2011 and 2019, HFRS was calculated for each patient. Multivariable logistic regression models were used to assess the relationship between the HFRS and postoperative adverse events. Adverse events were compared between patients with high or low frailty risk. RESULTS: Patients with intermediate or high frailty risk showed a higher rate of reoperation (19.7% vs. 12.2%, p < 0.01), surgical site infection (3.4% vs. 0.4%, p < 0.001), internal complications (4.1% vs. 1.1%, p < 0.01), Clavien-Dindo IV complications (8.8% vs. 3.4%, p < 0.001) and transfusion (10.9% vs. 1.5%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for reoperation [odds ratio (OR) = 1.1; 95% confidence interval (CI) 1.0-1.2], transfusion (OR = 1.3; 95% CI 1.2-1.4), internal complications (OR = 1.2; 95% CI 1.1-1.3), surgical site infections (OR = 1.3; 95% CI 1.2-1.5) and other complications (OR = 1.3; 95% CI 1.2-1.4). CONCLUSION: The HFRS can predict adverse events and is an easy instrument, fed from routine hospital data. By identifying risk patients at an early stage, the individual patient risk could be minimized, which leads to less complications and lower costs. LEVEL OF EVIDENCE: Level III - retrospective cohort study TRIAL REGISTRATION: The study was approved by the local ethics committee (20-1821-104) of the University of Regensburg in February 2020.

Epidemiology, virology and clinical aspects of hantavirus infections: an overview.

At the end of 2019 and 2020s, a wave of coronavirus disease 19 (COVID-19) epidemics worldwide has catalyzed a new era of 'communicable infectious diseases'. However, the world is not currently prepared to deal with the growing burden of COVID-19, with the unexpected arrival of Hantavirus infection heading to the next several healthcare emergencies in public. Hantavirus is a significant class of zoonotic pathogens of negative-sense single-stranded ribonucleic acid (RNA). Hemorrhagic renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) are the two major clinical manifestations. Till date, there is no effective treatments or vaccines available, public awareness and precautionary measures can help to reduce the spread of hantavirus disease. In this study, we outline the epidemiology, virology, clinical aspects, and existing HFRS and HCPS management approaches. This review will give an understanding of virus-host interactions and will help for the early preparation and effective handling of further outbreaks in an ever-changing environment.

New class of hantaan virus inhibitors based on conjugation of the isoindole fragment to (+)-camphor or (-)-fenchone hydrazonesv.

This work presents the design and synthesis of camphor, fenchone, and norcamphor N-acylhydrazone derivatives as a new class of inhibitors of the Hantaan virus, which causes haemorrhagic fever with renal syndrome (HFRS). A cytopathic model was developed for testing chemotherapeutics against the Hantaan virus, strain 76-118. In addition, a study of the antiviral activity was carried out using a pseudoviral system. It was found that the hit compound possesses significant activity (IC50 = 7.6 ± 2 µM) along with low toxicity (CC50 > 1000 µM). Using molecular docking procedures, the binding with Hantavirus nucleoprotein was evaluated and the correlation between the structure of the synthesised compounds and the antiviral activity was established.

Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is still attracting public attention because of its outbreak in various cities in China. Predicting future outbreaks or epidemics disease based on past incidence data can help health departments take targeted measures to prevent diseases in advance. In this study, we propose a multistep prediction strategy based on extreme gradient boosting (XGBoost) for HFRS as an extension of the one-step prediction model. Moreover, the fitting and prediction accuracy of the XGBoost model will be compared with the autoregressive integrated moving average (ARIMA) model by different evaluation indicators. METHODS: We collected HFRS incidence data from 2004 to 2018 of mainland China. The data from 2004 to 2017 were divided into training sets to establish the seasonal ARIMA model and XGBoost model, while the 2018 data were used to test the prediction performance. In the multistep XGBoost forecasting model, one-hot encoding was used to handle seasonal features. Furthermore, a series of evaluation indices were performed to evaluate the accuracy of the multistep forecast XGBoost model. RESULTS: There were 200,237 HFRS cases in China from 2004 to 2018. A long-term downward trend and bimodal seasonality were identified in the original time series. According to the minimum corrected akaike information criterion (CAIC) value, the optimal ARIMA (3, 1, 0) × (1, 1, 0)12 model is selected. The index ME, RMSE, MAE, MPE, MAPE, and MASE indices of the XGBoost model were higher than those of the ARIMA model in the fitting part, whereas the RMSE of the XGBoost model was lower. The prediction performance evaluation indicators (MAE, MPE, MAPE, RMSE and MASE) of the one-step prediction and multistep prediction XGBoost model were all notably lower than those of the ARIMA model. CONCLUSIONS: The multistep XGBoost prediction model showed a much better prediction accuracy and model stability than the multistep ARIMA prediction model. The XGBoost model performed better in predicting complicated and nonlinear data like HFRS. Additionally, Multistep prediction models are more practical than one-step prediction models in forecasting infectious diseases.

Interlaboratory comparison investigations (ICIs) and external quality assurance schemes (EQUASs) for flame retardant analysis in biological matrices: Results from the HBM4EU project.

The European Human Biomonitoring Initiative (HBM4EU) is coordinating and advancing human biomonitoring (HBM). For this purpose, a network of laboratories delivering reliable analytical data on human exposure is fundamental. The analytical comparability and accuracy of laboratories analysing flame retardants (FRs) in serum and urine were investigated by a quality assurance/quality control (QA/QC) scheme comprising interlaboratory comparison investigations (ICIs) and external quality assurance schemes (EQUASs). This paper presents the evaluation process and discusses the results of four ICI/EQUAS rounds performed from 2018 to 2020 for the determination of ten halogenated flame retardants (HFRs) represented by three congeners of polybrominated diphenyl ethers (BDE-47, BDE-153 and BDE-209), two isomers of hexabromocyclododecane (α-HBCD and γ-HBCD), two dechloranes (anti-DP and syn-DP), tetrabromobisphenol A (TBBPA), decabromodiphenylethane (DBDPE), and 2,4,6-tribromophenol (2,4,6-TBP) in serum, and four metabolites of organophosphorus flame retardants (OPFRs) in urine, at two concentration levels. The number of satisfactory results reported by laboratories increased during the four rounds. In the case of HFRs, the scope of the participating laboratories varied substantially (from two to ten) and in most cases did not cover the entire target spectrum of chemicals. The highest participation rate was reached for BDE-47 and BDE-153. The majority of participants achieved more than 70% satisfactory results for these two compounds over all rounds. For other HFRs, the percentage of successful laboratories varied from 44 to 100%. The evaluation of TBBPA, DBDPE, and 2,4,6-TBP was not possible because the number of participating laboratories was too small. Only seven laboratories participated in the ICI/EQUAS scheme for OPFR metabolites and five of them were successful for at least two biomarkers. Nevertheless, the evaluation of laboratory performance using Z-scores in the first three rounds required an alternative approach compared to HFRs because of the small number of participants and the high variability of experts' results. The obtained results within the ICI/EQUAS programme showed a significant core network of comparable European laboratories for HBM of BDE-47, BDE-153, BDE-209, α-HBCD, γ-HBCD, anti-DP, and syn-DP. On the other hand, the data revealed a critically low analytical capacity in Europe for HBM of TBBPA, DBDPE, and 2,4,6-TBP as well as for the OPFR biomarkers.

Frailty status, timely goals of care documentation and clinical outcomes in older hospitalised medical patients.

BACKGROUND: Hospitalised frail older patients are at risk of clinical deterioration. Early goals of care (GOC) documentation is vital to avoid futile/unwarranted interventions in the event of deterioration. AIMS: To investigate the impact of frailty on timely GOC and its association with clinical outcomes in hospitalised older patients. METHODS: This was a single-centre retrospective study of all medical patients aged ≥80 years admitted to the acute medical unit between 1/3/2015 and 31/8/2015, with GOC derived from electronic records. Frailty was measured using the Hospital Frailty Risk Score (HFRS) derived from hospital coding data. Primary outcome compared proportions of timely GOC within 72-h between frail (HFRS ≥ 5) and non-frail (HFRS < 5) patients. Exploratory secondary outcomes included in-hospital mortality, rapid response calls (RRC), prolonged length of stay (LOS) and 28-day readmission rates. RESULTS: Of the 1118 admitted patients, 529 (47.3%) were frail. Timely GOC occurred in 50% (559/1118), more commonly in frail patients (283/529, 53.5%) than non-frail patients (276/589, 46.9%), P = 0.027. Frailty was positively associated with timely GOC independent of age and gender (odds ratio = 1.28; 95% confidence interval = 1.01-163; P = 0.041). In univariable analyses, timely GOC was associated with greater in-hospital mortality, RRC, and hospital LOS in both frail and non-frail patients (all P < 0.05) and greater 28-day readmissions only among frail patients (P = 0.028). Multivariable regression demonstrated that timely GOC was associated only with in-hospital mortality in both frail and non-frail patients, independent of age and gender. CONCLUSION: Older frail hospitalised patients were more likely to have timely GOC than older non-frail patients. Timely GOC in such patients may avoid burdensome treatments.

Hospital Frailty Risk Score Outperforms Current Risk Stratification Models in Primary Total Hip and Knee Arthroplasty.

BACKGROUND: Models for risk stratification and prediction of outcome, such as the Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Method (ECM), the 5-factor modified Frailty Index (mFI-5), and the Hospital Frailty Risk Score (HFRS) have been validated in orthopedic surgery. The aim of this study is to compare the predictive power of these models in total hip and knee replacement. METHODS: In a retrospective analysis of 8250 patients who had undergone total joint replacement between 2011 and 2019, CCI, ECM, mFI-5, and HFRS were calculated for each patient. Receiver operating characteristic curve plots were generated and the area under the curve (AUC) was compared between each score with regard to adverse events such as transfusion, surgical, medical, and other complications. Multivariate logistic regression models were used to assess the relationship among risk stratification models, demographic factors, and postoperative adverse events. RESULTS: In prediction of surgical complications, HFRS performed best (AUC: 0.719, P < .001), followed by ECM (AUC: 0.578, P < .001), mFI-5 (AUC: 0.564, P = .003), and CCI (AUC: 0.555, P = .012). With regard to medical complications, other complications, and transfusion, HFRS also was superior to ECM, mFI-5, and CCI. Multivariate logistic regression analyses revealed HFRS as an independent risk stratification model associated with all captured adverse events (P ≤ .001). CONCLUSION: The HFRS is superior to current risk stratification models in the context of total joint replacement. As the HRFS derives from routinely collected administrative data, healthcare providers can identify at-risk patients without additional effort or expense.

Hospital Frailty Risk Score predicts adverse events in revision total hip and knee arthroplasty.

INTRODUCTION: The Hospital Frailty Risk Score (HFRS) is a validated risk stratification model referring to the cumulative deficits model of frailty. The purpose of this study was to evaluate the HFRS as a predictor of 90-day readmission and complications after revision total hip (rTHA) and knee (rTKA) arthroplasty. METHODS: In a retrospective analysis of 565 patients who had undergone rTHA or rTKA between 2011 and 2019, the HFRS was calculated for each patient. Rates of adverse events were compared between patients with low and intermediate or high frailty risk. Multivariable logistic regression models were used to assess the relationship between the HFRS and post-operative adverse events. RESULTS: Patients with intermediate or high frailty risk showed higher rates of readmission (30days: 23.8% vs. 9.9%, p = 0.006; 90days: 26.2% vs. 13.0%, p < 0.018), surgical complications (28.6% vs. 7.8%, p < 0.001), medical complications (11.9% vs. 1.0%, p < 0.001), other complications (28.6% vs. 2.3%, p < 0.001), Clavien-Dindo grade IV complications (14.3% vs. 4.8%, p = 0.009), and transfusion (33.3% vs. 6.1%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for surgical complications (OR = 3.45, 95% CI 1.45-8.18, p = 0.005), medical complications (OR = 7.29, 95% CI 1.72-30.97, p = 0.007), and other complications (OR = 14.15, 95% CI 5.16-38.77, p < 0.001). CONCLUSION: The HFRS predicts adverse events after rTHA and rTKA. As it derives from routinely collected data, the HFRS could be implemented automated in hospital information systems to facilitate identification of at-risk patients.

[The potential role of mirnas in the pathogenesis of hemorrhagic fever with renal syndrome].

Hemorrhagic fever with renal syndrome (HFRS) is an acute natural focal viral disease caused by viruses of the genus hantavirus, characterized by damage to small blood vessels, kidneys, lungs and other organs of a person. MicroRNAs (miRNAs) are 18-22 nucleotide endogenously expressed RNA molecules that inhibit gene expression at the post-transcriptional level by binding to the 3-untranslated region of the target mRNA. It has been proven that miRNAs play a significant role in various biological processes, including the cell cycle, apoptosis, cell proliferation and differentiation. It has been proven that miRNAs may be involved in the pathogenesis of infectious diseases, including HFRS. Hantavirus infection predominantly affects endothelial cells and causes dysfunction of the endothelium of capillaries and small vessels. It is known that the immune response induced by Hantavirus infection plays an important role in disrupting the endothelial barrier. In a few studies, both in vitro and in vivo, it has been shown that endothelial dysfunction and the immune response after infection with Hantavirus can be partially regulated by miRNAs by acting on certain genes. Most of the miRNAs is expressed within the cells themselves. However, in some biological fluids of the human body, for example, plasma or blood serum, numerous miRNAs, called circulating miRNAs, have been found. Circulating miRNAs can be secreted by cells into human biological fluids as part of extracellular vesicles as exosomes or be part of an RNA-bound protein complex as miRNA-Argonaute 2 (Ago2). These miRNAs are resistant to nucleases, which makes them attractive as potential biomarkers in various human diseases. There is no specific antiviral therapy for HFRS, and the determination of laboratory parameters that are used to diagnose, assess the severity, and predict the course of the disease remains a challenge due to the peculiarities of the pathophysiology and clinical course of the disease. Studying the role of miRNAs in HFRS seems to be expedient for the development of specific and effective therapy, as well as for use as diagnostic and prognostic biomarkers (in relation to circulating miRNAs).

A case-control study on the risk factors for hemorrhagic fever with renal syndrome.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is an endemic communicable disease in China, accounting for 90% of total reported cases worldwide. In this study, the authors want to investigate the risk factors for HFRS in recent years to provide the prevention and control advices. METHODS: A community-based, 1:2 matched case-control study was carried out to investigate the risk factors for HFRS. Cases were defined as laboratory-confirmed cases that tested positive for hantavirus-specific IgM antibodies. Two neighbourhood controls of each case were selected by sex, age and occupation. Standardized questionnaires were used to collect information and identify the risk factors for HFRS. RESULTS: Eighty-six matched pairs were investigated in the study. The median age of the cases was 55.0 years, 72.09% were male, and 73.26% were farmers. In the multivariate logistic regression analysis, cleaning spare room at home (OR = 3.310, 95%CI 1.335-8.210) was found to be risk factor for infection; storing food and crops properly (OR = 0.279 95%CI 0.097-0.804) provided protection from infection. CONCLUSION: Storing food and crops properly seemed to be protective factor, which was important for HFRS prevention and control. More attention should be paid to promote comprehensive health education and behaviour change among high-risk populations in the HFRS endemic area.

Investigation on risk factors of haemorrhagic fever with renal syndrome (HFRS) in Xuancheng City in Anhui Province, Mainland China.

Haemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a major public health concern in both developed and developing countries. China is the most severe endemic country in the world, constituting 90% of the cases. Although the incidence of HFRS has substantively decreased in most areas of China, HFRS has rebounded remarkably in some epidemic areas. Xuancheng is one of these areas. In this study, we collected the case data reported recently in Xuancheng and designed a 1:3 case-control study. The Chi-square test, univariate and multivariate logistic regression analysis were performed. In all cases, farmers made up the highest proportion of occupations. And there were 20 variables with statistical significance including indoor hygienic conditions; the surrounding environment; whether bitten by rats at work and other criteria. In addition, exposure to rodents and rats bites is a high-risk factor for HFRS. Rodent density was calculated at 20.9% (159/760), the virus carrier rate was 9.4% (15/159) and the index of rats with a virus was about 2.0%. Exposure to rodents and insect bites is also high-risk factors for HFRS among local residents in Xuancheng. More importantly, during the flood years, the increased density of rodents led to an increased risk of human exposure to rodents. As our statistical analysis proves, targeted strategies should be developed and implemented to reduce the incidence of local diseases in the future.

Hospital Frailty Risk Score Predicts Adverse Events in Primary Total Hip and Knee Arthroplasty.

BACKGROUND: The Hospital Frailty Risk Score (HFRS) is a validated geriatric comorbidity measure derived from routinely collected administrative data. The purpose of this study is to evaluate the utility of the HFRS as a predictor for postoperative adverse events after primary total hip (THA) and knee (TKA) arthroplasty. METHODS: In a retrospective analysis of 8250 patients who had undergone THA or TKA between 2011 and 2019, the HFRS was calculated for each patient. Reoperation rates, readmission rates, complication rates, and transfusion rates were compared between patients with low and intermediate or high frailty risk. Multivariate logistic regression models were used to assess the relationship between the HFRS and postoperative adverse events. RESULTS: Patients with intermediate or high frailty risk showed a higher rate of reoperation (10.6% vs 4.1%, P < .001), readmission (9.6% vs 4.3%, P < .001), surgical complications (9.1% vs 1.8%, P < .001), internal complications (7.3% vs 1.1%, P < .001), other complications (24.4% vs 2.0%, P < .001), Clavien-Dindo grade IV complications (4.1% vs 1.5%, P < .001), and transfusion (10.4% vs 1.3%, P < .001). Multivariate logistic regression analyses revealed a high HFRS as independent risk factor for reoperation (odds ratio [OR] = 2.1; 95% confidence interval [CI], 1.46-3.09; P < .001), readmission (OR = 1.78; 95% CI, 1.21-2.61; P = .003), internal complications (OR = 3.72; 95% CI, 2.28-6.08; P < .001), surgical complications (OR = 3.74; 95% CI, 2.41-5.82; P < .001), and other complications (OR = 9.00; 95% CI, 6.58-12.32; P < .001). CONCLUSION: The HFRS predicts adverse events after THA and TKA. As it derives from routinely collected data, the HFRS enables hospitals to identify at-risk patients without extra effort or expense. LEVEL OF EVIDENCE: Level III-retrospective cohort study.