bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multicenter, phase 1 study of etavopivat (FT-4202) treatment for up to 12 weeks in patients with sickle cell disease
Authors: Saraf Santosh L. , Hagar Robert , Idowu Modupe , Osunkwo Ifeyinwa , Cruz Kimberly , Kuypers Frans A. , Brown R. Clark , Geib James , Ribadeneira Maria , Schroeder Patricia , Wu Eric , Forsyth Sanjeev , Kelly Patrick F. , Kalfa Theodosia A. , Telen Marilyn J. 
Published: April 2024

Abstract
Etavopivat is an investigational, once daily, oral, selective erythrocyte pyruvate kinase (PKR) activator. A multicenter, randomized, placebo-controlled, double-blind, 3-part, phase 1 study was conducted to characterize the safety and clinical activity of etavopivat. Thirty-six patients with sickle cell disease (SCD) were enrolled into 4 cohorts: 1 single-dose, 2 multiple ascending doses, and 1 open-label (OL). In the OL cohort, 15 patients (median age 33.0 years [range, 17-55]) received 400 mg etavopivat once daily for 12 weeks; 14 patients completed treatment. Consistent with the mechanism of PKR activation, increases in adenosine triphosphate and decreases in 2,3-diphosphoglycerate were observed and sustained over 12 weeks’ treatment. This translated clinically to an increase in hemoglobin (Hb; mean maximal increase 1.6 g/dL [range, 0.8-2.8]), with &gt;1 g/dL increase in 11 (73%) patients during treatment. In addition, the oxygen tension at which Hb is 50% saturated was reduced (P = .0007) with a concomitant shift in point of sickling (P = .0034) to lower oxygen tension in oxygen-gradient ektacytometry. Hemolysis markers (absolute reticulocyte count, indirect bilirubin, and lactate dehydrogenase) decreased from baseline, along with matrix metalloproteinase-9 and erythropoietin. In the OL cohort, adverse events (AEs) were mostly grade 1/2, consistent with underlying SCD; 5 patients had serious AEs. Vaso-occlusive pain episode was the most common treatment-emergent AE (n = 7) in the OL cohort. In this, to our knowledge, the first study of etavopivat in SCD, 400 mg once daily for 12 weeks was well tolerated, resulting in rapid and sustained increases in Hb, improved red blood cell physiology, and decreased hemolysis. This trial was registered at www.ClinicalTrials.gov as #NCT03815695.
A 69 long noncoding RNA signature predicts relapse and acts as independent prognostic factor in pediatric AML
Authors: Ren Zhiyao , Vanhooren Jolien , Derpoorter Charlotte , De Moerloose Barbara , Lammens Tim 
Published: April 2024

Abstract
Risk stratification using genetics and minimal residual disease has allowed for an increase in the cure rates of pediatric acute myeloid leukemia (pedAML) to up to 70% in contemporary protocols. Nevertheless, ∼30% of patients still experience relapse, indicating a need to optimize stratification strategies. Recently, long noncoding RNA (lncRNA) expression has been shown to hold prognostic power in multiple cancer types. Here, we aimed at refining relapse prediction in pedAML using lncRNA expression. We built a relapse–related lncRNA prognostic signature, named AMLlnc69, using 871 transcriptomes of patients with pedAML obtained from the Therapeutically Applicable Research to Generate Effective Treatments repository. We identified a 69 lncRNA signature AMLlnc69 that is highly predictive of relapse risk (c-index = 0.73), with area under the receiver operating characteristic curve (AUC) values for predicting the 1-, 2-, and 3-year relapse-free survival (RFS) of 0.78, 0.77, and 0.77, respectively. The internal validation using a bootstrap method (resampling times = 1000) resulted in a c-index of 0.72 and AUC values for predicting the 1-, 2-, and 3-year RFS of 0.77, 0.76, and 0.76, respectively. Through a Cox regression analysis, AMLlnc69, nucleophosmin mutation, and white blood cell at diagnosis were identified as independent predictors of RFS. Finally, a nomogram was build using these 2 parameters, showing a c-index of 0.80 and 0.71 after bootstrapping (n = 1000). In conclusion, the identified AMLlnc69 will, after prospective validation, add important information to guide the management of patients with pedAML. The nomogram is a promising tool for easy stratification of patients into a novel scheme of relapse-risk groups.
Diagnostic value of the pepsin concentration in saliva and induced sputum for gastroesophageal reflux-induced chronic cough: a prospective clinical study
Authors: Gu Wenhua , Chen Wei , Zhang Tongyangzi , Zhu Yiqing , Li Wanzhen , Shi Wenbo , Li Na , Wang Shengyuan , Xu Xianghuai , Yu Li 
Published: April 2024

BackgroundFinding a simple, effective and rapid diagnostic method to improve the diagnosis of gastroesophageal reflux-induced chronic cough (GERC) is indicated. Our objective was to determine the diagnostic value of the pepsin concentration in saliva and induced sputum for GERC.Methods171 patients with chronic cough were enrolled. The diagnosis and treatment followed the chronic cough diagnosis and treatment protocol. Saliva and induced sputum were collected, and the pepsin concentration was determined using Peptest. A Gastroesophageal Reflux Diagnostic Questionnaire (GerdQ) was completed. The diagnostic value of the pepsin concentration in saliva and induced sputum for GERC was analysed and compared.ResultsThe salivary pepsin concentration predicted GERC with an area under the receiver operating characteristic curve (AUC) of 0.845. The optimal cut-off value was 76.10 ng·mL−1, the sensitivity was 83.58% and the specificity was 82.69%. The pepsin concentration in the induced sputum supernatant for GERC had an AUC of 0.523. When GerdQ was used for GERC diagnosis, the AUC was 0.670 and the diagnostic value of salivary pepsin was better compared to GerdQ (DeLong test, p=0.0008). Salivary pepsin had a comparable diagnostic value to GerdQ (AUC 0.779versus0.826; p=0.4199) in acidic GERC. Salivary pepsin had superior diagnostic value compared to GerdQ (AUC 0.830versus0.533; p<0.0001) in non-acidic GERC.ConclusionsA salivary pepsin concentration >76.10 ng·mL−1is of good diagnostic value for GERC, especially in non-acidic GERC. The pepsin concentration in induced sputum has a low diagnostic value.
Epidemiology of patients with severe asthma in Japan: a nationwide descriptive study
Authors: Kimura Yuya , Suzukawa Maho , Jo Taisuke , Hashimoto Yohei , Kumazawa Ryosuke , Ishimaru Miho , Matsui Hiroki , Yokoyama Akira , Tanaka Goh , Yasunaga Hideo 
Published: April 2024

BackgroundThe 2014 European Respiratory Society/American Thoracic Society guidelines defined severe asthma based on treatment intensity and estimated the proportion of severe asthma among all asthma cases to be 5–10%. However, data supporting the estimate and comprehensive and sequential data on asthma cases are scarce. We aimed to estimate the national prevalence and proportion of severe asthma during the last decade.MethodsUsing a Japanese national administrative database, which covers ≥99% of the population, we evaluated the prevalence and proportion of severe asthma in 2013, 2015, 2017 and 2019. Additionally, we elucidated the demographic characteristics, treatments and outcomes of patients with asthma.ResultsThe national prevalence of mild–moderate and severe asthma in 2019 was 800 and 36 per 100 000 persons, respectively. While the prevalence of mild–moderate asthma remained almost constant in the study years, the prevalence of severe asthma decreased, resulting in a reduction in the proportion of severe asthma from 5.6% to 4.3%. Although treatment modalities have evolved, such as the increased use of combination inhalers and asthma biologics, approximately 15% of mild–moderate and 45% of severe asthma cases were still considered “uncontrolled”. The number of deaths from asthma decreased in patients with both mild–moderate and severe asthma.ConclusionsThis study revealed that the prevalence of severe asthma in Japan decreased during the study period and fell below 5% in the most recent data. Despite treatment evolution, a substantial proportion of patients with both mild–moderate and severe asthma still have poor asthma control.
Longitudinal change in ultrasound-derived rectus femoris cross-sectional area in COPD
Authors: Jenkins Timothy O. , Patel Suhani , Edwards George D. , Nolan Claire M. , Canavan Jane , Kon Samantha , Jones Sarah , Barker Ruth E. , Littlemore Hannah , Maddocks Matthew , Man William D-C. 
Published: April 2024

BackgroundSkeletal muscle dysfunction is common in COPD. Ultrasound-derived rectus femoris cross-sectional area (RFCSA) is a radiation free, non-invasive measure of muscle bulk that relates to quadriceps strength in people with COPD. However, there are limited longitudinal data for RFCSA, and it is not known whether longitudinal change in RFCSA reflects change in quadricep strength, exercise capacity, lower limb function or muscle mass. We aimed to quantify longitudinal change in ultrasound-derived RFCSA and assess its relationship with change in quadriceps maximal voluntary contraction (QMVC), incremental shuttle walk test (ISWT), five-repetition sit-to-stand (5STS) and fat-free mass (FFM) over 12 months in people with COPD.MethodsWe measured ultrasound-derived RFCSA, QMVC, ISWT, 5STS and FFM (measured by bioelectric impedance analysis) at baseline and 12 months in 169 people with stable COPD. Change was correlated using Pearson's or Spearman's coefficients.ResultsBaseline characteristics: mean±sdage 70.4±9.4 years; FEV153.3±18.9% predicted. Over the course of 12 months mean RFCSA change was −33.7 mm2(99% CI −62.6– −4.9 mm2; p=0.003) representing a mean±sdpercentage change of −1.8±33.5%. There was a weak correlation between change in RFCSA and FFM (r=0.205, p=0.009), but not with change in QMVC, ISWT or 5STS.ConclusionThere is a statistically significant decrease in ultrasound-derived RFCSA over 12 months in people with stable COPD, but this decrease does not correlate with change in quadriceps strength, exercise capacity, FFM or lower limb function.
Prognostic role of haemodynamics at follow-up in patients with pulmonary arterial hypertension: a challenge to current European Society of Cardiology/European Respiratory Society risk tools
Authors: Dardi Fabio , Guarino Daniele , Ballerini Alberto , Bertozzi Riccardo , Donato Federico , Cennerazzo Francesco , Salvi Monica , Nardi Elena , Magnani Ilenia , Manes Alessandra , Galiè Nazzareno , Palazzini Massimiliano 
Published: April 2024

BackgroundHaemodynamic variables like right atrial pressure (RAP), cardiac index (CI), stroke volume index (SVI) and mixed venous oxygen saturation (SvO2) predict survival in patients with pulmonary arterial hypertension (PAH). However, there is the need to identify further prognostic haemodynamic parameters as well as to redefine their role in PAH risk stratification compared to current risk tools and non-invasive parameters.MethodsThis cohort study includes treatment-naïve patients assessed at baseline and after first-line PAH therapy with clinical, functional, exercise, laboratory and haemodynamic evaluations. Using a stepwise multivariate Cox regression analysis, independent prognostic haemodynamic parameters were identified and stratified according to cut-offs already defined in the European Society of Cardiology (ESC)/European Respiratory Society (ERS) risk table or defined based on the highest Chi-squared of the log-rank test. Their discriminatory power was tested for all-cause death and a combined end-point of death, hospitalisation and need of treatment escalation.Results794 patients with PAH were enrolled. At first follow-up, RAP and pulmonary artery elastance were independently associated with death. Because of high correlations between haemodynamic parameters, different multivariable analyses were done identifying six other variables (pulmonary arterial compliance, cardiac efficiency, pulmonary vascular resistance,SvO2, CI and SVI). Haemodynamic parameters were of no added prognostic value compared to ESC/ERS risk tools for the all-cause death end-point but they showed additional value to non-invasive parameters for the combined end-point and, when taken alone, had a discriminatory capacity comparable to ESC/ERS risk tools.ConclusionHaemodynamics’ discriminative ability for clinical worsening is comparable to current ESC/ERS risk tools and is of added value to non-invasive parameters.
Patients at risk of nontuberculous mycobacterial pulmonary disease who need testing evaluated using a modified Delphi process by European experts
Authors: Loebinger Michael R. , Aliberti Stefano , Haworth Charles , Jankovic Makek Mateja , Lange Christoph , Lorent Natalie , Papavasileiou Apostolos , Polverino Eva , Rohde Gernot , Veziris Nicolas , Wagner Dirk , van Ingen Jakko 
Published: April 2024

BackgroundIdentifying patients at risk of nontuberculous mycobacterial pulmonary disease (NTM-PD) is challenging. Delays in NTM-PD identification and management are associated with declining lung function and increased morbidity and mortality.Study design and methodsEuropean NTM-PD experts (n=12) participated in a three-round modified Delphi process to score symptoms and comorbidities potentially associated with NTM-PD as reasons to test for nontuberculous mycobacteria.ResultsExperts reached a consensus on the symptoms and comorbidities that should and should not prompt testing for nontuberculous mycobacteria. Requirements for testing were scored as high (mean ≥7), medium (mean ≥4–<7) or low (mean <4). Nontuberculous mycobacteria testing should be undertaken when multiple suggestive symptoms are present simultaneously in all patients except those with cancer (7.3–8.8), or when radiology is indicative of NTM-PD (≥8.9). Symptoms of persistent sputum production, recurrent respiratory infection and haemoptysis should prompt testing for nontuberculous mycobacteria, particularly in those with underlying respiratory diseases. Symptomatic patients with bronchiectasis or previous tuberculosis/NTM-PD or those being prescribed or undergoing long-term macrolide therapy for a respiratory condition should also be tested. Testing is not warranted in patients without an underlying respiratory disorder or in those without a history of respiratory disorders unless presenting with multiple symptoms.ConclusionsAssessing patients’ risk of NTM-PD is challenging. This Delphi consensus process provides insight into symptoms and clinical characteristics that should prompt NTM-PD assessment. Timely testing and diagnosis would enable initiation of appropriate management.
A robust web-based tool to predict viral shedding in patients with Omicron SARS-CoV-2 variants
Authors: Zhang Weilong , Gai Xiaoyan , Wang Ben , Duan Zhonghui , Zhou Qingtao , Dai Lili , Yan Changjian , Wu Chaoling , Fan Jiarun , Wang Ping , Yang Ping , Bao Fang , Jing Hongmei , Cai Chao , Song Chunli , Ma Yingmin , Sun Yongchang 
Published: April 2024

BackgroundData on viral kinetics and variants affecting the duration of viral shedding were limited. Our objective was to determine viral shedding in distinct severe acute respiratory syndrome coronavirus 2 variants, including Omicron BA.4/5 and BF.7, and to identify the relevant influencing factors.MethodsWe carried out a longitudinal cohort study at Beijing Xiaotangshan Fangcang shelter hospital from May to June 2022 (Omicron BA.4/5) and from November to December 2022 (Omicron BF.7). Nucleocapsid protein (N) and open reading frame (ORF) genes were considered as the target genes of the reverse transcription PCR. The daily results of cycle threshold (CT), including lowest ORF1ab-CT values for days 1–3 post-hospitalisation and lowest N-CT values for days 1–3 post-hospitalisation (CT3minN) and demographic and clinical characteristics were collected.Results1433 patients with coronavirus disease 2019 (COVID-19) were recruited from the Fangcang shelter hospital, in which 278 patients were diagnosed with Omicron BA.4/5 and 1155 patients with Omicron BF.7. Patients with BF.7 infection showed a longer duration of viral shedding. The duration of viral shedding was associated with the variants age, alcohol use, the severity of COVID-19 and CT3minN. Moreover, the nomogram had excellent accuracy in predicting viral shedding.ConclusionsOur results indicated that patients with Omicron BF.7 had a longer period of contagiousness than those with BA.4/5. The duration of viral shedding was affected by a variety of factors and the nomogram may become an applicable clinical instrument to predict viral shedding. Furthermore, we developed a new COVID-19 viral shedding predicting model that can accurately predict the duration of viral shedding for COVID-19, and created a user-friendly website to apply this prediction model (https://puh3.shinyapps.io/CVSP_Model/).
Interpretable machine learning-based clinical prediction model for predicting lymph node metastasis in patients with intrahepatic cholangiocarcinoma
Authors: Xie Hui , Hong Tao , Liu Wencai , Jia Xiaodong , Wang Le , Zhang Huan , Xu Chan , Zhang Xiaoke , Li Wen-Le , Wang Quan , Yin Chengliang , Lv Xu 
Published: April 2024

Abstract
Objective
Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC.

Methods
A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis. The selected variables were used for developing prediction models for LNM by six ML algorithms, including Logistic regression (LR), Gradient boosting machine (GBM), Extreme gradient boosting (XGB), Random Forest (RF), Decision tree (DT), Multilayer perceptron (MLP). We applied 10-fold cross validation as internal validation and calculated the average of the areas under the receiver operating characteristic (ROC) curve to measure the performance of all models. A feature selection approach was applied to identify importance of predictors in each model. The heat map was used to investigate the correlation of features. Finally, we established a web calculator using the best-performing model.

Results
In multivariate logistic regression analysis, factors including alcoholic liver disease (ALD), smoking, boundary, diameter, and white blood cell (WBC) were identified as independent predictors for LNM in patients with ICC. In internal validation, the average values of AUC of six models ranged from 0.820 to 0.908. The XGB model was identified as the best model, the average AUC was 0.908. Finally, we established a web calculator by XGB model, which was useful for clinicians to calculate the likelihood of LNM.

Conclusion
The proposed ML-based predicted models had a good performance to predict LNM of patients with ICC. XGB performed best. A web calculator based on the ML algorithm showed promise in assisting clinicians to predict LNM and developed individualized medical plans.
Development and validation of a novel nomogram model for predicting delayed graft function in deceased donor kidney transplantation based on pre-transplant biopsies
Authors: Li Meihe , Hu Xiaojun , Li Yang , Chen Guozhen , Ding Chen-guang , Tian Xiaohui , Tian Puxun , Xiang Heli , Pan Xiaoming , Ding Xiaoming , Xue Wujun , Zheng Jin 
Published: April 2024

Abstract
Background
Delayed graft function (DGF) is an important complication after kidney transplantation surgery. The present study aimed to develop and validate a nomogram for preoperative prediction of DGF on the basis of clinical and histological risk factors.

Methods
The prediction model was constructed in a development cohort comprising 492 kidney transplant recipients from May 2018 to December 2019. Data regarding donor and recipient characteristics, pre-transplantation biopsy results, and machine perfusion parameters were collected, and univariate analysis was performed. The least absolute shrinkage and selection operator regression model was used for variable selection. The prediction model was developed by multivariate logistic regression analysis and presented as a nomogram. An external validation cohort comprising 105 transplantation cases from January 2020 to April 2020 was included in the analysis.

Results
266 donors were included in the development cohort, 458 kidneys (93.1%) were preserved by hypothermic machine perfusion (HMP), 96 (19.51%) of 492 recipients developed DGF. Twenty-eight variables measured before transplantation surgery were included in the LASSO regression model. The nomogram consisted of 12 variables from donor characteristics, pre-transplantation biopsy results and machine perfusion parameters. Internal and external validation showed good discrimination and calibration of the nomogram, with Area Under Curve (AUC) 0.83 (95%CI, 0.78–0.88) and 0.87 (95%CI, 0.80–0.94). Decision curve analysis demonstrated that the nomogram was clinically useful.

Conclusion
A DGF predicting nomogram was developed that incorporated donor characteristics, pre-transplantation biopsy results, and machine perfusion parameters. This nomogram can be conveniently used for preoperative individualized prediction of DGF in kidney transplant recipients.
Continued versus discontinued oxytocin stimulation in the active phase of labour (CONDISOX): individual management based on artificial intelligence - a secondary analysis
Authors: Boie Sidsel , Glavind Julie , Bor Pinar , Steer Philip , Riis Anders Hammerich , Thiesson Bo , Uldbjerg Niels 
Published: April 2024

Abstract
Background
Current guidelines regarding oxytocin stimulation are not tailored to individuals as they are based on randomised controlled trials. The objective of the study was to develop an artificial intelligence (AI) model for individual prediction of the risk of caesarean delivery (CD) in women with a cervical dilatation of 6 cm after oxytocin stimulation for induced labour. The model included not only variables known when labour induction was initiated but also variables describing the course of the labour induction.

Methods
Secondary analysis of data from the CONDISOX randomised controlled trial of discontinued vs. continued oxytocin infusion in the active phase of induced labour. Extreme gradient boosting (XGBoost) software was used to build the prediction model. To explain the impact of the predictors, we calculated Shapley additive explanation (SHAP) values and present a summary SHAP plot. A force plot was used to explain specifics about an individual’s predictors that result in a change of the individual’s risk output value from the population-based risk.

Results
Among 1060 included women, 160 (15.1%) were delivered by CD. The XGBoost model found women who delivered vaginally were more likely to be parous, taller, to have a lower estimated birth weight, and to be stimulated with a lower amount of oxytocin. In 108 women (10% of 1060) the model favoured either continuation or discontinuation of oxytocin. For the remaining 90% of the women, the model found that continuation or discontinuation of oxytocin stimulation affected the risk difference of CD by less than 5% points.

Conclusion
In women undergoing labour induction, this AI model based on a secondary analysis of data from the CONDISOX trial may help predict the risk of CD and assist the mother and clinician in individual tailored management of oxytocin stimulation after reaching 6 cm of cervical dilation.