bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of ABO blood groups with venous thrombosis recurrence in middle-aged patients: insights from a weighted Cox analysis dedicated to ambispective design
Authors: Munsch Gaëlle , Goumidi Louisa , van Hylckama Vlieg Astrid , Ibrahim-Kosta Manal , Bruzelius Maria , Deleuze Jean-François , Rosendaal Frits R. , Jacqmin-Gadda Hélène , Morange Pierre-Emmanuel , Trégouët David-Alexandre 
Published: April 2023

AbstractBackgroundIn studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. When the studied risk factors are independent of time, including both pre- and post-inclusion events in the analyses, generally referred to as relying on an ambispective design, increases the statistical power but may lead to a selection bias. In the field of venous thromboembolism (VT),ABOblood groups have been the subject of extensive research due to their substantial effect on VT risk. However, few studies have investigated their effect on the risk of VT recurrence. Motivated by the study of the association of genetically determinedABOblood groups with VT recurrence, we propose a methodology to include pre-inclusion events in the analysis of ambispective studies while avoiding the selection bias due to mortality.MethodsThis work relies on two independent cohorts of VT patients, the French MARTHA study built on an ambispective design and the Dutch MEGA study built on a standard prospective design. For the analysis of the MARTHA study, a weighted Cox model was developed where weights were defined by the inverse of the survival probability at the time of data collection about the events. Thanks to the collection of information on the vital status of patients, we could estimate the survival probabilities using a delayed-entry Cox model on the death risk. Finally, results obtained in both studies were then meta-analysed.ResultsIn the combined sample totalling 2,752 patients including 993 recurrences, the A1 blood group has an increased risk (Hazard Ratio (HR) of 1.18,p = 4.2 × 10–3) compared with the O1 group, homogeneously in MARTHA and in MEGA. The same trend (HR = 1.19,p = 0.06) was observed for the less frequent A2 group.ConclusionThe proposed methodology increases the power of studies relying on an ambispective design which is frequent in epidemiologic studies about recurrent events. This approach allowed to clarify the association ofABOblood groups with the risk of VT recurrence. Besides, this methodology has an immediate field of application in the context of genome wide association studies.
Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms
Authors: Hassanzadeh Roghayyeh , Farhadian Maryam , Rafieemehr Hassan 
Published: April 2023

Abstract
Background
Trauma is one of the most critical public health issues worldwide, leading to death and disability and influencing all age groups. Therefore, there is great interest in models for predicting mortality in trauma patients admitted to the ICU. The main objective of the present study is to develop and evaluate SMOTE-based machine-learning tools for predicting hospital mortality in trauma patients with imbalanced data.

Methods
This retrospective cohort study was conducted on 126 trauma patients admitted to an intensive care unit at Besat hospital in Hamadan Province, western Iran, from March 2020 to March 2021. Data were extracted from the medical information records of patients. According to the imbalanced property of the data, SMOTE techniques, namely SMOTE, Borderline-SMOTE1, Borderline-SMOTE2, SMOTE-NC, and SVM-SMOTE, were used for primary preprocessing. Then, the Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) methods were used to predict patients' hospital mortality with traumatic injuries. The performance of the methods used was evaluated by sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), accuracy, Area Under the Curve (AUC), Geometric Mean (G-means), F1 score, and P-value of McNemar's test.

Results
Of the 126 patients admitted to an ICU, 117 (92.9%) survived and 9 (7.1%) died. The mean follow-up time from the date of trauma to the date of outcome was 3.98 ± 4.65 days. The performance of ML algorithms is not good with imbalanced data, whereas the performance of SMOTE-based ML algorithms is significantly improved. The mean area under the ROC curve (AUC) of all SMOTE-based models was more than 91%. F1-score and G-means before balancing the dataset were below 70% for all ML models except ANN. In contrast, F1-score and G-means for the balanced datasets reached more than 90% for all SMOTE-based models. Among all SMOTE-based ML methods, RF and ANN based on SMOTE and XGBoost based on SMOTE-NC achieved the highest value for all evaluation criteria.

Conclusions
This study has shown that SMOTE-based ML algorithms better predict outcomes in traumatic injuries than ML algorithms. They have the potential to assist ICU physicians in making clinical decisions.
Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems
Authors: Zondag Anna G. M. , Groenhof T. Katrien J. , van der Graaf Rieke , van Solinge Wouter W. , Bots Michiel L. , Haitjema Saskia ,   UCC-CVRM study group, de Jong Pim A. , Verhaar Marianne C. , Visseren Frank L. J. , Asselbergs Folkert W. , van der Kaaij Niels P. , Hoefer Imo E. , de Borst Gert J. , Ruigrok Ynte M. , Hollander Monika , Lely A. Titia , Emmelot-Vonk Mariëlle H. 
Published: April 2023

Abstract
Background
The Utrecht Cardiovascular Cohort – CardioVascular Risk Management (UCC-CVRM) was set up as a learning healthcare system (LHS), aiming at guideline based cardiovascular risk factor measurement in all patients in routine clinical care. However, not all patients provided informed consent, which may lead to participation bias. We aimed to study participation bias in a LHS by assessing differences in and completeness of cardiovascular risk management (CVRM) indicators in electronic health records (EHRs) of consenting, non-consenting, and non-responding patients, using the UCC-CVRM as an example.

Methods
All patients visiting the University Medical Center Utrecht for first time evaluation of a(n) (a)symptomatic vascular disease or condition were invited to participate. Routine care data was collected in the EHR and an informed consent was asked. Differences in patient characteristics were compared between consent groups. We performed multivariable logistic regression to identify determinants of non-consent. We used multinomial regression for an exploratory analysis for the determinants of non-response. Presence of CVRM indicators were compared between consent groups. A waiver (19/641) was obtained from our ethics committee.

Results
Out of 5730 patients invited, 2378 were consenting, 1907 non-consenting, and 1445 non-responding. Non-consent was related to young and old age, lower education level, lower BMI, physical activity and haemoglobin levels, higher heartrate, cardiovascular disease history and absence of proteinuria. Non-response increased with young and old age, higher education level, physical activity, HbA1c and decreased with lower levels of haemoglobin, BMI, and systolic blood pressure. Presence of CVRM indicators was 5–30% lower in non-consenting patients and even lower in non-responding patients, compared to consenting patients. Non-consent and non-response varied across specialisms.

Conclusions
A traditional informed consent procedure in a LHS may lead to participation bias and potentially to suboptimal CVRM, which is detrimental for feedback on findings in a LHS. This underlines the importance of reassessing the informed consent procedure in a LHS.
Hierarchical network meta-analysis models for synthesis of evidence from randomised and non-randomised studies
Authors: Hussein Humaira , Abrams Keith R. , Gray Laura J. , Anwer Sumayya , Dias Sofia , Bujkiewicz Sylwia 
Published: April 2023

Abstract
Background
With the increased interest in the inclusion of non-randomised data in network meta-analyses (NMAs) of randomised controlled trials (RCTs), analysts need to consider the implications of the differences in study designs as such data can be prone to increased bias due to the lack of randomisation and unmeasured confounding. This study aims to explore and extend a number of NMA models that account for the differences in the study designs, assessing their impact on the effect estimates and uncertainty.

Methods
Bayesian random-effects meta-analytic models, including naïve pooling and hierarchical models differentiating between the study designs, were extended to allow for the treatment class effect and accounting for bias, with further extensions allowing for bias terms to vary depending on the treatment class. Models were applied to an illustrative example in type 2 diabetes; using data from a systematic review of RCTs and non-randomised studies of two classes of glucose-lowering medications: sodium-glucose co-transporter 2 inhibitors and glucagon-like peptide-1 receptor agonists.

Results
Across all methods, the estimated mean differences in glycated haemoglobin after 24 and 52 weeks remained similar with the inclusion of observational data. The uncertainty around these estimates reduced when conducting naïve pooling, compared to NMA of RCT data alone, and remained similar when applying hierarchical model allowing for class effect. However, the uncertainty around these effect estimates increased when fitting hierarchical models allowing for the differences in study design. The impact on uncertainty varied between treatments when applying the bias adjustment models. Hierarchical models and bias adjustment models all provided a better fit in comparison to the naïve-pooling method.

Conclusions
Hierarchical and bias adjustment NMA models accounting for study design may be more appropriate when conducting a NMA of RCTs and observational studies. The degree of uncertainty around the effectiveness estimates varied depending on the method but use of hierarchical models accounting for the study design resulted in increased uncertainty. Inclusion of non-randomised data may, however, result in inferences that are more generalisable and the models accounting for the differences in the study design allow for more detailed and appropriate modelling of complex data, preventing overly optimistic conclusions.
SGLT-2 inhibitors may increase ultrafiltration in incident peritoneal dialysis patients: a case report
Authors: Lai Jia-Wen , Lin Hsuan-Jen , Chou Che-Yi 
Published: April 2023

Abstract
Background
Adequate fluid removal to achieve euvolemic status can be difficult in patients with incident peritoneal dialysis (PD). Limited treatments such as increased high dextrose PD solutions and icodextrin are currently available. We reported four incident PD patients whose’ ultrafiltration volume was increased after sodium-glucose cotransporter-2 inhibitors.
Case presentation.
The four reported cases were diabetic kidney disease stage 5 (cases 1–3) and IgA nephritis (case 4) patients whostartedt PD because of acute pulmonary edema (case 1 and 3), nausea vomiting (case 2), and hyperkalemia (case 4). They had an ultrafiltration volume of 700-1000 ml per day but hpersistentted peripheral pitting edema or pulmonary edema. Their ultrafiltration volincreased after dapagliflozin 5 mg daily, and the fluid overload symptoms ere improved. No hypotension, or hypoglycemia was found, and the urine was not increased during dapagliflozin treatment.

Conclusions
SGLT-2 inhibitors may increase ultrafiltration in incident PD patients. More studies are needed to support the safety of SGLT-2 inhibitors in PD patients.
Cycling in primary progressive multiple sclerosis (CYPRO): study protocol for a randomized controlled superiority trial evaluating the effects of high-intensity interval training in persons with primary progressive multiple sclerosis
Authors: Kupjetz Marie , Joisten Niklas , Rademacher Annette , Gonzenbach Roman , Bansi Jens , Zimmer Philipp 
Published: April 2023

Abstract
Background
Primary progressive multiple sclerosis (PPMS) is the least prevalent multiple sclerosis (MS) phenotype. For persons with PPMS (pwPPMS), pharmacological treatment options are limited. As a complementary non-pharmacological treatment, endurance training improves the health-related quality of life (HRQoL), numerous MS symptoms, and MS-related performance impediments. High-intensity interval training (HIIT) has been shown to induce superior effects compared to moderate-intensity continuous training (MCT). As current evidence is based on MS samples with mixed phenotypes, generalizability to pwPPMS remains unclear.

Methods
CYPRO is a parallel-group, single-center, and single-blind randomized controlled superiority trial evaluating the effects of HIIT compared to MCT in pwPPMS. Sixty-one pwPPMS are randomized (1:1) to perform volume-matched HIIT or MCT sessions on bicycle ergometers two to three times per week in addition to standard rehabilitative care during their three-week inpatient stay at Valens rehabilitation clinic, Switzerland. Standard rehabilitative care comprises endurance and strength training, physiotherapy, and occupational therapy. HIIT sessions include six 90-second intervals at 95% peak heart rate (HRpeak), interspersed by 90-second active breaks with unloaded pedaling, aimed to reach 60%HRpeak. MCT represents the standard treatment at Valens rehabilitation clinic and is performed as continuous cycling at 60%HRpeak for the duration of 26 minutes. The primary outcome is cardiorespiratory fitness, assessed as peak oxygen consumption (V̇O2peak) during cardiopulmonary exercise testing (CPET). Secondary outcomes include peak power output during CPET, walking capacity, cognitive performance, HRQoL, fatigue, anxiety and depressive symptoms, and blood-derived biomarkers (e.g., serum neurofilament light chain, glial fibrillary acidic protein, kynurenine pathway metabolites) related to MS pathophysiology. All outcomes are assessed at baseline and discharge after three weeks. Venous blood sampling is additionally performed immediately and two hours after the first HIIT or MCT session.

Discussion
CYPRO will expand current knowledge on symptom management and rehabilitation in MS to the subpopulation of pwPPMS, and will contribute to the exploration of potential disease-modifying effects of endurance training in MS. The superiority design of CYPRO will allow deriving explicit recommendations on endurance training design in pwPPMS that can be readily translated into clinical practice.

Trial registration
CYPRO has been prospectively registered at ClinicalTrials.gov on 8 February 2022 (NCT05229861).
Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit
Authors: Dang Johnny , Lal Amos , Montgomery Amy , Flurin Laure , Litell John , Gajic Ognjen , Rabinstein Alejandro ,   on behalf of The Digital Twin Platform for education, research, and healthcare delivery investigator group, Cervantes-Arslanian Anna , Marcellino Chris , Robinson Chris , Kramer Christopher L. , Freeman David W. , Hwang David Y. , Manno Edward , Wijdicks Eelco , Siegel Jason , Fugate Jennifer , Gomes Joao A. , Burns Joseph , Gobeske Kevin , Hawkes Maximiliano , Couillard Philippe , Hocker Sara , Datar Sudhir , Chakraborty Tia 
Published: April 2023

Abstract
Introduction
Digital twins, a form of artificial intelligence, are virtual representations of the physical world. In the past 20 years, digital twins have been utilized to track wind turbines' operations, monitor spacecraft's status, and even create a model of the Earth for climate research. While digital twins hold much promise for the neurocritical care unit, the question remains on how to best establish the rules that govern these models. This model will expand on our group’s existing digital twin model for the treatment of sepsis.

Methods
The authors of this project collaborated to create a Direct Acyclic Graph (DAG) and an initial series of 20 DELPHI statements, each with six accompanying sub-statements that captured the pathophysiology surrounding the management of acute ischemic strokes in the practice of Neurocritical Care (NCC). Agreement from a panel of 18 experts in the field of NCC was collected through a 7-point Likert scale with consensus defined a-priori by ≥ 80% selection of a 6 (“agree”) or 7 (“strongly agree”). The endpoint of the study was defined as the completion of three separate rounds of DELPHI consensus. DELPHI statements that had met consensus would not be included in subsequent rounds of DELPHI consensus. The authors refined DELPHI statements that did not reach consensus with the guidance of de-identified expert comments for subsequent rounds of DELPHI. All DELPHI statements that reached consensus by the end of three rounds of DELPHI consensus would go on to be used to inform the construction of the digital twin model.

Results
After the completion of three rounds of DELPHI, 93 (77.5%) statements reached consensus, 11 (9.2%) statements were excluded, and 16 (13.3%) statements did not reach a consensus of the original 120 DELPHI statements.

Conclusion
This descriptive study demonstrates the use of the DELPHI process to generate consensus among experts and establish a set of rules for the development of a digital twin model for use in the neurologic ICU. Compared to associative models of AI, which develop rules based on finding associations in datasets, digital twin AI created by the DELPHI process are easily interpretable models based on a current understanding of underlying physiology.
Robot-assisted percutaneous balloon compression for trigeminal neuralgia- preliminary experiences
Authors: Li Ning , Sun Tao , Hu Bin , Zhao Kun , Zhang Changming , Liu Jinlong , Yang Chao 
Published: April 2023

Abstract
Objectives
This study aims to discuss the availability of robot-assisted percutaneous balloon compression (PBC) for trigeminal neuralgia (TN) and share our preliminary experiences.

Methods
Patients with TN who underwent robot-assisted PBC from June to September 2022 were enrolled. We designed a fixing plug for robot-assisted PBC, three-dimensional structured light registration was used, puncture trajectory was the line connects the medial third of inner and outer aperture of foramen ovale. Numerical Rating Scale (NRS), Barrow Neurological Institute (BNI) pain and numbness intensity score were used to evaluate the facial pain and numbness.

Results
Eventually, nine patients were enrolled, the structured light registrations were successfully finished in all patients with a mean registration error of 0.68 mm. All the punctures of foramen ovales were successfully done one-time. Of note, the balloons were all got pear-shaped followed by 150 to 180 s compression. Though, postoperatively, all the patients complained of facial numbness and four patients suffered from transient masseter weakness, all patients got fully or mostly pain relief. It should be noted that is the numbness and weakness gradually relieved during follow-up.

Conclusion
Three-dimensional structured light registration and robot assisted PBC is an effective choice for patients with TN. Extension line between the medial third of the inner and outer aperture of foramen ovale might be a safe and effective puncture trajectory to this procedure.
Correlation of ABO blood groups with treatment response and efficacy in infants with persistent pulmonary hypertension of the newborn treated with inhaled nitric oxide
Authors: Guan Yi , Jin Ya , Lu Yongxue , Ao Dang , Gu Pingjiao , Yang Jiyan , Liu Guosheng , Han Shasha 
Published: April 2023

AbstractObjectiveNot all infants with persistent pulmonary hypertension of the newborn (PPHN) respond to inhaled nitric oxide (iNO) therapy, as it is known to improve oxygenation in only 50% to 60% of cases. In this study, we investigated whether ABO blood groups were a relevant factor affecting the improvement of oxygenation by nitric oxide (NO) therapy in infants with PPHN.MethodsThis study was a retrospective, multicenter, and cohort-controlled trial that involved 37 medical units. Infants with PPHN who met the inclusion criteria and were treated with NO (a vasodilator) alone from July 1, 2015, to June 30, 2020, were selected and assigned into three groups: blood type A, blood type B, and blood type O (there were only 7 cases of blood type AB, with a small number of cases, and therefore, blood type AB was excluded for further analysis). The response to iNO therapy was defined as an increase in the ratio of the partial pressure of arterial oxygen (PaO2)/fraction of inspired oxygen (FiO2) > 20% from the basal value after treatment. Oxygenation was assessed mainly based on the two values, oxygenation index (OI) and PaO2/FiO2. The correlation of ABO blood groups with responses to iNO therapy and their influence on the efficacy of iNO therapy was analyzed based on the collected data.ResultsThe highest proportion of infants with PPHN who eventually responded to iNO therapy was infants with blood type O. Infants with blood type O more readily responded to iNO therapy than infants with blood type B. Oxygenation after iNO treatment group was optimal in the blood type O group and was the worst in the blood type A group among the three groups. Infants with blood type O showed better efficacy than those with blood types A and B.ConclusionABO blood groups are correlated with responses to iNO therapy in infants with PPHN, and different blood groups also affect the efficacy of NO therapy in infants with PPHN. Specifically, infants with blood type O have a better response and experience the best efficacy to iNO therapy.