bluuebunny/crossref_metadata_2025_split huggingface dataset:
Online COVID-19 diagnosis prediction using complete blood count: an innovative tool for public health
Authors: Teng Xiaojing , Wang Zhiyi 
Published: December 2023

Abstract
Background
COVID-19, caused by SARS-CoV-2, presents distinct diagnostic challenges due to its wide range of clinical manifestations and the overlapping symptoms with other common respiratory diseases. This study focuses on addressing these difficulties by employing machine learning (ML) methodologies, particularly the XGBoost algorithm, to utilize Complete Blood Count (CBC) parameters for predictive analysis.

Methods
We performed a retrospective study involving 2114 COVID-19 patients treated between December 2022 and January 2023 at our healthcare facility. These patients were classified into fever (1057 patients) and pneumonia groups (1057 patients), based on their clinical symptoms. The CBC data were utilized to create predictive models, with model performance evaluated through metrics like Area Under the Receiver Operating Characteristics Curve (AUC), accuracy, sensitivity, specificity, and precision. We selected the top 10 predictive variables based on their significance in disease prediction. The data were then split into a training set (70% of patients) and a validation set (30% of patients) for model validation.

Results
We identified 31 indicators with significant disparities. The XGBoost model outperformed others, with an AUC of 0.920 and high precision, sensitivity, specificity, and accuracy. The top 10 features (Age, Monocyte%, Mean Platelet Volume, Lymphocyte%, SIRI, Eosinophil count, Platelet count, Hemoglobin, Platelet Distribution Width, and Neutrophil count.) were crucial in constructing a more precise predictive model. The model demonstrated strong performance on both training (AUC = 0.977) and validation (AUC = 0.912) datasets, validated by decision curve analysis and calibration curve.

Conclusion
ML models that incorporate CBC parameters offer an innovative and effective tool for data analysis in COVID-19. They potentially enhance diagnostic accuracy and the efficacy of therapeutic interventions, ultimately contributing to a reduction in the mortality rate of this infectious disease.
Computed tomography-based patient-specific cutting guides used for positioning of the femoral component of implants during unicompartmental knee arthroplasty: a cadaver study
Authors: Cai Junfeng , Ma Min , Zeng Wen , Luo Shuling , Yuan Feng , Yin Feng 
Published: December 2023

Abstract
Background
To investigate whether patient-specific instrumentation (PSI) improves the femoral component positioning of implants during unicompartmental knee arthroplasty (UKA) using cadaver bone models.

Methods
Fifty adult cadaveric femoral bone specimens collected from February 2016–2018, were randomized to receive medial UKA with a PSI guide (n = 25) or conventional instrumentation (CI) (n = 25). Standard anteroposterior and lateral view radiographs were obtained postoperatively to assess the coronal and sagittal positioning of the femoral prostheses, respectively. The osteotomy time was recorded to assess the convenience of PSI in guiding osteotomy.

Results
Osteotomy time significantly shortened in the PSI group (3.12 ± 0.65 versus 4.33 ± 0.73 min, p < 0.001). There was a significant difference in the postoperative coronal alignment of the femoral component between the PSI and CI groups (varus/valgus angle: 1.43 ± 0.93° vs. 2.65 ± 1.50°, p = 0.001). The prevalence of outliers in coronal alignment was lower in the PSI than the CI group (2/25, 8% vs. 9/25, 36%). Sagittal posterior slope angle of the femoral component was significantly different between the two groups (8.80 ± 0.65° and 6.29 ± 1.88° in the CI and PSI groups, respectively, p < 0.001). The malalignment rate of the femoral component in the sagittal plane was 60% in the CI group, whereas no positioning deviation was observed in the PSI group.

Conclusion
This study used a cadaver model to support the fact that CT-based PSI shows an advantage over CI in optimizing implant positioning for UKAs.
Predictive value of systematic immune-inflammation index combined with Ki-67 index on prognosis of prostate cancer patients after laparoscopic radical prostatectomy
Authors: Wu Rongxin , Hu Mingjin , Zhang Pei 
Published: December 2023

Abstract
Background
Prostate cancer (PCa) presents a wide spectrum. Systemic immune-inflammation index (SII) and Ki-67 index are new biomarkers that can predict prognosis in different types of cancer. We explored the predictive value of their combination on the prognosis of PCa patients after laparoscopic radical prostatectomy (LRP).

Methods
In this retrospective study, 290 patients who underwent LRP at Nanjing Lishui People’s Hospital between January 2016 and February 2021 were enrolled. They were divided into the good prognosis group (N = 235) and poor prognosis group (N = 55) based on the follow-up results. Both the baseline data and postoperative pathological results were collected. The Ki-67 index was determined using immunohistochemical kits, and the patients were allocated to the SII/Ki-67 index high/low expression groups according to the cut-off values to further analyze their relationship with clinical/pathological data of PCa patients. Logistics multivariate regression analysis was utilized to analyze the independent factors affecting post-LRP prognosis of CPa patients. ROC curve was plotted to assess the predictive value for post-LRP prognosis, and Kaplan-Meier curve/Log-rank were used for analysis.

Results
Significant differences were found in PSA/Gleason score/T stage/lymph node metastasis/seminal vesicle invasion/neutrophils/lymphocytes/platelets/preoperative SII/Ki-67 index between the good/poor prognosis groups. Preoperative SII/Ki-67 were related to PSA/lymphocytes/platelets in PCa. Seminal vesicle invasion and preoperative SII + Ki-67 index were independent factors affecting post-LRP prognosis. Preoperative SII + Ki-67 index had a better predictive value than preoperative SII or Ki-67 index alone. Patients with high preoperative SII and Ki-67 index levels had an increased risk of poor prognosis after LRP.

Conclusion
Preoperative SII + Ki-67 index had a better predictive value for poor prognosis after LRP than SII or Ki-67 index alone.
Anti-inflammatory and tissue repair effect of cinnamaldehyde and nano cinnamaldehyde on gingival fibroblasts and macrophages
Authors: Ghardashpour Mostafa , Saeedi Majid , Negarandeh Reza , Enderami Seyed Ehsan , Ghorbani Anahita , Lotfizadeh Anahita , Jafari Ali , Arezoumandi Alireza , Hassannia Hadi , Molania Tahereh 
Published: December 2023

Abstract
Background
Recurrent aphthous stomatitis has a complex and inflammatory origin. Among the great variety of medications it is increasingly common to use herbal medicines due to the adverse side effects of chemical medications. Considering the anti-inflammatory properties of cinnamaldehyde and the lack of studies related to the effectiveness of its nano form; This study investigates the effect of cinnamaldehyde and nano cinnamaldehyde on the healing rate of recurrent aphthous stomatitis lesions.

Methods
In a laboratory experiment, cinnamaldehyde was converted into niosomal nanoparticles. The niosome vesicles diameter and polydispersity index were measured at 25°C using a dynamic light scattering (DLS) Mastersizer 2000 (Malvern Panalytical technologies: UK) and Zetasizer Nano ZS system (Malvern Instruments Worcestershire: UK). After characterizing these particles, the (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) [XTT] assay was used to assess the toxicity of cinnamaldehyde and nano cinnamaldehyde on gingival fibroblast (HGF) and macrophage (THP-1) cells. By determining the release of TNF-α, IL-6, and TGF-β cytokines using ELISA kits, the level of tissue repair and anti-inflammatory capabilities of these two substances were evaluated.

Results
The size and loading rate of the cinnamaldehyde nanoparticles were established after its creation. The optimized nanovesicle exhibited the following characteristics: particle size of 228.75 ± 2.38 nm, PDI of 0.244 ± 0.01, the zeta potential of -10.87 ± 1.09 mV and the drug encapsulation percentage of 66.72 ± 3.93%. PDIs range was between 0.242–0.274. The zeta potential values at 25°C were from -2.67 to -12.9 mV. The results of the XTT test demonstrated that nano cinnamaldehyde exhibited dose-dependent toxicity effects. Moreover, nano cinnamaldehyde released more TGF-β and had better reparative effects when taken at lower concentrations than cinnamaldehyde.

Conclusion
Nano cinnamaldehyde and cinnamaldehyde are effective in repairing tissue when used in non-toxic amounts. After confirmation in animal models, it is envisaged that these substances can be utilized to treat recurrent aphthous stomatitis.
Validation of the Malay version of Epworth sleepiness scale for children and adolescents (MESS-CHAD)
Authors: Lee Wan Ying , Lau May Nak , Soh Eunice Xinwei , Yuen Sze Wan , Ashari Asma , Radzi Zamri 
Published: December 2023

Abstract
Background
Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD) is a valid and reliable eight-item self-administered questionnaire for the assessment of excessive daytime sleepiness and is commonly used to screen sleep-disordered breathing for children and adolescents. The cross-sectional study aimed to translate and cross-culturally adapt ESS-CHAD into a Malay version of Epworth Sleepiness Scale for Children and Adolescents (MESS-CHAD) for the Malaysian population, and to assess the validity and reliability of MESS-CHAD.

Methods
Forward-backward translation method was used to translate and cross-culturally adapt ESS-CHAD. Three linguistic experts and two paediatricians content validated the translated version. Face validity was conducted through audio-recorded semi-structured in-depth interviews with 14 native Malay-speaking children and adolescents followed by thematic analysis. The revised questionnaire was then proofread by a linguistic expert. A total of 40 subjects answered the MESS-CHAD twice, 2 weeks apart, for test-retest reliability and internal consistency. For criterion validity, 148 eligible subjects and their parents answered MESS-CHAD and the Malay version of Sleep-Related Breathing Disorder scale extracted from the Paediatric Sleep Questionnaire (M-PSQ:SRBD) concurrently. Variance Inflation Factor (VIF) and P values of the model’s outer weight and outer loading were analysed using SmartPLS software to assess the indicator’s multicollinearity and significance for formative construct validity.

Results
Intraclass Correlation Coefficient (ICC) ranging from 0.798 to 0.932 and Cronbach’s alpha ranging from 0.813 to 0.932 confirmed good to excellent test-retest reliability and internal consistency, respectively. Spearman Correlation Coefficient value of 0.789 suggested a very strong positive correlation between MESS-CHAD and M-PSQ:SRBD. VIF ranging from 1.109 to 1.455 indicated no collinearity problem. All questionnaire items in MESS-CHAD were retained as the P value of either outer model weight or outer model loading was significant (P < 0.05).

Conclusion
ESS-CHAD has been translated and cross-culturally adapted into Malay version for the Malaysian population, and found to be valid and reliable.
Cost-effectiveness of a second opinion program on spine surgeries: an economic analysis
Authors: Antonioli Eliane , Tavares Malheiro Daniel , Damazio Teich Vanessa , Dias Paião Isabela , Cendoroglo Neto Miguel , Lenza Mario 
Published: December 2023

Abstract
Background
In this study we proposed a new strategy to measure cost-effectiveness of second opinion program on spine surgery, using as measure of effectiveness the minimal important change (MIC) in the quality of life reported by patients, including the satisfaction questionnaire regarding the treatment and direct medical costs.

Methods
Retrospective analysis of patients with prior indication for spine surgery included in a second opinion program during May 2011 to May 2019. Treatment costs and outcomes were compared considering each patients’ recommended treatment before and after the second opinion. Costs were measured under the perspective of the hospital, including hospital stay, surgical room, physician and staff fees and other costs related to hospitalization when surgery was performed and physiotherapy or injection costs when a conservative treatment was recommended. Reoperation costs were also included. For comparison analysis, we used data based on our clinical practice, using data from patients who underwent the same type of surgical procedure as recommended by the first referral. The measure of effectiveness was the percentage of patients who achieved the MIC in quality of life measured by the EQ-5D-3 L 2 years after starting treatment. An incremental cost-effectiveness ratio (ICER) was calculated.

Results
Based upon the assessment of 1,088 patients that completed the entire second opinion process, conservative management was recommended for 662 (60.8%) patients; 49 (4.5%) were recommended to injection and 377 (34.7%) to surgery. Complex spine surgery, as arthrodesis, was recommended by second opinion in only 3.7% of cases. The program resulted in financial savings of -$6,705 per patient associated with appropriate treatment indication, with an incremental effectiveness of 0.077 patients achieving MIC when compared to the first referral, resulting in an ICER of $-87,066 per additional patient achieving the MIC, ranging between $-273,016 and $-41,832.

Conclusion
After 2 years of treatment, the second opinion program demonstrated the potential for cost-offsets associated with improved quality of life.
Prediction of acute kidney injury incidence following acute type A aortic dissection surgery with novel biomarkers: a prospective observational study
Authors: Wang Zhigang , Xu Jingfang , Zhang Yu , Chen Cheng , Kong Chuiyu , Tang Lu , Jiang Yi , Yu Ronghuang , Zong Qiuyan , Zhang Lifang , Wang Dongjin 
Published: December 2023

Abstract
Background
Acute kidney injury (AKI) is a prevalent complication following acute type A aortic dissection (ATAAD) surgery and is closely associated with unfavorable prognostic outcomes. Hence, the development of a robust and efficient diagnostic approach to identify high-risk patients is of paramount importance.

Methods
We conducted a prospective study involving 328 patients who underwent ATAAD surgery at our institution, comprising three distinct cohorts. In addition, 52 patients undergoing alternative cardiopulmonary surgeries and 37 healthy individuals were enrolled as control groups. Employing proteomic analysis, we initially identified plasma proteins potentially linked to AKI occurrence within the plasma proteomic cohort. Subsequent validation was performed in an independent cohort. Utilizing predictors derived from multivariate logistic regression analysis, a nomogram was meticulously formulated and its efficacy was validated in the model construction cohort.

Results
Proteomics revealed significant elevation of plasma levels of S100A8/A9, pentraxin 3 (PTX3), and chitinase 3-like 1 (CHI3L1) immediately post-surgery in patients who developed ATAAD surgery-associated AKI (ASA-AKI). Receiver operating characteristic (ROC) curves demonstrated impressive predictive performance of S100A8/A9, PTX3, and CHI3L1 at 0 h post-surgery, yielding area under the curve (AUC) values of 0.823, 0.786, and 0.803, respectively, for ASA-AKI prediction. Furthermore, our findings exhibited positive correlations between plasma levels of S100A8/A9, PTX3, CHI3L1, and urinary neutrophil gelatinase-associated lipocalin (NGAL) at 0 h post-surgery, along with correlations between plasma S100A8/A9, CHI3L1 levels, and the Cleveland Clinic score. A logistic regression model incorporating plasma S100A8/A9, PTX3, CHI3L1 levels, urinary NGAL levels, and the Cleveland Clinic score facilitated the construction of a predictive nomogram for ASA-AKI. This nomogram demonstrated robust discriminative ability, achieving an AUC of 0.963 in the model construction cohort.

Conclusions
Our study underscored the augmentation of plasma S100A8/A9, PTX3, and CHI3L1 levels immediately post-surgery in patients developing ASA-AKI. The incorporation of these three biomarkers, in conjunction with the Cleveland Clinic score and NGAL, into a nomogram demonstrated commendable predictive efficacy. This presents a practical tool for identifying patients at an elevated risk of AKI following ATAAD surgery.
Virtual reality applications based on instrumental activities of daily living (iADLs) for cognitive intervention in older adults: a systematic review
Authors: Buele Jorge , Varela-Aldás José Luis , Palacios-Navarro Guillermo 
Published: December 2023

Abstract
Background
In recent years, the use of virtual reality (VR) as a complementary intervention in treating cognitive impairment has significantly increased. VR applications based on instrumental activities of daily living (iADL-VR) could offer a promising approach with greater ecological validity for intervention in groups with cognitive impairments. However, the effectiveness of this approach is still debated.

Objective
This systematic review aims to synthesize the effects of iADL-VR interventions to rehabilitate, train, or stimulate cognitive functions in healthy adults and people with mild cognitive impairment (MCI) and different types of dementia.

Methods
A systematic search was performed in the Scopus, PubMed, IEEE Xplore, Web of Science, and APA PsycNet databases until September 2022 and repeated in April 2023. The selected studies met the search terms, were peer-reviewed, included an iADL-VR intervention, and were written in English. Descriptive, qualitative studies, reviews, cognitive assessment, non-intervention studies, those unrelated to VR or iADL, those focused on motor aspects, and non-degenerative disorders were excluded. The PEDro scale was used to assess the methodological quality of the controlled studies. To present and synthesize the results, we organized the extracted data into three tables, including PEDro scores, participant characteristics, and study characteristics.

Results
Nineteen studies that met the inclusion and exclusion criteria were included. The total sample reached 590 participants, mostly women (72.67%). Approximately 30% were diagnosed with Alzheimer’s disease or dementia, and 20% had mild cognitive impairment. Variables such as authors and year of publication, study design, type of intervention and VR applied, duration of the intervention, main findings, and conclusions were extracted. Regarding demographic characteristics, the sample size, age, sex, years of education, neurological diagnosis, dropouts, and the city and country where the intervention took place were recorded. Almost all studies showed improvements in some or all the outcomes after the intervention, generally greater in the iADL-VR group than in the control group.

Conclusion
iADL-VR interventions could be beneficial in improving the performance of cognitive functions in older adults and people with MCI and different types of dementia. The ecological component of these tasks makes them very suitable for transferring what has been learned to the real world. However, such transfer needs to be confirmed by further studies with larger and more homogeneous samples and longer follow-up periods. This review had no primary funding source and was registered with PROSPERO under registration ID: 375166.
Artificial Intelligence and Acute Appendicitis: A Systematic Review of Diagnostic and Prognostic Models
Authors: Issaiy Mahbod , Zarei Diana , Saghazadeh Amene 
Published: December 2023

Abstract
Background
To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes.

Main body
A systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points extracted included model type, input features, validation strategies, and key performance metrics.

Results
In total, 29 studies were analyzed, out of which 21 focused on diagnosis, seven on prognosis, and one on both. Artificial neural networks (ANNs) were the most commonly employed algorithm for diagnosis. Both ANN and logistic regression were also widely used for categorizing types of AA. ANNs showed high performance in most cases, with accuracy rates often exceeding 80% and AUC values peaking at 0.985. The models also demonstrated promising results in predicting postoperative outcomes such as sepsis risk and ICU admission. Risk of bias was identified in a majority of studies, with selection bias and lack of internal validation being the most common issues.

Conclusion
AI algorithms demonstrate significant promise in diagnosing and prognosticating AA, often surpassing traditional methods and clinical scores such as the Alvarado scoring system in terms of speed and accuracy.
Prehospital blood gas analyses in acute patients treated by a ground-based physician-manned emergency unit: a cohort study
Authors: Walther Louise Houlberg , Lassen Annmarie Touborg , Mogensen Christian Backer , Christensen Erika Frischknecht , Mikkelsen Søren 
Published: December 2023

Abstract
Background
The prehospital patients treated by ambulances and mobile emergency care units (MECU) are potentially critically ill or injured. Knowing the risks of serious outcomes in these patients is important for guiding their treatment. Some settings allow for prehospital arterial blood gas analyses. This study aimed to assess the outcomes of prehospital patients in relation to their prehospitally measured lactate, pH, and CO2 levels. The primary outcome was 7-day mortality.

Methods
This register-based cohort study included patients with one or more prehospital blood gas analyses during their prehospital treatment by a physician-manned MECU, from January 2015 to December 2018. The blood samples were analyzed on an ABL90 Flex analyzer. Absolute values with percentages and odds ratios (OR) with 95% confidence intervals (CI) were calculated for the primary and secondary outcomes within prespecified subgroups.

Results
The study included 745 patients, with an overall 7-day mortality rate of 20.0%.

Lactate level

The 7-day mortality rates were 11.5% in patients with normal lactate levels (< 2.0 mmol/L), 14.4% with intermediate lactate levels (2.0–3.9 mmol/L), and 33.0% with high lactate levels (≥ 4.0 mmol/L). This corresponded to an OR of 1.30 (95% CI: 0.75–2.24) in the intermediate lactate group (2.0–3.9 mmol/L) and an OR of 3.77 (95% CI: 2.44–5.85) in the high lactate group (≥ 4.0 mmol/L), compared to the reference group with normal lactate.

pH level
The ORs of 7-day mortality rates were 4.82 (95% CI: 3.00–7.75) in patients with blood pH of < 7.35 and 1.33 (95% CI: 0.65–2.72) in patients with blood pH > 7.45, compared to the reference group with normal pH (7.35–7.45).

CO2
level

The ORs of 7-day mortality rates were 2.54 (95% CI: 1.45–4.46) in patients with blood CO2 of < 4.3 kPa and 2.62 (95% CI: 1.70–4.03) in patients with blood CO2 > 6.0 kPa, compared to the reference group with normal CO2 (4.3–6.0 kPa).

Conclusions
This study found a strong correlation between increasing 7-day mortality rates and high blood lactate levels, low levels of pH, and abnormal CO2 blood levels, in prehospital patients undergoing prehospital blood analysis.