Validation of Pre-/Post-TACE-Predict Models among Patients with Hepatocellular Carcinoma Receiving Transarterial Chemoembolization

This study attempted to validate the prognostic performance of the proposed Pre- and Post-TACE (transarterial chemoembolization)-Predict models, in comparison with other models for prognostication. One-hundred-and-eighty-seven patients with HCC who underwent TACE were recruited. Regarding overall survival (OS), the predictive performance of the Pre-TACE-Predict model (one-year integrated area under the curve (iAUC) 0.685 (95% confidence interval (CI) 0.593–0.772)) was better than that of the Post-TACE-Predict model (iAUC 0.659 (95% CI 0.580–0.742)). However, there was no significant statistical difference between two models at any time point. For comparison between models using pre-treatment factors, the modified hepatoma arterial embolization prognostic (mHAP)-II model demonstrated significantly better predictive performance at one year (iAUC 0.767 (95% CI 0.683–0.847)) compared with Pre-TACE-Predict. For comparison between models using first TACE response, the SNACOR model was significantly more predictive at one year (iAUC 0.778 (95% CI 0.687–0.866) vs. 0.659 (95% CI 0.580–0.742), respectively) and three years (iAUC 0.707 (95% CI 0.646–0.770) vs. 0.624 (95% CI 0.564–0.688), respectively) than the Post-TACE-Predict model. mHAP-II and SNACOR may be preferred over the Pre- and Post-TACE-Predict models, respectively, considering their similar or better performance and the ease of application.

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A predictive model for pain response following radiotherapy for treatment of spinal metastases

Scientific Reports ◽

10.1038/s41598-021-92363-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kohei Wakabayashi ◽

Yutaro Koide ◽

Takahiro Aoyama ◽

Hidetoshi Shimizu ◽

Risei Miyauchi ◽

...

Keyword(s):

Radiation Therapy ◽

Predictive Model ◽

Spinal Metastasis ◽

Spinal Metastases ◽

Area Under The Curve ◽

Predictive Performance ◽

Pain Response ◽

International Consensus ◽

Combined Features ◽

Pre Treatment

AbstractTo establish a predictive model for pain response following radiotherapy using a combination of radiomic and clinical features of spinal metastasis. This retrospective study enrolled patients with painful spine metastases who received palliative radiation therapy from 2018 to 2019. Pain response was defined using the International Consensus Criteria. The clinical and radiomic features were extracted from medical records and pre-treatment CT images. Feature selection was performed and a random forests ensemble learning method was used to build a predictive model. Area under the curve (AUC) was used as a predictive performance metric. 69 patients were enrolled with 48 patients showing a response. Random forest models built on the radiomic, clinical, and ‘combined’ features achieved an AUC of 0.824, 0.702, 0.848, respectively. The sensitivity and specificity of the combined features model were 85.4% and 76.2%, at the best diagnostic decision point. We built a pain response model in patients with spinal metastases using a combination of clinical and radiomic features. To the best of our knowledge, we are the first to examine pain response using pre-treatment CT radiomic features. Our model showed the potential to predict patients who respond to radiation therapy.

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The Clinical Utility of Serial Procalcitonin and Procalcitonin Clearance in Predicting the Outcome of COVID-19 Patients

10.1101/2021.06.14.21258855 ◽

2021 ◽

Author(s):

Sara I. Taha ◽

Aalaa K. Shata ◽

Shereen A. Baioumy ◽

Shaimaa H. Fouad ◽

Mariam K. Youssef

Keyword(s):

Hospital Mortality ◽

Prospective Observational Study ◽

Operating Characteristic ◽

Area Under The Curve ◽

Predictive Performance ◽

Roc Curve Analysis ◽

Laboratory Tool ◽

Serial Measurements ◽

Better Than

Background: The pandemic of coronavirus disease 2019 (COVID‐19) represents a great threat to global health. Sensitive tests that effectively predict the disease outcome are essentially required to guide proper intervention. Objectives: To evaluate the prognostic ability of serial procalcitonin (PCT) measurement to predict the outcome of COVID-19 patients, using PCT clearance (PCT-c) as a tool to reflect its dynamic changes. Methods: A prospective observational study of inpatients diagnosed with COVID-19 at the Quarantine Hospitals of Ain-Shams University, Cairo, Egypt. During the first five days of hospitalization, serial PCT and PCT-c values were obtained and compared between survivors and non-survivors. Patients were followed up to hospital discharge or in-hospital mortality. Results: Compared to survivors, serial PCT levels of non-survivors were significantly higher (p<0.001) and progressively increased during follow-up, in contrast, PCT-c values were significantly lower (p<0.01) and progressively decreased. Receiver operating characteristic (ROC) curve analysis showed that by using the initial PCT value alone, at a cut off value of 0.80 ng/ml, the area under the curve for predicting in-hospital mortality was 0.81 with 61.1% sensitivity and 87.3% accuracy. Serial measurements showed better predictive performance and the combined prediction value was better than the single prediction by the initial PCT. Conclusions: Serial PCT measurement could be a useful laboratory tool to predict the prognosis and outcome of COVID-19 patients. Moreover, PCT-c could be a reliable tool to assess PCT progressive kinetics.

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Time-variant strategies for optimizing the performance of non-pharmaceutical interventions (NPIs) in protecting lives and livelihoods during the COVID-19 pandemic

10.1101/2020.04.13.20063248 ◽

2020 ◽

Cited By ~ 1

Author(s):

Yap Wei Aun ◽

Dhesi Baha Raja

Keyword(s):

Health System ◽

Total Duration ◽

Area Under The Curve ◽

Performance Outcomes ◽

System Capacity ◽

Time Dimension ◽

One Year ◽

Individual Contact ◽

Pharmaceutical Interventions ◽

Better Than

AbstractA stochastic Individual Contact Model (ICM) using SIR compartments allowing for time-variant parameters was used to simulate 100 non-pharmaceutical intervention (NPI) strategies and exit trajectories for a hypothetical population, and to collect epidemiological and non-epidemiological outcomes to measure the performance of these strategies over the course of a period of intervention (up to six months) for a total duration of one-year to allow the full implications of the strategy and endgame to manifest. We find that variations in the time dimension and intensity of various strategies can have vastly different performance outcomes: (i) the timing of NPIs can ‘shrink the area under the curve’ (cumulative infections) not just ‘flatten the curve’; (ii) prolonged lockdowns have diminishing margins of returns; (iii) smooth, submaximal lockdowns perform better than pulsatile lockdowns; and (iv) the efficiency of various strategies incorporating both epidemiological and non-epidemiological outcomes vary substantially. Most sobering, none of the simulated strategies allow for an ‘acceptable’ path to exit within six months due to very large gaps in health system capacity.

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The Role of Chess in the Intellectual Development of Childrens from Primary School

SPORT AND SOCIETY ◽

10.36836/uaic/fefs/10.56 ◽

2019 ◽

pp. 58-62

Author(s):

Vlad Stegariu ◽

Simona Andreea Popușoi ◽

Beatrice Abălașei ◽

Nicolae Lucian Voinea ◽

Ioan Stelescu ◽

...

Keyword(s):

Cognitive Development ◽

Primary School ◽

Intellectual Development ◽

Resources Allocation ◽

Control Group ◽

Cognitive Resources ◽

One Year ◽

Better Than ◽

Chess Playing

Chess playing has a significant role in participants’ resources allocation, both at a psychological level, but mostly concerning the cognitive resources. The aim of the present study was to examine the effect of chess playing on the intellectual development of primary-class students. 67 children were tested using the Raven Standard Progressive Matrices and were distributed in three different groups according to their experience with chess, namely: the control group (formed by students with no experience with chess playing), the beginners group (students with less than one year in chess playing training) and the advanced group (children with more than two years experience with chess). Results indicated that chess playing had a significant effect on the SPM performance, indicating that those in the advanced group performed significantly better than those in the control or in the beginners group. Conclusions of this study tap into the benefits of playing chess with a focus on the children’s’ cognitive development.

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Isolation of an Anti-fatigue Preparation from Cellulase-treated Maca by Hydroalcoholic Extraction

Current Topics in Nutraceutical Research ◽

10.37290/ctnr2641-452x.17:93-98 ◽

2017 ◽

Vol 17 (1) ◽

pp. 93-98

Author(s):

Zheng Yue ◽

Zhang Wen-Cheng ◽

Wu Ze-Yu ◽

Fu Chuan-Xiang ◽

Gao Han ◽

...

Keyword(s):

Positive Control ◽

Glycogen Storage ◽

Hepatic Glycogen ◽

Time To Exhaustion ◽

High Dose ◽

Hydroalcoholic Extract ◽

Swimming Time ◽

Significant Difference ◽

Pre Treatment ◽

Better Than

The purpose of this study was to evaluate the anti-fatigue activity of maca hydroalcoholic extract (ME), which mainly contains macamides and polysaccharides. ME was prepared by circumfluence extraction with enzymatic pre-treatment. Anti-fatigue activity of ME was investigated in weight-loaded forced swimming mice, with pure macamides and commercially available maca tablet as positive control. Compared with normal group, pure macamides treatment group could prolong the swimming time to exhaustion, but there was no statistically significant difference (P > 0.05); while ME (middle-dose and high-dose groups) could effectively prolong the swimming durations (P < 0.05). Supplementation with pure macamides significantly decreased blood lactic acid (BLA), whereas ME significantly increased hepatic glycogen (HG), decreased BLA, and blood urea nitrogen (BUN) compared with those in normal control (P < 0.05). The results suggested that the anti-fatigue effect of ME was better than that of pure macamides, which can be explained by the increase of glycogen storage and the reduction of metabolites accumulation.

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Magnetic resonance cisternography imaging findings related to the leakage of Gadolinium into the subarachnoid space

Japanese Journal of Radiology ◽

10.1007/s11604-021-01137-1 ◽

2021 ◽

Author(s):

Rei Nakamichi ◽

Toshiaki Taoka ◽

Hisashi Kawai ◽

Tadao Yoshida ◽

Michihiko Sone ◽

...

Keyword(s):

Magnetic Resonance ◽

Subarachnoid Space ◽

Area Under The Curve ◽

Rank Correlation ◽

Predictive Performance ◽

Roc Curves ◽

Imaging Findings ◽

Spearman’S Rank Correlation ◽

Sagittal Sinus ◽

Magnetic Resonance Cisternography

Abstract Purpose To identify magnetic resonance cisternography (MRC) imaging findings related to Gadolinium-based contrast agent (GBCA) leakage into the subarachnoid space. Materials and methods The number of voxels of GBCA leakage (V-leak) on 3D-real inversion recovery images was measured in 56 patients scanned 4 h post-intravenous GBCA injection. Bridging veins (BVs) were identified on MRC. The numbers of BVs with surrounding cystic structures (BV-cyst), with arachnoid granulations protruding into the superior sagittal sinus (BV-AG-SSS) and the skull (BV-AG-skull), and including any of these factors (BV-incl) were recorded. Correlations between these variables and V-leak were examined based on the Spearman’s rank correlation coefficient. Receiver-operating characteristic (ROC) curves were generated to investigate the predictive performance of GBCA leakage. Results V-leak and the number of BV-incl were strongly correlated (r = 0.609, p < 0.0001). The numbers of BV-cyst and BV-AG-skull had weaker correlations with V-leak (r = 0.364, p = 0.006; r = 0.311, p = 0.020, respectively). The number of BV-AG-SSS was not correlated with V-leak. The ROC curve for contrast leakage exceeding 1000 voxels and the number of BV-incl had moderate accuracy, with an area under the curve of 0.871. Conclusion The number of BV-incl may be a predictor of GBCA leakage and a biomarker for waste drainage function without using GBCA.

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Therapeutic efficacy of artemether–lumefantrine and artesunate–amodiaquine for the treatment of uncomplicated Plasmodium falciparum malaria in Mali, 2015–2016

Malaria Journal ◽

10.1186/s12936-021-03760-9 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Youssouf Diarra ◽

Oumar Koné ◽

Lansana Sangaré ◽

Lassina Doumbia ◽

Dade Bouye Ben Haidara ◽

...

Keyword(s):

Plasmodium Falciparum ◽

Uncomplicated Malaria ◽

Artemisinin Resistance ◽

National Malaria Control Programme ◽

Plasmodium Falciparum Malaria ◽

Control Programme ◽

Malaria Control Programme ◽

Pre Treatment ◽

Better Than

Abstract Background The current first-line treatments for uncomplicated malaria recommended by the National Malaria Control Programme in Mali are artemether–lumefantrine (AL) and artesunate–amodiaquine (ASAQ). From 2015 to 2016, an in vivo study was carried out to assess the clinical and parasitological responses to AL and ASAQ in Sélingué, Mali. Methods Children between 6 and 59 months of age with uncomplicated Plasmodium falciparum infection and 2000–200,000 asexual parasites/μL of blood were enrolled, randomly assigned to either AL or ASAQ, and followed up for 42 days. Uncorrected and PCR-corrected efficacy results at days 28 and 42. were calculated. Known markers of resistance in the Pfk13, Pfmdr1, and Pfcrt genes were assessed using Sanger sequencing. Results A total of 449 patients were enrolled: 225 in the AL group and 224 in the ASAQ group. Uncorrected efficacy at day 28 was 83.4% (95% CI 78.5–88.4%) in the AL arm and 93.1% (95% CI 89.7–96.5%) in the ASAQ arm. The per protocol PCR-corrected efficacy at day 28 was 91.0% (86.0–95.9%) in the AL arm and 97.1% (93.6–100%) in the ASAQ arm. ASAQ was significantly (p < 0.05) better than AL for each of the aforementioned efficacy outcomes. No mutations associated with artemisinin resistance were identified in the Pfk13 gene. Overall, for Pfmdr1, the N86 allele and the NFD haplotype were the most common. The NFD haplotype was significantly more prevalent in the post-treatment than in the pre-treatment isolates in the AL arm (p < 0.01) but not in the ASAQ arm. For Pfcrt, the CVIET haplotype was the most common. Conclusions The findings indicate that both AL and ASAQ remain effective for the treatment of uncomplicated malaria in Sélingué, Mali.

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Postoperative analgesia effects of sulfentanyl plus dexmedetomidine in patients received VATS

Pteridines ◽

10.1515/pteridines-2020-0007 ◽

2020 ◽

Vol 31 (1) ◽

pp. 55-60

Author(s):

Haoyu Jiang ◽

Ying Zheng ◽

Chang Liu ◽

Ying Bao

Keyword(s):

Statistical Difference ◽

Control Group ◽

Control Groups ◽

Significant Statistical Difference ◽

Post Surgery ◽

Intravenous Analgesia ◽

The Mean ◽

Nsclc Patients ◽

And Control ◽

Time Point

AbstractBackground To evaluate sulfentanyl combined with dexmedetomidine hydrochloride on postoperative analgesia in patients who received video-assisted thoracic surgery (VATS) and its effects on serum norepinephrine (NE), dopamine (DA), 5-hydroxytryptamine (5-HT), and prostaglandin (PGE2).Material and Methods Ninety-nine non-small cell lung cancer (NSCLC) patients who received VATS were included in the study. All the patients received intravenous inhalation compound anesthesia. Of the 99 cases, 49 subjects (control group) received sulfentanyl for patient controlled intravenous analgesia (PICA) and other 50 cases (experiment group) received sulfentanyl combined with dexmedetomidine hydrochloride for PICA after operation of VATS. The analgesic effects of the two groups were evaluated according to Visual Analogue Scales (VAS) and the Bruggrmann Comfort Scale (BCS). The serum pain mediator of NE, DA, 5-HT, and PGE2 were examined and compared between the two groups in the first 24 h post-surgery.Results The VAS scores for the experiment group were significant lower than that of control group on the time points of 8, 16, and 24 h post-surgery (pall<0.05), and the BCS scores of the experiment group in the time points of 8, 16, and 24 h were significantly higher than that of controls (p<0.05). However, the VAS and BCS scores were not statistical differently in the time point of 1, 2, and 4 h post-surgery (pall>0.05). The mean sulfentanyl dosage was 63.01 ± 5.14 μg and 67.12 ± 6.91 μg for the experiment and control groups respectively with significant statistical difference (p<0.05). The mean analgesic pump pressing times were 4.30 ± 1.31 and 5.31 ± 1.46 for experiment and control groups respectively with significant statistical difference (p<0.05). The serum NE, DA, 5-HT, and PGE2 levels were significantly lower in the experimental group compared to that of control group in the time point of 12 h post-surgery (pall<0.05). The side effects of nausea, vomiting, delirium, rash, and hypotension atrial fibrillation were not statistically different between the two groups (pall>0.05).Conclusion Patient controlled intravenous analgesia of sulfentanyl combined with dexmedetomidine hydrochloride was effective in reducing the VAS score and serum pain mediators in NSCLC patients who received VAST.

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Circulatory Inflammatory Mediators in the Prediction of Anti-Tuberculous Drug-Induced Liver Injury Using RUCAM for Causality Assessment

Biomedicines ◽

10.3390/biomedicines9080891 ◽

2021 ◽

Vol 9 (8) ◽

pp. 891

Author(s):

Cheng-Maw Ho ◽

Chi-Ling Chen ◽

Chia-Hao Chang ◽

Meng-Rui Lee ◽

Jann-Yuan Wang ◽

...

Keyword(s):

Liver Injury ◽

Inflammatory Mediators ◽

Cox Regression ◽

Causality Assessment ◽

Area Under The Curve ◽

Assessment Method ◽

Drug Induced ◽

Drug Induced Liver Injury ◽

Tb Treatment ◽

Pre Treatment

Background: Anti-tuberculous (TB) medications are common causes of drug-induced liver injury (DILI). Limited data are available on systemic inflammatory mediators as biomarkers for predicting DILI before treatment. We aimed to select predictive markers among potential candidates and to formulate a predictive model of DILI for TB patients. Methods: Adult active TB patients from a prospective cohort were enrolled, and all participants received standard anti-tuberculous treatment. Development of DILI, defined as ≥5× ULN for alanine transaminase or ≥2.6× ULN of total bilirubin with causality assessment (RUCAM, Roussel Uclaf causality assessment method), was regularly monitored. Pre-treatment plasma was assayed for 15 candidates, and a set of risk prediction scores was established using Cox regression and receiver-operating characteristic analyses. Results: A total of 19 (7.9%) in 240 patients developed DILI (including six carriers of hepatitis B virus) following anti-TB treatment. Interleukin (IL)-22 binding protein (BP), interferon gamma-induced protein 1 (IP-10), soluble CD163 (sCD163), IL-6, and CD206 were significant univariable factors associated with DILI development, and the former three were backward selected as multivariable factors, with adjusted hazards of 0.20 (0.07–0.58), 3.71 (1.35–10.21), and 3.28 (1.07–10.06), respectively. A score set composed of IL-22BP, IP-10, and sCD163 had an improved area under the curve of 0.744 (p < 0.001). Conclusions: Pre-treatment IL-22BP was a protective biomarker against DILI development under anti-TB treatment, and a score set by additional risk factors of IP-10 and sCD163 employed an adequate DILI prediction.

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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Scientific Reports ◽

10.1038/s41598-021-81844-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Espen Jimenez-Solem ◽

Tonny S. Petersen ◽

Casper Hansen ◽

Christian Hansen ◽

Christina Lioma ◽

...

Keyword(s):

Prediction Models ◽

Severe Disease ◽

External Validation ◽

Area Under The Curve ◽

Predictive Performance ◽

Mortality Prediction ◽

Icu Admission ◽

Risk Of Death ◽

Online Risk ◽

The United Kingdom

AbstractPatients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

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