scholarly journals Development of a risk scoring system for prognostication in HIV-related toxoplasma encephalitis

2020 ◽  
Author(s):  
Yao Li ◽  
Yanming Zeng ◽  
Min Liu ◽  
Yanqiu Lu ◽  
Xueyan Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Risk Model ◽  
Therapeutic Interventions ◽  
Scoring Model ◽  
Cell Counts ◽  
Toxoplasma Encephalitis ◽  
Specific Risk ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Objective: This study aims to evaluate specific risk factors influencing prognosis of HIV-infected patients with toxoplasma encephalitis (TE) in order to develop a prognostic risk scoring system for them.Methods: This is a six-center retrospective study of hospitalized HIV/TE patients. Data including six-week mortality after diagnosis, baseline characteristics, clinical features, laboratory tests and radiological characteristics of eligible patients were assimilated for risk model establishing.Results: In this study, the six-week mortality among 94 retrospective cases was 11.7% (11/94). Seven specific risk factors, viz. time from symptom onset to presentation, fever, dizziness, CD4+ T-cell counts, memory deficits, patchy brain lesions, and disorders of consciousness were calculated to be statistically associated with mortality. A criterion value of ‘9’ was selected as the optimal cut-off value of the established model. The AUC of the ROC curve of this scoring model was 0.976 (p<0.001). The sensitivity and specificity of the risk scoring model was 100.0% and 86.9%, respectively, which were 81.8% and 94.1% of this scoring model in the verification cohort, respectively. Conclusions: The developed scoring system was established with simple risk factors, which also allows expeditious implementation of accurate prognostication, and appropriate therapeutic interventions in HIV-infected patients with TE.

scholarly journals Development of a risk scoring system for prognostication in HIV-related toxoplasma encephalitis

2020 ◽  
Author(s):  
Yao Li ◽  
Yanming Zeng ◽  
Min Liu ◽  
Yanqiu Lu ◽  
Xueyan Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Risk Model ◽  
Therapeutic Interventions ◽  
Scoring Model ◽  
Cell Counts ◽  
Toxoplasma Encephalitis ◽  
Specific Risk ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Objective: This study aims to evaluate specific risk factors influencing prognosis of HIV-infected patients with toxoplasma encephalitis (TE) in order to develop a prognostic risk scoring system for them. Methods: This is a six-center retrospective study of hospitalized HIV/TE patients. Data including six-week mortality after diagnosis, baseline characteristics, clinical features, laboratory tests and radiological characteristics of eligible patients were assimilated for risk model establishing.Results: In this study, the six-week mortality among 94 retrospective cases was 11.7% (11/94). Seven specific risk factors, viz. time from symptom onset to presentation, fever, dizziness, CD4+ T-cell counts, memory deficits, patchy brain lesions, and disorders of consciousness were calculated to be statistically associated with mortality. A criterion value of ‘9’ was selected as the optimal cut-off value of the established model. The AUC of the ROC curve of this scoring model was 0.976 (p<0.001). The sensitivity and specificity of the risk scoring model was 100.0% and 86.9%, respectively, which were 81.8% and 94.1% of this scoring model in the verification cohort, respectively. Conclusions: The developed scoring system was established with simple risk factors, which also allows expeditious implementation of accurate prognostication, and appropriate therapeutic interventions in HIV-infected patients with TE.

scholarly journals Development of a risk scoring system for prognostication in HIV-related toxoplasma encephalitis

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yao Li ◽  
Yan-Ming Zeng ◽  
Min Liu ◽  
Yan-Qiu Lu ◽  
Xue-Yan Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Risk Model ◽  
Therapeutic Interventions ◽  
Scoring Model ◽  
Cell Counts ◽  
Toxoplasma Encephalitis ◽  
Specific Risk ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Background This study aims to evaluate specific risk factors influencing prognosis of HIV-infected patients with toxoplasma encephalitis (TE) in order to develop a prognostic risk scoring system for them. Methods This is a six-center retrospective study of hospitalized HIV/TE patients. Data including six-week mortality after diagnosis, baseline characteristics, clinical features, laboratory tests and radiological characteristics of eligible patients were assimilated for risk model establishing. Results In this study, the six-week mortality among 94 retrospective cases was 11.7% (11/94). Seven specific risk factors, viz. time from symptom onset to presentation, fever, dizziness, CD4+ T-cell counts, memory deficits, patchy brain lesions, and disorders of consciousness were calculated to be statistically associated with mortality. A criterion value of ‘9’ was selected as the optimal cut-off value of the established model. The AUC of the ROC curve of this scoring model was 0.976 (p < 0.001). The sensitivity and specificity of the risk scoring model was 100.0 and 86.9%, respectively, which were 81.8 and 94.1% of this scoring model in the verification cohort, respectively. Conclusions The developed scoring system was established with simple risk factors, which also allows expeditious implementation of accurate prognostication, and appropriate therapeutic interventions in HIV-infected patients with TE.

scholarly journals Development of a risk scoring system for prognostication in HIV-related toxoplasma encephalitis

2020 ◽  
Author(s):  
Yao Li ◽  
Yanming Zeng ◽  
Min Liu ◽  
Yanqiu Lu ◽  
Xueyan Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Risk Model ◽  
Therapeutic Interventions ◽  
Scoring Model ◽  
Cell Counts ◽  
Toxoplasma Encephalitis ◽  
Specific Risk ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Background: This study aims to evaluate specific risk factors influencing prognosis of HIV-infected patients with toxoplasma encephalitis (TE) in order to develop a prognostic risk scoring system for them. Methods: This is a six-center retrospective study of hospitalized HIV/TE patients. Data including six-week mortality after diagnosis, baseline characteristics, clinical features, laboratory tests and radiological characteristics of eligible patients were assimilated for risk model establishing.Results: In this study, the six-week mortality among 94 retrospective cases was 11.7% (11/94). Seven specific risk factors, viz. time from symptom onset to presentation, fever, dizziness, CD4+ T-cell counts, memory deficits, patchy brain lesions, and disorders of consciousness were calculated to be statistically associated with mortality. A criterion value of ‘9’ was selected as the optimal cut-off value of the established model. The AUC of the ROC curve of this scoring model was 0.976 (p<0.001). The sensitivity and specificity of the risk scoring model was 100.0% and 86.9%, respectively, which were 81.8% and 94.1% of this scoring model in the verification cohort, respectively. Conclusions: The developed scoring system was established with simple risk factors, which also allows expeditious implementation of accurate prognostication, and appropriate therapeutic interventions in HIV-infected patients with TE.

A risk scoring system to predict overall survival for patients with liver cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16635-e16635
Author(s):  
Haibei Xin ◽  
Guanxiong Zhang ◽  
Wei Zhou ◽  
Huan Chen ◽  
Dandan Liang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Overall Survival ◽  
Surgical Resection ◽  
Scoring System ◽  
Therapeutic Interventions ◽  
Primary Hepatocellular Carcinoma ◽  
Cd8 Cells ◽  
Risk Scoring ◽  
Risk Scoring System

e16635 Background: Surgical resection is a common curative treatment for patients with primary hepatocellular carcinoma (HCC), and conventional strategies of assessing clinical and pathologic risk factors have been adopted to predict clinic outcomes in patients after curative surgery. We hypothesized that an ensemble learning approach which incorporates multidimensional features would enable effective prediction of patient survival. Methods: We analyzed data from 222 stage II-III HCC patients who underwent surgical resection at Eastern Hepatobiliary Surgery Hospital (Shanghai, China). Baseline information for each patient includes clinical and pathologic risk factors, laboratory tests and in situ immunological profiles. Using machine learning, we developed CoxPH, GBS, CGBS, FSVM and NSVM models for patient overall survival (OS). Models were trained on 155 cases with 48 features. Thirteen-fold cross-validation (CV) was used to measure performance with area under the ROC curve (AUC) and C-Index (CI). The ensemble model was used to predict patient OS and validated on the subsequent 67 cases. Results: For all models tested, immune features, including the fraction of CD68+ and CD8+ cells in tumor, and CD8+ cells in stroma, play a crucial role in predicting patient OS. Using the ensemble CoxPH model (with superior value of AUC and CI), a risk scoring system for patient OS was developed. The scoring system could stratify patients into high-risk or low-risk groups, revealing different prognosis (validation cohort: HR, 6.5, 95% CI, 2.4-18, P = 3.4e-05). The CoxPH model was also predictive of the time to-recurrence (p < 0.0001). In validation set, the scoring system predicted half-year mortality of patients with AUC of 0.9, and 1-year mortality of patients with AUC of 0.897. The scoring system could also predict half-year recurrence and 1-year recurrence with AUC more than 0.83. Conclusions: The machine learning-based risk scoring system offers a novel strategy for incorporating multidimensional risk factors to predict clinic outcome and may help medical practitioners to optimize clinical follow-up or therapeutic interventions. [Table: see text]

scholarly journals Development of a Sex-Specific Risk Scoring System for Predicting Cognitive Normal to Mild Cognitive Impairment (SRSS-CNMCI)

2021 ◽  
Author(s):  
Wen Luo ◽  
Hao Wen ◽  
Shuqi Ge ◽  
Chunzhi Tang ◽  
Xiufeng Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Scoring System ◽  
External Validation ◽  
Scoring Systems ◽  
Cutoff Point ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Objective: We aim to develop a sex-specific risk scoring system for predicting cognitive normal (CN) to mild cognitive impairment (MCI), abbreviated SRSS-CNMCI, to provide a reliable tool for the prevention of MCI.Methods: Participants aged 61-90 years old with a baseline diagnosis of CN and an endpoint diagnosis of MCI were screened from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database with at least one follow-up. Multivariable Cox proportional hazards models were used to identify risk factors associated with conversion from CN to MCI and to build risk scoring systems for male and female groups. Receiver operating characteristic (ROC) curve analysis was applied to determine the risk probability cutoff point corresponding to the optimal prediction effect. We ran an external validation of the discrimination and calibration based on the Harvard Aging Brain Study (HABS) database.Results: A total of 471 participants, including 240 women (51%) and 231 men (49%), aged 61 to 90 years, were included in the study cohort for subsequent primary analysis. The final multivariable models and the risk scoring systems for females and males included age, APOE ε4, Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR). The scoring systems for females and males revealed C statistics of 0.902 (95% CI 0.840-0.963) and 0.911 (95% CI 0.863-0.959), respectively, as measures of discrimination. The cutoff point of high and low risk was 33% in females, and more than 33% was considered high risk, while more than 9% was considered high risk for males. The external validation effect of the scoring systems was good: C statistic 0.950 for the females and C statistic 0.965 for the males. Conclusions: Our parsimonious model accurately predicts conversion from CN to MCI with four risk factors and can be used as a predictive tool for the prevention of MCI.

scholarly journals The Efficacy of Risk Score System Establishment and Methylprednisolone Stratification Treatment for Pre-Engraftment Syndrome after Unrelated Cord Blood Transplantation: A Retrospective (development) and a Prospective (validation) Study

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4501-4501
Author(s):  
Xiaoyu Zhu ◽  
Jiang Zhu ◽  
Baolin Tang ◽  
Kaidi Song ◽  
Linlin Jin ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Risk Score ◽  
Cumulative Incidence ◽  
Scoring System ◽  
Cord Blood Transplantation ◽  
High Risk Factors ◽  
Risk Scoring ◽  
Risk Scoring System ◽  
Different Doses

Introduction Pre-engraftment syndrome (PES) is a common immune reaction prior to neutrophil engraftment after unrelated cord blood transplantation (UCBT), with a unique clinical manifestation of non-infectious fever and skin rash. The reported incidence of PES ranges from 20% to 78%. Although many researchers believe that PES is associated with a high incidence of acute graft-versus-host disease (GVHD) but not with transplant-related mortality (TRM) , relapse, or overall survival (OS), they did not stratify the risk factors of PES, and how to carry out different doses of methylprednisolone (MP) stratified intervention therapy still remains unknown. Method s First, 136 hematological malignancy patients treated with UCBT from April 2000 to February 2012 in our transplantation center were retrospectively analysis. Among them, 92 patients occurred PES. High-risk factors for 180-day TRM in PES patients were established by univariate and multivariate analysis. Then, from January 2013 to August 2016, 221 PES patients were scored according to the risk scoring system and stratified treated with different doses of MP. Finally, in order to validate the efficacy of MP stratification treatment, we conducted a prospective, open label and non-randomized clinical trial including 240 PES patients who underwent UCBT from September 2016 to December 2018. This trial is registered at www.chictr.org.cn as ChiCTR-ONC-16009013. Results The cumulative incidence of neutrophil and platelet engraftment was significantly higher in PES group than non-PES group (97.8% vs 70.5%, P<0.001; 75.0% vs 54.5%, P=0.05). In 92 PES patients, multivariate analysis showed that failed MP treatment, multiple clinical symptoms and early onset of PES were independent high risk factors affecting180-day TRM. One high risk factor was scored as 1. The 92 PES patients were divided into PES-0, PES-1,PES-2 and PES-3, and the higher the score, the higher the TRM (17.7% vs 21.9% vs 62.5% vs 100%,respectively; P<0.001), and the lower the OS (68.3% vs 56.2% vs 25.0% vs 0%, respectively; P<0.001). Then, from January 2013 to August 2016, 221 PES patients were scored as PES-0, PES-1 and PES-2 according to the following two high risk factors (multiple clinical symptoms and early onset of PES) and stratified treated with different doses of MP (0.5mg/kg/d for PES-0, 1mg/kg/d for PES-1 and 2mg/kg/d for PES-2). Compared to the previous PES patients with the same risk score, the 180-day TRM of PES-1 and PES-2 patients was significantly reduced and the OS, disease free survival (DFS), and GVHD-free and Relapse-free survival (GRFS) were significantly increased after stratified treatment. The results in the prospective trial were similar to the retrospective study. In addition, although stratified therapy could significantly improve the prognosis of PES-2 patients cohort, the cumulative incidence of acute GVHD and GRFS are still the worst compared with other risk score patients. Therefore, how to improve the outcomes of PES-2 patients remains to be further studied. Conclusion s PES after UCBT is benefit for engraftment, but should be graded according the risk scoring system. Different doses of MP stratified intervention therapy can significantly improve the prognosis of severe PES patients. The risk scoring system of PES after UCBT and MP stratification treatment are worthy of clinical application. But the cumulative incidence of acute GVHD and GRFS in severe PES patients still need to be ameliorated in the further study. Disclosures No relevant conflicts of interest to declare.

scholarly journals Development and Validation of a Risk Scoring System for Cephamycin-Associated Hemorrhagic Events

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tong-Ling Chien ◽  
Fei-Yuan Hsiao ◽  
Li-Ju Chen ◽  
Yu-Wen Wen ◽  
Shu-Wen Lin
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Scoring System ◽  
Goodness Of Fit ◽  
Bleeding Tendency ◽  
Multivariate Logistic Regression ◽  
Goodness Of Fit Test ◽  
Hemorrhagic Events ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Cephamycin-associated hemorrhages have been reported since their launch. This research aimed to determine risk factors for cephamycin-associated hemorrhagic events and produce a risk scoring system using National Taiwan University Hospital (NTUH) database. Patients who were older than 20 years old and consecutively used study antibiotics for more than 48 hours (epidode) at NTUH between January 1st, 2009 and December 31st, 2015 were included. The population was divided into two cohorts for evaluation of risk factors and validation of the scoring system. Multivariate logistic regression was used for the assessment of the adjusted association between factors and the outcome of interest. Results of the multivariate logistic regression were treated as the foundation to develop the risk scoring system. There were 46402 and 22681 episodes identified in 2009–2013 and 2014–2015 cohorts with 356 and 204 hemorrhagic events among respective cohorts. Use of cephamycins was associated with a higher risk for hemorrhagic outcomes (aOR 2.03, 95% CI 1.60–2.58). Other risk factors included chronic hepatic disease, at least 65 years old, prominent bleeding tendency, and bleeding history. A nine-score risk scoring system (AUROC = 0.8035, 95% CI 0.7794–0.8275; Hosmer-Lemeshow goodness-of-fit test p = 0.1044) was developed based on the identified risk factors, with higher scores indicating higher risk for bleeding. Use of cephamycins was associated with more hemorrhagic events compared with commonly used penicillins and cephalosporins. The established scoring system, CHABB, may help pharmacists identify high-risk patients and provide recommendations according to the predictive risk, and eventually enhance the overall quality of care.

scholarly journals Endocarditis surgery: Need for a specific risk scoring system

2011 ◽  
Vol 142 (3) ◽  
pp. 721
Author(s):  
Alessandro Della Corte ◽  
Maurizio Cotrufo ◽  
Antonio Carozza
Keyword(s):  
Scoring System ◽  
Specific Risk ◽  
Risk Scoring ◽  
Risk Scoring System

scholarly journals Development of a Genetic and Clinical Data-Based (GC) Risk Score for Predicting Survival of Hepatocellular Carcinoma Patients After Tumor Resection

2018 ◽  
Vol 48 (2) ◽  
pp. 491-502 ◽  
Author(s):  
Shengsen Chen ◽  
Chao Wang ◽  
An Cui ◽  
Kangkang Yu ◽  
Chong Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Clinical Data ◽  
Scoring System ◽  
Cancer Tissue ◽  
Predictive Tool ◽  
Internal Validation ◽  
Scoring Model ◽  
Risk Scoring ◽  
Risk Scoring System

Background/Aims: Carnitine palmitoyltransferase 1A (CPT1A) is a rate-limiting enzyme in the transport of long-chain fatty acids for β-oxidation. Increasing evidence has indicated that CPT1A plays an important role in carcinogenesis. However, the expression and prognostic value of CPT1A in hepatocellular carcinoma (HCC) have not been extensively studied. Methods: Here, we collected 66 post-operative liver cancer tissue samples. Gene profile expression was tested by RT-PCR. Receiver operating characteristic (ROC) analysis was performed and multivariate analysis with Cox’s Proportional Hazard Model was used for confirming the selected markers’ predictive efficiency for HCC patients’ survival. A simple risk scoring system was created based on Cox’s regression modeling and bootstrap internal validation. Results: Cox multivariate regression analysis demonstrated that CPT1A, tumor size, intrahepatic metastasis, TNM stage and histological grade were independent risk factors for the prognosis of HCC patients after surgery. Our genetic and clinical data-based (GC) risk scoring system revealed that HCC patients whose total score≥3 are more likely to relapse and die than patients whose total score < 3. Finally, the good discriminatory power of our risk scoring model was validated by bootstrap internal validation. Conclusions: The genetic and clinical data-based risk scoring model can be a promising predictive tool for liver cancer patients’ prognosis after operation.

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