scholarly journals Establishment and evaluation of a prognostic model for surgical outcomes of patients with atlanto-axial dislocations

2016 ◽  
Vol 44 (6) ◽  
pp. 1474-1482
Author(s):  
Shuai Guo ◽  
Jie Chen ◽  
Baohui Yang ◽  
Haopeng Li
Keyword(s):  
Prognostic Model ◽  
Binary Logistic Regression ◽  
Cord Compression ◽  
Receiver Operating Curve ◽  
Calibration Plot ◽  
Binary Logistic Regression Analysis ◽  
Internal Validation ◽  
Japanese Orthopedic Association ◽  
Spinal Cord Compression Syndrome ◽  
Receiver Operating

Objective Atlanto-axial dislocations (AADs) are potentially fatal disturbances with high spinal cord compression syndrome. As surgeons are still uncertain who is likely to benefit the most from surgery, a prediction tool is needed to provide decision-making support. Methods The model was established based on 108 patients with AADs using multiple binary logistic regression analysis and evaluated by calibration plot and the area under the receiver operating curve (AUC). Bootstrapping was used for internal validation. Results The prognostic model can be expressed as: logit(P) = −2.2428 + 0.3168SCOPE − 2.0375SIGNAL, in which two covariates were accepted (SCORE represents the preoperative modified Japanese Orthopedic Association (mJOA) score and SIGNAL represents the intramedullary hyperintense T2-weighted imaging (T2WI) with AUC = 0.8081). Conclusions The model was internally valid, and the preoperative mJOA score and hyperintense T2WI were important predictors of outcomes. The threshold was defined as logit(P) = −0.7282 according to the receiver operating curve (ROC).

scholarly journals AFP and CA-125 as an accurate risk factor to predict eye metastasis in hypertension patients with liver Carcinoma： A STROBE-compliant article

2021 ◽  
Author(s):  
Jing Tang ◽  
Li-Juan Zhang ◽  
Yan-Cheng Huang ◽  
Rong Huang ◽  
Hui-Ye Shu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Liver Cancer ◽  
Cancer Metastasis ◽  
Binary Logistic Regression ◽  
Receiver Operating Curve ◽  
Ca 125 ◽  
Liver Carcinoma ◽  
Binary Logistic Regression Analysis ◽  
History Of ◽  
Ocular Metastasis

Abstract Purpose Primary liver carcinoma is a common malignant tumor. In this study, we analyzed the differences between hypertension patients with ocular metastasis of liver cancer and those with metastases to other sites, the correlation between history of HBV and liver cancer metastasis, and independent risk factors for ocular metastasis. METHODS We used treatment records from 488 patients with metastases of primary liver cancer from August 2001 to May 2015, divided into two groups based on metastatic sites: OM (ocular metastasis) and NOM (non-ocular, other sites of metastasis) groups. The Student’s t-test and Chi-square test were used to assess the significance of differences between the groups and define the relationship between history of HBV and ocular metastasis of liver cancer. Binary logistic regression analysis was used to identify indicators of ocular metastasis of liver cancer and receiver operating curve (ROC) analyses to estimate their diagnostic value. RESULTS No significant differences in sex, age, tumor stage, pathological type, or treatment were identified between the OM and NOM groups, while the prevalence of HBV was higher in the former than that in latter, confirming the association between history of HBV and ocular metastasis. Binary logistic regression demonstrated that AFP and CA-125 were independent indicators of liver metastasis (both P < 0.001). ROC curve analyses generated cut-off values for AFP and CA-125 of 957.2 ng/ml and 114.25 U/ml, respectively, with corresponding AUC values of 0.739 and 0.810. The specificity of the combination of AFP and CA-125 was higher than either factor separately.

Front-line thrombectomy for acute large-vessel occlusion with underlying severe intracranial stenosis: stent retriever versus contact aspiration

2020 ◽  
Vol 132 (4) ◽  
pp. 1202-1208 ◽  
Author(s):  
Dong-Hun Kang ◽  
Woong Yoon ◽  
Byung Hyun Baek ◽  
Seul Kee Kim ◽  
Yun Young Lee ◽  
...  
Keyword(s):  
Binary Logistic Regression ◽  
Stent Retriever ◽  
Large Vessel ◽  
Binary Logistic Regression Analysis ◽  
Large Vessel Occlusion ◽  
Front Line ◽  
Vessel Occlusion ◽  
Aspiration Thrombectomy ◽  
Atherosclerotic Stenosis ◽  
Antegrade Flow

OBJECTIVEThe optimal front-line thrombectomy choice for primary recanalization of a target artery remains unknown for patients with acute large-vessel occlusion (LVO) and an underlying intracranial atherosclerotic stenosis (ICAS). The authors aimed to compare procedural characteristics and outcomes between patients who received a stent-retriever thrombectomy (SRT) and patients who received a contact aspiration thrombectomy (CAT), as the front-line approach for treating LVO due to severe underlying ICAS.METHODSOne hundred thirty patients who presented with acute LVO and underlying severe ICAS at the occlusion site were included. Procedural characteristics and treatment outcomes were compared between patients treated with front-line SRT (n = 70) and those treated with front-line CAT (n = 60). The primary outcomes were the rate of switching to an alternative thrombectomy technique, time from groin puncture to initial reperfusion, and duration of the procedure. Initial reperfusion was defined as revealing the underlying culprit stenosis with an antegrade flow after thrombectomy.RESULTSThe rate of switching to an alternative thrombectomy after failure of the front-line technique was significantly higher in the CAT group than in the SRT group (40% vs 4.3%; OR 2.543, 95% CI 1.893–3.417, p < 0.001). The median time from puncture to initial reperfusion (17 vs 31 minutes, p < 0.001) and procedure duration (39 vs 75.5 minutes, p < 0.001) were significantly shorter in the SRT group than in the CAT group. In the binary logistic regression analysis, a longer time from puncture to initial reperfusion was an independent predictor of a 90-day poor (modified Rankin Scale score 3–6) functional outcome (per 1-minute increase; OR 1.029, 95% CI 1.008–1.050, p = 0.006).CONCLUSIONSThe authors’ results suggest that SRT may be more effective than CAT for identifying underlying culprit stenosis and therefore considered the optimal front-line thrombectomy technique in acute stroke patients with LVO and severe underlying ICAS.

scholarly journals OP0147 RHEUMATIC? - A DIGITAL DIAGNOSTIC DECISION SUPPORT TOOL FOR INDIVIDUALS SUSPECTING RHEUMATIC DISEASES: A MULTICENTER VALIDATION STUDY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 87.1-88
Author(s):  
R. Knevel ◽  
J. Knitza ◽  
A. Hensvold ◽  
A. Circiumaru ◽  
T. Bruce ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Rheumatic Disease ◽  
Rheumatic Diseases ◽  
Receiver Operating Curve ◽  
Musculoskeletal Complaints ◽  
Immune Mediated ◽  
Diagnostic Decision ◽  
Ocean Observations ◽  
Receiver Operating

Background:Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations for individuals suspecting a rheumatic disease.1,2 The tool can be used by people suspicious for rheumatic diseases resulting in individual advise on eventually seeking further health care.Objectives:We tested Rheumatic? for its ability to differentiate symptoms from immune-mediated diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.Methods:The performance of Rheumatic? was tested using data from 175 patients from three university rheumatology centers covering two different settings:A.Risk-RA phase setting. Here, we tested whether Rheumatic? could predict the development of arthritis in 50 at risk-individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity from the KI (Karolinska Institutet)B.Early arthritis setting. Here, we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic disease in i) EUMC (Erlangen) n=52 patients and ii) LUMC (Leiden) n=73 patients.In each setting, we examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC).Results:In setting A, the total test score clearly differentiated between individuals developing arthritis or not, median 245 versus 163, P < 0.0001, AUC-ROC = 75.3 (Figure 1). Also within patients with arthritis the Rheumatic? total score was significantly higher in patients developing an immune-mediated arthritic disease versus those who did not: median score EUMC 191 versus 107, P < 0.0001, AUC-ROC = 79.0, and LUMC 262 versus 212, P < 0.0001, AUC-ROC = 53.6.Figure 1.(Area under) the receiver operating curve for the total Rheumatic? scoreConclusion:Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. A following subject of research is how the tool performs in a population-wide setting.References:[1]Knitza J. et al. Mobile Health in Rheumatology: A Patient Survey Study Exploring Usage, Preferences, Barriers and eHealth Literacy. JMIR mHealth and uHealth. 2020.[2]https://rheumatic.elsa.science/en/Acknowledgements:This project has received funding from EIT Health. EIT Health is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union that receives support from the European Union’s Horizon 2020 Research and Innovation program.This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777357, RTCure.Disclosure of Interests:Rachel Knevel: None declared, Johannes Knitza: None declared, Aase Hensvold: None declared, Alexandra Circiumaru: None declared, Tor Bruce Employee of: Ocean Observations, Sebastian Evans Employee of: Elsa Science, Tjardo Maarseveen: None declared, Marc Maurits: None declared, Liesbeth Beaart- van de Voorde: None declared, David Simon: None declared, Arnd Kleyer: None declared, Martina Johannesson: None declared, Georg Schett: None declared, Thomas Huizinga: None declared, Sofia Svanteson Employee of: Elsa Science, Alexandra Lindfors Employee of: Ocean Observations, Lars Klareskog: None declared, Anca Catrina: None declared

scholarly journals How well do neurosurgeons predict survival in patients with high-grade glioma?

2021 ◽  
Author(s):  
Lisa Millgård Sagberg ◽  
Asgeir S. Jakola ◽  
Ingerid Reinertsen ◽  
Ole Solheim
Keyword(s):  
Median Survival ◽  
Survival Curve ◽  
Binary Logistic Regression ◽  
High Grade Glioma ◽  
Accurate Estimation ◽  
Binary Logistic Regression Analysis ◽  
High Grade ◽  
Clinical Prediction ◽  
Individual Level ◽  
Actual Survival

AbstractDue to the lack of reliable prognostic tools, prognostication and surgical decisions largely rely on the neurosurgeons’ clinical prediction skills. The aim of this study was to assess the accuracy of neurosurgeons’ prediction of survival in patients with high-grade glioma and explore factors possibly associated with accurate predictions. In a prospective single-center study, 199 patients who underwent surgery for high-grade glioma were included. After surgery, the operating surgeon predicted the patient’s survival using an ordinal prediction scale. A survival curve was used to visualize actual survival in groups based on this scale, and the accuracy of clinical prediction was assessed by comparing predicted and actual survival. To investigate factors possibly associated with accurate estimation, a binary logistic regression analysis was performed. The surgeons were able to differentiate between patients with different lengths of survival, and median survival fell within the predicted range in all groups with predicted survival < 24 months. In the group with predicted survival > 24 months, median survival was shorter than predicted. The overall accuracy of surgeons’ survival estimates was 41%, and over- and underestimations were done in 34% and 26%, respectively. Consultants were 3.4 times more likely to accurately predict survival compared to residents (p = 0.006). Our findings demonstrate that although especially experienced neurosurgeons have rather good predictive abilities when estimating survival in patients with high-grade glioma on the group level, they often miss on the individual level. Future prognostic tools should aim to beat the presented clinical prediction skills.

A Ventilator-associated Pneumonia Prediction Model in Patients With Acute Respiratory Distress Syndrome

2020 ◽  
Vol 71 (Supplement_4) ◽  
pp. S400-S408
Author(s):  
Zongsheng Wu ◽  
Yao Liu ◽  
Jingyuan Xu ◽  
Jianfeng Xie ◽  
Shi Zhang ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Neuromuscular Blocking ◽  
Calibration Plot ◽  
Binary Logistic Regression Analysis ◽  
Ventilator Associated Pneumonia ◽  
Mechanical Ventilation Duration

Abstract Background Mechanical ventilation is crucial for acute respiratory distress syndrome (ARDS) patients and diagnosis of ventilator-associated pneumonia (VAP) in ARDS patients is challenging. Hence, an effective model to predict VAP in ARDS is urgently needed. Methods We performed a secondary analysis of patient-level data from the Early versus Delayed Enteral Nutrition (EDEN) of ARDSNet randomized controlled trials. Multivariate binary logistic regression analysis established a predictive model, incorporating characteristics selected by systematic review and univariate analyses. The model’s discrimination, calibration, and clinical usefulness were assessed using the C-index, calibration plot, and decision curve analysis (DCA). Results Of the 1000 unique patients enrolled in the EDEN trials, 70 (7%) had ARDS complicated with VAP. Mechanical ventilation duration and intensive care unit (ICU) stay were significantly longer in the VAP group than non-VAP group (P &lt; .001 for both) but the 60-day mortality was comparable. Use of neuromuscular blocking agents, severe ARDS, admission for unscheduled surgery, and trauma as primary ARDS causes were independent risk factors for VAP. The area under the curve of the model was .744, and model fit was acceptable (Hosmer-Lemeshow P = .185). The calibration curve indicated that the model had proper discrimination and good calibration. DCA showed that the VAP prediction nomogram was clinically useful when an intervention was decided at a VAP probability threshold between 1% and 61%. Conclusions The prediction nomogram for VAP development in ARDS patients can be applied after ICU admission, using available variables. Potential clinical benefits of using this model deserve further assessment.

scholarly journals Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongsheng He ◽  
Shengyin Liao ◽  
Lifang Cai ◽  
Weiming Huang ◽  
Xuehua Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Factors ◽  
Risk Score ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Calibration Plot ◽  
Clinical Parameters ◽  
T Stage

Abstract Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

scholarly journals Rwanda’s Land Policy Reform: Self-Employment Perspectives from a Case Study of Kimonyi Sector

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 117
Author(s):  
Mireille Mizero ◽  
Aristide Maniriho ◽  
Bosco Bashangwa Mpozi ◽  
Antoine Karangwa ◽  
Philippe Burny ◽  
...  
Keyword(s):  
Rural Areas ◽  
Policy Reform ◽  
Binary Logistic Regression ◽  
Literacy Skills ◽  
Land Policy ◽  
Binary Logistic Regression Analysis ◽  
Self Employment ◽  
Expropriation Risk ◽  
Main Activity

Rwanda’s Land Policy Reform promotes agri-business and encourages self-employment. This paper aims to analyze the situation from a self-employment perspective when dealing with expropriation risk in rural areas. In this study, we conducted a structured survey addressed to 63 domestic units, complemented by focus groups of 47 participants from Kimonyi Sector. The binary logistic regression analysis revealed that having job alternatives, men heading domestic units, literacy skills in English, and owning land lease certificates (p < 0.05) are positively and significantly related to awareness of land expropriation risk. The decision of the head of the domestic unit to practice the main activity under self-employment status is positively influenced by owning a land lease certificate, number of plots, and French skills, while skills in English and a domestic unit’s size have a positive and significant influence on involvement in a second activity as self-employed. Information on expropriation risk has no significant effect on self-employment. The domestic unit survey revealed that 34.9% of the heads of domestic units only have one job, 47.6% have at least two jobs in their everyday life, 12.7% have a minimum of three jobs, and 4.8% are inactive. The focus group synthesis exposed the limits to self-employment ability and facilities.

scholarly journals Raised TSH is associated with endothelial dysfunction in Metabolic Syndrome: A case control study

2017 ◽  
Vol 55 (4) ◽  
pp. 212-221 ◽  
Author(s):  
Ashok Kumar Ahirwar ◽  
Archana Singh ◽  
Anju Jain ◽  
Surajeet Kumar Patra ◽  
Binita Goswami ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Endothelial Dysfunction ◽  
Subclinical Hypothyroidism ◽  
Serum Insulin ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Healthy Controls ◽  
Healthy Control ◽  
Study Population ◽  
Serum Tsh

AbstractIntroduction. Endothelial dysfunction has been considered as one of the important factors in pathogenesis of Metabolic Syndrome (Met S). Subclinical hypothyroidism (SCH) has also been reported to be associated with Met S. The aim of our study is to evaluate the association of raised TSH with mediators of endothelial dysfunction in Met S with Subclinical hypothyroidism as compared to healthy controls.Methods. Study population consisted of 100 subjects, out of which 50 were cases of Met S and 50 were healthy controls. Met S group were further divided into two, based on the presence & absence of SCH. Serum insulin, T3, T4, TSH were measured by chemiluminescence based immunoassay (CLIA). Serum nitric oxide (NO) levels were measured by Modified Griess’s method and serum endothelin-1 (ET-1) levels were measured by ELISA.Results. Out of 50 cases of Met S, SCH was diagnosed in 22. The mean serum TSH levels were significantly higher in Met S cases as compared to healthy controls (5.7 ± 1.2 μIU/mL vs. 2.3 ± 1.6 μIU/mL, P <0.0001). Mean serum NO levels were significantly lower in Met S cases as compared to healthy control (15.4 ± 10 μM vs. 21 ± 10 μM, p = 0.009). Mean serum ET-1 levels were significantly higher in Met S cases as compared to healthy controls (2.68 ± 1.7 fmol/mL vs. 2.1 ± 0.84 fmol/mL, p = 0.011). On Pearson’s correlation analysis, TSH showed positive correlation with ET-1 (r = 0.341, p = 0.001) and negative correlation with NO (r = −0.331, p = 0.001). Binary logistic regression analysis showed that TSH, NO and ET-1 has significant odd’s ratio for predicting Met S.Conclusion. Met S cases were screened for thyroid abnormalities and found to have 44% of SCH along with co-existing endothelial dysfunction. Raised TSH in SCH could cause endothelial dysfunction which may lead to Met S and associated co-morbidities. Present study gives new insight in linking endothelial dysfunction and raised TSH in Met S. Therefore, Met S cases should be screened for SCH and treated appropriately to attenuate endothelial dysfunction and associated comorbidities in Met S.

scholarly journals Predicting Burn Mortality Using a Simple Novel Prediction Model

2021 ◽  
Author(s):  
Sneha Sharma ◽  
Raman Tandon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Receiver Operating Characteristic ◽  
Logistic Regression Analysis ◽  
Operating Characteristic ◽  
Binary Logistic Regression ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Binary Logistic Regression Analysis

Abstract Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

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