scholarly journals Synergistic Effect of Static Compliance and D-dimers to Predict Outcome of Patients with COVID-19-ARDS: A Prospective Multicenter Study

Biomedicines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1228
Author(s):  
Tommaso Tonetti ◽  
Giacomo Grasselli ◽  
Paola Rucci ◽  
Francesco Alessandri ◽  
Alessio Dell’Olio ◽  
...  
Keyword(s):  
Cox Regression ◽  
Classification Tree ◽  
Characteristic Curve ◽  
Training Sample ◽  
Static Compliance ◽  
Chi Square ◽  
Time To Death ◽  
Interaction Detection ◽  
Parenchymal Injury ◽  
D Dimer

The synergic combination of D-dimer (as proxy of thrombotic/vascular injury) and static compliance (as proxy of parenchymal injury) in predicting mortality in COVID-19-ARDS has not been systematically evaluated. The objective is to determine whether the combination of elevated D-dimer and low static compliance can predict mortality in patients with COVID-19-ARDS. A “training sample” (March–June 2020) and a “testing sample” (September 2020–January 2021) of adult patients invasively ventilated for COVID-19-ARDS were collected in nine hospitals. D-dimer and compliance in the first 24 h were recorded. Study outcome was all-cause mortality at 28-days. Cut-offs for D-dimer and compliance were identified by receiver operating characteristic curve analysis. Mutually exclusive groups were selected using classification tree analysis with chi-square automatic interaction detection. Time to death in the resulting groups was estimated with Cox regression adjusted for SOFA, sex, age, PaO2/FiO2 ratio, and sample (training/testing). “Training” and “testing” samples amounted to 347 and 296 patients, respectively. Three groups were identified: D-dimer ≤ 1880 ng/mL (LD); D-dimer > 1880 ng/mL and compliance > 41 mL/cmH2O (LD-HC); D-dimer > 1880 ng/mL and compliance ≤ 41 mL/cmH2O (HD-LC). 28-days mortality progressively increased in the three groups (from 24% to 35% and 57% (training) and from 27% to 39% and 60% (testing), respectively; p < 0.01). Adjusted mortality was significantly higher in HD-LC group compared with LD (HR = 0.479, p < 0.001) and HD-HC (HR = 0.542, p < 0.01); no difference was found between LD and HD-HC. In conclusion, combination of high D-dimer and low static compliance identifies a clinical phenotype with high mortality in COVID-19-ARDS.

Abstract 3649: Menstrual Cycling and Mechanisms of Cardiovascular Disease Events in Post-Menopausal Women: Results from the NIH-NHLBI-Sponsored Women’s Ischemia Syndrome Evaluation (WISE)

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
B. Delia Johnson ◽  
C. Noel Bairey Merz ◽  
Ricardo Azziz ◽  
Glenn D Braunstein ◽  
Leslee J Shaw ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Coronary Angiography ◽  
Cox Regression ◽  
Chi Square ◽  
Time To Death ◽  
History Of ◽  
Post Menopausal ◽  
Explanatory Mechanism ◽  
Cad Risk

Background: Menstrual cycling irregularity is being associated with greater frequency of diabetes and adverse cardiovascular (CV) events, suggesting a mechanistic link between ovarian dysfunction, CAD risk factors, and CAD. Confirmation of this link and potential explanatory mechanism(s) have not been established. Methods: We compared 686 postmenopausal women with and without a history of irregular cycles who were undergoing coronary angiography for suspected ischemia and enrolled in the WISE study. Coronary angiography was assessed by a core laboratory, and the women were prospectively followed for a median of 5.9 years. Chi square and rank sums analyses were used to compare the women on the presence and severity of CAD, CAD risk factors, and CV events. Multivariate Cox regression, adjusting for angiographic CAD and CAD risk factors was used to define time to death, MI, stroke, and angina hospitalization. Results: Overall mean age was 62, 18% were non-white, 130 (19%) reported a history of irregular cycles, and 42% had CAD (≥ 50% stenosis). Women with irregular cycles were younger (p=0.01) but did not exhibit more diabetes, obesity, or metabolic syndrome than those with regular cycles. They became menopausal at a younger age (42 ±10 vs 46 ±8, p=0.001) and had more frequent hysterectomy or oophorectomy (both p<0.01). Women with irregular cycles had a similar adjusted prevalence and severity of angiographic CAD compared to those without irregular cycles, yet had a doubled risk for MI (6% vs. 3%, p=0.02) and higher angina hospitalization rate (34% vs. 28%, p=0.01). No differences were found for the incidence of stroke or death. The relationship was maintained in risk-adjusted models controlling for metabolic syndrome, ethnicity and angiographic CAD severity (p=0.01 for MI and p=0.01 for angina hospitalization). Conclusion: Although less commonly applied, a history of menstrual cycling irregularity may be an important clinical marker of downstream risk, which is not immediately explained by the presence or severity of CAD risk factors or angiographic CAD. Additional, non-CAD risk factors, such as hormonal, inflammatory and thrombotic variables, may play a role mechanistically in the link between menstrual irregularity and adverse events.

Visitors' Spending on Accommodation: A Segmentation Model using Two-Step CHAID Analysis

2021 ◽  
Vol 12 (3) ◽  
pp. 602-612
Author(s):  
Rosmini Ismail Et.al
Keyword(s):  
Classification Tree ◽  
Regression Tree ◽  
Local Economy ◽  
Chi Square ◽  
Interaction Detection ◽  
Chaid Analysis ◽  
Fourth Segment ◽  
Level 3 ◽  
Level 1 ◽  
Level 2

Tourism receipt through visitors' spending is one of the contributors that stimulate the local economy. Therefore, it is crucial to determine the factors influencing these spending preferences. This study determines factors and average spending on accommodations using segmentation techniques for Perhentian Island's visitors. Determinant factors include demographic, trip-related, and psychographic characteristics. Data were collected through a survey and run for 929 visitors using two-step Chi-Square Automatic Interaction Detection (CHAID) analysis. The analysis produces a three-level regression tree and later a classification tree. The findings documented that, level 1 consisted of four segments and were segmented according to the country of origin (COO). Overall, the Italian is a segment that has the highest average spending. The fourth segment of level 1, namely Malaysia, branched out further to level 2 and level 3. These levels were segmented based on the number of dependents during the trip and length of stay, respectively. For domestic visitors, Malaysian with dependents on the trip spend the highest. Based on the results, recommendations for the Perhentian Islands accommodation operator were to provide infrastructure to accommodate families for domestic market and marketing strategy that target Italians for the international market. The results could also assist local authorities outlining tourism planning.

scholarly journals Exploring Quality of Life Reported by Norwegian Older Adults Using Classification Tree Approach on Group Profiles

2021 ◽  
Author(s):  
Lidia Santora ◽  
Don Byrne ◽  
Christian Klöckner
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Living Arrangement ◽  
Classification Tree ◽  
Postal Questionnaire ◽  
Subjective Quality Of Life ◽  
Chi Square ◽  
Interaction Detection ◽  
Ongoing Assessment

AbstractThis study aims to explore the variation between- and within subgroups of older adults with regard to low, medium, and high levels of self-reported quality of life (QoL) measured by the WHOQOL-BREF scale. The contribution of interacting personal and contextual life conditions to QoL was examined in a sample of 1,910 (sample frame 6,000) Norwegian men and women aged 62 to 99 years. The data collected by a postal questionnaire were analyzed using the Chi-square Automatic Interaction Detection (CHAID) classification method in order to detect unique profiles of groups who shared common characteristics. The CHAID model revealed 15 relatively homogenous groups, but distinct from one another, whose profiles were defined by unique constellations of several interacting variables significantly related to a given QoL level. Mental functioning was predominantly linked to perception of life meaning along with health status, and/or in some cases living arrangement, loneliness, neighborhood quality, and satisfaction with income, and placed an individual at different likelihood levels of reporting low, medium, or high QoL. Socio-demographics had no statistically significant impact on QoL for any subgroup. Through this individual-oriented approach, a periodically ongoing assessment of subjective quality of life (QoL) may be sufficiently powerful to allow detecting and addressing personal concerns and specific needs that detract from quality of life in advancing age.

P5587Elevated D-dimer level after 1 month anticoagulant therapy as a predictor for adverse outcomes in patients with venous thromboembolism: 10-year follow-up results

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
N M Vorobyeva ◽  
A B Dobrovolsky ◽  
E P Panchenko ◽  
E V Titaeva ◽  
M B Karabasheva ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
Anticoagulant Therapy ◽  
Prognostic Value ◽  
Cox Regression ◽  
Fold Increase ◽  
Adverse Outcomes ◽  
Chi Square ◽  
D Dimer

Abstract Background Our previous study showed that elevated D-dimer (D-D) level after 1 month of the anticoagulant therapy was an independent predictor of deep vein thrombosis (DVT) recurrences and combined endpoint (DVT recurrence and/or death from any causes) during 18 months. Prognostic value of elevated D-D level after 1 month of the anticoagulant therapy for the long-term venous thromboembolism (VTE) outcomes is unknown. Purpose To estimate the elevated D-D level influence after 1 month of the anticoagulant therapy on the 10-year prognosis in VTE pts. Methods One hundred and twelve pts (77 men) aged 18–76 (mean 54±14) years with DVT and/or pulmonary embolism were included in the study. Pts received unfractionated or low molecular weight heparin for at least 5 days followed by the long-term warfarin therapy (target international normalized ratio 2,0–3,0). D-D level was measured after 1 month from the start of the anticoagulant therapy by a quantitative assay with an estimated cut-off level of 0,5 ug/ml. The follow-up period was 10 years. Endpoints were VTE recurrence and combined endpoint (VTE recurrence and/or death from any causes). Results In all pts, median of follow-up was 2,77 years (min 2 weeks, max 11,61 years, IQR 1,44 to 10,31 years). Seventy seven (69%) pts had ended the 10-year follow-up period completely or achieved the endpoint. In these pts, median of follow-up was 9,23 years (IQR 1,70 to 10,53 years). Thirty-five cases were censored. During 10 years, the VTE recurrences rate was 27,7%, 14 pts died, the combined endpoint rate was 36,6%. Kaplan-Meier analysis showed that pts with elevated D-D level after 1 month of the anticoagulant therapy had higher 10-year cumulative risk for adverse outcomes (chi-square=6,0, p=0,014 for VTE recurrence; chi-square=13,7, p<0,001 for combined endpoint). Cox regression confirmed that elevated D-D level after 1 month of the anticoagulant therapy was associated with a 2,5-fold increase in the 10-year VTE recurrences risk (HR 2,52; 95% CI 1,18–5,42; p=0,018) and a 3,2-fold increase in the 10-year combined endpoint risk (HR 3,21; 95% CI 1,68–6,15; p<0,001) compared pts with normal D-D level after 1 month of the anticoagulant therapy. Conclusions During 10 years, the VTE recurrences rate was 27,7%, combined endpoint rate (VTE recurrence and/or death from any causes) was 36,6%. Elevated (>0,5 ug/ml) D-D level after 1 month of the anticoagulant therapy had a prognostic value and was associated with the 2,5-fold increase in the 10-year VTE recurrences risk and the 3,2-fold increase in the 10-year adverse outcomes risk.

Classification tree for the inference of the nursing diagnosis Fluid Volume Excess (00026)

2021 ◽  
Vol 55 ◽  
Author(s):  
Micnéias Lacerda Botelho ◽  
Marisa Dibbern Lopes Correia ◽  
Juliana Prado Biani Manzoli ◽  
Fábio Luis Montanari ◽  
Luciana Aparecida Costa Carvalho ◽  
...  
Keyword(s):  
Sodium Intake ◽  
Classification Tree ◽  
Cross Sectional Study ◽  
Fluid Volume ◽  
Chi Square ◽  
Related Factors ◽  
Cross Sectional ◽  
Interaction Detection ◽  
Nursing Diagnosis ◽  
Chi Square Test

ABSTRACT Objective: To generate a Classification Tree for the correct inference of the Nursing Diagnosis Fluid Volume Excess (00026) in chronic renal patients on hemodialysis. Method: Methodological, cross-sectional study with patients undergoing renal treatment. The data were collected through interviews and physical evaluation, using an instrument with socio-demographic variables, related factors, associated conditions and defining characteristics of the studied diagnosis. The classification trees were generated by the Chi-Square Automation Interaction Detection method, which was based on the Chi-square test. Results: A total of 127 patients participated, of which 79.5% (101) presented the diagnosis studied. The trees included the elements “Excessive sodium intake” and “Input exceeds output”, which were significant for the occurrence of the event, as the probability of occurrence of the diagnosis in the presence of these was 0.87 and 0.94, respectively. The prediction accuracy of the trees was 63% and 74%, respectively. Conclusion: The construction of the trees allowed to quantify the probability of the occurrence of Fluid Volume Excess (00026) in the studied population and the elements “Excessive sodium intake” and “Input exceeds output” were considered predictors of this diagnosis in the sample.

scholarly journals Prealbumin-to-Globulin Ratio Can Predict the Chemotherapy Outcomes and Prognosis of Patients with Gastric Cancer Receiving First-Line Chemotherapy

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhuo Wang ◽  
Liqun Zhang ◽  
Jingyan Wang ◽  
Yuanhe Wang ◽  
Qian Dong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Protective Factor ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Progression Free Survival ◽  
First Line ◽  
Chi Square ◽  
Cox Regression Analysis ◽  
The Relationship ◽  
Line Chemotherapy

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related mortality worldwide. Inflammation and the nutritional status of patients with GC are important factors affecting the therapeutic effect and prognosis. Inflammatory and nutrition-related markers have been shown to be prognostic factors for patients with GC. However, few studies have investigated the relationship of the prealbumin-to-globulin ratio (PGR) with the prognosis of GC patients. The objective of the present study was to examine whether pretreatment PGR is related to the prognosis and chemotherapy outcomes of in-patients with advanced GC undergoing first-line chemotherapy. We retrospectively reviewed the data of 281 patients with unresectable GC from January 2013 to January 2018. The receiver operating characteristic curve analysis determined the cut-off values for the PGR. The relationship between the PGR and chemotherapy effectiveness was evaluated using the chi-square test. Kaplan-Meier’s method was used to plot progression-free survival (PFS) and overall survival (OS) curves, using multivariable Cox regression analysis to identify promising predictors of mortality. The cut-off value for the PGR was 7.21. The high-PGR (≥7.21) group had a higher disease control rate than that of the low-PGR group (93.66% vs. 78.42%, p<0.001). Kaplan-Meier’s analysis showed significantly higher median PFS (189 vs. 125 days, p<0.001) and OS (350 vs. 288 days, p<0.001) in the high-PGR group. The multivariate analyses revealed that a high PGR is an independent protective factor in patients with advanced GC, both in terms of PFS (hazard ratio [HR]: 0.672; 95% confidence interval [CI]: 0.527–0.857; p<0.001) and OS (HR: 0.675; 95% CI: 0.530–0.861; p=0.002). In conclusion, the prechemotherapy PGR can accurately predict the chemotherapy outcome, PFS, and OS of patients with advanced GC. Therefore, medical practitioners can utilize the PGR as a novel dependable prognostic tool to weigh the prognosis of patients with GC.

PENERAPAN CHAID DENGAN PENDEKATAN SMOTE PADA KEMATIAN BALITA DI KAWASAN TIMUR INDONESIA TAHUN 2017

2020 ◽  
Vol 2019 (1) ◽  
pp. 357-367
Author(s):  
Isti Samrotul Hidayati ◽  
I Made Arcana
Keyword(s):  
Sampling Technique ◽  
Chi Square ◽  
Interaction Detection ◽  
Chi Squared

Metode Chi-squared Automatic Interaction Detection (CHAID) merupakan metode segmentasi berdasarkan hubungan variabel respon dan penjelas menggunakan uji chi-square, yang dalam penerapannya perlu memperhatikan keseimbangan data untuk meminimalkan kesalahan dalam klasifikasi. Salah satu pendekatan yang dapat digunakan pada data yang tidak seimbang adalah metode Synthetic Minority Over-sampling Technique (SMOTE). Dalam penelitian ini, metode CHAID dengan pendekatan SMOTE diterapkan pada Angka Kematian Balita (AKBa) di Kawasan Timur Indonesia (KTI). Tujuannya adalah untuk mengetahui variabel-variabel yang mencirikan kematian balita berdasarkan metode analisis CHAID yang diterapkan dan membandingkannya dengan pendekatan SMOTE. Hasil perbandingan menunjukkan bahwa pendekatan SMOTE lebih baik digunakan dengan nilai sensitivitas sebesar 48,3% dan nilai presisi sebesar 75,9%. Variabel yang signifikan mencirikan kematian balita di KTI adalah berat badan saat lahir, jenis kelahiran, status bekerja ibu dan kekayaan rumah tangga, dengan karakteristik utama adalah balita yang memiliki berat badan lahir rendah dan terlahir kembar.

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 43-55
Author(s):  
Chao Yuan ◽  
Hongjun Yuan ◽  
Li Chen ◽  
Miaomiao Sheng ◽  
Wenru Tang
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Triple Negative Breast Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Gene Expression Omnibus ◽  
Prognostic Prediction

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan–Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

scholarly journals Haemoconcentration as a predictor of severity in acute pancreatitis

2016 ◽  
Vol 4 (1) ◽  
pp. 3-7
Author(s):  
Tanka Prasad Bohara ◽  
Dimindra Karki ◽  
Anuj Parajuli ◽  
Shail Rupakheti ◽  
Mukund Raj Joshi
Keyword(s):  
Acute Pancreatitis ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Cost Effective ◽  
Receiver Operator Characteristic Curve ◽  
First Episode ◽  
P Value ◽  
Receiver Operator Characteristic ◽  
Chi Square

Background: Acute pancreatitis is usually a mild and self-limiting disease. About 25 % of patients have severe episode with mortality up to 30%. Early identification of these patients has potential advantages of aggressive treatment at intensive care unit or transfer to higher centre. Several scoring systems are available to predict severity of acute pancreatitis but are cumbersome, take 24 to 48 hours and are dependent on tests that are not universally available. Haematocrit has been used as a predictor of severity of acute pancreatitis but some have doubted its role.Objectives: To study the significance of haematocrit in prediction of severity of acute pancreatitis.Methods: Patients admitted with first episode of acute pancreatitis from February 2014 to July 2014 were included. Haematocrit at admission and 24 hours of admission were compared with severity of acute pancreatitis. Mean, analysis of variance, chi square, pearson correlation and receiver operator characteristic curve were used for statistical analysis.Results: Thirty one patients were included in the study with 16 (51.61%) male and 15 (48.4%) female. Haematocrit at 24 hours of admission was higher in severe acute pancreatitis (P value 0.003). Both haematocrit at admission and at 24 hours had positive correlation with severity of acute pancreatitis (r: 0.387; P value 0.031 and r: 0.584; P value 0.001) respectively.Area under receiver operator characteristic curve for haematocrit at admission and 24 hours were 0.713 (P value 0.175, 95% CI 0.536 - 0.889) and 0.917 (P value 0.008, 95% CI 0.813 – 1.00) respectively.Conclusion: Haematocrit is a simple, cost effective and widely available test and can predict severity of acute pancreatitis.Journal of Kathmandu Medical College, Vol. 4(1) 2015, 3-7

scholarly journals A radiomics-based model for predicting prognosis of locally advanced gastric cancer in the preoperative setting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaeseung Shin ◽  
Joon Seok Lim ◽  
Yong-Min Huh ◽  
Jie-Hyun Kim ◽  
Woo Jin Hyung ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Cox Regression ◽  
Characteristic Curve ◽  
External Validation ◽  
Locally Advanced ◽  
Clinical Model ◽  
Locally Advanced Gastric Cancer ◽  
Contrast Enhanced Ct ◽  
Preoperative Ct

AbstractThis study aims to evaluate the performance of a radiomic signature-based model for predicting recurrence-free survival (RFS) of locally advanced gastric cancer (LAGC) using preoperative contrast-enhanced CT. This retrospective study included a training cohort (349 patients) and an external validation cohort (61 patients) who underwent curative resection for LAGC in 2010 without neoadjuvant therapies. Available preoperative clinical factors, including conventional CT staging and endoscopic data, and 438 radiomic features from the preoperative CT were obtained. To predict RFS, a radiomic model was developed using penalized Cox regression with the least absolute shrinkage and selection operator with ten-fold cross-validation. Internal and external validations were performed using a bootstrapping method. With the final 410 patients (58.2 ± 13.0 years-old; 268 female), the radiomic model consisted of seven selected features. In both of the internal and the external validation, the integrated area under the receiver operating characteristic curve values of both the radiomic model (0.714, P < 0.001 [internal validation]; 0.652, P = 0.010 [external validation]) and the merged model (0.719, P < 0.001; 0.651, P = 0.014) were significantly higher than those of the clinical model (0.616; 0.594). The radiomics-based model on preoperative CT images may improve RFS prediction and high-risk stratification in the preoperative setting of LAGC.

Sign in / Sign up

Export Citation Format

Share Document