scholarly journals VALIDATION OF A DYNAMIC RISK CLASSIFICATION SYSTEM FOR IN-HOSPITAL DEATH, BASED ON ELECTRONIC RECORDS OF NON-SURGICAL ADMISSIONS TO GENERAL HOSPITALS

RAHIS ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. 101-112
Author(s):  
Lucimar Leão Gomes ◽  
Fernando Madalena Volpe
Keyword(s):  
Classification System ◽  
Severity Index ◽  
Risk Classification ◽  
Index Admission ◽  
Independent Effect ◽  
Hospital Death ◽  
Discriminative Performance ◽  
General Hospitals ◽  
Predictive Variables ◽  
Temporal Validation

Objective: To develop and validate a risk-classification system for in-hospital death, clinically useful for general hospital adult primarily non-surgical cases. Methods: Admissions for non-surgical conditions at 5 public general hospitals of Minas Gerais were included. Procedures: Build a predictive model for death during admission, using logistic regression; Create a severity index based on the independent effect of the selected variables, and then, validate its ability to predict in-hospital death during index admission; Validate the predictive scale by challenging it with a new dataset. Results: The final multivariate model included seven significant predictive variables: age, gender, diagnostic-related group, hospital of index admission, admission to the ICU, total length of stay, and unplanned surgical procedure. This model presented adequate fit and fair discriminative performance (AUC=0.78). Temporal validation with a new sample also presented an adequate fit, and the discriminative performance was again fair (AUC=0.76). Conclusions: A dynamic and clinically useful risk classification system for in-hospital death of non-surgical admissions has been validated.

Soluble form of suppression of tumorigenicity-2 predicts clinical stability of inpatients with community-acquired pneumonia

2021 ◽  
pp. 153537022110271
Author(s):  
Yifeng Zeng ◽  
Mingshan Xue ◽  
Teng Zhang ◽  
Shixue Sun ◽  
Runpei Lin ◽  
...  
Keyword(s):  
Regression Model ◽  
Predictive Value ◽  
Cox Regression ◽  
Pneumonia Severity Index ◽  
Severity Index ◽  
Community Acquired Pneumonia ◽  
Risk Classification ◽  
Soluble Form ◽  
Pneumonia Severity ◽  
Clinical Stability

The soluble form of the suppression of tumorigenicity-2 (sST2) is a biomarker for risk classification and prognosis of heart failure, and its production and secretion in the alveolar epithelium are significantly correlated with the inflammation-inducing in pulmonary diseases. However, the predictive value of sST2 in pulmonary disease had not been widely studied. This study investigated the potential value in prognosis and risk classification of sST2 in patients with community-acquired pneumonia. Clinical data of ninety-three CAP inpatients were retrieved and their sST2 and other clinical indices were studied. Cox regression models were constructed to probe the sST2’s predictive value for patients’ restoring clinical stability and its additive effect on pneumonia severity index and CURB-65 scores. Patients who did not reach clinical stability within the defined time (30 days from hospitalization) have had significantly higher levels of sST2 at admission ( P <  0.05). In univariate and multivariate Cox regression analysis, a high sST2 level (≥72.8 ng/mL) was an independent reverse predictor of clinical stability ( P < 0.05). The Cox regression model combined with sST2 and CURB-65 (AUC: 0.96) provided a more accurate risk classification than CURB-65 (AUC:0.89) alone (NRI: 1.18, IDI: 0.16, P < 0.05). The Cox regression model combined with sST2 and pneumonia severity index (AUC: 0.96) also provided a more accurate risk classification than pneumonia severity index (AUC:0.93) alone (NRI: 0.06; IDI: 0.06, P < 0.05). sST2 at admission can be used as an independent early prognostic indicator for CAP patients. Moreover, it can improve the predictive power of CURB-65 and pneumonia severity index score.

scholarly journals Percepção de enfermeiros sobre utilização do protocolo do sistema de classificação de risco manchester/ Nurses’ perception on the use of the manchester risk classification system protocol

2015 ◽  
Vol 14 (2) ◽  
pp. 1004 ◽  
Author(s):  
Marcia Luciane da Silva Bohn ◽  
Maria Alice Dias da Silva Lima ◽  
Carmen Lúcia Mottin Duro ◽  
Kelly Piacheski de Abreu
Keyword(s):  
Classification System ◽  
Risk Classification

Predictive value of the new ESGO-ESTRO-ESP endometrial cancer risk classification on survival and recurrence in the Danish population

2021 ◽  
pp. ijgc-2021-002582
Author(s):  
Gitte Ortoft ◽  
Claus Høgdall ◽  
Estrid Stæhr Hansen ◽  
Margit Dueholm
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Recurrence Rate ◽  
European Society ◽  
Classification System ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Classification ◽  
Recurrence Rates ◽  
Disease Specific

ObjectiveTo compare the performance of the new ESGO-ESTRO-ESP (European Society of Gynecological Oncology-European Society for Radiotherapy & Oncology-European Society for Pathology) 2020 risk classification system with the previous 2016 risk classification in predicting survival and patterns of recurrence in the Danish endometrial cancer population.MethodsThis Danish national cohort study included 4516 patients with endometrial cancer treated between 2005 and 2012. Five-year Kaplan–Meier adjusted and unadjusted survival estimates and actuarial recurrence rates were calculated for the previous and the new classification systems.ResultsIn the 2020 risk classification system, 81.0% of patients were allocated to low, intermediate, or high-intermediate risk compared with 69.1% in the 2016 risk classification system, mainly due to reclassification of 44.5% of patients previously classified as high risk to either intermediate or especially high-intermediate risk. The survival of the 2020 high-risk group was significantly lower, and the recurrence rate, especially the non-local recurrence rate, was significantly higher than in the 2016 high risk group (2020/2016, overall survival 59%/66%; disease specific 69%/76%; recurrence 40.5%/32.3%, non-local 34.5%/25.8%). Survival and recurrence rates in the other risk groups and the decline in overall and disease-specific survival rates from the low risk to the higher risk groups were similar in patients classified according to the 2016 and 2020 systems.ConclusionThe new ESGO-ESTRO-ESP 2020 risk classification system allocated fewer patients to the high risk group than the previous risk classification system. The main differences were lower overall and disease-specific survival and a higher recurrence rate in the 2020 high risk group. The introduction of the new 2020 risk classification will potentially result in fewer patients at high risk and allocation to the new high risk group will predict lower survival, potentially allowing more specific selection for postoperative adjuvant therapy.

scholarly journals Statistical Framework in Support of a Revised Children's Oncology Group Neuroblastoma Risk Classification System

2018 ◽  
pp. 1-15 ◽  
Author(s):  
Arlene Naranjo ◽  
Meredith S. Irwin ◽  
Michael D. Hogarty ◽  
Susan L. Cohn ◽  
Julie R. Park ◽  
...  
Keyword(s):  
Classification System ◽  
Recursive Partitioning ◽  
Diagnostic Category ◽  
Staging System ◽  
Risk Classification ◽  
Imaging Data ◽  
Oncology Group ◽  
Clinical Validity ◽  
International Consensus ◽  
Str Analysis

Purpose The International Neuroblastoma Risk Group (INRG) Staging System (INRGSS) was developed through international consensus to provide a presurgical staging system that uses clinical and imaging data at diagnosis. A revised Children's Oncology Group (COG) neuroblastoma (NB) risk classification system is needed to incorporate the INRGSS and within the context of modern therapy. Herein, we provide statistical support for the clinical validity of a revised COG risk classification system. Patients and Methods Nine factors were tested for potential statistical and clinical significance in 4,569 patients diagnosed with NB who were enrolled in the COG biology/banking study ANBL00B1 (2006-2016). Recursive partitioning was performed to create a survival-tree regression (STR) analysis of event-free survival (EFS), generating a split by selecting the strongest prognostic factor among those that were statistically significant. The least absolute shrinkage and selection operator (LASSO) was applied to obtain the most parsimonious model for EFS. COG patients were risk classified using STR, LASSO, and per the 2009 INRG classification (generated using an STR analysis of INRG data). Results were descriptively compared among the three classification approaches. Results The 3-year EFS and overall survival (± SE) were 72.9% ± 0.9% and 84.5% ± 0.7%, respectively (N = 4,569). In each approach, the most statistically and clinically significant factors were diagnostic category (eg, NB, ganglioneuroblastoma), INRGSS, MYCN status, International Neuroblastoma Pathology Classification, ploidy, and 1p/11q status. The results of the STR analysis were more concordant with those of the INRG classification system than with LASSO, although both methods showed moderate agreement with the INRG system. Conclusion These analyses provide a framework to develop a new COG risk classification incorporating the INRGSS. There is statistical evidence to support the clinical validity of each of the three classifications: STR, LASSO, and INRG.

scholarly journals Combination of D-dimer and simplified pulmonary embolism severity index to improve prediction of hospital death in patients with acute pulmonary embolism

2020 ◽  
Vol 48 (10) ◽  
pp. 030006052096229
Author(s):  
Hai-Di Wu ◽  
Zi-Kai Song ◽  
Xiao-Yan Xu ◽  
Hong-Yan Cao ◽  
Qi Wei ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Acute Pulmonary Embolism ◽  
Operating Characteristic ◽  
Troponin T ◽  
Characteristic Curve ◽  
Severity Index ◽  
Hospital Death ◽  
Operating Characteristic Curve ◽  
Death Group ◽  
D Dimer

Objective To investigate whether the combination of D-dimer and simplified pulmonary embolism severity index (sPESI) could improve prediction of in-hospital death from pulmonary embolism (PE). Methods Patients with PE (n = 272) were divided into a surviving group (n = 249) and an in-hospital death group (n = 23). Results Compared with surviving patients, patients who died in hospital had significantly higher rates of hypotension and tachycardia, reduced SaO2 levels, elevated D-dimer and troponin T levels, higher sPESI scores, and were more likely to be classified as high risk. Elevated D-dimer levels and high sPESI scores were significantly associated with in-hospital death. Using thresholds for D-dimer and sPESI of 3.175 ng/mL and 1.5, respectively, the specificity for prediction of in-hospital death was 0.357 and 0.414, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.665 and 0.668, respectively. When D-dimer and sPESI were considered together, the specificity for prediction of in-hospital death increased to 0.838 and the AUC increased to 0.74. Conclusions D-dimer and sPESI were associated with in-hospital death from PE. Considering D-dimer levels together with sPESI can significantly improve the specificity of predicting in-hospital death for patients with PE.

The TAME Risk Classification System: Acute Toxicity Burden and IPD Analysis of RTOG 90–03

2005 ◽  
Vol 63 ◽  
pp. S131 ◽  
Author(s):  
T.F. Pajak ◽  
A. Trotti ◽  
C.K. Gwede ◽  
R. Paulus ◽  
J. Cooper ◽  
...  
Keyword(s):  
Acute Toxicity ◽  
Classification System ◽  
Risk Classification

scholarly journals Weight-for-Age Percentile as a Pediatric Predictor of Emergency Department Outcome

2019 ◽  
Vol 6 ◽  
pp. 2333794X1987703
Author(s):  
Vishal Naik ◽  
Cheryl Lefaiver ◽  
Avni Dervishi ◽  
Vinod Havalad
Keyword(s):  
Emergency Department ◽  
Severity Index ◽  
Normal Weight ◽  
Independent Effect ◽  
Key Factors ◽  
Emergency Severity Index ◽  
Logistic Regression Models ◽  
Younger Age ◽  
Ed Visits ◽  
Weight For Age

This study is a retrospective cohort study that examines the association between weight-for-age percentile and pediatric admission incidence from the emergency department (ED) for all diagnoses. The charts of 1432 pediatric patients under 18 years with ED visits from 2013 to 2015 at a tertiary children’s hospital were reviewed. Analyses of subject age/weight stratifications were performed, along with ED disposition, reason for visit, and Emergency Severity Index (ESI). Multivariable logistic regression models were used to evaluate the independent effect of weight-for-age percentile on ED disposition while controlling for age, ESI, and reason for visit. Underweight subjects were more likely to be admitted than their normal weight counterparts when analyzed overall (odds ratio [OR] = 2.58, P < .01) and by age: less than 2.0 years of age (OR = 2.04, P = .033), between 2.01 and 6.0 years of age (OR = 8.60, P = .004), and between 6.01 and 13.0 years of age (OR = 3.83, P = .053). Younger age (OR = 0.935, P < .001) and higher acuity (OR = 3.49, P < .001) were also significant predictors of admission. No significant associations were found between weight and likelihood of admission for patients older than 13.01 years or between overweight/obese weight categories and admission for any age subgroups. This study suggests that underweight children younger than 13 years are at higher risk to be admitted from the ED than their normal weight, overweight, and obese counterparts. Even when controlling for other key factors, such as the ESI, a lower weight-for-age percentile was a reliable predictor of hospitalization.

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