Current Scoring Systems Research Articles

The Performance of the Current Risk Prediction Scoring Systems in Patients Undergoing Anaortic Off-pump Coronary Artery Bypass Grafting.

BackgroundThis study aimed to evaluate the performance of the Society of Thoracic Surgeons (STS) risk model and European System for Cardiac Operative Risk Evaluation (EuroSCORE) II for patients undergoing anaortic off-pump coronary artery bypass grafting (OPCAB).MethodsFrom January 2010 to June 2017, 1,048 patients (isolated anaortic OPCAB: 1,043, on-pump conversion:5) undergoing isolated anaortic OPCAB were enrolled. The STS risk score and EuroSCORE II were calculated with dedicated online software. Calibration of the models were performed by the risk-adjusted event ratio that was defined as observed events divided by expected events (O/E ratio) and Hosmer-Lemeshow test. The discrimination powers were evaluated by the area under the receiver operating characteristic curve (AUC).ResultsOperative mortality occurred in 10 patients (0.95%). The predicted mortality rates by the EuroSCORE II and STS risk model were 2.58 ± 4.15% and 1.72 ± 2.92%, respectively. The O/E ratio of the EuroSCORE II was 0.370 with significant overprediction of operative mortality (confidence interval [CI], 0.157–0.652; P = 0.003). The STS score also overpredicted the operative mortality (O/E ratio, 0.556) with marginal significance (CI, 0.266–1.023; P = 0.052). Permanent stroke occurred in 6 patients (0.53%). The predicted permanent stroke occurrence rate was 1.73 ± 1.48%. The O/E ratio was 0.332 with significant overprediction of permanent stroke (CI, 0.121–0.722; P = 0.011). Regarding discrimination power for the STS risk model, the operative mortality was excellent (AUC, 0.876) and permanent stroke was acceptable (AUC, 0.740). The EuroSCORE II showed good discrimination power (AUC, 0.784). There was a significant difference in discrimination power for mortality between STS and EuroSCORE II risk models (P = 0.007).ConclusionPreexisting risk predicting scoring systems, STS risk model and EuroSCORE II, overpredict the risk of mortality and stroke rate for anaortic OPCAB. These findings suggest the possibility that anaortic OPCAB can lower the operative mortality and occurrence of postoperative stroke than conventional coronary artery bypass grafting.

Accuracy of available scoring systems for prediction of in-hospital major bleeding in acute pulmonary embolism patients

Bleeding prediction scores may help guide acute management of patients with pulmonary embolism (PE). However existing scoring systems have not been validated for in-hospital assessment. We compared 6 available bleeding scores for the prediction of major bleeding in the in-hospital phase in a real-life cohort. We recorded in-hospital characteristics of 2754 PE patients included in a prospective observational multicenter cohort study contributing 18,028 person-days of follow-up. The VTE-BLEED, RIETE, ORBIT, HEMORR 2 HAGES, ATRIA, and HAS-BLED scores were assessed at baseline. ISTH-defined bleeding events were independently adjudicated. The accuracy of the overall, original 3-level and newly defined optimal 2-level outcome of the scores were evaluated and compared. We observed 82 first in-hospital major bleeding events [3.0% (95% CI, 2.4–3.7)]. Overall, the predictive power of bleeding scores was poor, with a Harrel's C index ranging from 0.57 to 0.69. The Riete score had the numerically highest model fit and discrimination capacity but without reaching statistical significance versus the ORBIT, HEMORR 2 HAGES, and ATRIA scores. The VTE-BLEED and HAS-BLED scores had significantly lower C indices, integrated discrimination improvement, and net reclassification improvement compared to the others. The rate of observed in-hospital major bleeding in score-defined low-risk patients was high, at between 15% to 34%. Current available scoring systems are not sufficiently accurate for the prediction of in-hospital major bleeding in patients with acute PE. There is a need to develop risk scores specific to acute PE to optimally target bleeding-prevention strategies.

Predicting post-operative pancreatic fistula: a systematic review of scoring systems

Background: Post-operative pancreatic fistula (POPF) cause major morbidity following pancreaticoduodenectomy. There are multiple published scoring systems which predict the probability of fistula, but few have undergone rigorous external validation. This systematic review aimed to identify current scoring systems and combine the results of external validation to assess scores clinical validity.

Long-Term Survival Benefit after Allogeneic Hematopoietic Cell Transplantation for Chronic Myelomonocytic Leukemia

The critical question in the management of chronic myelomonocytic leukemia (CMML) is which patients may benefit from allogeneic hematopoietic cell transplantation (allo-HCT). Using ad hoc statistical analysis, we designed a multicenter retrospective study to determine outcomes in 261 patients age ≤70 years at diagnosis who underwent allo-HCT (n=119) compared with those who did not (n=142) according to the current CMML-specific prognostic scoring system (CPSS). Categorizing patients as lower risk (CPSS low/intermediate-1) or higher risk (intermediate-2/high) showed significantly improved outcomes after transplantation in higher-risk patients, with a 37% reduced hazard for death. However, although higher CPSS was associated with worse outcomes in the nontransplantation group, the score was of limited utility for post-transplantation risk stratification. This study may provide further support for the potentially beneficial role of allo-HCT in terms of long-term survival in higher-risk patients but also underscores the need for transplantation-specific risk assessment. Recognizing limitations of retrospective comparisons, larger and prospective comparisons are needed to further refine the indication for allo-HCT and thus counseling of patients with CMML.

Current Surgical Risk Scores Overestimate Risk in Minimally Invasive Aortic Valve Replacement.

Risk-scoring systems for surgical aortic valve replacement (AVR) were largely derived from sternotomy cases. We evaluated the accuracy of current risk scores in predicting outcomes after minimally invasive AVR (mini-AVR). Because transcatheter AVR (TAVR) is being considered for use in low-risk patients with aortic stenosis, accurate mini-AVR risk assessment is necessary. We reviewed 1,018 consecutive isolated mini-AVR cases (2009 to 2015). After excluding patients with Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) scores ≥4, we calculated each patient's European System for Cardiac Operative Risk Evaluation (EuroSCORE) II, TAVR Risk Score (TAVR-RS), and age, creatinine, and ejection fraction score (ACEF). We compared all 4 scores' accuracy in predicting mini-AVR 30-day mortality by computing each score's observed-to-expected mortality ratio (O:E). Area under the receiver operating characteristic (ROC) curves tested discrimination, and the Hosmer-Lemeshow goodness-of-fit tested calibration. Among 941 patients (mean age, 72 ± 12 years), 6 deaths occurred within 30 days (actual mortality rate, 0.6%). All 4 scoring systems overpredicted expected mortality after mini-AVR: ACEF (1.4%), EuroSCORE II (1.9%), STS-PROM (2.0%), and TAVR-RS (2.1%). STS-PROM best estimated risk for patients with STS-PROM scores 0 to <1 (0.6 O:E), ACEF for patients with STS-PROM scores 2 to <3 (0.6 O:E), and TAVR-RS for patients with STS-PROM scores 3 to <4 (0.7 O:E). ROC curves showed only fair discrimination and calibration across all risk scores. In low-risk patients who underwent mini-AVR, current surgical scoring systems overpredicted mortality 2-to-3-fold. Alternative dedicated scoring systems for mini-AVR are needed for more accurate outcomes assessment.

Development of a scoring system to predict outcomes of i.v. corticosteroid pulse therapy in rapidly progressive alopecia areata adopting digital image analysis of hair recovery.

Alopecia areata (AA) is a common autoimmune disease manifesting varying degrees of hair loss. Rapidly progressive AA (RP-AA) is a severe subtype of AA and often resistant to skin-directed treatments. i.v. corticosteroid pulse therapy has been applied for RP-AA; however, the treatment outcome can only become evaluable several months after the intervention, discomposing the patients. In this study, we attempted to develop a scoring system to predict treatment outcomes based on statistical correlations between newly identified predictors and the recovery rates calculated by digital image analysis. Thirty RP-AA patients (15 men and 15 women) who underwent pulse therapy and demonstrated total hair loss during the clinical course were included. The percentages of hair regrowth (%HR) at 6months after the treatment were quantitatively calculated by image analysis software. The correlation between %HR and clinicopathological and immunological variables were statistically assessed. The analysis identified four confirmatory contributors including female sex (P=0.015), absence of previous AA history (P=0.02), lower peripheral blood eosinophil count (P=0.02) and mild to moderate cell infiltration around the hair bulb (P=0.034), together with a potential contributor, namely absence of atopic dermatitis in their medical history (P=0.08). The scoring system was developed by double counting confirmatory variables and single counting a potential variable. Importantly, the scores obtained by this system demonstrated significant correlation with %HR (r=0.61, P<0.001). The usefulness of this scoring system was further validated by assessing additional 20 cases of RP-AA. When combined with a recently published algorithm for early detection of self-healing subset, the current scoring system may help strategize the therapeutic approach for RP-AA.

Abstract 15885: Disagreement of the Current Diagnostic Criteria for Cardiac Sarcoidosis

Introduction: Diagnosis of cardiac sarcoidosis (CS) poses a clinical challenge. Different diagnostic recommendations are proposed from JSNC, WASOG, and HRS expert consensus statement. Hypothesis: Current CS scoring systems classify patients inconsistent. The aim of this study was to compare the later with imaging-based cardiac magnetic resonance imaging (CMR) and 18F-fluorodeoxyglucose (FDG)- positron emission tomography (PET) criteria for diagnosis of CS. Methods: Between January 2016 and April 2020 patients with suspected cardiac sarcoidosis were systematically evaluated by history, ECG, lab values, echocardiogram, cardiac biopsy and both CMR and PET. Current scoring systems and criteria for diagnosis of CS were applied and compared to proposed imaging classifications. Results: Out of 45 patients (mean age 53 ± 9 years, 66.7% males), 40.0% were diagnosed with CS according to the JSNC guidelines. Applying the WASOG criteria, CS was "at least probable" in 91%, whereas the HRS guidelines classified 24.4% as CS patients. Using CMR imaging criteria 13.3%, 48.9% and 11.1% were categorized as possible, probable or highly probable for CS, and based on FDG-PETs 15.6%, 11.1% and 31.1%, respectively. There were only 9 patients (20.0%) that were classified as CS in all 4 scoring systems, and 4 patients (8.9%) that did not fulfil criteria for CS in any of the scoring systems. Conclusions: Current scoring systems for cardiac sarcoidosis showed significant disagreement and led to an inconclusive classification of CS likelihood. A refinement of the diagnostic tools for cardiac sarcoidosis is necessary.

Derivation and Validation of a Novel Lipid Metabolism Level-Based Prognostic Scoring System, Enbc Score, for Newly Diagnosed Mature T and NK Cell Lymphoma

Introduction:The current prognostic scoring systems for mature T and NK cell lymphomas are still insufficient in predicting the outcomes of patients. It is urgently needed to identify novel predictors and develop a more accurate risk stratification system. Lipid metabolism accounts for a significant proportion in the tumor energy metabolism and even occupies a dominant position in non-glycolysis-dependent tumors. Dyslipidemia has been confirmed to be related to inferior outcomes of patients with solid tumors and several hematological malignancies. Nevertheless, there has been none prognostic scoring system containing lipid metabolism-related indicator reported at present. Thus, we aimed to investigate the association between lipid metabolism level and clinical outcomes, and further develop a novel lipid-based prognostic model in patients with newly-diagnosed mature T and NK cell lymphomas. Methods:The study was performed retrospectively in Shandong Provincial Hospital. The patients were divided to the training cohort (from January 2006 to December 2016) and the prospective validation cohort (from January 2017 to June 2020). The inclusion criteria contain: (1) pathologically confirmed; (2) newly diagnosed; (3) with complete clinical and follow-up data; (4) without previous malignancies. The basic data comparison of the two cohorts was performed by Studentttest or Mann-Whitney U test for continuous variables and the chi-square test or Fisher's exact test for categorical data. Univariate analysis and multivariate Cox regression analysis were performed to detect independent predictors and generate a novel prognostic staging system. The efficiency and accuracy of the new scoring system were assessed in two cohorts from different aspects, including time-dependent receiver operating characteristic curves, Brier score and decision curve analysis. Results:We developed EnBC score from a retrospective 115-patient training cohort using a multivariate Cox regression model and tested it in a prospective 58-patient validation cohort. The score was calculated by the extranodal involved sites, β2-microglobulin and serum total cholesterol (Table 1). EnBC score divided patients into four risk grades, low risk (0 point), low-intermediate risk (1 point), intermediate-high risk (2 points), high risk (3 points) (Table 2). Kaplan-Meier curves proved that patients in four risk grades presented significantly distinct long-term prognoses (median OS, NA vs. NA vs. 14.0 vs. 4.0 months, P&amp;lt;0.0001; median PFS, 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P&amp;lt;0.0001) (Figure 1). Therewith, we examined the efficiency and accuracy of EnBC score in the training and validation cohort, respectively. Its predictive discrimination capacity, as determined by the area under the time-dependent receiver operating characteristic curves, was greater than that of the present commonly used scoring systems (AUCs of OS, EnBC 0.885-0.963 vs. IPI 0.785-0.873 vs. PIT 0.781-0.845; AUCs of PFS, EnBC 0.832-0.922 vs. IPI 0.781-0.842 vs. PIT 0.761-0.799). The Brier score, as an indicator of predictive calibrating performance, was also better or similar to the other models (OS, EnBC 0.146-0.181 vs. IPI 0.155-0.203 vs. PIT 0.167-0.209; PFS, EnBC 0.164-0.189 vs. IPI 0.159-0.183 vs. PIT 0.168-0.190). In addition, the decision curve analysis also proved that EnBC score possessed larger net benefits than IPI and PIT in the entire patient population (Figure 2). Conclusion:We verified for the first time that abnormal serum lipid metabolism level was significantly associated with the prognosis of patients with mature T and NK cell lymphoma. Furthermore, we developed a novel lipid-based EnBC score and proved that this score was more accurate and effective in predicting the prognoses of treat-naïve de novo mature T and NK cell lymphoma patients than other staging systems. This study provided novel evidences for precise prognostic stratification and individualized therapy of mature T and NK cell lymphoma patients. Disclosures No relevant conflicts of interest to declare.

Design of English Translation Computer Intelligent Scoring System Based on Natural Language Processing

With the development and maturity of automatic scoring technology of English composition, the computer-aided composition marking system based on automatic scoring technology has begun to enter colleges and universities to assist English writing teaching. However, there are still many problems in the current scoring system, such as long running time and large deviation of scoring results, which requires us to design an English translation computer intelligent scoring system based on natural language processing. Through the system, we can reduce the workload of manual scoring, which will improve the efficiency of scoring. Therefore, we need to construct the structure of English translation scoring system, including translation data collection module, information feature extraction module, analysis model construction module and result feedback scoring module. By building a language model, the system can translate the probability distribution of specific sentences or word sequences. As an adaptive learning model, BP neural network has more advantages in dealing with the relationship between complex variables. Through BP network model, the system can extract the feature information of translation translation and translation training set. Through fitting calculation, the system will realize the intelligent scoring of English translation.

O01 Adult onset PIMS-TS with secondary haemophagocytic lymphistiocytosis: into the eye of the cytokine storm

O01 Adult onset PIMS-TS with secondary haemophagocytic lymphistiocytosis: into the eye of the cytokine storm

EXPLAINABLE MACHINE LEARNING MODEL FOR PREDICTING GI BLEED MORTALITY IN THE ICU

SESSION TITLE: Critical Care Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: Acute upper and lower gastrointestinal (GI) bleed is a common reason for hospitalization with 2-10% risk of mortality. Several scoring systems for mortality prediction in GI bleed have been developed, however, none of these are considered part of the standard of care. In this study we used machine learning to develop a model to calculate the risk of mortality in critically ill patients admitted for GI bleed and compared it to the traditionally used mortality risk assessment score, APACHE IVa. Since one of the limitations for using machine learning models in practical setting has been lack of physician trust in the model, we utilized explainable methods to provide insight into the model's prediction and outcome. METHODS: We analyzed patient data in the eICU Collective Research Database consisting of critically ill patients and extracted data for 5691 patients (mean age = 67.4 years; 61% males) admitted with GI bleed (upper-, lower- and unknown GI bleed). The data was utilized in training a gradient-boosting machine learning model to identify patients who died in the ICU. We compared the predictive performance of the machine learning model with the APACHE IVa score, a widely accepted risk scoring system for critically ill patients. Performance was measured by area under receiver operating characteristic curve (AUC) analysis. This study also utilizes explainable machine learning methods to provide insights into the model’s outcome prediction using the SHAP (SHapley Additive exPlanations) method. RESULTS: The machine learning model performed better than APACHE IVa risk score in correctly classifying patients who are low risk. The ML model had a specificity of 55% (95% CI: 52 – 64) at sensitivity of 100% compared with APACHE score which had a specificity of 4% (95% CI: 3 –43) at sensitivity of 100%. The model identified patients who died with an AUC of 0.90 (95% CI: 0.93 - 0.86) in the internal validation set while the APACHE IVa clinical scoring systems identified patients who died with AUC values of 0.82 (95% CI: 0.88 - 0.76) with p-value <0.001. CONCLUSIONS: We developed a machine learning model that identifies patients with GI bleed who are at risk of dying with a greater accuracy than current risk scoring systems. We also provide insights into why the model is predicting a certain outcome in order to build trust with physician. CLINICAL IMPLICATIONS: We developed a machine learning model that predicts mortality in patients with GI bleed with a greater AUC than that of the current scoring system. This model could help with identification of critically ill GI bleed patients who are at low risk of mortality and can be moved out of the ICU into a step-down unit for monitoring. By making machine learning model explainable, clinicians would be better able to understand the reasoning behind the outcome and thus would be more likely to implement it in clinical practice to make patient-centered decisions. DISCLOSURES: No relevant relationships by Farah Deshmukh, source=Web Response No relevant relationships by Shamel Merchant, source=Web Response

Determining the reliability of liver biopsies in NASH clinical studies.

Liver biopsy sample evaluation is an essential part of clinical studies in nonalcoholic steatohepatitis (NASH) and is key in excluding confounding morbidities. Current scoring systems, which are decisive for study inclusion, rely on imprecisely defined histological features, leading to a high observer variability of disease categorization. In this News & Views, measures to overcome these limitations are discussed.

The Fluff test: Improved scoring system to account for different degrees of contralesional and ipsilesional personal neglect in brain damaged patients

ABSTRACT The Fluff test is a simple test to assess evidence of personal neglect (PN) in brain-damaged patients. While blindfolded, patients are asked to remove targets previously attached to their body and the number of targets detached provides information about possible spatial bias. This test has been widely used for clinical and research purposes. However, the current scoring system presents some limitations, which make difficult to interpret patients’ performance in terms of both contralalesional and ipsilesional PN when they omit targets on the ipsilesional side. Moreover, it does not consider possible confounding variables, such as non-spatial cognitive deficits or lack of compliance that may affect patients’ performance and lead to incorrect diagnosis. The present paper proposes a new scoring method overcoming the limitations mentioned above and it analyses data from a large sample of 243 brain-damaged patients. Findings showed that contralesional PN was significantly more severe, but not more frequent, following right (31%) than left (21%) brain damage. We also found evidence of left ipsilesional PN and cases of potential mis-diagnosis that would have passed unnoticed with the original scoring system. The new scoring method allows to identify different degrees of contralesional and ipsilesional PN and potential confounding variable.

The fuzzy common vulnerability scoring system (F-CVSS) based on a least squares approach with fuzzy logistic regression

This study presents a new approach for calculations within the Common Vulnerability Scoring System that scoring the effects of vulnerabilities in software on the security status. These calculations is the method that is most commonly used in scoring software vulnerabilities. The present model demonstrates how software security vulnerabilities can be calculated using linguistic terms. Therefore, the proposed method has a more flexible structure than this system. The current Common Vulnerability Scoring System formula and scores were used to assess and implement the presented model. The aim was to form a fuzzy model called the Fuzzy Common Vulnerability Scoring System based on the success probabilities which are defined using linguistic terms such as low, very low or high. Moreover, the Fuzzy Logistic Regression (FLR) method was used to define the relationship between the exact inputs and fuzzy multiple outputs, and the Least Squares Method was used to estimate the parameters of the presented model. The performance of the model was evaluated by a comparison using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Kim and Bishu’s criterion. Validity of the fuzzy regression model is demonstrated with different fitness functions. The expectation was that more practical estimations with better error tolerance can be achieved by using linguistic terms to assess common vulnerabilities.

The impact of the scoring system of a large-scale standardized EFL writing assessment on its score variability and reliability: Implications for assessment policy makers

Using generalizability (G-) theory and rater interviews as research methods, this study examined the impact of the current scoring system of the CET-4 (College English Test Band 4, a high-stakes national standardized EFL assessment in China) writing on its score variability and reliability. One hundred and twenty CET-4 essays written by 60 non-English major undergraduate students at one Chinese university were scored holistically by 35 experienced CET-4 raters using the authentic CET-4 scoring rubric. Ten purposively selected raters were further interviewed for their views on how the current scoring system could impact its score variability and reliability. The G-theory results indicated that the current single-task and single-rater holistic scoring system would not be able to yield acceptable generalizability and dependability coefficients. The rater interview results supported the quantitative findings. Important implications for the CET-4 writing assessment policy in China are discussed.

Apparent diffusion coefficient as a valuable quantitative parameter for predicting clinical outcomes in patients with newly diagnosed primary CNS lymphoma

BackgroundThis study attempted to identify novel prognostic factors in patients with newly diagnosed primary central nervous system lymphoma (PCNSL) using magnetic resonance imaging (MRI).MethodsWe retrospectively evaluated 67 patients diagnosed with central nervous system (CNS) tumors. The enrollment criteria were as follows: i) pathologic diagnosis of CNS lymphoma, ii) no evidence of systemic involvement, iii) no evidence of human immunodeficiency virus-1 infection or other immunodeficiencies, and iv) MRI scans available at diagnosis. Fifty-two patients met these criteria and were enrolled.ResultsThe 3-year overall survival (OS) and failure-free survival rates were 69.7% and 45.6%, respectively, with a median follow-up duration of 36.2 months. OS of patients with low apparent diffusion coefficient (ADC) was lower than those with higher ADC. Multivariate analysis revealed that old age (>60 yr) [hazard ratio (HR), 20.372; P=0.001], Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2 (HR, 10.429; P<0.001), higher lactate dehydrogenase (LDH) levels (HR, 7.408; P=0.001), and low ADC (HR, 0.273; P=0.009) were associated with lower OS. We modified the conventional prognostic scoring system using low ADC, old age (>60 yr), ECOG PS ≥2, and higher LDH. The risk of death was categorized as high (score 3-4), intermediate-2 (score 2), intermediate-1 (score 1), and low (score 0), with three-year OS rates of 33.5%, 55.4%, 88.9%, and 100%, respectively.ConclusionADC demonstrated significant prognostic value for long-term survival in patients with newly diagnosed PCNSL. Low ADC was an independent unfavorable prognostic factor, suggesting that ADC obtained from MRI can improve the current prognostic scoring system.

Predictive Effect of Inflammatory Response and Foot Ulcer Localization on Outcome in Younger and Older Individuals with Infected Diabetic Foot Syndrome.

The diabetic foot syndrome (DFS) is the most important cause for non-traumatic major amputation in adult individuals and actually one of the most frightening events in diabetics' life. Despite the often protracted treatment of infected DFS at the end patients are often confronted with amputation. We investigated 352 individuals with infected DFS in two age separated-groups. Older individuals presented with significant worse renal function and lower HbA1c on day of admittance. Most detected ulcers involved the plantar sides of the metatarsal heads (MTH) and the toes. We saw an age-dependent translocation of foot ulcers from plantar and hindfoot to the forefoot and toes. In average every third wound provoked amputation, in the majority (94%) minor amputations, only 1.9% major amputations occurred. Lesions of the 5th toe or its MTH and interdigital or interphalangeal joint ulcers led to amputation in more than 60%. Worse renal function and WBC above 11 tsd/µl were linked with higher amputation risk. But in particular current scoring systems like SINBAD or Wagner-Armstrong scale and thus finally clinician's assessment of the wound situation gave a substantial hint for subsequent amputation - regardless of age.

Prospective Validation of PREDICT and Its Impact on the Transesophageal Echocardiography Use in Management of Staphylococcus aureus Bacteremia.

Infective endocarditis (IE) is the most feared complication of Staphylococcus aureus bacteremia (SAB). Transesophageal echocardiogram (TEE) is generally recommended for all patients with SAB; however, supporting data for this are limited. We previously developed a scoring system, "PREDICT," that quantifies the risk of IE and identifies patients who would most benefit most from undergoing TEE. The current prospective investigation aims to validate this score. We prospectively screened all consecutive adults (≥18 years) hospitalized with SAB at 3 Mayo Clinic sites between January 2015 and March 2017. Of 220 patients screened, 199 with SAB met study criteria and were included in the investigation. Of them, 23 (11.6%) patients were diagnosed with definite IE within 12 weeks of initial presentation based on modified Duke's criteria. Using the previously derived PREDICT model, the day 1 score of ≥4 had a sensitivity of 30.4% and a specificity of 93.8%, whereas a day 5 score of ≤2 had a sensitivity and negative-predictive value of 100%. Additional factors including surgery or invasive procedure in the past 30 days, prosthetic heart valve, and higher number of positive blood culture bottles in the first set of cultures were associated with increased risk of IE independent of the day 5 risk score. We validated the previously developed PREDICT scoring tools for stratifying risk of IE, and the need for undergoing a TEE, among cases of SAB. We also identified other factors with predictive potential, although larger prospective studies are needed to further evaluate possible enhancements to the current scoring system.

The Significance of Performance-Based Assessment for the Physical Education School Subject According to the Scoring System Used in the Romanian Educational System

The main aim of the present paper is to observe the application of the assessment system within secondary school education in Romania. The study was conducted between 2015 and 2018, in the rural area, the subjects of the study being 7th and 8th grade pupils. Pupils were tested at the beginning and at the end of the school year by using 4 trials chosen from the National Assessment System. PE lessons were conducted during the school year according to the planning documents approved by the school management. Practical activities were focused on the development of motor skills and the learning of new, basic, applicative skills from different sports. We noticed an inconsistency between the pupils' performance and their note at the end of each semester. The average performances obtained in the trials were variable depending on the particularities of each one. The average of the results obtained in all 4 trials was equivalent to note between 6 and 6.5. At the end of each semester the pupils obtained the note 10. The obtained performance has a weight of about 60% of the final note obtained by the pupils. Other scoring factors, which do not have a real foundation or an assessment scale, have contributed to this. They are subjective factors used in order to justify the significant difference between the performance and the final note. The current scoring system is not objective and does not reflect pupils' competencies or their value-based ranking.

Comparison of radiological scoring systems, clinical scores, neutrophil-lymphocyte ratio and serum C-reactive protein level for severity and mortality in acute pancreatitis.

Comparison of radiological scoring systems, clinical scores, neutrophil-lymphocyte ratio and serum C-reactive protein level for severity and mortality in acute pancreatitis BACKGROUND/AIMS To compare radiological scoring systems, clinical scores, serum C-reactive protein (CRP) levels and the neutrophil-lymphocyte ratio (NLR) for predicting the severity and mortality of acute pancreatitis (AP). MATERIALS AND METHODS Demographic, clinical, and radiographic data from 80 patients with AP were retrospectively evaluated. The harmless acute pancreatitis score (HAPS), systemic inflammatory response syndrome (SIRS), bedside index for severity in acute pancreatitis (BISAP), Ranson score, Balthazar score, modified computed tomography severity index (CTSI), extrapancreatic inflammation on computed tomography (EPIC) score and renal rim grade were recorded. The prognostic performance of radiological and clinical scoring systems, NLR at admission, and serum CRP levels at 48 hours were compared for severity and mortality according to the revised Atlanta Criteria. The data were evaluated by calculating the receiver operator characteristic (ROC) curves and area under the ROC (AUROC). RESULTS Out of 80 patients, 19 (23.8%) had severe AP, and 9 (11.3%) died. The AUROC for the BISAP score was 0.836 (95%CI: 0.735-0.937), with the highest value for severity. With a cut-off of BISAP ≥2, sensitivity and specificity were 68.4% and 78.7%, respectively. The AUROC for NLR was 0.915 (95%CI: 0.790-1), with the highest value for mortality. With a cut-off of NLR >11.91, sensitivity and specificity were 76.5% and 94.1%, respectively. Of all the radiological scoring systems, the EPIC score had the highest AUROC, i.e., 0.773 (95%CI: 0.645-0.900) for severity and 0.851 (95%CI: 0.718-0.983) for mortality, with a cut-off value ≥6. CONCLUSION The BISAP score and NLR might be preferred as early determinants of severity and mortality in AP. The EPIC score might be suggested from the current radiological scoring systems.