scholarly journals Evaluation of Severity of Illness Scores in the Pediatric ECMO Population

2021 ◽  
Vol 9 ◽  
Author(s):  
Venessa L. Pinto ◽  
Danielle Guffey ◽  
Laura Loftis ◽  
Melania M. Bembea ◽  
Philip C. Spinella ◽  
...  
Keyword(s):  
Retrospective Cohort ◽  
Pediatric Patients ◽  
Area Under The Curve ◽  
Severity Of Illness ◽  
Roc Curves ◽  
Operating Characteristics ◽  
Logistic Organ Dysfunction ◽  
Risk Of Mortality ◽  
Pediatric Icu ◽  
Pediatric Index Of Mortality

Though commonly used for adjustment of risk, severity of illness and mortality risk prediction scores, based on the first 24 h of intensive care unit (ICU) admission, have not been validated in the pediatric extracorporeal membrane oxygenation (ECMO) population. We aimed to determine the association of Pediatric Index of Mortality 2 (PIM2), Pediatric Risk of Mortality Score III (PRISM III) and Pediatric Logistic Organ Dysfunction (PELOD) scores with mortality in pediatric patients on ECMO. This was a retrospective cohort study of children ≤18 years of age included in the Pediatric ECMO Outcomes Registry (PEDECOR) from 2014 to 2018. Logistic regression and Receiver Operating Characteristics (ROC) curves were used to calculate the area under the curve (AUC) to evaluate association of mortality with the scores. Of the 655 cases, 289 (44.1%) did not survive until hospital discharge. AUCs for PIM2, PRISM III, and PELOD predicting mortality were 0.52, 0.52, and 0.51 respectively. PIM2, PRISM III, and PELOD scores are not associated with odds of mortality for pediatric patients receiving ECMO. These scores for a general pediatric ICU population should not be used for prognostication or risk stratification of a select population such as ECMO patients.

scholarly journals MicroRNAs Which Can Prognosticate Aggressiveness of Bladder Cancer

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1551 ◽  
Author(s):  
Edyta Marta Borkowska ◽  
Tomasz Konecki ◽  
Michał Pietrusiński ◽  
Maciej Borowiec ◽  
Zbigniew Jabłonowski
Keyword(s):  
Bladder Cancer ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Control Group ◽  
Low Grade ◽  
Operating Characteristics ◽  
High Death Rate ◽  
Biological Potential ◽  
High Death ◽  
Muscle Invasive

Bladder cancer (BC) is still characterized by a very high death rate in patients with this disease. One of the reasons for this is the lack of adequate markers which could help determine the biological potential of the tumor to develop into its invasive stage. It has been found that some microRNAs (miRNAs) correlate with disease progression. The purpose of this study was to identify which miRNAs can accurately predict the presence of BC and can differentiate low grade (LG) tumors from high grade (HG) tumors. The study included 55 patients with diagnosed bladder cancer and 30 persons belonging to the control group. The expression of seven selected miRNAs was estimated with the real-time PCR technique according to miR-103-5p (for the normalization of the results). Receiver operating characteristics (ROC) curves and the area under the curve (AUC) were used to evaluate the feasibility of using selected markers as biomarkers for detecting BC and discriminating non-muscle invasive BC (NMIBC) from muscle invasive BC (MIBC). For HG tumors, the relevant classifiers are miR-205-5p and miR-20a-5p, whereas miR-205-5p and miR-182-5p are for LG (AUC = 0.964 and AUC = 0.992, respectively). NMIBC patients with LG disease are characterized by significantly higher miR-130b-3p expression values compared to patients in HG tumors.

scholarly journals Predicting PICU patient survival prognosis: Pediatric Logistic Organ Dysfunction vs Pediatric Index of Mortality scores

2012 ◽  
Vol 52 (3) ◽  
pp. 165 ◽  
Author(s):  
Edwina Winiarti ◽  
Muhammad Sholeh Kosim ◽  
Mohammad Supriatna
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Pediatric Intensive Care ◽  
Scoring Systems ◽  
Survival Prognosis ◽  
Logistic Organ Dysfunction ◽  
Risk Of Mortality ◽  
Sensitivity Specificity ◽  
Pediatric Index Of Mortality

Background Determining prognosis of patients using scoringsystems have been done in many pediatric intensive care units(PICU). The scoring systems frequently used are pediatric logisticorgan dy sfunction (PELOD), pediatric index of mortality (PIM)and pediatric risk of mortality (PRISM).Objective To compare the performance of PELOD and PIM scoresin predicting the prognosis of survival vs death in PICU patients.Methods A prognostic test in this prospective, cohort study wasconducted in the PICU of the Kariadi General Hospital, Semarang.PELOD and PIM calculations were performed using formulae frompreviously published articles. Statistical analyses included receiveroperating curve (ROC) characteristics to describe discriminationcapacity, sensitivity, specificity, positive predictive value, negativepredictive value and accuracy.Results Thirty-three patients fulfilling the inclusion criteria wereenrolled in the study. PELOD score for area under the ROCwas 0.87 (95% CI 0.73 to 1.0; P=0.003), while that for PIMwas 0.65 (95% CI 0.39 to 0.90; P=0.2). PELOD scores showedsensitivity 85.7% (95% CI 59.8 to 100), specificity 84.6% (95%CI 70.7 to 98.5), positive predictive value 60.0% (95% CI 29.6to 90.4) negative predictive value 95.6% (95% CI 87.3 to 100)and accuracy 84.8%. PIM scores showed sensitivity 85.7% (95%CI 59.8 to 100), specificity 50.0% (95% CI 30.8 to 69.2), positivepredictive value 31.6% (95% CI 10,7 to 52.5), negative predictivevalue 92.9% (95% CI 79.4 to 100) and accuracy 57.6%.Conclusion PELOD scoring had better specificity, positive predictivevalue, negative predictive value, accuracy and discrimination capacitythan PIM scoring for predicting the survival prognosis of patients inthe PICU. [Paediatr Indones. 2012;52:165-9].

Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs

2021 ◽  
pp. 20200513
Author(s):  
Su-Jin Jeon ◽  
Jong-Pil Yun ◽  
Han-Gyeol Yeom ◽  
Woo-Sang Shin ◽  
Jong-Hyun Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cone Beam Ct ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Learning System ◽  
Operating Characteristics ◽  
Panoramic Radiographs ◽  
Test Sets ◽  
Sensitivity Specificity ◽  
Deep Learning Model

Objective: The aim of this study was to evaluate the use of a convolutional neural network (CNN) system for predicting C-shaped canals in mandibular second molars on panoramic radiographs. Methods: Panoramic and cone beam CT (CBCT) images obtained from June 2018 to May 2020 were screened and 1020 patients were selected. Our dataset of 2040 sound mandibular second molars comprised 887 C-shaped canals and 1153 non-C-shaped canals. To confirm the presence of a C-shaped canal, CBCT images were analyzed by a radiologist and set as the gold standard. A CNN-based deep-learning model for predicting C-shaped canals was built using Xception. The training and test sets were set to 80 to 20%, respectively. Diagnostic performance was evaluated using accuracy, sensitivity, specificity, and precision. Receiver-operating characteristics (ROC) curves were drawn, and the area under the curve (AUC) values were calculated. Further, gradient-weighted class activation maps (Grad-CAM) were generated to localize the anatomy that contributed to the predictions. Results: The accuracy, sensitivity, specificity, and precision of the CNN model were 95.1, 92.7, 97.0, and 95.9%, respectively. Grad-CAM analysis showed that the CNN model mainly identified root canal shapes converging into the apex to predict the C-shaped canals, while the root furcation was predominantly used for predicting the non-C-shaped canals. Conclusions: The deep-learning system had significant accuracy in predicting C-shaped canals of mandibular second molars on panoramic radiographs.

scholarly journals Predicting Outcome in Mechanically Ventilated Pediatric Patients

2019 ◽  
Vol 09 (02) ◽  
pp. 092-098
Author(s):  
Selman Kesici ◽  
Şenay Kenç ◽  
Ayşe Filiz Yetimakman ◽  
Benan Bayrakci
Keyword(s):  
Respiratory Failure ◽  
Mortality Risk ◽  
Pediatric Patients ◽  
Oxygenation Index ◽  
Mortality Rates ◽  
Mechanically Ventilated ◽  
Risk Of Mortality ◽  
Predicting Outcome ◽  
Expected Mortality ◽  
Pediatric Index Of Mortality

AbstractTo apply and determine whether standardized mortality scores are appropriate to predict the risk of mortality in mechanically ventilated pediatric patients, 150 patients were retrospectively evaluated. Pediatric risk of mortality (PRISM) III-24 and pediatric index of mortality (PIM)-2 scores were unable to discriminate survivors and nonsurvivors; the observed mortality rate was lower than expected mortality rates. Oxygenation index (OI) was calculated at 0, 12, 24, and 72 hours of ventilation. OI-12 and OI-72 were found to be higher in nonsurvivors. PRISM III-24 and PIM-2 scores failed to predict mortality risk in mechanically ventilated pediatric patients. OI can be used to predict degree of respiratory failure and mortality risk.

Off-Hours Admissions and Mortality in PICU Without 24-Hour Onsite Intensivist Coverage

2018 ◽  
Vol 35 (7) ◽  
pp. 694-699 ◽  
Author(s):  
Farah Chedly Thabet ◽  
Faisal Ahmed alHaffaf ◽  
Iheb Mohamed Bougmiza ◽  
Hend Ali Bafaqih ◽  
May Said Chehab ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Severity Of Illness ◽  
Pediatric Intensive Care ◽  
Icu Stay ◽  
Risk Of Mortality ◽  
Public Holidays ◽  
Time Of Admission ◽  
Pediatric Icu ◽  
Length Of Icu Stay

Objective: To evaluate whether the off-hours admission has any effect on risk-adjusted mortality and length of stay for nonelective patients admitted to a pediatric intensive care unit (PICU) without 24-hour in-house intensivist coverage. Design: Prospective cohort study. Setting: A 34-bed tertiary PICU. Patients: All consecutive nonelective patients aged 0 to 14 years admitted from January 2012 to June 2015. Measurements and Main Results: A total of 1254 patients were nonelectively admitted to the PICU. They were categorized according to time of PICU admission as either office hours (07:30 to 16:30 from Sunday to Thursday and whenever an intensivist is present in the ICU) or off-hours (16:30 to 07:30, Friday and Saturday and public holidays). Standardized mortality rates (SMRs) of patients admitted during off-hours were compared to SMRs of patients admitted during office hours using Pediatric Risk of Mortality (PRISM2) score. Multivariate logistic regression was used to assess the effect of time of admission on outcome after adjustment for severity of illness using the PRISM2. The mortality observed in the office-hours group was 9.4% and in the off-hours group was 8.1%. The PRISM2-based SMR was 0.83 (95% confidence interval [CI]: 0.43-1.47) for the office-hours group and 0.68 (95% CI: 0.34-1.36) for the off-hours group. No significant differences in length of ICU stay or duration of mechanical ventilation were observed between patients admitted during off-hours and those admitted during office hours. In the logistic regression model, off-hours admission was not significantly associated with a higher mortality (odds ratio: 0.85, 95% CI: 0.57-1.27; P = .44). Conclusions: The absence of an in-house intensivist during off-hours is not associated with an increase in mortality, length of ICU stay, or duration of mechanical ventilation for patients admitted to our pediatric ICU.

scholarly journals Association between metabolic indicators and clinical endometritis during the transition period in Brown Swiss cows

2021 ◽  
Vol 77 (05) ◽  
pp. 6524-2021
Author(s):  
MURAT ONUR YAZLIK ◽  
HATICE ESRA COLAKOGLU ◽  
MERT PEKCAN ◽  
UFUK KAYA ◽  
SERDAL KURT ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Transition Period ◽  
Area Under The Curve ◽  
Subsequent Development ◽  
Roc Curves ◽  
Nefa Concentration ◽  
Operating Characteristics ◽  
Brown Swiss ◽  
Metabolite Profiles ◽  
The Relationship

The objective of the current study was to evaluate the relationship between the serum macromineral, metabolite profiles, and the clinical endometritis during the transition period in Brown Swiss dairy cows. Sixty Brown Swiss dairy cows were used in the present study. Blood samples collected at d 10 (± 4) antepartum and 3, 10 and 30 (± 4) days in milk (DIM) to determine calcium (Ca), phosphorus, glucose, cholesterol, non-esterified fatty acid (NEFA) levels. Beta-hydroxybutyric acid (BHB) concentration measured during the postpartum period. Receiver operating characteristics (ROC) curves were used to determine the cow-level thresholds for the subsequent development of clinical endometritis. In addition, pairwise comparisons were made of the area under the curve (AUC) of ROC curves for the thresholds of NEFA, Ca, and glucose predicting clinical endometritis. The mean Ca concentration at 3 DIM was 8.85 ± 0.20 mg/dL in healthy cows compared to 8.30 ± 0.22 mg/dL in cows that subsequently developed endometritis (P < 0.05). NEFA concentrations at 10 DIM and BHB concentration at 10 and 30 ± 4 DIM were higher (P < 0.05) in cows that subsequently developed endometritis. Serum NEFA concentration at 10 days postpartum is the best predictor for diagnosis of clinical endometritis with the AUC values of 0.741. The cows with clinical endometritis also had significantly higher values of glucose at 3 DIM and lower BCS at 10 DIM (P < 0.05). While 58.6% of the cows that developed clinical endometritis were cyclic, 64.5% were cyclic in healthy cows at 30 ± 4 DIM. Serum NEFA concentration was the only risk factor for clinical endometritis at 10 DIM. In addition, a decrease in serum Ca at 3 DIM and increase in NEFA and BHB concentrations at 10 and 30 ± 4 DIM may be associated with clinical endometritis and delayed resumption activity on the ovaries.

scholarly journals Optimized Combination of Circulating Biomarkers as Predictors of Prognosis in AECOPD Patients Complicated with Heart Failure

2020 ◽  
Author(s):  
Can Yao ◽  
Lingwei Wang ◽  
Fei Shi ◽  
Rongchang Chen ◽  
Binbin Li ◽  
...  
Keyword(s):  
Heart Failure ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Chronic Obstructive ◽  
Circulating Biomarkers ◽  
Operating Characteristics ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Survivor Group ◽  
Significant Difference

Abstract BackgroundSystematic inflammation, nutritional status, and cardiovascular function have been associated with the outcomes of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients with heart failure (HF). However, the value of their relevant biomarkers in predicting mortality has not been well defined yet. We aimed to investigate the prognostic value of circulating biomarkers including C-reaction protein (CRP) /albumin (ALB), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and N-terminal pro-brain natriuretic peptide (NT-proBNP) for AECOPD patients with HF.Methods A total of 146 cases of AECOPD complicated with HF were enrolled and classified into survivor group (n=94) and non-survivor group (n=52). The baseline characteristics and blood-based biomarkers were collected. The predictors for prognosis were analyzed by multivariate logistic regression, and the ability to predict 28-day mortality was evaluated by receiver operating characteristics curve (ROC) and the area under the curve (AUC).ResultsThe patients in non-survivors had significantly higher levels of CRP, CRP/ALB, NLR, PCT and NT-proBNP, but lower ALB levels compared to the survivors [145.8±110.1 VS. 66.6±70.2mg/L, 5.9±4.9 VS. 2.3±2.6, 22.2 (11.1, 40.1) VS. 12.0 (6.2, 24.8), 2.6 (0.2, 10.3) VS. 0.08 (0.1, 0.5)ng/ml, 17912.5 (9344.0, 34344.5) VS. 9809.0 (4415.9, 16387.2)ng/ml, 26.8±6.4 VS. 31.0±4.6g/L; P < 0.001, <0.001, 0.001, <0.001, <0.001, and < 0.001, respectively]. No significant difference in PLR was found between the two groups (P=0.413). The logistic analysis revealed that CRP/ALB (OR=1.303, 95%CI: 1.145-1.483, P<0.001), NT-proBNP (OR=1.041, 95%CI: 1.010-1.073, P=0.009) and NLR (OR=1.010, 95%CI: 0.999-1.022, P<0.001) are independent risk factors for predicting the 28-day mortality. The AUC of the ROC curves were 0.768, 0.767, 0.757, 0.723, 0.716, and 0.668 for CRP/ALB, PCT, CRP, NT-proBNP, ALB, and NLR, respectively. The combination of CRP/ALB, NLR and NT-proBNP as biomarkers was shown to have better accuracy for predicting prognosis (AUC=0.830, 95%CI: 0.761-0.899, P<0.001), with a higher specificity of 80.8% and specificity of 77.7% as compared with each single biomarkers.ConclusionsHigh levels of NLR, CRP/ALB and NT-proBNP may be clinical usefully predictors for death in AECOPD patients with HF. Combination of NLR with CRP/ALB and NT-proBNP can provide a higher accuracy for predicting 28-day mortality in these patients.

Retrospective Evaluation Of The Accuracy Of Five Different Severity Scores To Predict The Mortality In Burns Patients

2021 ◽  
Author(s):  
Viviane Fernandes de Carvalho ◽  
André Oliveira Paggiaro ◽  
Alexandre Goldner ◽  
Rolf Gemperli
Keyword(s):  
Characteristic Curve ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Severity Index ◽  
Apache Ii ◽  
Saps Ii ◽  
Logistic Organ Dysfunction ◽  
Severity Scores ◽  
Clinical Impairment ◽  
Extensive Burns

Abstract Background Patients with great clinical impairment, due to extensive burns, need to be admitted to intensive care units, in these treatment sites, indices are used to classify the severity of patients. The aim of the study was to compare the accuracy of the FLAMES score in relation to the Acute Physiologic and Chronic Health Evaluation II (APACHE II), the Simplified Acute Physiologic Score II (SAPS II), the Logistic Organ Dysfunction System (LODS) and the Abbreviated Burn Severity Index (ABSI) applied to the severe burn patient facing mortality in an ICU of a reference center for burns in Brazil. Methods A retrospective study conducted in ICU comparing the accuracy the APACHE II, SAPS II, LODS, ABSI and FLAMES instruments were applied to all the selected medical records. To evaluate the accuracy of the SIs, the Receiver Operating Characteristic curve was calculated and the area under the curve (AUC). Results Among the 574 patients included in the study, male individuals (70.13%), with an average age of 44.01 ± 28.64 prevailed and the majority of the burns were caused by accidents (76.53%). The outcome accounted for 35.29% of deaths. It was observed that the FLAMES and ABSI presented the two largest areas under the ROC curves and the highest sensitivities (96% and 89%, respectively). The APACHE II, SAPS II and LODS presented sensitivities equal to or greater than 80%. Conclusions It has been demonstrated that indices specifically developed for burn patients, specifically the FLAMES and ABSI indices, presented better accuracies and prediction performances.

Sign in / Sign up

Export Citation Format

Share Document