scholarly journals Which Clinical Scoring Systems Are Most Useful in Showing Severity in COVID-19 Patients?

2021 ◽  
Author(s):  
Ishak San ◽  
Emin Gemcioglu ◽  
Salih Baser ◽  
Nuray Yilmaz Cakmak ◽  
Abdulsamet Erden ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Outcomes ◽  
Predictive Value ◽  
Independent Predictor ◽  
Severe Disease ◽  
Scoring Systems ◽  
High Risk Group ◽  
World Health ◽  
Severe Group ◽  
Clinical Scoring

Abstract IntroductionIn this study, we compare the predictive value of clinical scoring systems that are already in use in patients with COVID-19, including the BCRSS, qSOFA, SOFA, MuLBSTA and HScore, for determining the severity of the disease. Our aim in this study is to determine which scoring system is most useful in determining disease severity and to guide clinicians.Materials and MethodsWe classified the patients into two groups according to the stage of the disease (severe and non-severe) by using the slightly modified and adopted interim guidance of the World Health Organization. Severe cases were divided into a group of surviving patients and a deceased group according to the prognosis. According to admission values, the BCRSS, qSOFA, SOFA, MuLBSTA, and HScore were evaluated at admission using the worst parameters available in the first 24 hours.ResultsOf the 417 patients included in our study, 46 (11%) were in the severe group, while 371 (89%) were in the non-severe group. Of these 417 patients, 230 (55.2%) were men. The median (IQR) age of all patients was 44 (25) years. In multivariate logistic regression analyses, BRCSS in the highest tertile (HR: 6.1, 95% CI: 2.105–17.674, p = 0.001) was determined as an independent predictor of severe disease in cases of COVID-19. In multivariate analyses, qSOFA was also found to be an independent predictor of severe COVID-19 (HR: 4.757, 95% CI: 1.438–15.730, p = 0.011). The area under the curve (AUC) of the BRCSS, qSOFA, SOFA, MuLBSTA, and HScore was 0.977, 0.961, 0.958, 0.860, and 0.698, respectively.ConclusionCalculation of the BRCSS and qSOFA at the time of hospital admission can predict critical clinical outcomes in patients with COVID-19, and their predictive value is superior to that of HScore, MuLBSTA, and SOFA. With early identification of the high-risk group using BRCSS and qSOFA, early interventions for high-risk patients can improve clinical outcomes in COVID-19.

scholarly journals Brescia-COVID Respiratory Severity Scale (BRCSS) and Quick SOFA (qSOFA) score are most useful in showing severity in COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ishak San ◽  
Emin Gemcioglu ◽  
Salih Baser ◽  
Nuray Yilmaz Cakmak ◽  
Abdulsamet Erden ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Outcomes ◽  
Predictive Value ◽  
Scoring System ◽  
Independent Predictor ◽  
Severe Disease ◽  
World Health ◽  
Smoking History ◽  
Severity Scale ◽  
Severe Group

AbstractIn this study, we compare the predictive value of clinical scoring systems that are already in use in patients with Coronavirus disease 2019 (COVID-19), including the Brescia-COVID Respiratory Severity Scale (BCRSS), Quick SOFA (qSOFA), Sequential Organ Failure Assessment (SOFA), Multilobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension, and Age (MuLBSTA) and scoring system for reactive hemophagocytic syndrome (HScore), for determining the severity of the disease. Our aim in this study is to determine which scoring system is most useful in determining disease severity and to guide clinicians. We classified the patients into two groups according to the stage of the disease (severe and non-severe) and adopted interim guidance of the World Health Organization. Severe cases were divided into a group of surviving patients and a deceased group according to the prognosis. According to admission values, the BCRSS, qSOFA, SOFA, MuLBSTA, and HScore were evaluated at admission using the worst parameters available in the first 24 h. Of the 417 patients included in our study, 46 (11%) were in the severe group, while 371 (89%) were in the non-severe group. Of these 417 patients, 230 (55.2%) were men. The median (IQR) age of all patients was 44 (25) years. In multivariate logistic regression analyses, BRCSS in the highest tertile (HR 6.1, 95% CI 2.105–17.674, p = 0.001) was determined as an independent predictor of severe disease in cases of COVID-19. In multivariate analyses, qSOFA was also found to be an independent predictor of severe COVID-19 (HR 4.757, 95% CI 1.438–15.730, p = 0.011). The area under the curve (AUC) of the BRCSS, qSOFA, SOFA, MuLBSTA, and HScore was 0.977, 0.961, 0.958, 0.860, and 0.698, respectively. Calculation of the BRCSS and qSOFA at the time of hospital admission can predict critical clinical outcomes in patients with COVID-19, and their predictive value is superior to that of HScore, MuLBSTA, and SOFA. Our prediction is that early interventions for high-risk patients, with early identification of high-risk group using BRCSS and qSOFA, may improve clinical outcomes in COVID-19.

scholarly journals 688 Pediatric Obstructive Sleep Apnea (OSA) and COVID-19-Related Adverse Clinical Outcomes

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A269-A269
Author(s):  
Vaishal Shah ◽  
Nancy Foldvary-Schaefer ◽  
Lu Wang ◽  
Lara Jehi ◽  
Cynthia Pena Obrea ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Outcome ◽  
Clinical Outcomes ◽  
Pediatric Patients ◽  
Control Design ◽  
Supplemental Oxygen ◽  
Case Control ◽  
World Health ◽  
Invasive Ventilation ◽  
High Flow Oxygen

Abstract Introduction The relationship of OSA and human coronavirus (COVID-19) in the pediatric population is unknown. We postulate that OSA is associated with SARS-CoV-2 positivity and with adverse COVID-19 outcomes in children. Methods A retrospective review of 120 consecutive patients (<18 years) with prior polysomnogram (PSG) and COVID-19 testing from the Cleveland Clinic COVID-19 registry was conducted. Using a case control design of SARS-CoV-2 positive and negative pediatric patients, we examined COVID-19 and pre-existing OSA (dichotomized AHI≥1) using logistic (OR,95%CI) regression and as continuous measures: AHI, oxygen(SpO2) nadir, %time SpO2<90%) using linear regression(beta+/-SE). In those positive for SARS-CoV-2(cases only), we assessed the association of OSA and World Health Organization(WHO) COVID-19 clinical outcome composite score (hospitalization, requiring supplemental oxygen, non-invasive ventilation/high-flow oxygen, invasive ventilation/ECMO or death) using Wilcoxon rank sum test for ordinal data. Results Cases (n=36) were 11.8±4.4 years, 61% male, 27.8% black and 88.9% with OSA, while 85.7% of controls (n=84) had OSA. OSA was not associated with increased SARS-CoV-2 positivity: OR=1.33(0.40, 4.45,p=0.64). No significant difference between cases and controls for mean AHI 3.7(1.5,6.0) vs 3.5(1.5,7.1),p=0.91,SpO2 nadir 88.6±5.4 vs 89.1±4.4,p=0.58,%time SpO2<90% 0.05[0.00,1.00) vs 0.10 (0.00,1.00, p=0.65) respectively was noted. WHO-7 COVID-19 clinical outcome did not meet statistical significance in relation to OSA due to the low event frequency (p=0.49). Of note, those with OSA vs without OSA had a higher WHO-7 outcome score of 2 vs 0 and prevalence of hospitalization: 12.5 vs 0% respectively. Of hospitalized patients, the following was observed: 23% had moderate/severe OSA vs 4.3% mild OSA, 50% required supplemental oxygen and 25% required intubation/invasive ventilation. No deaths or readmissions were reported. High risk conditions included: 75% obesity, 50% asthma, 25% sickle cell disease and 25% hypoplastic left heart. Conclusion In this first report of which we are aware focused on COVID-19 in pediatric OSA, we use a case control design leveraging COVID-19 and sleep laboratory registries. Albeit not statistically significant, pediatric patients with OSA had a higher percentage of worse clinical outcomes. Larger network studies are needed to clarify whether poorer COVID-19 outcomes may be attributable to OSA or modulated via high risk health conditions. Support (if any):

scholarly journals Early Prediction of Multiple Organ Dysfunction in the Pediatric Intensive Care Unit

2021 ◽  
Vol 9 ◽  
Author(s):  
Sanjukta N. Bose ◽  
Joseph L. Greenstein ◽  
James C. Fackler ◽  
Sridevi V. Sarma ◽  
Raimond L. Winslow ◽  
...  
Keyword(s):  
High Risk ◽  
Random Forest ◽  
Positive Predictive Value ◽  
Organ Dysfunction ◽  
Predictive Value ◽  
Prediction Models ◽  
Pediatric Intensive Care ◽  
Multiple Organ ◽  
High Risk Group ◽  
Early Prediction

Objective: The objective of the study is to build models for early prediction of risk for developing multiple organ dysfunction (MOD) in pediatric intensive care unit (PICU) patients.Design: The design of the study is a retrospective observational cohort study.Setting: The setting of the study is at a single academic PICU at the Johns Hopkins Hospital, Baltimore, MD.Patients: The patients included in the study were <18 years of age admitted to the PICU between July 2014 and October 2015.Measurements and main results: Organ dysfunction labels were generated every minute from preceding 24-h time windows using the International Pediatric Sepsis Consensus Conference (IPSCC) and Proulx et al. MOD criteria. Early MOD prediction models were built using four machine learning methods: random forest, XGBoost, GLMBoost, and Lasso-GLM. An optimal threshold learned from training data was used to detect high-risk alert events (HRAs). The early prediction models from all methods achieved an area under the receiver operating characteristics curve ≥0.91 for both IPSCC and Proulx criteria. The best performance in terms of maximum F1-score was achieved with random forest (sensitivity: 0.72, positive predictive value: 0.70, F1-score: 0.71) and XGBoost (sensitivity: 0.8, positive predictive value: 0.81, F1-score: 0.81) for IPSCC and Proulx criteria, respectively. The median early warning time was 22.7 h for random forest and 37 h for XGBoost models for IPSCC and Proulx criteria, respectively. Applying spectral clustering on risk-score trajectories over 24 h following early warning provided a high-risk group with ≥0.93 positive predictive value.Conclusions: Early predictions from risk-based patient monitoring could provide more than 22 h of lead time for MOD onset, with ≥0.93 positive predictive value for a high-risk group identified pre-MOD.

scholarly journals Adnexal mass risk assessment: a multivariate index assay for malignancy risk stratification

2019 ◽  
Vol 15 (33) ◽  
pp. 3783-3795
Author(s):  
Zhen Zhang ◽  
Rowan G Bullock ◽  
Herbert Fritsche
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Risk Stratification ◽  
Predictive Value ◽  
Adnexal Mass ◽  
Clinical Performance ◽  
Risk Group ◽  
High Risk Group ◽  
Adnexal Masses ◽  
Immediate Surgery

Aims: Adnexal mass risk assessment (AMRA) stratifies patients with adnexal masses, identifying the relatively small number of malignancies from benigns which might take a ‘watchful waiting’ approach. Methods: AMRA uses seven biomarkers and derived from women with adnexal masses scheduled for surgery. Estimated clinical performance was calculated using fixed prevalence. Results: At 5% prevalence, the high-risk group, 7.9% total, captured 75.9% of invasive malignancies at a positive predictive value of 35.8%. High risk/intermediate risk combined had a sensitivity of 89.7 and 95.6% for pre- and post-menopausal cancers, respectively. The low-risk group, 67.8% total, had an negative predictive value of 99.0%. Conclusion: With highly differentiating risk stratification capability across histological subtypes and stages, AMRA is potentially applicable to patients with adnexal masses to assist deciding whether immediate surgery is recommended.

scholarly journals Donorszelekciós kritériumok vizsgálata a debreceni veseátültetési programban

2016 ◽  
Vol 157 (24) ◽  
pp. 946-955
Author(s):  
Gergely Zádori ◽  
Vera Tarjányi ◽  
Réka P. Szabó ◽  
Lajos Zsom ◽  
Roland Fedor ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Index ◽  
Graft Function ◽  
Scoring Systems ◽  
Deceased Donor ◽  
Risk Groups ◽  
Favourable Outcome ◽  
High Risk Group ◽  
Organ Shortage ◽  
Kidney Transplantations

Introduction: To ease organ shortage many transplant centres developed different donor scoring systems, however, a general consensus among clinicians on the use of these systems does not still exist. Aim: The aim of the authors was to analyse the effect of expanded criteria donor, deceased donor score and kidney donor risk index on postoperative kidney function and graft survival. Method: Analysis of the characteristics of 138 kidney transplantations and 205 donors in a retrospective study of a five-year period. Results: There was a trend towards rejecting donors in higher risk groups; 22.7% of standard criteria donors belonged to the high risk group of deceased donor score. Graft function was worse in high risk patients. High risk donors can be divided due to the use of deceased donor score. Patients with the highest risk had worse graft function and survival. Conclusions: With the use of these scoring systems grafts with favourable outcome can be selected more precisely. Orv. Hetil., 2016, 157(24), 946–955.

scholarly journals Negative latent tuberculosis at time of incarceration: identifying a very high-risk group for infection

2017 ◽  
Vol 145 (12) ◽  
pp. 2491-2499 ◽  
Author(s):  
L. ARROYAVE ◽  
Y. KEYNAN ◽  
L. LÓPEZ ◽  
D. MARIN ◽  
M. P. ARBELÁEZ ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Latent Tuberculosis ◽  
Risk Groups ◽  
High Risk Group ◽  
World Health ◽  
Formerly Incarcerated ◽  
Adjusted Risk ◽  
Number Needed To Screen ◽  
Health Organization

SUMMARYThe main aim was to measure the incidence of latent tuberculosis infection (LTBI) and identify risk factors associated with infection. In addition, we determined the number needed to screen (NNS) to identify LTBI and active tuberculosis. We followed 129 prisoners for 2 years following a negative two-step tuberculin skin test (TST). The cumulative incidence of TST conversion over 2 years was 29·5% (38/129), among the new TST converters, nine developed active TB. Among persons with no evidence of LTBI, the NNS to identify a LTBI case was 3·4 and an active TB case was 14·3. The adjusted risk factors for LTBI conversion were incarceration in prison number 1, being formerly incarcerated, and overweight. In conclusion, prisoners have higher risk of LTBI acquisition compared with high-risk groups, such as HIV-infected individuals and children for whom LTBI testing should be performed according to World Health Organization guidance. The high conversion rate is associated with high incidence of active TB disease, and therefore we recommend mandatory LTBI screening at the time of prison entry. Individuals with a negative TST at the time of entry to prison are at high risk of acquiring infection, and should therefore be followed in order to detect convertors and offer LTBI treatment. This approach has a very low NNS for each identified case, and it can be utilized to decrease development of active TB disease and transmission.

scholarly journals A clinical scoring system for predicting tumor recurrence after percutaneous radiofrequency ablation for 3 cm or less hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Zhu He ◽  
Kun He ◽  
Rui Qin Huang ◽  
Li Wen Liu ◽  
Shao Wei Ye ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Tumor Recurrence ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Derivation Cohort ◽  
Medium Risk ◽  
Clinical Scoring

AbstractPreoperative prediction of tumor recurrence after radiofrequency ablation (RFA) in patients with early hepatocellular carcinoma (HCC) is helpful for clinical decision-making before treatment. A total of 162 patients with HCC of 3 cm or less who were completely ablated by percutaneous RFA were divided into a derivation cohort (n = 108) and a validation cohort (n = 54). Based on X-Tiles software, Kaplan–Meier curve analysis and COX multivariate analysis to obtain valuable predictive indicators, a clinical scoring system for predicting tumor recurrence was established. In the verall cohort, derivation cohort and validation cohort, we found circulating tumor cells (CTC) > 2/3.2 mL, alpha-fetoprotein (AFP) > 20 ng/mL, and des-γ-carboxyprothrombin (DCP) > 40 mAU/mL, maximum tumor diameter > 20 mm, and the number of multiple tumors (≥ 2) are independent risk factors affecting tumor recurrence. Each independent risk factor was assigned a score of 1 to construct a predictive clinical scoring system, and X-Tiles software was used to divide the clinical score into a low-risk group (0 score–1 score), a medium-risk group (2 scores–3 scores), and a high-risk group (4 scores–5 scores). The cumulative tumor recurrence rates of patients in the low-risk group, middle-risk group, and high-risk group in 1 year, 2 years, and 3 years were 19.4%/27.5%/30.9%, 37.0%/63.2%/79.9% and 68.2%/100%/100%, respectively (Low-risk group vs medium-risk group: P < 0.001; medium-risk group vs high-risk group: P < 0.001). This clinical scoring system can predict the prognosis of patients with HCC of 3 cm or smaller undergoing percutaneous RFA, which has certain application value for making preoperative clinical decisions.

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