Quick COVID-19 Severity Index Research Articles

Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study

A myriad of early warning scores (EWSs) exist, yet there is a need to identify the most clinically valid score to be used in prehospital respiratory assessments to estimate short-term and midterm mortality, intensive-care unit admission, and airway management in life-threatening acute respiratory distress. This is a prospective, observational, multicentre, ambulance-based, external validation study performed in 44 ambulance services and four hospitals across three Spanish provinces (ie, Salamanca, Segovia, and Valladolid). We identified adults (ie, those aged 18 years and older) discharged to the emergency department with suspected acute respiratory distress. The primary outcome was 2-day all-cause in-hospital mortality, for all the patients or according to prehospital respiratory conditions, including dyspnoea, chronic obstructive pulmonary disease (COPD), COVID-19, other infections, and other conditions (asthma exacerbation, haemoptysis, and bronchoaspirations). 30-day mortality, intensive-care unit admission, and invasive and non-invasive mechanical ventilation were secondary outcomes. Eight EWSs, namely, the National Early Warning Score 2, the Modified Rapid Emergency Medicine Score, the Rapid Acute Physiology Score, the Quick Sequential Organ Failure Assessment Score, the CURB-65 Severity Score for Community-Acquired Pneumonia, the BAP-65 Score for Acute Exacerbation of COPD, the Quick COVID-19 Severity Index, and the Modified Sequential Organ Failure Assessment (mSOFA), were explored to determine their predictive validity through calibration, clinical net benefit as determined through decision curve analysis, and discrimination analysis (area under the curve of the receiver operating characteristic [AUROC], compared with Delong's test). Between Jan 1, 2020, and Nov 31, 2022, 902 patients were enrolled. The global 2-day mortality rate was 87 (10%); in proportion to various respiratory conditions, the rates were 35 (40%) for dyspnoea, nine (10%) for COPD, 13 (15%) for COVID-19, 28 (32%) for other infections, and two (2%) for others conditions. mSOFA showed the best calibration, a higher net benefit, and the best discrimination (AUROC 0·911, 95% CI 0·86-0·95) for predicting 2-day mortality, and its discrimination was statistically significantly more accurate (p<0·0001) compared with the other scores. The performance of mSOFA for predicting 2-day mortality was higher than the other scores when considering the prehospital respiratory conditions, and was also higher for the secondary outcomes, except for non-invasive mechanical ventilation. Our results showed that mSOFA outperformed other EWSs. The inclusion of mSOFA in prehospital decision making will entail a quick identification of patients in acute respiratory distress at high risk of deterioration, allowing prioritisation of resources and patient care. Gerencia Regional de Salud, Public Health System of Castilla y León (GRS Spain). For the Spanish translation of the abstract see Supplementary Materials section.

Comparison of different prognostic scores in estimating short- and long-term mortality in COVID-19 patients above 60years old in a university hospital in Belgium.

Multiple scoring systems were used for risk stratification in COVID-19 patients. The objective was to determine among 6 scores which performed the best in predicting short-and long-term mortality in hospitalized COVID-19 patients ≥ 60years. An observational, retrospective cohort study conducted between 21/10/2020 and 20/01/2021. 6 scores were calculated (Clinical Frailty Scale (CFS), Charlson Comorbidity Index (CCI), 4C Mortality Score (4CMS), NEWS score (NEWS), quick-SOFA score (qSOFA), and Quick COVID-19 Severity Index (qCSI)). We included unvaccinated hospitalized patients with COVID-19 ≥ 60years old in Brugmann hospital, detected by PCR and/or suggestive CT thorax images. Old and nosocomial infections, and patients admitted immediately at the intensive care unit were excluded. 199 patients were included, mean age was 76.2years (60-99). 47.2% were female. 56 patients (28%) died within 1year after the first day of hospitalization. The 4CMS predicted the best intrahospital, 30days and 6months mortality, with area under the ROC curve (AUROC) 0.695 (0.58-0.81), 0.76 (0.65-0.86) and 0.72 (0.63-0.82) respectively. The CCI came right after with respectively AUROC of 0.69 (0.59-0.79), 0.74 (0.65-0.83) and 0.71 (0.64-0.8). To predict mortality at 12months after hospitalization, the CCI had the highest AUROC with 0.77 (0.69-0.85), before the 4CMS with 0.69 (0.60-0.79). Among 6 scores, the 4CMS was the best to predict intrahospital, 30-day and 6-month mortality. To predict mortality at 12months, CCI had the best performance before 4CMS. This reflects the importance of considering comorbidities for short- and long-term mortality after COVID 19. This study was approved by the ethical committee of Brugmann University Hospital (reference CE 2020/228).

External validation of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study

BackgroundTools proposed to triage ED acuity in suspected COVID-19 were derived and validated in higher income settings during early waves of the pandemic. We estimated the accuracy of seven risk-stratification...

Performance of point-of-care severity scores to predict prognosis in patients admitted through the emergency department with COVID-19.

Identifying COVID-19 patients at the highest risk of poor outcomes is critical in emergency department (ED) presentation. Sepsis risk stratification scores can be calculated quickly for COVID-19 patients but have not been evaluated in a large cohort. To determine whether well-known risk scores can predict poor outcomes among hospitalized COVID-19 patients. A retrospective cohort study of adults presenting with COVID-19 to 156 Hospital Corporation of America (HCA) Healthcare EDs, March 2, 2020, to February 11, 2021. Quick Sequential Organ Failure Assessment (qSOFA), Shock Index, National Early Warning System-2 (NEWS2), and quick COVID-19 Severity Index (qCSI) at presentation. The primary outcome was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) admission, mechanical ventilation, and vasopressors receipt. Patients scored positive with qSOFA ≥ 2, Shock Index > 0.7, NEWS2 ≥ 5, and qCSI ≥ 4. Test characteristics and area under the receiver operating characteristics curves (AUROCs) were calculated. We identified 90,376 patients with community-acquired COVID-19 (mean age 64.3 years, 46.8% female). 17.2% of patients died in-hospital, 28.6% went to the ICU, 13.7% received mechanical ventilation, and 13.6% received vasopressors. There were 3.8% qSOFA-positive, 45.1% Shock Index-positive, 49.8% NEWS2-positive, and 37.6% qCSI-positive at ED-triage. NEWS2 exhibited the highest AUROC for in-hospital mortality (0.593, confidence interval [CI]: 0.588-0.597), ICU admission (0.602, CI: 0.599-0.606), mechanical ventilation (0.614, CI: 0.610-0.619), and vasopressor receipt (0.600, CI: 0.595-0.604). Sepsis severity scores at presentation have low discriminative power to predict outcomes in COVID-19 patients and are not reliable for clinical use. Severity scores should be developed using features that accurately predict poor outcomes among COVID-19 patients to develop more effective risk-based triage.

Comparison of CURB-65 Pneumonia Severity Score, Quick COVID-19 Severity Index, and Brescia-COVID Respiratory Severity Scale in Emergently Hospitalized COVID-19 Patients with Pneumonia.

This study aimed to assess the performance of the CURB-65, the quick COVID-19 severity index (qCSI), and the Brescia-COVID respiratory severity scale (BCRSS) scores in predicting ICU (intensive care unit) hospitalization and in-hospital mortality in emergently hospitalized patients with COVID-19 pneumonia. We retrospectively reviewed the emergently hospitalized 258 patients with COVID-19 pneumonia consecutively. The required sample size was calculated to compare the areas under the two ROC (receiver operating characteristic) curves (AUC) using the MedCalc 20.0 program (MedCalc Software Ltd., Ostend, Belgium). In addition, we actualized ROC analyses of the CURB-65, the qCSI, and the BCRSS scores and compared the ROC curves of these three scores. The median age of the patients was 73, and 63.6% (n=164) were male. Of 258 patients, 29.5% (n=76) were hospitalized in the intensive care unit (ICU), and 15.9% (n=41) died. The CURB-65 and the qCSI scores predicted ICU admission at a moderate level (p≤0.001; AUC values were 0.743 and 0.723, respectively). However, the predictive effect of the BCRSS score for ICU admission was lower (p≤0.001; AUC value was 0.667). The CURB-65 predicted in-hospital mortality at a moderate level ( p≤0.001; AUC value was 0.762). However, the predictive effect of the qCSI and the BCRSS scores for in-hospital mortality were lower ( p≤0.001 and p=0.012, respectively; AUC values were 0.655 and 0.612, respectively). The CURB-65 score predicted ICU hospitalization and in-hospital mortality better than the qCSI and the BCRSS scores. Also, the qCSI score predicted ICU admission better than the BCRSS score.The predictive effect of the BCRSS score was the lowest. We recommend future studies to evaluate the value and utility of COVID-19 risk classification models.

Evaluation of the effectiveness of quick COVID-19 Severity Index and COVID-GRAM Critical Illness Risk Score in determining mortality and severity in COVID-19

Background/Aim: With the COVID-19 pandemic, the increase in the number of patients admitted to the emergency department has led to an increase in the need for intensive care and mechanical ventilation. Methods that can predict the development of serious disease will allow for a more accurate use of resources. This study was conducted to test the ability of the Quick COVID-19 Severity Index and the COVID-GRAM Critical Illness Risk Score to predict serious disease development and mortality.&#x0D; Methods: This is a prospective cohort study. Among the patients admitted to the emergency department, those hospitalized due to COVID-19 were included in the study. The Quick COVID-19 Severity Index and COVID-GRAM Critical Illness Risk Scores of the patients were calculated, and the ability of these scores to predict serious illness and mortality was investigated.&#x0D; Results: A total of 556 patients were included in this study. Development of critical illness, described as the need for non-invasive / invasive ventilation or the need for intensive care unit admission, was found significant when the Quick COVID-19 Severity Index was above 5 and the COVID-GRAM Critical Illness Risk Score showed high risk (AUC: 0.927; P &lt; 0.001, AUC: 0.986; P &lt; 0.001, respectively). A Quick COVID-19 Severity Index over 6 and COVID-GRAM Critical Illness Risk Score indicating high risk were found to be associated with mortality (AUC: 0.918, P &lt; 0.001, AUC: 0.982, P &lt; 0.001, respectively).&#x0D; Conclusion: Both the Quick COVID-19 Severity Index and the COVID-GRAM Critical Illness Risk Score can be used to assess severity in COVID-19 patients in the emergency room. However, the COVID-GRAM Critical Illness Risk Score was more successful in differentiating low- and high-risk patients.

Tomography and Prognostic Indices in the State of the Art of Evaluation in Hospitalized Patients with COVID-19 Pneumonia.

Evaluation in medical emergencies of COVID-19 patients represents a challenge to regulate preventive and timely management. There are key imaging and laboratory tools to classify the severity. The aim of the study was to evaluate the chest CT score performance and prognostic indices in COVID-19 patients to predict the progression to critical illness. This was a retrospective study between run between April and December 2020, in which 109 patients were included. Patients of any age and gender and who required hospitalization due to a confirmed COVID-19 diagnosis by RT-PCR and chest CT and laboratory were analyzed. In 75% of them, there was at least one comorbidity, and 30% developed critical illness, and the average mortality was 10%. In 49.5%, there was a CORADS-5 on admission, and in 50%, there was a peripheral distribution of the interstitial infiltrate in the left lower lobe. The risk factors were FiO2, CT score &gt; 18, and the NRL index. The combination of the high-risk Quick COVID-19 Severity Index (qCSI) plus CT score &gt; 18 indices was the best prediction index for the development of a critical condition. The combined use of indices in infected COVID-19 patients showed diagnostic accuracy and predicted severity. Imaging and the laboratory tests are key tools independent of the wave of recurrence.

Diagnostic accuracy of clinical gestalt of doctors with different experiences in COVID-19 suspected patients

This study aims to evaluate the ability of physicians' predictions to predict mortality in COVID-19 patients and compare physician predictions with scores developed for COVID-19 patients in predicting mortality and patient worsening. This study was conducted prospectively in the emergency department. Patient data were collected between 20.03.2021 and 20.06.2021. Patients who applied to our hospital with COVID-19 symptoms and were confirmed to be COVID-19 by rt-PCR results were included in our study. Patients aged 18 years and over who were tr-PCR positive were included in the study. Quick COVID-19 Severity Index (qCSI), Brescia-COVID Respiratory Severity Scale (BCRSS), and CURB- 65 scale were calculated and recorded by a researcher. A total of 176 patients were included in our study. There was no significant relationship between physicians' gestalt and 28-day mortality (p=0.121, p=0.282, Mann-Whitney U Test, respectively). Physicians' gestalt was found to be insufficient to predict mortality in COVID-19 patients. There was a significant difference between the CURB-65 short-term mortality group and the survivors.

What is the role of proton pump inhibitors consumption on the clinical presentation and severity of COVID-19 infection?

Objective: Proton pump inhibitors (PPI) are among the most prescribed drugs worldwide; therefore, assessing their effect on COVID-19 infection symptoms and severity is of great importance. This study was designed to evaluate the role of PPI consumption on the clinical presentation and severity of COVID-19.Patients and Methods: All adult COVID-19 patients were eligible in this observational cross-sectional study. The patients’ demographic and clinical data, history of PPI consumption, and comorbid disease were recorded. Charlson comorbidity index (CCI) and quick COVID-19 severity index (qCSI) score were calculated for each patient. IBM SPSS version 25 was used for statistical analysis.Results: Totally 670 patients completed the study (PPI users=121). The average severity (qCSI) score of PPI user patients with comorbidity score of zero was significantly higher than non-users (P-value=0.001). Mortality rate was 6.6% and 3.8% in PPI-users and non-users respectively (P-value= 0.117). PPI users were significantly more symptomatic compared to non-users (p value=0.001).Conclusion: We found that PPI users were meaningfully more symptomatic and had a higher severity (qCSI) score. Rational prescription of PPIs should be considered by physicians during and after the pandemic.

Accuracy of Quick Covid-19 Severity Index and Brescia-Covid Respiratory Severity Scale in Predicting ICU Admission and Mortality

The usefulness of risk screening tools in triaging and predicting likelihood of adverse outcomes of COVID-19 patients at first point of contact, would prevent overestimation or underestimation of severity risk in COVID pneumonia. BCRSS algorithm, a dynamic risk predictor, that uses clinical parameters of patient to assess need for escalating levels of respiratory support(Non-invasive ventilation, intubation, proning) to suggest treatment recommendations. Quick COVID-19 Severity Index (qCSI) is based on 3 variables (nasal cannula flow rate, respiratory rate, minimum documented pulse oximetry). To compare prognostic performance of BCRSS and qCSI-scores of hospitalized patients diagnosed with COVID-19. This is a Retrospective record-based study conducted at a tertiary hospital in Karnataka among COVID-19 patients. Patient’s clinical severity grade classification was done according to standard guidelines by Government of India. BCRSS and qCSI scores were calculated using baseline clinical information of patients. Statistical analysis used were Chi-squared test, regression analysis and ROC curve. The study results showed that out of 363 patients, majority of patients with high qCSI risk score of 3 and those with high BCRSS risk score of 4 were found to have high rates of ICU admissions and in-hospital deaths (66.9% and 44.4% for qCSI-3; 34.6% and 1.9% for BCRSS-4). With every unit increase in qCSI and BCRSS scores, there were 2.68 and 1.58 times more risk of fatality respectively. ROC curves for qCSI and BCRSS scales showed high area under curve:qCSI(AUC:0.761) and BCRSS(AUC:0.760), to predict in-hospital fatality. The study has shown that both qCSI and BCRSS scoring models have good results for predicting probabilities of ICU admissions and in-hospital mortality of COVID-19 patients. Key Messages: These risk prediction models, if applied during the initial clinical assessment stage, could help in better triaging, risk prediction, better treatment of COVID-19 patients. Keywords: Quick COVID-19 Severity Index, Brescia-COVID Respiratory Severity Scale, in-hospital mortality, COVID-19, ICU admission

Quick COVID-19 Severity Index, CURB-65 and Quick SOFA Scores Comparison in Predicting Mortality and Risk Factors of COVID-19 Patients.

This study aimed to investigate CURB-65, quick COVID-19 Severity Index (qCSI) and quick Sepsis Related Organ Failure Assessment (qSOFA) scores in predicting mortality and risk factors for death in patients with COVID-19. We retrospectively analyzed a total of 1919 cases for whom the rRT-PCR assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was positive. For mortality risk factors, univariate and multivariate logistic regression analyses were used. Receiver operator characteristics (ROC) analysis and Kaplan-Meier survival analysis were performed for CURB-65, qCSI and qSOFA scores. The patients' average age was 45.7 (21.6) years. Male patients accounted for 51.7% (n=992). In univariate analysis, some clinical variables including age over 65 years and comorbid diseases such as hypertension, chronic kidney disease, malignancy, lymphopenia, troponin, lactate dehydrogenase (LDH) and fibrinogen elevation were associated with the mortality rate. In multivariate logistic regression analysis: Neutrophil lymphocyte ratio (NLR) 3.3 and above (OR, 9.1; 95% CI, 1.9-42), C-reactive protein (CRP)30 mg/L and above (OR, 4.1; 95% CI, 1.2-13.6), D-dimer 1000 ng/mL and above (OR, 4; 95% CI, 1.5-10.7) and age (OR, 1.11; 95% CI, 1.04-1.18-year increase) were identified as risk factors for mortality among COVID-19 patients. The CURB-65 and qCSI scores exhibited a high degree of discrimination in mortality prediction (AUC values were 0.928 and 0.865, respectively). Also, the qSOFA score had a moderate discriminant power (AUC value was 0.754). CURB-65 and qSCI scores had a high discriminatory power to predict mortality. Also, this study identified CURB-65, qCSI and qSOFA scores, NLR, CRP, D-dimer level, and annual age increase as important mortality risk factors.

Correlation of Chest X-Ray Scores in SARS-CoV-2 Patients With the Clinical Severity Classification and the Quick COVID-19 Severity Index.

ObjectivesThis study aimed to assess the role of chest X-ray (CXR) scoring methods and their correlations with the clinical severity categories and the Quick COVID-19 Severity Index (qCSI).MethodsWe conducted a retrospective study of 159 COVID-19 patients who were diagnosed and treated at the University Medical Center between July and September 2021. Chest X-ray findings were evaluated, and severity scores were calculated using the modified CXR (mCXR), Radiographic Assessment of Lung Edema (RALE), and Brixia scoring systems. The three scores were then compared to the clinical severity categories and the qCSI using Spearman's correlation coefficient.ResultsOverall, 159 patients (63 males and 96 females) (mean age: 58.3 ± 15.7 years) were included. The correlation coefficients between the mCXR score and the Brixia and RALE scores were 0.9438 and 0.9450, respectively. The correlation coefficient between the RALE and Brixia scores was marginally higher, at 0.9625. The correlation coefficients between the qCSI and the Brixia, RALE, and mCXR scores were 0.7298, 0.7408, and 0.7156, respectively. The significant difference in the mean values of the three CXR scores between asymptomatic, mild, moderate, severe, and critical groups was also noted.ConclusionsThere were strong correlations between the three CXR scores and the clinical severity classification and the qCSI.

One-on-one comparison between qCSI and NEWS scores for mortality risk assessment in patients with COVID-19

Objective To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients. Methods Multicenter retrospective cohort study conducted in adult patients transferred by ambulance to an emergency department (ED) with suspected COVID-19 infection subsequently confirmed by a SARS-CoV-2 test (polymerase chain reaction). We collected epidemiological data, clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and use of supplemental oxygen) and hospital variables. The primary outcome was cumulative all-cause mortality during a 90-day follow-up, with mortality assessment monitoring time points at 1, 2, 7, 14, 30 and 90 days from ED attendance. Comparison of performances for 90-day mortality between both scores was carried out by univariate analysis. Results From March to November 2020, we included 2,961 SARS-CoV-2 positive patients (median age 79 years, IQR 66–88), with 49.2% females. The qCSI score provided an AUC ranging from 0.769 (1-day mortality) to 0.749 (90-day mortality), whereas AUCs for NEWS ranging from 0.825 for 1-day mortality to 0.777 for 90-day mortality. At all-time points studied, differences between both scores were statistically significant (p < .001). Conclusion Patients with SARS-CoV-2 can rapidly develop bilateral pneumonias with multiorgan disease; in these cases, in which an evacuation by the EMS is required, reliable scores for an early identification of patients with risk of clinical deterioration are critical. The NEWS score provides not only better prognostic results than those offered by qCSI at all the analyzed time points, but it is also better suited for COVID-19 patients. KEY MESSAGES This work aims to determine whether NEWS is the best score for mortality risk assessment in patients with COVID-19. AUCs for NEWS ranged from 0.825 for 1-day mortality to 0.777 for 90-day mortality and were significantly higher than those for qCSI in these same outcomes. NEWS provides a better prognostic capacity than the qCSI score and allows for long-term (90 days) mortality risk assessment of COVID-19 patients.

Early warning scores to assess the probability of critical illness in patients with COVID-19

ObjectiveValidated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current...

14 External Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation

To externally validate a risk-stratification tool—the Quick COVID-19 Severity Index (qCSI)—developed by Haimovich et al. to predict 24-hour respiratory decompensation in admitted patients with COVID-19.

Predicting hospital mortality in COVID-19 hemodialysis patients with developed scores.

Various risk scores such as COVID‐GRAM Critical Illness Risk Score (COVID‐GRAM), quick COVID‐19 Severity Index (qCSI), and systemic immune‐inflammation index (SII) have been developed to determine critical illness in hospitalized patients. None of these risk scoring systems was evaluated in HD patients who indeed carry the highest risk of developing critical illnesses. We aimed to evaluate, in hemodialysis (HD) patients with COVID‐19, the performance of these scoring systems for the need of intensive care unit (ICU) and mortality. The qCSI, COVID‐GRAM, and SII scores of the patients at admission to hospital were calculated and grouped according to the scoring results. The primary outcome of the study was mortality and need of ICU. Critical illness was described as a composition of admission to the ICU, invasive ventilation, or death. It was determined that when the qCSI is over 6.5, the need for ICU increased 13.8 times and mortality increased 21.3 times. When the COVID‐GRAM score is >157, the ICU need increased 14.7 times and the mortality increased 33.7 times. We found that the need for ICU increased 4.2 times and mortality increased 3.1 times when the SII score was >1145. These tests, which can be easily calculated, could be used to estimate the risk of developing critical illness among COVID‐19 HD patients. Estimating the risk of critical illness could help to reduce mortality in HD patients.

In adults hospitalized with COVID-19, the quick COVID-19 Severity Index predicted 24-h respiratory decompensation.

Haimovich AD, Ravindra NG, Stoytchev S, et al. Development and validation of the quick COVID-19 Severity Index: a prognostic tool for early clinical decompensation. Ann Emerg Med. 2020;76:442-53. 33012378.