Performance of the Pandemic Medical Early Warning Score (PMEWS), Simple Triage Scoring System (STSS) and Confusion, Uremia, Respiratory rate, Blood pressure and age ≥ 65 (CURB-65) score among patients with COVID-19 pneumonia in an emergency department triage setting: a retrospective study

Patient self-inflicted lung injury associated pneumothorax/pneumomediastinum is a risk factor for worse outcomes of severe COVID-19: a case-control study

We aimed to determine the clinical characteristics of patient self-inflicted lung injury (P-SILI)-associated pneumothorax/pneumomediastinum, to reveal its risk factors, and to assess its impact on severe COVID-19 cases. In total, 229 patients were included in this case-control study. They were randomly divided into either the case group or the control group as per the inclusion and exclusion criteria. The two groups were further analyzed to reveal the risk factors of spontaneous pneumothorax/pneumomediastinum (SP/P). Finally, risk factors for death were analyzed in the case group and the relationship between death and SP/P was also analyzed among all patients. The mean age of patients was 59.69 ± 17.01 years, most of them were male (74.2%), and 62.0% of them had comorbidities upon admission. A respiratory rate higher than 30 BPM was a risk factor for SP/P (OR 7.186, 95% CI 2.414-21.391, P < 0.001). Patients with delayed intubation due to early application of HFNC or NIV had a higher mortality rate when they developed SP/P (P < 0.05). Additionally, advanced age increased the risk of death (P < 0.05). Finally, SP/P may be a risk factor for death among patients with severe COVID-19 (OR 2.047). P-SILI occurs in severe COVID-19 with acute respiratory failure. It is necessary to identify the risk factors of P-SILI, the indicators of severe P-SILI, and the preventive measures.

Machine learning-based prediction of in-hospital mortality in patients with pneumonic chronic obstructive pulmonary disease exacerbations

OBJECTIVE

While linear regression and LASSO models have been established for predicting in-hospital mortality, there is currently no validated clinical prediction algorithm to predict in-hospital mortality for patients with chronic obstructive pulmonary disease (COPD) exacerbations using machine learning. Thus, we will evaluate the BAP-65 and CURB-65, and construct a novel prediction model using the random forest (RF) technique.

METHODS

A dataset of 1,418 patients with COPD exacerbations was collected. Age, gender, mental status, vital signs, and laboratory results were all taken into account for predictors. The categorical outcome variable was hospital-based mortality of people over 65 years. The dataset was divided randomly into a training dataset (70%) and a testing dataset (30%). We trained three prediction models, BAP-65, CURB-65, and the RF model, estimated the area under the receiver operating characteristic curve (AUROC) for the entire dataset. We also conducted a comparison of the AUROC values using the Delong test.

RESULTS

A total of 658 individuals with COPD acute exacerbations were enrolled. Our analysis using the receiver operating characteristic curve demonstrated that the RF model exhibited excellent performance, with an AUROC of 0.80 (95% confidence interval: 0.75-0.84). In comparison, the BAP-65 prediction model yielded an AUROC of 0.72 (0.68-0.75), while the CURB-65 prediction model achieved an AUROC of 0.69 (0.67-0.73).

CONCLUSIONS

The RF model demonstrated superior predictive capabilities than the BAP-65 and CURB-65 models in predicting in-hospital mortality. The results further highlighted significant factors for predicting in-hospital mortality, including blood eosinophil count, systolic blood pressure, and prior history of asthma.

Reverse shock index multiplied by simplified motor score as a predictor of clinical outcomes for patients with COVID-19

BACKGROUND

The reverse shock index (rSI) combined with the Simplified Motor Score (sMS), that is, the rSI-sMS, is a novel and efficient prehospital triage scoring system for patients with COVID-19. In this study, we evaluated the predictive accuracy of the rSI-sMS for general ward and intensive care unit (ICU) admission among patients with COVID-19 and compared it with that of other measures, including the shock index (SI), modified SI (mSI), rSI combined with the Glasgow Coma Scale (rSI-GCS), and rSI combined with the GCS motor subscale (rSI-GCSM).

METHODS

All patients who visited the emergency department of Taipei Tzu Chi Hospital between January 2021 and June 2022 were included in this retrospective cohort. A diagnosis of COVID-19 was confirmed through a SARS-CoV-2 reverse-transcription polymerase chain reaction test or SARS-CoV-2 rapid test with oropharyngeal or nasopharyngeal swabs and was double confirmed by checking International Classification of Diseases, Tenth Revision, Clinical Modification codes in electronic medical records. In-hospital mortality was regarded as the primary outcome, and sepsis, general ward or ICU admission, endotracheal intubation, and total hospital length of stay (LOS) were regarded as secondary outcomes. Multivariate logistic regression was used to determine the relationship between the scoring systems and the three major outcomes of patients with COVID-19, including. The discriminant ability of the predictive scoring systems was investigated using the area under the receiver operating characteristic curve, and the most favorable cutoff value of the rSI-sMS for each major outcome was determined using Youden's index.

RESULTS

After 74,183 patients younger than 20 years (n = 11,572) and without COVID-19 (n = 62,611) were excluded, 9,282 patients with COVID-19 (median age: 45 years, interquartile range: 33-60 years, 46.1% men) were identified as eligible for inclusion in the study. The rate of in-hospital mortality was determined to be 0.75%. The rSI-sMS scores were significantly lower in the patient groups with sepsis, hyperlactatemia, admission to a general ward, admission to the ICU, total length of stay ≥ 14 days, and mortality. Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS exhibited a significantly higher accuracy for predicting general ward admission, ICU admission, and mortality but a similar accuracy to that of the rSI-GCS. The optimal cutoff values of the rSI-sMS for predicting general ward admission, ICU admission, and mortality were calculated to be 3.17, 3.45, and 3.15, respectively, with a predictive accuracy of 86.83%, 81.94%%, and 90.96%, respectively.

CONCLUSIONS

Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS has a higher predictive accuracy for general ward admission, ICU admission, and mortality among patients with COVID-19.

Performance of CURB-65 and ISARIC 4C mortality scores for hospitalized patients with confirmed COVID-19 infection in Saudi Arabia

Background

The COVID-19 pandemic continues with new waves that could persist with the arrival of new SARS-CoV-2 variants. Therefore, the availability of validated and effective triage tools is the cornerstone for proper clinical management. Thus, this study aimed to assess the validity of the ISARIC-4C score as a triage tool for hospitalized COVID-19 patients in Saudi Arabia and to compare its performance with the CURB-65 score.

Material and methods

This retrospective observational cohort study was conducted between March 2020 and May 2021 at KFHU, Saudi Arabia, using 542 confirmed COVID-19 patient data on the variables relevant to the application of the ISARIC-4C mortality score and the CURB-65 score. Chi-square and t-tests were employed to study the significance of the CURB-65 score and the ISARIC-4C score variables considering the ICU requirements and the mortality of COVID-19 hospitalized patients. In addition, logistic regression was used to predict the variables related to COVID-19 mortality. In addition, the diagnostic accuracy of both scores was validated by calculating sensitivities, specificities, positive predictive value, negative predictive value, and Youden's J indices (YJI).

Results

ROC analysis showed an AUC value of 0.834 [95% CI; 0.800-0.865]) for the CURB-65 score and 0.809 [95% CI; 0.773-0.841]) for the ISARIC-4C score. The sensitivity for CURB-65 and ISARIC-4C is 75% and 85.71%, respectively, while the specificity was 82.31% and 62.66%, respectively. The difference between AUCs was 0.025 (95% [CI; -0.0203-0.0704], p = 0.2795).

Conclusion

Study results support external validation of the ISARIC-4C score in predicting the mortality risk of hospitalized COVID-19 patients in Saudi Arabia. In addition, the CURB-65 and ISARIC-4C scores showed comparable performance with good consistent discrimination and are suitable for clinical utility as triage tools for hospitalized COVID-19 patients.

Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19

OBJECTIVES

This meta-analysis aimed to establish a clinical evidence base for respiratory rate (RR) as a single predictor of early-onset COVID-19. The review also looked to determine the practical implementation of mobile respiratory rate measuring devices where information was available.

METHODS

We focused on domestic settings with older adults. Relevant studies were identified through MEDLINE, Embase, and CENTRAL databases. A snowballing method was also used. Articles published from the beginning of the COVID-19 pandemic (2019) until Feb 2022 were selected. Databases were searched for terms related to COVID-19 and respiratory rate measurements in domestic patients.

RESULTS

A total of 2,889 articles were screened for relevant content, of which 60 full-text publications were included. We compared the Odds Ratios and statistically significant results of both vital signs.

CONCLUSION

Multinational studies across dozens of countries have shown respiratory rate to have predictive accuracy in detecting COVID-19 deterioration. However, considerable variability is present in the data, making it harder to be sure about the effects. There is no meaningful difference in data quality in terms of variability (95% CI intervals) between vital signs as predictors of decline in COVID-19 patients. Contextual and economic factors will likely determine the choice of measurement used.

Comparison of prognostic scores for inpatients with COVID-19: a retrospective monocentric cohort study

Background

The SARS-CoV-2 pandemic led to a steep increase in hospital and intensive care unit (ICU) admissions for acute respiratory failure worldwide. Early identification of patients at risk of clinical deterioration is crucial in terms of appropriate care delivery and resource allocation. We aimed to evaluate and compare the prognostic performance of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Uraemia, Respiratory Rate, Blood Pressure and Age ≥65 (CURB-65), Respiratory Rate and Oxygenation (ROX) index and Coronavirus Clinical Characterisation Consortium (4C) score to predict death and ICU admission among patients admitted to the hospital for acute COVID-19 infection.

Methods and analysis

Consecutive adult patients admitted to the Geneva University Hospitals during two successive COVID-19 flares in spring and autumn 2020 were included. Discriminative performance of these prediction rules, obtained during the first 24 hours of hospital admission, were computed to predict death or ICU admission. We further exluded patients with therapeutic limitations and reported areas under the curve (AUCs) for 30-day mortality and ICU admission in sensitivity analyses.

Results

A total of 2122 patients were included. 216 patients (10.2%) required ICU admission and 303 (14.3%) died within 30 days post admission. 4C score had the best discriminatory performance to predict 30-day mortality (AUC 0.82, 95% CI 0.80 to 0.85), compared with SOFA (AUC 0.75, 95% CI 0.72 to 0.78), qSOFA (AUC 0.59, 95% CI 0.56 to 0.62), CURB-65 (AUC 0.75, 95% CI 0.72 to 0.78) and ROX index (AUC 0.68, 95% CI 0.65 to 0.72). ROX index had the greatest discriminatory performance (AUC 0.79, 95% CI 0.76 to 0.83) to predict ICU admission compared with 4C score (AUC 0.62, 95% CI 0.59 to 0.66), CURB-65 (AUC 0.60, 95% CI 0.56 to 0.64), SOFA (AUC 0.74, 95% CI 0.71 to 0.77) and qSOFA (AUC 0.59, 95% CI 0.55 to 0.62).

Conclusion

Scores including age and/or comorbidities (4C and CURB-65) have the best discriminatory performance to predict mortality among inpatients with COVID-19, while scores including quantitative assessment of hypoxaemia (SOFA and ROX index) perform best to predict ICU admission. Exclusion of patients with therapeutic limitations improved the discriminatory performance of prognostic scores relying on age and/or comorbidities to predict ICU admission.

Trends in Geriatric Trauma Emergency Department Admissions During COVID-19

BACKGROUND

The impact of coronavirus disease-2019 (COVID-19) on geriatric trauma presenting to the emergency department is unknown.

OBJECTIVE

To examine geriatric trauma emergency department admission trends during the COVID-19 pandemic.

METHODS

This retrospective, observational, comparison study was conducted in an academic emergency department in Turkey. Trauma patients 65 years and older who presented to the emergency department within 1 year of March 12, 2020, were included. Patients admitted in the same date range in the previous year were included as the control group. The characteristics of the patients, injured area, and injury mechanisms were compared.

RESULTS

Geriatric trauma admissions decreased (relative risk = 0.71, odds ratio [OR] = 0.69 [95% confidence interval, CI: 0.62, 0.77], p < .001). According to the type of injury, there was no significant difference in admissions to the emergency department (p = .318). During the pandemic, there was an increase in falls and a decrease in stab wounds and gunshot wounds (p = .001). Multiple trauma (OR = 5.56 [95% CI: 3.75, 8.23], p < .001), fall (OR = 2.41 [95% CI: 1.6, 3.73], p < .001), and-assault related injuries (OR = 4.43 [95% CI: 2.06, 9.56], p < .001) were determined as factors that increased the admissions to the emergency department compared with the prepandemic.

CONCLUSION

Although geriatric trauma emergency department admissions decreased during the pandemic, those due to falls and assaults increased. Although curfews and social isolation resulted in a decrease in penetrating injuries, assault-related trauma has increased.

Bioelectric impedance body composition and phase angle in relation to 90-day adverse outcome in hospitalized COVID-19 ward and ICU patients: The prospective BIAC-19 study

BACKGROUND & AIMS

Gaining insight into readily obtainable baseline characteristics that allow prediction of adverse outcome in COVID-19 aids both treatment and healthcare planning. Bioelectric impedance (BIA) Phase Angle (PhA) is correlated with outcome in a multitude of diseases and may be of added value in predicting adverse outcome of COVID-19. We aimed to associate baseline body composition parameters with 90-day adverse outcome of COVID-19 including ICU-admission and to explore the added predictive value of baseline PhA.

METHODS

We performed a prospective observational study, conducting BIA amongst COVID-19 patients within 24 hours of hospital admission, with a follow-up of 90 days. Data were compared between ward-only and ICU-patients. Regression models were used to assess the associations between baseline characteristics, body composition and 90-day adverse outcome, including a composite outcome score of morbidity, ICU-admission, and mortality. An ROC-curve was used to explore the added predictive value of PhA to other clinical parameters at baseline for the prediction of adverse outcome.

RESULTS

One-hundred-and-fifty patients were included. Mean age was 68 (66-70) years, 67% were male. Forty-one (27%) patients were admitted to ICU and 77 (51%) met the criteria of the composite outcome score. In multiple regression, PhA was independently, inversely correlated with risk of ICU-admission (OR .531, p = .021), complications (OR .579, p = .031), hospital length of stay (OR .875, p = .037) and the composite outcome score (OR .502, p = .012). An ROC-curve showed that the incorporation of PhA in a composite risk-score improved the discriminative power for the composite outcome from poor to fair, compared to individual predictors (AUC 0.79 (95% CI 0.71-0.87)).

CONCLUSION

BIA measurements including Phase Angle are independently correlated with an adverse outcome of COVID-19. Interpretation of Phase Angle can be a valuable addition to risk assessment of adverse outcome of COVID-19 at hospital admission.

CLINICAL TRIAL REGISTRATION

Netherlands Trial Register number NL8562, registered 2020-04-21.

The feasibility of home self-assessment of vital signs and symptoms: A new key to telehealth for individuals?

Objective

During the COVID-19 pandemic, social distancing and self-isolation called for innovative, readily implementable, and effective short-term health solutions. The objective of this study was to assess the feasibility of self-assessment of vital signs and symptoms with electronic transmission of results, by self-isolating individuals with positive SARS-CoV-2 polymerase chain reaction (PCR) test. The secondary objective was to describe the association between the presence of abnormal vital signs and severe symptoms as well as their evolution over time.

Method

Participants with positive SARS-CoV-2 PCR test were asked to perform twice daily standardized vital signs measurements and self-assessment of symptoms for 14 consecutive days. All data were transmitted electronically through a mobile application and a web-based platform. Participants were provided with decision support tools based on the severity of their condition and a weekly nurse practitioner telephone follow-up. Abnormal values for vital signs and severe symptoms were determined. Per participant and per days, proportions of abnormal vital signs and severe symptoms were calculated.

Results

Data from 46 participants (mean age 54.1 ± 6.9 years, 54% male) were available for analysis. On average, participants performed the standardized self-assessment for 12.3 ± 3.4 days (89% performed at least 7 measurement days and 61% completed all 14 days). The highest proportions abnormal values for vital signs were for oximetry (20.1%) and respiratory rate (12.1%). The highest proportions of severe symptoms were for fatigue (16.9%) and myalgia. (10.2%). The combined proportion of abnormal vital signs and severe symptoms was maximal on day 1 with 20.3% of total measurements, with a linear decrease to 3.5% on day 14.

Conclusion

Remote initiation of home measurements of vital signs and symptoms, self-management of these measures, accompanied by a decision support tool and supported by preplanned nurse follow-up are feasible. This could allow to opening up new insight for the care of sick individuals.

Performance of the CURB-65, ISARIC-4C and COVID-GRAM scores in terms of severity for COVID-19 patients

BACKGROUND

In the COVID-19 pandemic, difficulties have been experienced in the provision of healthcare services because of excessive patient admissions to hospitals and emergency departments. It has become important to use clear and objective criteria for the early diagnosis of patients with high-risk classification and clinical worsening risk.

OBJECTIVE

The aim of this study was to assess the prognostic accuracy of CURB-65, ISARIC-4C and COVID-GRAM scores in patients hospitalised for COVID-19 and to compare the scoring systems in terms of predicting in-hospital mortality and intensive care unit requirement.

METHODS

The files of all COVID-19 patients over the age of 18 who were admitted to the emergency department and hospitalised between September 1, 2020 and December 1, 2020 were retrospectively scanned. The area under the receiver operating characteristic curve and Youden J Index were used to compare scoring systems for predicting in-hospital mortality and intensive care requirement.

RESULTS

There were 481 patients included in this study. The median age of the patients was 67 (52-79). In terms of in-hospital mortality, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.846, 0.784 and 0.701 respectively. In terms of intensive care requirement, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.898, 0.797 and 0.684 respectively. In our study, Youden's J indexes of CURB-65, ISARIC-4C and COVID-GRAM scores were found to be 0.59, 0.27 and 0.01 respectively, for mortality prediction of COVID-19 patients. Whereas Youden's J indexes were found to be 0.63, 0.26 and 0.01 respectively for determining intensive care requirement.

CONCLUSIONS

Among the scoring systems assessed, CURB-65 score had better performance in predicting in-hospital mortality and ICU requirement in COVID-19 patients. ISARIC-4C has been found successful in identifying low-risk patients and the use of the ISARIC-4C score with CURB-65 increases the accuracy of risk assessment.

External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

Purpose

The Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19.

Methods

We used “COVID-19 Evidence Alerts” (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer.

Results

We included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome.

Conclusion

Seven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06524-w.

A catalogue of tools and variables from crisis and routine care to support decision-making about allocation of intensive care beds and ventilator treatment during pandemics: Scoping review

PURPOSE

This scoping review sought to identify objective factors to assist clinicians and policy-makers in making consistent, objective and ethically sound decisions about resource allocation when healthcare rationing is inevitable.

MATERIALS AND METHODS

Review of guidelines and tools used in ICUs, hospital wards and emergency departments on how to best allocate intensive care beds and ventilators either during routine care or developed during previous epidemics, and association with patient outcomes during and after hospitalisation.

RESULTS

Eighty publications from 20 countries reporting accuracy or validity of prognostic tools/algorithms, or significant correlation between prognostic variables and clinical outcomes met our eligibility criteria: twelve pandemic guidelines/triage protocols/consensus statements, twenty-two pandemic algorithms, and 46 prognostic tools/variables from non-crisis situations. Prognostic indicators presented here can be combined to create locally-relevant triage algorithms for clinicians and policy makers deciding about allocation of ICU beds and ventilators during a pandemic. No consensus was found on the ethical issues to incorporate in the decision to admit or triage out of intensive care.

CONCLUSIONS

This review provides a unique reference intended as a discussion starter for clinicians and policy makers to consider formalising an objective a locally-relevant triage consensus document that enhances confidence in decision-making during healthcare rationing of critical care and ventilator resources.

Impact of COVID-19 Outbreak on Emergency Visits and Emergency Consultations: A Cross-Sectional Study

Background

This study aimed to determine the effect of the COVID-19 outbreak on emergency department (ED) visits and emergency consultations according to the triage levels indicating the patients' urgency.

Methods

A cross-sectional retrospective study was performed in the ED of a tertiary training and research hospital between 1 April and 31 May 2020 in İstanbul, Turkey. The daily count of emergency visits and the count of the emergency consultations during the study period were recorded. The emergency visits and consultations in the same months of the previous year (1 April-31 May 2019) were included as a control group.

Results

Approximately 50% reduction in ED visits and a 30% reduction in emergency consultations were detected. A significant decrease was detected in all triage levels of visits and emergency consultations (p < 0.001). Within total ED visits, a significant increase was found in the red (4.32% vs. 4.74%) and yellow (21.66% vs. 33.16%) triage levels visit rates, while the green (74.01% vs. 62.1%) level was decreased. Within total emergency consultations, anesthesiology (0.83% vs. 1.56%) and cardiology (3.17% vs. 3.75%) consultation rates increased, neurology (2.22% vs. 1.15%), orthopedics (3.53% vs. 3.01%), and ophthalmology (2.89% vs. 1.57%) consultation rates decreased, internal medicine (2.45% vs. 2.49%), and general surgery (4.46% vs. 4.64%) consultation rates did not change.

Conclusions

During the COVID-19 pandemic, ED visits at all triage levels decreased. While the rate of critical patient visits increased, non-emergency patient visit rates decreased. The total count of consultations decreased, while the total consultation rates increased. The management of the COVID-19 pandemic will be easier by using or developing appropriate triage scores, as well as establishing good interdisciplinary coordination.