Quick-SOFA score to predict mortality among geriatric patients with influenza in the emergency department

Performance of established disease severity scores in predicting severe outcomes among adults hospitalized with influenza-FluSurv-NET, 2017-2018

Background

Influenza is a substantial cause of annual morbidity and mortality; however, correctly identifying those patients at increased risk for severe disease is often challenging. Several severity indices have been developed; however, these scores have not been validated for use in patients with influenza. We evaluated the discrimination of three clinical disease severity scores in predicting severe influenza-associated outcomes.

Methods

We used data from the Influenza Hospitalization Surveillance Network to assess outcomes of patients hospitalized with influenza in the United States during the 2017-2018 influenza season. We computed patient scores at admission for three widely used disease severity scores: CURB-65, Quick Sepsis-Related Organ Failure Assessment (qSOFA), and the Pneumonia Severity Index (PSI). We then grouped patients with severe outcomes into four severity tiers, ranging from ICU admission to death, and calculated receiver operating characteristic (ROC) curves for each severity index in predicting these tiers of severe outcomes.

Results

Among 8252 patients included in this study, we found that all tested severity scores had higher discrimination for more severe outcomes, including death, and poorer discrimination for less severe outcomes, such as ICU admission. We observed the highest discrimination for PSI against in-hospital mortality, at 0.78.

Conclusions

We observed low to moderate discrimination of all three scores in predicting severe outcomes among adults hospitalized with influenza. Given the substantial annual burden of influenza disease in the United States, identifying a prediction index for severe outcomes in adults requiring hospitalization with influenza would be beneficial for patient triage and clinical decision-making.

Two-stage prediction model for in-hospital mortality of patients with influenza infection

BACKGROUND

Infleunza is a challenging issue in public health. The mortality and morbidity associated with epidemic and pandemic influenza puts a heavy burden on health care system. Most patients with influenza can be treated on an outpatient basis but some required critical care. It is crucial for frontline physicians to stratify influenza patients by level of risk. Therefore, this study aimed to create a prediction model for critical care and in-hospital mortality.

METHODS

This retrospective cohort study extracted data from the Chang Gung Research Database. This study included the patients who were diagnosed with influenza between 2010 and 2016. The primary outcome of this study was critical illness. The secondary analysis was to predict in-hospital mortality. A two-stage-modeling method was developed to predict hospital mortality. We constructed a multiple logistic regression model to predict the outcome of critical illness in the first stage, then S1 score were calculated. In the second stage, we used the S1 score and other data to construct a backward multiple logistic regression model. The area under the receiver operating curve was used to assess the predictive value of the model.

RESULTS

In the present study, 1680 patients met the inclusion criteria. The overall ICU admission and in-hospital mortality was 10.36% (174 patients) and 4.29% (72 patients), respectively. In stage I analysis, hypothermia (OR = 1.92), tachypnea (OR = 4.94), lower systolic blood pressure (OR = 2.35), diabetes mellitus (OR = 1.87), leukocytosis (OR = 2.22), leukopenia (OR = 2.70), and a high percentage of segmented neutrophils (OR = 2.10) were associated with ICU admission. Bandemia had the highest odds ratio in the Stage I model (OR = 5.43). In stage II analysis, C-reactive protein (OR = 1.01), blood urea nitrogen (OR = 1.02) and stage I model's S1 score were assocaited with in-hospital mortality. The area under the curve for the stage I and II model was 0.889 and 0.766, respectively.

CONCLUSIONS

The two-stage model is a efficient risk-stratification tool for predicting critical illness and mortailty. The model may be an optional tool other than qSOFA and SIRS criteria.

Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study

BACKGROUND

Identification of patients on admission to hospital with coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes has not yet been comprehensively assessed.

OBJECTIVE

To compare severity scores used for community-acquired pneumonia to identify high-risk patients with COVID-19 pneumonia.

DESIGN

PSI, CURB-65, qSOFA, and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality, admission to an intensive care unit (ICU), or use of mechanical ventilation. Area under receiver operating characteristics curve (AUROC), sensitivity, and specificity for each score were determined and AUROC was compared among them.

PARTICIPANTS

Patients with COVID-19 pneumonia included in the SEMI-COVID-19 Network.

KEY RESULTS

We examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were as follows: hypertension (49.2%), diabetes (18.8%), and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%. PSI and CURB-65 showed the highest AUROC (0.835 and 0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%.

CONCLUSIONS

PSI and CURB-65, specific severity scores for pneumonia, were better than qSOFA and MuLBSTA at predicting mortality in patients with COVID-19 pneumonia. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive.

Predictive value of geriatric-quickSOFA in hospitalized older people with sepsis

BACKGROUND

QuickSOFA, a prognostic score proposed for patients with infection, has shown a poor predictive value in the geriatric population, probably because of the inappropriateness of the Glasgow Coma Scale (GCS) in assessing acute alteration of mental status in older patients. Indeed, the GCS might result chronically low in older patient with pre-existing cognitive disorders. The aim of this study was to develop an alternative quickSOFA (geriatric-quickSOFA), using the presence of delirium, assessed according to DSM-5 criteria, instead of GCS assessment, to predict mortality in hospitalized older patients with sepsis.

METHODS

Retrospective observational study in Acute Geriatrics Unit of St. Anna Hospital of Ferrara (Italy). The study enrolled 165 patients hospitalized between 2017 and 2018 with diagnosis of sepsis or septic shock. Demographic, clinical data and 30-day survival were collected for each patient. Based on arterial blood pressure, respiratory rate, and the presence of delirium, geriatric-quickSOFA was calculated at admission. Primary outcome was 30-day mortality.

RESULTS

One hundred sixty-five patients were enrolled with a median age of 88 years; 60.6% were men. High quickSOFA score was not significantly correlated neither with in-hospital nor 30-day mortality. High geriatric-qSOFA score was significantly related to both in-hospital (13.3%vs 51.5%, p = 0.0003) and 30-day mortality (30.0%vs 84.3%, p < 0.00001).

CONCLUSION

Geriatric-quickSOFA is significantly associate with short-term mortality risk in older patients with sepsis. Geriatric quickSOFA seems to represent a more suitable and useful predictive tool than the traditional quickSOFA in the geriatric population.

Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: An observational retrospective study

Background

This study aims to describe the epidemiology of COVID-19 patients in a Swiss university hospital.

Methods

This retrospective observational study included all adult patients hospitalized with a laboratory confirmed SARS-CoV-2 infection from March 1 to March 25, 2020. We extracted data from electronic health records. The primary outcome was the need to mechanical ventilation at day 14. We used multivariate logistic regression to identify risk factors for mechanical ventilation. Follow-up was of at least 14 days.

Results

145 patients were included in the multivariate model, of whom 36 (24.8%) needed mechanical ventilation at 14 days. The median time from symptoms onset to mechanical ventilation was 9·5 days (IQR 7.00, 12.75). Multivariable regression showed increased odds of mechanical ventilation with age (OR 1.09 per year, 95% CI 1.03–1.16, p = 0.002), in males (OR 6.99, 95% CI 1.68–29.03, p = 0.007), in patients who presented with a qSOFA score ≥2 (OR 7.24, 95% CI 1.64–32.03, p = 0.009), with bilateral infiltrate (OR 18.92, 3.94–98.23, p<0.001) or with a CRP of 40 mg/l or greater (OR 5.44, 1.18–25.25; p = 0.030) on admission. Patients with more than seven days of symptoms on admission had decreased odds of mechanical ventilation (0.087, 95% CI 0.02–0.38, p = 0.001).

Conclusions

This study gives some insight in the epidemiology and clinical course of patients admitted in a European tertiary hospital with SARS-CoV-2 infection. Age, male sex, high qSOFA score, CRP of 40 mg/l or greater and a bilateral radiological infiltrate could help clinicians identify patients at high risk for mechanical ventilation.

Comparison of quick SOFA and SIRS scales at the bedside of patients with Staphylococcus aureus bacteremia

Introducción:

Staphylococcus aureus es una de las principales causas de bacteriemia, adquirida en la comunidad o asociada con la atención en salud, la cual presenta un gran porcentaje de complicaciones y elevadas tasas de morbilidad y mortalidad. Los criterios SRIS (Systemic Inflammatory Response Syndrome) se han usado tradicionalmente con el fin de establecer la presencia de sepsis; sin embargo, recientemente se ha cuestionado su valor predictivo dada su baja sensibilidad y especificidad. En el 2016, apareció la escala qSOFA (quick Sequential Organ Failure Assessment), como una nueva herramienta para la evaluación rápida de las infecciones en los servicios de urgencias.

Objetivo.

Comparar las herramientas qSOFA y SRIS para la predicción de la bacteriemia por S. aureus.

Materiales y métodos.

Se hizo un estudio observacional sobre el comportamiento clínico de pacientes con bacteriemia por S. aureus para evaluar el perfil de resistencia fenotípica, algunas características sociodemográficas, clínicas y de laboratorio, las complicaciones y la mortalidad, así como los resultados de las evaluaciones con la escala qSOFA y los criterios SRIS, para establecer cuál podría predecir mejor la presencia de bacteriemia por S. aureus.

Resultados.

Se seleccionaron 26 pacientes con bacteriemia, en cuyas muestras S. aureus había sido el segundo germen más frecuentemente aislado. Se encontró una mortalidad del 50 % (13 casos) y una prevalencia del 30 % de S. aureus resistente a meticilina (SARM). Según los puntajes clínicos obtenidos, la escala qSOFA fue positiva en 30,8 % de los pacientes y los criterios SRIS lo fueron en el 92,3 %.

Discusión.

Se encontró una elevada mortalidad en la población analizada. La escala qSOFA fue menos efectiva para el diagnóstico que los criterios clásicos de reacción inflamatoria sistémica.

Predictors of mortality of influenza virus infections in a Swiss Hospital during four influenza seasons: Role of quick sequential organ failure assessment

BACKGROUND

Influenza infections have been associated with high morbidity. The aims were to determine predictors of mortality among patients with influenza infections and to ascertain the role of quick Sequential Organ Failure Assessment (qSOFA) in predicting poor outcomes.

METHODS

All adult patients with influenza infection at the Hospital of Jura, Switzerland during four influenza seasons (2014/15 to 2017/18) were included. Cepheid Xpert Xpress Flu/RSV was used during the first three influenza seasons and Cobas Influenza A/B and RSV during the 2017/18 season.

RESULTS

Among 1684 influenza virus tests performed, 441 patients with influenza infections were included (238 for influenza A virus and 203 for B). The majority of infections were community onset (369; 83.7%). Thirty-day mortality was 6.0% (25 patients). Multivariate analysis revealed that infection due to A virus (P 0.035; OR 7.1; 95% CI 1.1-43.8), malnutrition (P < 0.001; OR 25.0; 95% CI 4.5-138.8), hospital-acquired infection (P 0.003; OR 12.2; 95% CI 2.3-65.1), respiratory insufficiency (PaO₂/FiO₂ < 300) (P < 0.001; OR 125.8; 95% CI 9.6-1648.7) and pulmonary infiltrate on X-ray (P 0.020; OR 6.0; 95% CI 1.3-27.0) were identified as predictors of mortality. qSOFA showed a very good accuracy (0.89) equivalent to other more specific and burdensome scores such as CURB-65 and Pneumonia Severity Index (PSI).

CONCLUSION

qSOFA performed similarly to specific severity scores (PSI, CURB-65) in predicting mortality. Infection by influenza A virus, respiratory insufficiency and malnutrition were associated with worse prognosis.