Nonadverse COVID-19 evolution predictors: the CoNAE scale. / Predictores de evolución no adversa en pacientes con COVID-19: escala CoNAE (COVID-19 non-adverse evolution).

OBJECTIVES: Tools to identify patients with mild to moderate COVID-19 are as yet unavailable. Our aims were to identify factors associated with nonadverse outcomes and develop a scale to predict nonadverse evolution in patients with COVID-19 (the CoNAE scale) in hospital emergency departments. MATERIAL AND METHODS: Retrospective cohort study of patients who came to one of our area's national health service hospitals for treatment of SARS-CoV-2 infection from July 1, 2020, to July 31, 2021. From case records we collected sociodemographic information, underlying comorbidity and ongoing treatments, other relevant medical history details, and vital constants on arrival for triage. Multilevel multivariable logistic regression models were used to identify predictors. RESULTS: The model showed that patients who had nonadverse outcomes were younger, female, and vaccinated against COVID-19 (2 doses at the time of the study). They arrived with normal vital signs (heart rate, diastolic and systolic pressures, temperature, and oxygen saturation) and had none of the following concomitant diseases or factors: heart failure other heart disease, hypertension, diabetes, liver disease, dementia, history of malignant tumors, and they were not being treated with oral or other systemic corticosteroids or immunosuppressant therapy. The area under the receiver operating characteristic curve for the model was 0.840 (95% CI, 0.834-0.847). CONCLUSION: We developed the CoNAE scale to predict nonadverse outcomes. This scale may be useful in triage for evaluating patients with COVID-19. It may also help predict safe discharge or plan the level of care that patients require not only in a hospital emergency department but also in urgent primary care settings or out-of-hospital emergency care.

OBJETIVO: Faltan herramientas para identificar a los pacientes con COVID-19 moderado o leve. El objetivo de este estudio fue identificar variables asociadas a la evolución no adversa y diseñar un modelo predictivo de evolución favorable en pacientes atendidos en servicios de urgencias hospitalarios (SUH) por infección por SARS-CoV-2. METODO: Estudio de cohorte retrospectivo de pacientes con infección por SARS-CoV-2 que acudieron a alguno de los SUH de hospitales públicos de una área por una infección por COVID-19 entre el 1 de julio de 2020 y el 31 de julio de 2021. Los datos recogidos para este estudio incluyeron información sociodemográfica, comorbilidades basales y tratamientos, otros datos de antecedentes y registro de los signos vitales a la llegada (triaje) al SUH. Se utilizaron modelos de regresión logística multivariable multinivel para desarrollar los modelos predictivos. RESULTADOS: Las personas que tuvieron resultados no adversos eran más jóvenes, mujeres, habían recibido dos dosis de la vacuna COVID-19 en el momento del estudio, tenían signos vitales (frecuencia cardiaca-presión diastólica/sistólica, temperatura y saturación de oxígeno) dentro de un rango normal al llegar al triaje del SUH, y no tenían ninguna de las siguientes comorbilidades: insuficiencia cardiaca, enfermedad coronaria, hipertensión arterial, diabetes, enfermedad hepática, demencia, antecedentes de tumores malignos o prescripción de corticosteroides orales sistémicos o inmunosupresores como medicación basal. El modelo tenía un área bajo la curva (ABC) de 0,8404 (IC 95%: 0,8342-0,8466). CONCLUSIONES: Se ha desarrollado una escala de predicción de resultados no adversos que pueden ser útil como herramienta de triaje, así como para determinar el alta segura y para adaptar el nivel de atención que el paciente requiere, no sólo en el SUH, sino también a nivel de atención de emergencia primaria o extrahospitalaria.

Predictores de evolución no adversa en pacientes con COVID-19: escala CoNAE (COVID-19 non-adverse evolution) / Nonadverse COVID-19 evolution predictors: the CoNAE scale

Objetivos: Faltan herramientas para identificar a los pacientes con COVID-19 moderado o leve. El objetivo de este estudio fue identificar variables asociadas a la evolución no adversa y diseñar un modelo predictivo de evolución favorable en pacientes atendidos en servicios de urgencias hospitalarios (SUH) por infección por SARS-CoV-2. Métodos: Estudio de cohorte retrospectivo de pacientes con infección por SARS-CoV-2 que acudieron a alguno de los SUH de hospitales públicos de unaa área por una infección por COVID-19 entre el 1 de julio de 2020 y el 31 de julio de 2021. Los datos recogidos para este estudio incluyeron información sociodemográfica, comorbilidades basales y tratamientos, otros datos de antecedentes y registro de los signos vitales a la llegada (triaje) al SUH. Se utilizaron modelos de regresión logística multivariable multinivel para desarrollar los modelos predictivos. Resultados: Las personas que tuvieron resultados no adversos eran más jóvenes, mujeres, habían recibido dos dosis de la vacuna COVID-19 en el momento del estudio, tenían signos vitales (frecuencia cardiaca-presión diastólica/sistólica, temperatura y saturación de oxígeno) dentro de un rango normal al llegar al triaje del SUH, y no tenían ninguna de las siguientes comorbilidades: insuficiencia cardiaca, enfermedad coronaria, hipertensión arterial, diabetes, enfermedad hepática, demencia, antecedentes de tumores malignos o prescripción de corticosteroides orales sistémicos o inmunosupresores como medicación basal. El modelo tenía un área bajo la curva (ABC) de 0,8404 (IC 95%: 0,8342-0,8466). Conclusiones: Se ha desarrollado una escala de predicción de resultados no adversos que pueden ser útil como herramienta de triaje, así como para determinar el alta segura y para adaptar el nivel de atención que el paciente requiere, no sólo en el SUH, sino también a nivel de atención de emergencia primaria o extrahospitalaria. (AU)

Background and objectives: Tools to identify patients with mild to moderate COVID-19 are as yet unavailable. Our aims were to identify factors associated with nonadverse outcomes and develop a scale to predict nonadverse evolution in patients with COVID-19 (the CoNAE scale) in hospital emergency departments. Methods: Retrospective cohort study of patients who came to one of our area’s national health service hospitals for treatment of SARS-CoV-2 infection from July 1, 2020, to July 31, 2021. From case records we collected sociodemographicinformation, underlying comorbidity and ongoing treatments, other relevant medical history details, and vital constants on arrival for triage. Multilevel multivariable logistic regression models were used to identify predictors. Results: The model showed that patients who had nonadverse outcomes were younger, female, and vaccinated against COVID-19 (2 doses at the time of the study). They arrived with normal vital signs (heart rate, diastolic and systolic pressures, temperature, and oxygen saturation) and had none of the following concomitant diseases or factors: heart failure other heart disease, hypertension, diabetes, liver disease, dementia, history of malignant tumors, and they were not being treated with oral or other systemic corticosteroids or immunosuppressant therapy. The area under the receiver operating characteristic curve for the model was 0.840 (95% CI, 0.834-0.847). Conclusions: We developed the CoNAE scale to predict nonadverse outcomes. This scale may be useful in triage for evaluating patients with COVID-19. It may also help predict safe discharge or plan the level of care that patients require not only in a hospital emergency department but also in urgent primary care settings or out-of-hospital emergency care. (AU)

Management of community-acquired pneumonia and secular trends at different hospitals.

STUDY OBJECTIVES: The goal of this study was to assess variability in the management of patients admitted to hospitals with community-acquired pneumonia (CAP), and changes in secular trends of this condition. METHODS: Observational study carried out, in 5 teaching hospitals, in northern Spain of patients admitted with CAP between March 1,1998 and March 1,1999 (baseline period), and between March 1, 2000 and September 30, 2001 (follow-up period). Clinical histories were analyzed retrospectively for relevant parameters for process-of-care and outcome performance. Those parameters among hospitals during the baseline period were compared. For each hospital, changes in these parameters between baseline and follow-up were also measured. All parameters were adjusted for disease severity. RESULTS: A total of 844 patients were included in the baseline period, and 654 in the follow-up period. During the baseline period, adjusted analyses revealed statistically significant differences in all process-of-care parameters except the coverage of atypical pathogens. With regard to clinical outcomes, however, only the 30-day readmission rate was significantly different (P=0.03). Adjusted mean length of stay ranged from 6.3 to 9.2 days (P<0.0001). In adjusted analyses of temporal changes within hospitals for process-of-care and outcome performance, revealed few statistically significant differences. CONCLUSIONS: Variability discovered between hospitals in the management of patients in the absence of relevant secular changes in each hospital points out the necessity to implement measures designed to reduce such variability between hospitals and to improve the quality of medical treatment.