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1. Fast track triage for COVID-19 based on a population study: The soda score

Author

Javier Lopez-Pais, Diego López Otero, Teba González-Ferrero, Carla Eugenia Cacho Antonio, Pablo José Antúnez Muiños, Marta Perez-Poza, Óscar Otero García, Victor Jimenez Ramos, Manuela Sestayo Fernández, María Bastos Fernandez, Xoan Carlos Sanmartin Pena, Alfonso Varela Roman, Manuel Portela Romero, Ana López Lago, Julián Álvarez Escudero, Alberto San Román, and Jose Ramón Gonzalez-Juanatey

Subjects
Score, Triage, Fast-track, COVID-19, Prognosis, Medicine
Abstract

Background: Healthcare systems are under prominent stress due to the COVID-19 pandemic. A fast and simple triage is mandatory to screen patients who will benefit from early hospitalization, from those that can be managed as outpatients. There is a lack of all-comers scores, and no score has been proposed for western-world population. Aims: To develop a fast-track risk score valid for every COVID-19 patient at diagnosis. Methods: Single-center, retrospective study based on all the inhabitants of a healthcare area. Logistic regression was used to identify simple and wide-available risk factors for adverse events (death, intensive care admission, invasive mechanical ventilation, bleeding > BARC3, acute renal injury, respiratory insufficiency, myocardial infarction, acute heart failure, pulmonary emboli, or stroke). Results: Of the total healthcare area population, 447.979 inhabitants, 965 patients (0.22%), were diagnosed with COVID-19. A total of 124 patients (12.85%) experienced adverse events. The novel SODA score (based on sex, peripheral O2 saturation, presence of diabetes, and age) demonstrated good accuracy for adverse events prediction (area under ROC curve 0.858, CI: 0.82–0.98). A cut-off value of ≤2 points identifies patients with low risk (positive predictive value [PPV] for absence of events: 98.9%) and a cut-off of ≥5 points, high-risk patients (PPV 58.8% for adverse events). Conclusions: This quick and easy score allows fast-track triage at the moment of diagnosis for COVID-19 using four simple variables: age, sex, SpO2, and diabetes. SODA score could improve preventive measures taken at diagnosis in high-risk patients and also relieve resources by identifying very low-risk patients.

Published
2021
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2. Prognostic Impact of Change in Nutritional Risk on Mortality and Heart Failure After Transcatheter Aortic Valve Replacement

Author

Javier López Pais, Ana Belen Cid Alvarez, Marta Perez Poza, Mária Juskowa, José Ramón González Juanatey, Rocío González Ferreiro, Xoan Carlos Sanmartín Pena, Ignacio Cruz-González, Pedro Luis Sánchez Fernández, Óscar Otero García, Diego López Otero, Leyre Álvarez Rodríguez, Ramiro Trillo Nouche, Carla Eugenia Cacho Antonio, and Pablo José Antúnez Muiños

Subjects
Heart Failure, medicine.medical_specialty, Transcatheter aortic, business.industry, medicine.medical_treatment, Nutritional status, Aortic Valve Stenosis, medicine.disease, Prognosis, Severity of Illness Index, Transcatheter Aortic Valve Replacement, Malnutrition, Treatment Outcome, Valve replacement, Risk Factors, Internal medicine, Heart failure, Aortic Valve, medicine, Cardiology, Humans, Prospective Studies, Cardiology and Cardiovascular Medicine, business, Nutritional risk
Abstract

Background: Limited data are available regarding change in the nutritional status after transcatheter aortic valve replacement (TAVR). This study evaluated the prognostic impact of the change in the geriatric nutritional risk index following TAVR. Methods: TAVR patients were analyzed in a prospective and observational study. To analyze the change in nutritional status, geriatric nutritional risk index of the patients was calculated on the day of TAVR and at 3-month follow-up. The impact of the change in nutritional risk index after TAVR on all-cause mortality, heart failure hospitalization (HF-h), and the composite of all-cause death and HF hospitalization was analyzed using the Cox Proportional Hazards model. Results: Four hundred thirty-three patients were included. After TAVR, 68.4% (n=182) patients with baseline nutritional risk improved compared with 31.6% (n=84) who remained at nutritional risk. The change from no-nutritional risk to nutritional risk after TAVR occurred in 15.0% (n=25), while 85.0% (n=142) remained without risk of malnutrition. During follow-up, 157 (36.3%) patients died and 172 patients (39.7%) were hospitalized due to HF. Patients who continued to be at nutritional risk had a higher risk of mortality (hazard ratio [HR], 2.10 [95% CI, 1.30–3.39], P =0.002), HF-h (HR, 1.97 [95% CI, 1.26–3.06], P =0.000), and the composite of death and HF-h (HR, 2.0 [95% CI, 1.37–2.91], P P =0.003), HF-h (HR, 0.50 [95% CI, 0.34–0.74], P =0.001), and the composite outcome (HR, 0.44 [95% CI, 0.32–0.62], P Conclusions: Remaining at nutritional risk after TAVR confers a poor prognosis and is associated with an increased risk of mortality and HF-h, while the change from risk of malnutrition to non-nutritional risk after TAVR was associated with a halving of the risk of mortality and HF-h. Further studies are needed to identify whether patients at nutritional risk would benefit from nutritional intervention during processes of care of TAVR programs.

Published
2021

3. The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients

Author

Diego López Otero, Jordi Candela, Carla Eugenia Cacho Antonio, J. Alberto San Román, Teba González Ferrero, Gino Rojas, Pablo Catalá, Javier López Pais, José Francisco Gil, Óscar Otero García, Carlos Veras, V. Ramos, Pablo José Antúnez Muiños, José Ramón González-Juanatey, Gonzalo Cabezón, Álvaro Aparisi, Ignacio J. Amat-Santos, and Marta Perez Poza

Subjects
Male, medicine.medical_specialty, Multivariate analysis, Science, medicine.medical_treatment, 030204 cardiovascular system & hematology, Risk Assessment, Procalcitonin, Article, law.invention, 03 medical and health sciences, 0302 clinical medicine, Medical research, law, Internal medicine, Medicine, Humans, 030212 general & internal medicine, Aged, Retrospective Studies, Mechanical ventilation, Multidisciplinary, Framingham Risk Score, business.industry, SARS-CoV-2, COVID-19, Retrospective cohort study, Intensive care unit, Hospitalization, Treatment Outcome, Spain, Multivariate Analysis, Infectious diseases, Observational study, Female, business, Risk assessment, Biomarkers
Abstract

Purpose: Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients.Methods: All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that contributed with significant predictive value for predicting mortality to the clinical model were included. Cut-off points were established, and finally a risk score was built. Results: 893 patients were included. Median age was 68.2 years(CI 95% 53.0-83.4). 87(9.7%) were admitted to Intensive Care Unit(ICU) and 72(8.1%) also needed mechanical ventilation support. 171(19.1%) patients died. A Covid-19 Lab score ranging from 0 to 30 points was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included haemoglobin, erythrocytes, leukocytes, neutrophils, lymphocytes, creatinine, C-reactive protein, interleukin-6, procalcitonin, lactate dehydrogenase (LDH), and D-dimer. Three groups were established. Low mortality risk group under 12 points, 12 to 18 were included as moderate risk, and high risk group were those with 19 or more points. Low risk group as reference, moderate and high patients showed mortality OR 4.75(CI95% 2.60-8.68) and 23.86(CI 95% 13.61-41.84), respectively. C-statistic was 0-85(0.82-0.88) and Hosmer-Lemeshow p-value 0.63.Conclusion: Covid-19 Lab score can very easily predict mortality in patients at any moment during admission secondary to SARS-CoV2 infection. It is a simple and dynamic score, and it can be very easily replicated. It could help physicians to identify high risk patients to foresee clinical deterioration.

Published
2020

4. TCT-136 Validation of Surgical Risk Scores (EuroSCORE, EuroSCORE II, and STS) Power to Predict Mortality After TAVR

Author

Pablo José Antúnez Muiños, Diego López Otero, Rocío González Ferreiro, Ana Belen Cid Alvarez, Fernando Gómez Peña, Alfredo Redondo Diéguez, Ramiro Trillo, Javier López-Pais, and Marta Perez Poza

Subjects
medicine.medical_specialty, Framingham Risk Score, Transcatheter aortic, business.industry, medicine.medical_treatment, EuroSCORE, Surgical risk, Clinical Practice, Euroscore ii, Valve replacement, Internal medicine, Cardiology, Medicine, Cardiology and Cardiovascular Medicine, business
Abstract

Transcatheter aortic valve replacement (TAVR) has been one of the greatest revolutions of twenty-first century cardiology. Despite its consolidation and the high worldwide volume of procedures, we are still missing a proper risk score, so that surgical risk scores are used in daily clinical practice

Published
2019

5. TCT-702 Impact of Transcatheter Aortic Valve Replacement on Anemia: New Approach to Heyde’s Syndrome

Author

Diego López Otero, Ramiro Trillo Nouche, Xabier Cia Mendioroz, Leyre Álvarez Rodríguez, Arturo García-Touchard, Marta Perez Poza, Javier López-Pais, Ana Belen Cid Alvarez, Juan Francisco Oteo Dominguez, Pablo José Antúnez Muiños, and Barbara Izquierdo Coronel

Subjects
Gastrointestinal bleeding, medicine.medical_specialty, Transcatheter aortic, Anemia, business.industry, Heyde's syndrome, medicine.medical_treatment, medicine.disease, Stenosis, Valve replacement, Von willebrand, hemic and lymphatic diseases, Internal medicine, medicine, Cardiology, Cardiology and Cardiovascular Medicine, business
Abstract

There is a frequent association between aortic stenosis and anemia due to gastrointestinal bleeding (GIB), also known as Heyde’s syndrome, caused by an acquired von Willebrand deficiency related to turbulent flow. Surgical valve replacement had shown a reduction in GIB. We postulate that

Published
2019

6. The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients

Author

Pablo Jose Antunez Muiños, Diego López Otero, Ignacio J. Amat-Santos, Javier López País, Alvaro Aparisi, Carla E. Cacho Antonio, Pablo Catalá, Teba González Ferrero, Gonzalo Cabezón, Oscar Otero García, José Francisco Gil, Marta Pérez Poza, Jordi Candela, Gino Rojas, Víctor Jiménez Ramos, Carlos Veras, J. Alberto San Román, and José R. González-Juanatey

Subjects
Medicine, Science
Abstract

Abstract Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients. All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that contributed with significant predictive value for predicting mortality to the clinical model were included. Cut-off points were established, and finally a risk score was built. 893 patients were included. Median age was 68.2 ± 15.2 years. 87(9.7%) were admitted to Intensive Care Unit (ICU) and 72(8.1%) needed mechanical ventilation support. 171(19.1%) patients died. A Covid-19 Lab score ranging from 0 to 30 points was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included haemoglobin, erythrocytes, leukocytes, neutrophils, lymphocytes, creatinine, C-reactive protein, interleukin-6, procalcitonin, lactate dehydrogenase (LDH), and D-dimer. Three groups were established. Low mortality risk group under 12 points, 12 to 18 were included as moderate risk, and high risk group were those with 19 or more points. Low risk group as reference, moderate and high patients showed mortality OR 4.75(CI95% 2.60–8.68) and 23.86(CI 95% 13.61–41.84), respectively. C-statistic was 0–85(0.82–0.88) and Hosmer–Lemeshow p-value 0.63. Covid-19 Lab score can very easily predict mortality in patients at any moment during admission secondary to SARS-CoV2 infection. It is a simple and dynamic score, and it can be very easily replicated. It could help physicians to identify high risk patients to foresee clinical deterioration.

Published
2021
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