Mortality reduction in older COVID-19-patients hospitalized in Spain during the second pandemic wave from the SEMI-COVID-19 Registry.

In 2020, the COVID-19 pandemic followed a two-wave pattern in most countries. Hospital admission for COVID-19 in one wave or another could have affected mortality, especially among the older persons. The objective of this study was to evaluate whether the admission of older patients during the different waves, before SARS-CoV-2 vaccination was available, was associated with a different mortality. We compared the mortality rates of patients hospitalized during 2020 before (first wave) and after (second wave) July 7, 2020, included in the SEMI-COVID-19 Registry, a large, multicenter, retrospective cohort of patients admitted to 126 Spanish hospitals for COVID-19. A multivariate logistic regression analysis was performed to control for changes in either the patient or disease profile. As of December 26, 2022, 22,494 patients had been included (17,784 from the first wave and 4710 from the second one). Overall mortality was 20.4% in the first wave and 17.2% in the second wave (risk difference (RD) - 3.2%; 95% confidence interval (95% CI) - 4.4 to - 2.0). Only patients aged 70 and older (10,973 patients: 8571 in the first wave and 2386 in the second wave) had a significant reduction in mortality (RD - 7.6%; 95% CI - 9.7 to - 5.5) (unadjusted relative risk reduction: 21.6%). After adjusting for age, comorbidities, variables related to the severity of the disease, and treatment received, admission during the second wave remained a protective factor. In Spain, patients aged 70 years and older admitted during the second wave of the COVID-19 pandemic had a significantly lower risk of mortality, except in severely dependent persons in need of corticosteroid treatment. This effect is independent of patient characteristics, disease severity, or treatment received. This suggests a protective effect of a better standard of care, greater clinical expertise, or a lesser degree of healthcare system overload.

Improving prediction of COVID-19 mortality using machine learning in the Spanish SEMI-COVID-19 registry.

COVID-19 is responsible for high mortality, but robust machine learning-based predictors of mortality are lacking. To generate a model for predicting mortality in patients hospitalized with COVID-19 using Gradient Boosting Decision Trees (GBDT). The Spanish SEMI-COVID-19 registry includes 24,514 pseudo-anonymized cases of patients hospitalized with COVID-19 from 1 February 2020 to 5 December 2021. This registry was used as a GBDT machine learning model, employing the CatBoost and BorutaShap classifier to select the most relevant indicators and generate a mortality prediction model by risk level, ranging from 0 to 1. The model was validated by separating patients according to admission date, using the period 1 February to 31 December 2020 (first and second waves, pre-vaccination period) for training, and 1 January to 30 November 2021 (vaccination period) for the test group. An ensemble of ten models with different random seeds was constructed, separating 80% of the patients for training and 20% from the end of the training period for cross-validation. The area under the receiver operating characteristics curve (AUC) was used as a performance metric. Clinical and laboratory data from 23,983 patients were analyzed. CatBoost mortality prediction models achieved an AUC performance of 84.76 (standard deviation 0.45) for patients in the test group (potentially vaccinated patients not included in model training) using 16 features. The performance of the 16-parameter GBDT model for predicting COVID-19 hospital mortality, although requiring a relatively large number of predictors, shows a high predictive capacity.

Nosocomial COVID-19: A Nationwide Spanish Study.

INTRODUCTION: SARS-CoV-2 is a highly contagious virus, and despite professionals' best efforts, nosocomial COVID-19 (NC) infections have been reported. This work aimed to describe differences in symptoms and outcomes between patients with NC and community-acquired COVID-19 (CAC) and to identify risk factors for severe outcomes among NC patients. METHODS: This is a nationwide, retrospective, multicenter, observational study that analyzed patients hospitalized with confirmed COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry) from March 1, 2020, to April 30, 2021. NC was defined as patients admitted for non-COVID-19 diseases with a positive SARS-CoV-2 test on the fifth day of hospitalization or later. The primary outcome was 30-day in-hospital mortality (IHM). The secondary outcome was other COVID-19-related complications. A multivariable logistic regression analysis was performed. RESULTS: Of the 23,219 patients hospitalized with COVID-19, 1,104 (4.8%) were NC. Compared to CAC patients, NC patients were older (median 76 vs. 69 years; p < 0.001), had more comorbidities (median Charlson Comorbidity Index 5 vs. 3; p < 0.001), were less symptomatic (p < 0.001), and had normal chest X-rays more frequently (30.8% vs. 12.5%, p < 0.001). After adjusting for sex, age, dependence, COVID-19 wave, and comorbidities, NC was associated with lower risk of moderate/severe acute respiratory distress syndrome (ARDS) (adjusted odds ratio [aOR]: 0.72; 95% confidence interval [CI]: 0.59-0.87; p < 0.001) and higher risk of acute heart failure (aOR: 1.40; 1.12-1.72; p = 0.003), sepsis (aOR: 1.73; 1.33-2.54; p < 0.001), and readmission (aOR: 1.35; 1.03-1.83; p = 0.028). NC was associated with a higher case fatality rate (39.1% vs. 19.2%) in all age groups. IHM was significantly higher among NC patients (aOR: 2.07; 1.81-2.68; p < 0.001). Risk factors for increased IHM in NC patients were age, moderate/severe dependence, malignancy, dyspnea, moderate/severe ARDS, multiple organ dysfunction syndrome, and shock; odynophagia was associated with lower IHM. CONCLUSIONS: NC is associated with greater mortality and complications compared to CAC. Hospital strategies to prevent NC must be strengthened.

Influencia de la historia de tabaquismo en la evolución de la hospitalización en pacientes COVID-19 positivos: datos del registro SEMI-COVID-19 / Influence of smoking history on the evolution of hospitalized in COVID-19 positive patients: results from the SEMI-COVID-19 registry

Introducción: El tabaquismo puede tener un papel importante en la infección por SARS-CoV-2 y en el curso de la enfermedad. Los estudios previos muestran resultados contradictorios o no concluyentes sobre la prevalencia de fumar y la severidad en la enfermedad por coronavirus (COVID-19).Material y métodosEstudio de cohortes observacional, multicéntrico y retrospectivo de 14.260 pacientes que ingresaron por COVID-19 en hospitales españoles desde febrero hasta septiembre de 2020. Se registraron sus características clínicas y se clasificaron en el grupo con tabaquismo si tabaquismo activo o previo, o en el grupo sin tabaquismo si nunca habían fumado. Se realizó un seguimiento hasta un mes después del alta. Se analizaron las diferencias entre grupos. La relación entre tabaquismo y mortalidad intrahospitalaria se valoró mediante una regresión logística multivariante y curvas de Kapplan Meier.ResultadosLa mediana de edad fue 68,6 (55,8-79,1) años, con un 57,7% de varones. El grupo con tabaquismo presentó mayor edad (69,9 [59,6-78,0 años]), predominio masculino (80,3%) y mayor índice de Charlson (4 [2-6]). La evolución fue peor en estos pacientes, con una mayor tasa de ingreso en UCI (10,4 vs. 8,1%), mayor mortalidad intrahospitalaria (22,5 vs. 16,4%) y reingreso al mes (5,8 vs. 4,0%) que el grupo sin tabaquismo. Tras el análisis multivariante, el tabaquismo permanecía asociado a estos eventos.ConclusionesEl tabaquismo de forma activa o pasada es un factor predictor independiente de mal pronóstico en los pacientes con COVID-19, estando asociado a mayor probabilidad de ingreso en UCI y a mayor mortalidad intrahospitalaria. (AU)

Introduction: Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the coronavirus disease (COVID-19).MethodsObservational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analyzed. A multivariate logistic regression and Kapplan Meier curves analyzed the relationship between smoking and in-hospital mortality.ResultsThe median age was 68.6 (55.8-79.1) years, with 57.7% of males. Smoking patients were older (69.9 [59.6-78.0 years]), more frequently male (80.3%) and with higher Charlson index (4 [2-6]) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events.ConclusionsActive or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality. (AU)

Influence of smoking history on the evolution of hospitalized in COVID-19 positive patients: Results from the SEMI-COVID-19 registry.

Introduction: Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the coronavirus disease (COVID-19). Methods: Observational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analysed. A multivariate logistic regression and Kapplan Meier curves analysed the relationship between smoking and in-hospital mortality. Results: The median age was 68.6 (55.8-79.1) years, with 57.7% of males. Smoking patients were older (69.9 (59.6-78.0 years)), more frequently male (80.3%) and with higher Charlson index (4 (2-6)) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs. 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events. Conclusions: Active or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality.

Introducción: El tabaquismo puede tener un papel importante en la infección por SARS-CoV-2 y en el curso de la enfermedad. Los estudios previos muestran resultados contradictorios o no concluyentes sobre la prevalencia de fumar y la severidad en la enfermedad por coronavirus (COVID-19). Material y métodos: Estudio de cohortes observacional, multicéntrico y retrospectivo de 14.260 pacientes que ingresaron por COVID-19 en hospitales españoles desde febrero a septiembre de 2020. Se registraron sus características clínicas y se clasificaron en el grupo con tabaquismo si tabaquismo activo o previo o en el grupo sin tabaquismo si nunca habían fumado. Se realizó un seguimiento hasta un mes después del alta. Se analizaron las diferencias entre grupos. La relación entre tabaquismo y mortalidad intrahospitalaria se valoró mediante una regresión logística multivariante y curvas de Kapplan Meier. Resultados: La mediana de edad fue 68,6 (55,8­79,1) años, con un 57,7% de varones. El grupo con tabaquismo presentó mayor edad (69,9 (59,6­78,0 años)), predominio masculino (80,3%) y mayor índice de Charlson (4 (2−6)). La evolución fue peor en estos pacientes, con una mayor tasa de ingreso en UCI (10,4 vs 8,1%), mayor mortalidad intrahospitalaria (22,5 vs 16,4%) y reingreso al mes (5,8 vs 4,0%) que el grupo sin tabaquismo. Tras el análisis multivariante, el tabaquismo permanecía asociado a estos eventos. Conclusiones: El tabaquismo de forma activa o pasada es un factor predictor independiente de mal pronóstico en los pacientes con COVID-19, estando asociada a mayor probabilidad de ingreso en UCI y a mayor mortalidad intrahospitalaria.

C-Reactive Protein and Serum Albumin Ratio: A Feasible Prognostic Marker in Hospitalized Patients with COVID-19.

(1) Background: C-reactive protein (CRP) and albumin are inflammatory markers. We analyzed the prognostic capacity of serum albumin (SA) and CRP for an outcome comprising mortality, length of stay, ICU admission, and non-invasive mechanical ventilation in hospitalized COVID-19 patients. (2) Methods: We conducted a retrospective cohort study based on the Spanish national SEMI-COVID-19 Registry. Two multivariate logistic models were adjusted for SA, CRP, and their combination. Training and testing samples were used to validate the models. (3) Results: The outcome was present in 41.1% of the 3471 participants, who had lower SA (mean [SD], 3.5 [0.6] g/dL vs. 3.8 [0.5] g/dL; p < 0.001) and higher CRP (108.9 [96.5] mg/L vs. 70.6 [70.3] mg/L; p < 0.001). In the adjusted multivariate model, both were associated with poorer evolution: SA, OR 0.674 (95% CI, 0.551−0.826; p < 0.001); CRP, OR 1.002 (95% CI, 1.001−1.004; p = 0.003). The CRP/SA model had a similar predictive capacity (honest AUC, 0.8135 [0.7865−0.8405]), with a continuously increasing risk and cutoff value of 25 showing the highest predictive capacity (OR, 1.470; 95% CI, 1.188−1.819; p < 0.001). (4) Conclusions: SA and CRP are good independent predictors of patients hospitalized with COVID-19. For the CRP/SA ratio value, 25 is the cutoff for poor clinical course.

Ethnicity and Clinical Outcomes in Patients Hospitalized for COVID-19 in Spain: Results from the Multicenter SEMI-COVID-19 Registry.

(1) Background: This work aims to analyze clinical outcomes according to ethnic groups in patients hospitalized for COVID-19 in Spain. (2) Methods: This nationwide, retrospective, multicenter, observational study analyzed hospitalized patients with confirmed COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry) from 1 March 2020 to 31 December 2021. Clinical outcomes were assessed according to ethnicity (Latin Americans, Sub-Saharan Africans, Asians, North Africans, Europeans). The outcomes were in-hospital mortality (IHM), intensive care unit (ICU) admission, and the use of invasive mechanical ventilation (IMV). Associations between ethnic groups and clinical outcomes adjusted for patient characteristics and baseline Charlson Comorbidity Index values and wave were evaluated using logistic regression. (3) Results: Of 23,953 patients (median age 69.5 years, 42.9% women), 7.0% were Latin American, 1.2% were North African, 0.5% were Asian, 0.5% were Sub-Saharan African, and 89.7% were European. Ethnic minority patients were significantly younger than European patients (median (IQR) age 49.1 (40.5−58.9) to 57.1 (44.1−67.1) vs. 71.5 (59.5−81.4) years, p < 0.001). The unadjusted IHM was higher in European (21.6%) versus North African (11.4%), Asian (10.9%), Latin American (7.1%), and Sub-Saharan African (3.2%) patients. After further adjustment, the IHM was lower in Sub-Saharan African (OR 0.28 (0.10−0.79), p = 0.017) versus European patients, while ICU admission rates were higher in Latin American and North African versus European patients (OR (95%CI) 1.37 (1.17−1.60), p < 0.001) and (OR (95%CI) 1.74 (1.26−2.41), p < 0.001). Moreover, Latin American patients were 39% more likely than European patients to use IMV (OR (95%CI) 1.43 (1.21−1.71), p < 0.001). (4) Conclusion: The adjusted IHM was similar in all groups except for Sub-Saharan Africans, who had lower IHM. Latin American patients were admitted to the ICU and required IMV more often.

WHO Ordinal Scale and Inflammation Risk Categories in COVID-19. Comparative Study of the Severity Scales.

BACKGROUND: The WHO ordinal severity scale has been used to predict mortality and guide trials in COVID-19. However, it has its limitations. OBJECTIVE: The present study aims to compare three classificatory and predictive models: the WHO ordinal severity scale, the model based on inflammation grades, and the hybrid model. DESIGN: Retrospective cohort study with patient data collected and followed up from March 1, 2020, to May 1, 2021, from the nationwide SEMI-COVID-19 Registry. The primary study outcome was in-hospital mortality. As this was a hospital-based study, the patients included corresponded to categories 3 to 7 of the WHO ordinal scale. Categories 6 and 7 were grouped in the same category. KEY RESULTS: A total of 17,225 patients were included in the study. Patients classified as high risk in each of the WHO categories according to the degree of inflammation were as follows: 63.8% vs. 79.9% vs. 90.2% vs. 95.1% (p<0.001). In-hospital mortality for WHO ordinal scale categories 3 to 6/7 was as follows: 0.8% vs. 24.3% vs. 45.3% vs. 34% (p<0.001). In-hospital mortality for the combined categories of ordinal scale 3a to 5b was as follows: 0.4% vs. 1.1% vs. 11.2% vs. 27.5% vs. 35.5% vs. 41.1% (p<0.001). The predictive regression model for in-hospital mortality with our proposed combined ordinal scale reached an AUC=0.871, superior to the two models separately. CONCLUSIONS: The present study proposes a new severity grading scale for COVID-19 hospitalized patients. In our opinion, it is the most informative, representative, and predictive scale in COVID-19 patients to date.

Use of glucocorticoids megadoses in SARS-CoV-2 infection in a spanish registry: SEMI-COVID-19.

OBJECTIVE: To describe the impact of different doses of corticosteroids on the evolution of patients with COVID-19 pneumonia, based on the potential benefit of the non-genomic mechanism of these drugs at higher doses. METHODS: Observational study using data collected from the SEMI-COVID-19 Registry. We evaluated the epidemiological, radiological and analytical scenario between patients treated with megadoses therapy of corticosteroids vs low-dose of corticosteroids and the development of complications. The primary endpoint was all-cause in-hospital mortality according to use of corticosteroids megadoses. RESULTS: Of a total of 14,921 patients, corticosteroids were used in 5,262 (35.3%). Of them, 2,216 (46%) specifically received megadoses. Age was a factor that differed between those who received megadoses therapy versus those who did not in a significant manner (69 years [IQR 59-79] vs 73 years [IQR 61-83]; p < .001). Radiological and analytical findings showed a higher use of megadoses therapy among patients with an interstitial infiltrate and elevated inflammatory markers associated with COVID-19. In the univariate study it appears that steroid use is associated with increased mortality (OR 2.07 95% CI 1.91-2.24 p < .001) and megadose use with increased survival (OR 0.84 95% CI 0.75-0.96, p 0.011), but when adjusting for possible confounding factors, it is observed that the use of megadoses is also associated with higher mortality (OR 1.54, 95% CI 1.32-1.80; p < .001). There is no difference between megadoses and low-dose (p .298). Although, there are differences in the use of megadoses versus low-dose in terms of complications, mainly infectious, with fewer pneumonias and sepsis in the megadoses group (OR 0.82 95% CI 0.71-0.95; p < .001 and OR 0.80 95% CI 0.65-0.97; p < .001) respectively. CONCLUSION: There is no difference in mortality with megadoses versus low-dose, but there is a lower incidence of infectious complications with glucocorticoid megadoses.

Influence of smoking history on the evolution of hospitalized in COVID-19 positive patients: results from the SEMI-COVID-19 registry. / Influencia de la historia de tabaquismo en la evolución de la hospitalización en pacientes COVID-19 positivos: datos del registro SEMI-COVID-19.

INTRODUCTION: Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the coronavirus disease (COVID-19). METHODS: Observational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analyzed. A multivariate logistic regression and Kapplan Meier curves analyzed the relationship between smoking and in-hospital mortality. RESULTS: The median age was 68.6 (55.8-79.1) years, with 57.7% of males. Smoking patients were older (69.9 [59.6-78.0 years]), more frequently male (80.3%) and with higher Charlson index (4 [2-6]) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events. CONCLUSIONS: Active or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality.

Screening Protocol and Prevalence of Venous Thromboembolic Disease in Hospitalized Patients With COVID-19.

BACKGROUND: SARS-CoV-2 disease (COVID-19) induces endothelial damage and sustained hypoxia and facilitates immobilization as factors of hypercoagulability. OBJECTIVES: The objective of our study was to assess the prevalence of venous thromboembolic disease (VTD) in COVID-19 patients and the usefulness of VTD screening based on age-adjusted D-dimer and point-of-care ultrasound (POCUS). PATIENTS/METHODS: We conducted a single cohort, prospective observational study in 102 consecutive hospitalized patients. RESULTS: A total of 102 POCUS and 39 pulmonary computed tomography angiography (PCTA) were performed diagnosing 27 VTD (26.5%): 17 deep vein thrombosis (DVT) (16.6% positive POCUS) and 18 pulmonary embolism (PE) (46.2% positive PCTA). COVID-19 patients with VTD were older (P < .030), had higher D-dimer (P < .001), higher International Society on Thrombosis and Hemostasis score (P < .001), and higher mortality (P = .025). However, there were no differences in inflammatory laboratory parameters neither in the cytokine storm syndrome (CSS) development. The ROC curve for D-dimer showed an AUC of 0.91. We have evidenced that patients with D-dimer between 2000 and 6000 ng/mL could benefit from a screening strategy with POCUS given the high sensitivity and specificity of the test. Furthermore, patients with D-dimer ≥6000 ng/mL should undergo POCUS and PCTA to rule out DVT and PE, respectively. CONCLUSIONS: In our cohort, 26.5% of the patients presented VTD. Screening strategy based on age-adjusted D-dimer and POCUS proved high sensitivity and specificity. Future trials focused on screening strategies are necessary to early detect the presence of DVT and PE and determine thromboprophylaxis strategies in patients with COVID-19.

Inadequate use of antibiotics in the covid-19 era: effectiveness of antibiotic therapy.

BACKGROUND: Since December 2019, the COVID-19 pandemic has changed the concept of medicine. This work aims to analyze the use of antibiotics in patients admitted to the hospital due to SARS-CoV-2 infection. METHODS: This work analyzes the use and effectiveness of antibiotics in hospitalized patients with COVID-19 based on data from the SEMI-COVID-19 registry, an initiative to generate knowledge about this disease using data from electronic medical records. Our primary endpoint was all-cause in-hospital mortality according to antibiotic use. The secondary endpoint was the effect of macrolides on mortality. RESULTS: Of 13,932 patients, antibiotics were used in 12,238. The overall death rate was 20.7% and higher among those taking antibiotics (87.8%). Higher mortality was observed with use of all antibiotics (OR 1.40, 95% CI 1.21-1.62; p < .001) except macrolides, which had a higher survival rate (OR 0.70, 95% CI 0.64-0.76; p < .001). The decision to start antibiotics was influenced by presence of increased inflammatory markers and any kind of infiltrate on an x-ray. Patients receiving antibiotics required respiratory support and were transferred to intensive care units more often. CONCLUSIONS: Bacterial co-infection was uncommon among COVID-19 patients, yet use of antibiotics was high. There is insufficient evidence to support widespread use of empiric antibiotics in these patients. Most may not require empiric treatment and if they do, there is promising evidence regarding azithromycin as a potential COVID-19 treatment.

Estimation of Admission D-dimer Cut-off Value to Predict Venous Thrombotic Events in Hospitalized COVID-19 Patients: Analysis of the SEMI-COVID-19 Registry.

BACKGROUND: Venous thrombotic events (VTE) are frequent in COVID-19, and elevated plasma D-dimer (pDd) and dyspnea are common in both entities. OBJECTIVE: To determine the admission pDd cut-off value associated with in-hospital VTE in patients with COVID-19. METHODS: Multicenter, retrospective study analyzing the at-admission pDd cut-off value to predict VTE and anticoagulation intensity along hospitalization due to COVID-19. RESULTS: Among 9386 patients, 2.2% had VTE: 1.6% pulmonary embolism (PE), 0.4% deep vein thrombosis (DVT), and 0.2% both. Those with VTE had a higher prevalence of tachypnea (42.9% vs. 31.1%; p = 0.0005), basal O2 saturation <93% (45.4% vs. 33.1%; p = 0.0003), higher at admission pDd (median [IQR]: 1.4 [0.6-5.5] vs. 0.6 [0.4-1.2] µg/ml; p < 0.0001) and platelet count (median [IQR]: 208 [158-289] vs. 189 [148-245] platelets × 109/L; p = 0.0013). A pDd cut-off of 1.1 µg/ml showed specificity 72%, sensitivity 49%, positive predictive value (PPV) 4%, and negative predictive value (NPV) 99% for in-hospital VTE. A cut-off value of 4.7 µg/ml showed specificity of 95%, sensitivity of 27%, PPV of 9%, and NPV of 98%. Overall mortality was proportional to pDd value, with the lowest incidence for each pDd category depending on anticoagulation intensity: 26.3% for those with pDd >1.0 µg/ml treated with prophylactic dose (p < 0.0001), 28.8% for pDd for patients with pDd >2.0 µg/ml treated with intermediate dose (p = 0.0001), and 31.3% for those with pDd >3.0 µg/ml and full anticoagulation (p = 0.0183). CONCLUSIONS: In hospitalized patients with COVID-19, a pDd value greater than 3.0 µg/ml can be considered to screen VTE and to consider full-dose anticoagulation.

Predicting critical illness on initial diagnosis of COVID-19 based on easily obtained clinical variables: development and validation of the PRIORITY model.

OBJECTIVES: We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of critical outcomes. METHODS: We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model. RESULTS: There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344). CONCLUSIONS: The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes.

Risk Categories in COVID-19 Based on Degrees of Inflammation: Data on More Than 17,000 Patients from the Spanish SEMI-COVID-19 Registry.

(1) Background: The inflammation or cytokine storm that accompanies COVID-19 marks the prognosis. This study aimed to identify three risk categories based on inflammatory parameters on admission. (2) Methods: Retrospective cohort study of patients diagnosed with COVID-19, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish SEMI-COVID-19 Registry. The three categories of low, intermediate, and high risk were determined by taking into consideration the terciles of the total lymphocyte count and the values of C-reactive protein, lactate dehydrogenase, ferritin, and D-dimer taken at the time of admission. (3) Results: A total of 17,122 patients were included in the study. The high-risk group was older (57.9 vs. 64.2 vs. 70.4 years; p < 0.001) and predominantly male (37.5% vs. 46.9% vs. 60.1%; p < 0.001). They had a higher degree of dependence in daily tasks prior to admission (moderate-severe dependency in 10.8% vs. 14.1% vs. 17%; p < 0.001), arterial hypertension (36.9% vs. 45.2% vs. 52.8%; p < 0.001), dyslipidemia (28.4% vs. 37% vs. 40.6%; p < 0.001), diabetes mellitus (11.9% vs. 17.1% vs. 20.5%; p < 0.001), ischemic heart disease (3.7% vs. 6.5% vs. 8.4%; p < 0.001), heart failure (3.4% vs. 5.2% vs. 7.6%; p < 0.001), liver disease (1.1% vs. 3% vs. 3.9%; p = 0.002), chronic renal failure (2.3% vs. 3.6% vs. 6.7%; p < 0.001), cancer (6.5% vs. 7.2% vs. 11.1%; p < 0.001), and chronic obstructive pulmonary disease (5.7% vs. 5.4% vs. 7.1%; p < 0.001). They presented more frequently with fever, dyspnea, and vomiting. These patients more frequently required high flow nasal cannula (3.1% vs. 4.4% vs. 9.7%; p < 0.001), non-invasive mechanical ventilation (0.9% vs. 3% vs. 6.3%; p < 0.001), invasive mechanical ventilation (0.6% vs. 2.7% vs. 8.7%; p < 0.001), and ICU admission (0.9% vs. 3.6% vs. 10.6%; p < 0.001), and had a higher percentage of in-hospital mortality (2.3% vs. 6.2% vs. 23.9%; p < 0.001). The three risk categories proved to be an independent risk factor in multivariate analyses. (4) Conclusion: The present study identifies three risk categories for the requirement of high flow nasal cannula, mechanical ventilation, ICU admission, and in-hospital mortality based on lymphopenia and inflammatory parameters.

Inappropriate antibiotic use in the COVID-19 era: Factors associated with inappropriate prescribing and secondary complications. Analysis of the registry SEMI-COVID.

BACKGROUND: Most patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use. METHODS: The SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified. RESULTS: Out of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001). CONCLUSION: The inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful.

Autoimmune Diseases and COVID-19 as Risk Factors for Poor Outcomes: Data on 13,940 Hospitalized Patients from the Spanish Nationwide SEMI-COVID-19 Registry.

(1) Objectives: To describe the clinical characteristics and clinical course of hospitalized patients with COVID-19 and autoimmune diseases (ADs) compared to the general population. (2) Methods: We used information available in the nationwide Spanish SEMI-COVID-19 Registry, which retrospectively compiles data from the first admission of adult patients with COVID-19. We selected all patients with ADs included in the registry and compared them to the remaining patients. The primary outcome was all-cause mortality during admission, readmission, and subsequent admissions, and secondary outcomes were a composite outcome including the need for intensive care unit (ICU) admission, invasive and non-invasive mechanical ventilation (MV), or death, as well as in-hospital complications. (3) Results: A total of 13,940 patients diagnosed with COVID-19 were included, of which 362 (2.6%) had an AD. Patients with ADs were older, more likely to be female, and had greater comorbidity. On the multivariate logistic regression analysis, which involved the inverse propensity score weighting method, AD as a whole was not associated with an increased risk of any of the outcome variables. Habitual treatment with corticosteroids (CSs), age, Barthel Index score, and comorbidity were associated with poor outcomes. Biological disease-modifying anti-rheumatic drugs (bDMARDs) were associated with a decrease in mortality in patients with AD. (4) Conclusions: The analysis of the SEMI-COVID-19 Registry shows that ADs do not lead to a different prognosis, measured by mortality, complications, or the composite outcome. Considered individually, it seems that some diseases entail a different prognosis than that of the general population. Immunosuppressive/immunoregulatory treatments (IST) prior to admission had variable effects.

Gender-Based Differences by Age Range in Patients Hospitalized with COVID-19: A Spanish Observational Cohort Study.

There is some evidence that male gender could have a negative impact on the prognosis and severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The aim of the present study was to compare the characteristics of coronavirus disease 2019 (COVID-19) between hospitalized men and women with confirmed SARS-CoV-2 infection. This multicenter, retrospective, observational study is based on the SEMI-COVID-19 Registry. We analyzed the differences between men and women for a wide variety of demographic, clinical, and treatment variables, and the sex distribution of the reported COVID-19 deaths, as well as intensive care unit (ICU) admission by age subgroups. This work analyzed 12,063 patients (56.8% men). The women in our study were older than the men, on average (67.9 vs. 65.7 years; p < 001). Bilateral condensation was more frequent among men than women (31.8% vs. 29.9%; p = 0.007). The men needed non-invasive and invasive mechanical ventilation more frequently (5.6% vs. 3.6%, p < 0.001, and 7.9% vs. 4.8%, p < 0.001, respectively). The most prevalent complication was acute respiratory distress syndrome, with severe cases in 19.9% of men (p < 0.001). In men, intensive care unit admission was more frequent (10% vs. 6.1%; p < 0.001) and the mortality rate was higher (23.1% vs. 18.9%; p < 0.001). Regarding mortality, the differences by gender were statistically significant in the age groups from 55 years to 89 years of age. A multivariate analysis showed that female sex was significantly and independently associated with a lower risk of mortality in our study. Male sex appears to be related to worse progress in COVID-19 patients and is an independent prognostic factor for mortality. In order to fully understand its prognostic impact, other factors associated with sex must be considered.