Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential.

Introduction: This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions. Methods: We describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19. For our demonstrative analysis, we use observational data from the registry of patients with COVID-19 who were admitted to the Bellvitge University Hospital in Spain from March 2020 to February 2021 and met our predefined inclusion criteria. We compare estimates of a single-dose, time-dependent treatment with the standard of care. We analyze the treatment effectiveness using common statistical approaches, either by ignoring or only partially accounting for the methodological biases. To address these challenges, we emulate a target trial through the clone-censor-weight approach. Results: Overlooking competing risk bias and employing the naïve Kaplan-Meier estimator led to increased in-hospital death probabilities in patients with COVID-19. Specifically, in the treatment effectiveness analysis, the Kaplan-Meier estimator resulted in an in-hospital mortality of 45.6% for treated patients and 59.0% for untreated patients. In contrast, employing an emulated trial framework with the weighted Aalen-Johansen estimator, we observed that in-hospital death probabilities were reduced to 27.9% in the "X"-treated arm and 40.1% in the non-"X"-treated arm. Immortal-time bias led to an underestimated hazard ratio of treatment. Conclusion: Overlooking competing risks, immortal-time bias, and confounding bias leads to shifted estimates of treatment effects. Applying the naïve Kaplan-Meier method resulted in the most biased results and overestimated probabilities for the primary outcome in analyses of hospital data from COVID-19 patients. This overestimation could mislead clinical decision-making. Both immortal-time bias and confounding bias must be addressed in assessments of treatment effectiveness. The trial emulation framework offers a potential solution to address all three methodological biases.

Prognostic Value of D-dimer to Lymphocyte Ratio (DLR) in Hospitalized Coronavirus Disease 2019 (COVID-19) Patients: A Validation Study in a National Cohort.

BACKGROUND: This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients. METHODS: A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission. RESULTS: A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68-0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09-4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03-2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis. CONCLUSIONS: This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice.

Prevalence of the limited vs. extensive scleroderma-related interstitial lung disease at the time of diagnosis of SSc-ILD based on Goh et al. criteria. Systematic review and meta-analysis.

INTRODUCTION: Goh et al. proposed in 2008 a classificatory algorithm of limited or extensive SSc-ILD. The prevalence of both at the time of diagnosis of SSc-ILD is not known with exactitude. METHODS: The review was undertaken by means of MEDLINE and SCOPUS from 2008 to 2023 and using the terms: "systemic", "scleroderma" or "interstitial lung disease" [MesH]. The Newcastle-Ottawa Scale was used for the qualifying assessment for observational studies and the Jadad scale for clinical trials. The inverse variance-weighted method was performed. RESULTS: Twenty-seven studies were initially included in the systematic review and meta-analysis (SRMA). Of these, 17 studies had no overlapping data. They reported data from 2,149 patients, 1,369 (81.2%) were female. The mean age was 52.4 (SD 6.6) years. 45.2% of the patients had the diffuse subtype and 54.8% had the limited or sine scleroderma subtype. A total of 38.7% of the patients showed positive antitopoisomerase antibodies (ATA) and 14.2% positive anticentromere antibodies (ACA). The mean percentage of forced vital capacity (FVC) at baseline was 80.5% (SD 6.9) and of diffusing capacity of the lungs for carbon monoxide (DLco) was 59.1% (SD 9.6). Twelve studies presented SSc-ILD extension data adjusted for PFTs and were included in the meta-analysis. The 10 observational cohort studies were analyzed separately. The overall percentage of limited extension was estimated at 63.5% (95%CI 55.3-73; p < 0.001) using the random-effects model. Heterogeneity between studies (I2) was 9.8% (95%CI 0-68.2%) with the random-effects model. Extensive pulmonary involvement was estimated at 34.3% (95%CI 26-45.4; p < 0.001). Heterogeneity between studies (I2) was 0% (95%CI 0-61.6%) with the random-effects model. CONCLUSION: The overall percentage of limited SSc-ILD at the time of diagnosis of SSc-ILD was estimated at 63.5% and extensive at 34.3%.

Key Genes of the Immune System and Predisposition to Acquired Hemophilia A: Evidence from a Spanish Cohort of 49 Patients Using Next-Generation Sequencing.

Acquired hemophilia A (AHA) is a rare bleeding disorder caused by the presence of autoantibodies against factor VIII (FVIII). As with other autoimmune diseases, its etiology is complex and its genetic basis is unknown. The aim of this study was to identify the immunogenetic background that predisposes individuals to AHA. HLA and KIR gene clusters, as well as KLRK1, were sequenced using next-generation sequencing in 49 AHA patients. Associations between candidate genes involved in innate and adaptive immune responses and AHA were addressed by comparing the alleles, genotypes, haplotypes, and gene frequencies in the AHA cohort with those in the donors' samples or Spanish population cohort. Two genes of the HLA cluster, as well as rs1049174 in KLRK1, which tags the natural killer (NK) cytotoxic activity haplotype, were found to be linked to AHA. Specifically, A*03:01 (p = 0.024; odds ratio (OR) = 0.26[0.06-0.85]) and DRB1*13:03 (p = 6.8 × 103, OR = 7.56[1.64-51.40]), as well as rs1049174 (p = 0.012), were significantly associated with AHA. In addition, two AHA patients were found to carry one copy each of the low-frequency allele DQB1*03:09 (nallele = 2, 2.04%), which was completely absent in the donors. To the best of our knowledge, this is the first time that the involvement of these specific alleles in the predisposition to AHA has been proposed. Further molecular and functional studies will be needed to unravel their specific contributions. We believe our findings expand the current knowledge on the genetic factors involved in susceptibility to AHA, which will contribute to improving the diagnosis and prognosis of AHA patients.

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.

Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data.

BACKGROUND: Real-world observational data are an important source of evidence on the treatment effectiveness for patients hospitalized with coronavirus disease 2019 (COVID-19). However, observational studies evaluating treatment effectiveness based on longitudinal data are often prone to methodological biases such as immortal time bias, confounding bias, and competing risks. METHODS: For exemplary target trial emulation, we used a cohort of patients hospitalized with COVID-19 (n = 501) in a single centre. We described the methodology for evaluating the effectiveness of a single-dose treatment, emulated a trial using real-world data, and drafted a hypothetical study protocol describing the main components. To avoid immortal time and time-fixed confounding biases, we applied the clone-censor-weight technique. We set a 5-day grace period as a period of time when treatment could be initiated. We used the inverse probability of censoring weights to account for the selection bias introduced by artificial censoring. To estimate the treatment effects, we took the multi-state model approach. We considered a multi-state model with five states. The primary endpoint was defined as clinical severity status, assessed by a 5-point ordinal scale on day 30. Differences between the treatment group and standard of care treatment group were calculated using a proportional odds model and shown as odds ratios. Additionally, the weighted cause-specific hazards and transition probabilities for each treatment arm were presented. RESULTS: Our study demonstrates that trial emulation with a multi-state model analysis is a suitable approach to address observational data limitations, evaluate treatment effects on clinically heterogeneous in-hospital death and discharge alive endpoints, and consider the intermediate state of admission to ICU. The multi-state model analysis allows us to summarize results using stacked probability plots that make it easier to interpret results. CONCLUSIONS: Extending the emulated target trial approach to multi-state model analysis complements treatment effectiveness analysis by gaining information on competing events. Combining two methodologies offers an option to address immortal time bias, confounding bias, and competing risk events. This methodological approach can provide additional insight for decision-making, particularly when data from randomized controlled trials (RCTs) are unavailable.

Nailfold videocapillaroscopy patterns in systemic sclerosis: implications for cutaneous subsets, disease features and prognostic value for survival.

OBJECTIVES: To assess the associations and prognostic value of scleroderma patterns by nailfold videocapillaroscopy (NVC) in patients with systemic sclerosis (SSc) and cutaneous subsets. METHODS: At baseline, 1356 SSc patients from the RESCLE registry were compared according to the scleroderma pattern as Late pattern and non-Late pattern, which included Early and Active patterns. Patient characteristics, disease features, survival time and causes of death were analysed. RESULTS: Late pattern was identified in 540 (39.8%), and non-Late pattern in 816 (60.2%) patients (88% women; 987 lcSSc/251 dcSSc). Late pattern was associated to dcSSc (OR=1.96; p<0.001), interstitial lung disease (ILD) (OR=1.29; p=0.031), and scleroderma renal crisis (OR=3.46; p<0.001). Once the cutaneous subset was disregarded in an alternative analysis, both digital ulcers (DU) (OR=1.29; p<0.037) and anti-topoisomerase I antibodies (OR=1.39; p< 0.036) emerged associated with the Late pattern. By cutaneous subsets, associations with Late pattern were: (1) in dcSSc, acro-osteolysis (OR=2.13; p=0.022), and systolic pulmonary artery pressure >40 mmHg by Doppler echocardiogram (OR=2.24; p<0.001); and (2) in lcSSc, ILD (OR=1.38; p=0.028). Survival was reduced in dcSSc with Late pattern compared to non-Late pattern (p=0.049). Risk factors for SSc mortality in multivariate regression Cox analysis were age at diagnosis (HR=1.03; p<0.001), dcSSc (HR=2.48; p<0.001), DU (HR=1.38; p=0.046), ILD (HR=2.81; p<0.001), and pulmonary arterial hypertension (HR=1.99; p<0.001). CONCLUSIONS: SSc patients with Late pattern more frequently present dcSSc and develop more fibrotic and vascular manifestations. Advanced microangiopathy by NVC identifies dcSSc patients at risk of reduced survival due to SSc-related causes.

Prognostic Factors Associated with Acute Heart Failure in Patients Admitted for COVID-19: Analysis of the SEMI-COVID-19 Registry.

INTRODUCTION: Since the beginning of the COVID-19 pandemic in March 2020, an intimate relationship between this disease and cardiovascular diseases has been seen. However, few studies assess the development of heart failure during this infection. This study aims to determine the predisposing factors for the development of heart failure (HF) during hospital admission of COVID-19 patients. METHODOLOGY: A retrospective and multicenter study of patients with HF admitted for COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry). A bivariate analysis was performed to relate the different variables evaluated in patients developing heart failure during hospital admission. A multivariate analysis including the most relevant clinical variables obtained in bivariate analyses to predict the outcome of heart failure was performed. RESULTS: A total of 16.474 patients hospitalized for COVID-19 were included (57.5% men, mean age 67 years), 958 of them (5.8%) developed HF during hospitalization. The risk factors for HF development were: age (odds ratio [OR]): 1.042; confidence interval 95% (CI 95%): 1.035-1.050; p < 0.001), atrial fibrillation (OR: 2.022; CI 95%: 1.697-2.410; p < 0.001), BMI > 30 kg/m2 (OR: 1.460 CI 95%: 1.230-1.733; p < 0001), and peripheral vascular disease (OR: 1.564; CI 95%: 1.217-2.201; p < 0.001). Patients who developed HF had a higher rate of mortality (54.1% vs. 19.1%, p < 0.001), intubation rate (OR: 2,36; p < 0.001), and ICU admissions (OR: 2.38; p < 0001). CONCLUSIONS: Patients who presented a higher risk of developing HF were older with cardiovascular risk factors. The risk factors for HF development were age, atrial fibrillation, obesity, and peripheral vascular disease. In addition, patients who developed HF more frequently required to be intubated or admitted to the ICU.

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.

Validation of the RIM Score-COVID in the Spanish SEMI-COVID-19 Registry.

The significant impact of COVID-19 worldwide has made it necessary to develop tools to identify patients at high risk of severe disease and death. This work aims to validate the RIM Score-COVID in the SEMI-COVID-19 Registry. The RIM Score-COVID is a simple nomogram with high predictive capacity for in-hospital death due to COVID-19 designed using clinical and analytical parameters of patients diagnosed in the first wave of the pandemic. The nomogram uses five variables measured on arrival to the emergency department (ED): age, sex, oxygen saturation, C-reactive protein level, and neutrophil-to-platelet ratio. Validation was performed in the Spanish SEMI-COVID-19 Registry, which included consecutive patients hospitalized with confirmed COVID-19 in Spain. The cohort was divided into three time periods: T1 from February 1 to June 10, 2020 (first wave), T2 from June 11 to December 31, 2020 (second wave, pre-vaccination period), and T3 from January 1 to December 5, 2021 (vaccination period). The model's accuracy in predicting in-hospital COVID-19 mortality was assessed using the area under the receiver operating characteristics curve (AUROC). Clinical and laboratory data from 22,566 patients were analyzed: 15,976 (70.7%) from T1, 4,233 (18.7%) from T2, and 2,357 from T3 (10.4%). AUROC of the RIM Score-COVID in the entire SEMI-COVID-19 Registry was 0.823 (95%CI 0.819-0.827) and was 0.834 (95%CI 0.830-0.839) in T1, 0.792 (95%CI 0.781-0.803) in T2, and 0.799 (95%CI 0.785-0.813) in T3. The RIM Score-COVID is a simple, easy-to-use method for predicting in-hospital COVID-19 mortality that uses parameters measured in most EDs. This tool showed good predictive ability in successive disease waves.

Factores de riesgo de mortalidad en pacientes con infección por SARS-CoV-2 y fibrilación auricular: datos del registro SEMI-COVID-19 / Mortality risk factors in patients with SARS-CoV-2 infection and atrial fibrillation: Data from the SEMI-COVID-19 registry

Introducción: La fibrilación auricular y las comorbilidades asociadas a ella suponen un factor de riesgo de mortalidad, morbilidad y de desarrollo de complicaciones en los pacientes ingresados por COVID-19.ObjetivosDescribir las características clínicas, epidemiológicas, radiológicas y analíticas de los pacientes con fibrilación auricular ingresados por COVID-19 en España. De forma secundaria, se pretende identificar aquellas variables que se asocian con mortalidad y mal pronóstico de la COVID-19 en pacientes que presentan fibrilación auricular.MétodosEstudio retrospectivo, observacional y multicéntrico de ámbito nacional de pacientes hospitalizados por COVID-19 desde el 1 de marzo hasta el 1 de octubre de 2020. Los datos fueron obtenidos del Registro SEMI-COVID-19 de la Sociedad Española de Medicina Interna (SEMI) en el que participan 150 hospitales españoles.ResultadosDe un total de 16.461 pacientes en el registro SEMI-COVID-19, 1.816 (11%) tenían antecedente de fibrilación auricular y el número de fallecidos entre los pacientes con fibrilación auricular ascendió a 738 (41%). En cuanto a la clínica, los pacientes fallecidos ingresaron con una frecuencia cardíaca mayor (88,38 vs. 84,95; p >0,01), con mayor porcentaje de insuficiencia respiratoria (67,2 vs. 20,1%; p <0,01) y mayor taquipnea (58 vs. 30%; p<0,09). En el análisis multivariante, el tratamiento con ACOD tuvo un papel protector para la mortalidad por infección por COVID-19 (OR: 0,597; IC: 0,402-0,888; p=0,011). (AU)

Introduction: Atrial fibrillation and associated comorbidities pose a risk factor for mortality, morbidity and development of complications in patients admitted for COVID-19.ObjectivesTo describe the clinical, epidemiological, radiological and analytical characteristics of patients with atrial fibrillation admitted for COVID-19 in Spain. Secondarily, we aim to identify those variables associated with mortality and poor prognosis of COVID-19 in patients with atrial fibrillation.MethodsRetrospective, observational, multicenter, nationwide, retrospective study of patients hospitalized for COVID-19 from March 1 to October 1, 2020. Data were obtained from the SEMI-COVID-19 Registry of the Spanish Society of Internal Medicine (SEMI) in which 150 Spanish hospitals participate.ResultsBetween March 1 and October 1, 2020, data from a total of 16,461 patients were entered into the SEMI-COVID-19 registry. 1816 (11%) had a history of atrial fibrillation and the number of deaths among AF patients amounted to 738 (41%). Regarding clinical characteristics, deceased patients were admitted with a higher heart rate (88.38 vs. 84.95; P>0.01), with a higher percentage of respiratory failure (67.2 vs. 20.1%; P<0.01) and high tachypnea (58 vs. 30%; P<0.01). The comorbidities that presented statistically significant differences in the deceased group were: age, hypertension and diabetes with target organ involvement. There was also a higher prevalence of a history of cardiovascular disease in the deceased. On multivariate analysis, DOACs treatment had a protective role for mortality (OR: 0.597; CI: 0.402-0.888; P=0.011). (AU)

Mortality risk factors in patients with SARS-CoV-2 infection and atrial fibrillation: Data from the SEMI-COVID-19 registry.

Introduction: Atrial fibrillation and associated comorbidities pose a risk factor for mortality, morbidity and development of complications in patients admitted for COVID-19. Objectives: To describe the clinical, epidemiological, radiological and analytical characteristics of patients with AF admitted for COVID-19 in Spain. Secondarily, we aim to identify those variables associated with mortality and poor prognosis of COVID-19 in patients with AF. Methods: Retrospective, observational, multicenter, nationwide, retrospective study of patients hospitalized for COVID-19 from March 1 to October 1, 2020. Data were obtained from the SEMI-COVID-19 Registry of the Spanish Society of Internal Medicine (SEMI) in which 150 Spanish hospitals participate. Results: Between March 1 and October 1, 2020, data from a total of 16,461 patients were entered into the SEMI-COVID-19 registry. 1,816 (11%) had a history of AF and the number of deaths among AF patients amounted to 738 (41%). Regarding clinical characteristics, deceased patients were admitted with a higher heart rate (88.38 vs 84.95; p > 0.01), with a higher percentage of respiratory failure (67.2% vs 20.1%; p < 0.01) and high tachypnea (58% vs 30%; p < 0.01). The comorbidities that presented statistically significant differences in the deceased group were: age, hypertension and diabetes with target organ involvement. There was also a higher prevalence of a history of cardiovascular disease in the deceased. On multivariate analysis, DOACs treatment had a protective role for mortality (OR:0,597) IC (0,402-0,888 ; p = 0.011). Conclusions: Previous treatment with DOACs and DOACs treatment during admission seem to have a protective role in patients with AF, although this fact should be verified in prospective studies.

Introducción: La fibrilación auricular y las comorbilidades asociadas a ella suponen un factor de riesgo de mortalidad, morbilidad y desarrollo de complicaciones en los pacientes ingresados por COVID-19. Objetivos: Describir las características clínicas, epidemiológicas, radiológicas y analíticas de los pacientes con FA ingresados por COVID-19 en España. De forma secundaria, se pretende identificar aquellas variables que se asocian con mortalidad y mal pronóstico de la COVID-19 en pacientes que presentan FA. Métodos: Estudio retrospectivo, observacional y multicéntrico de ámbito nacional de pacientes hospitalizados por COVID-19 desde el 1 de marzo al 1 de octubre de 2020. Los datos fueron obtenidos del Registro SEMI-COVID-19 de la Sociedad Española de Medicina Interna (SEMI) en el que participan 150 hospitales españoles. Resultados: De un total de 16.461 pacientes en el registro SEMI-COVID-19, 1.816 (11%) tenían antecedente de FA y el número de fallecidos entre los pacientes con FA ascendió a 738 (41%). En cuanto a la clínica, los pacientes fallecidos ingresaron con una frecuencia cardíaca mayor (88,38 vs 84,95; p > 0,01), con mayor porcentaje de insuficiencia respiratoria (67,2% vs 20,1%; p < 0,01) y mayor taquipnea (58% vs 30%; p < 0,09). En el análisis multivariante, el tratamiento con ACOD tuvo un papel protector para la mortalidad por infección por COVID 19 (OR:0,597; IC (0,402-0,888; p = 0.011). Conclusiones: El tratamiento previo con ACOD como el tratamiento con ACOD durante el ingreso parecen tener un papel protector en los pacientes con FA, aunque este hecho debería ser comprobado con estudios prospectivos.

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.

Standardized incidence ratios and risk factors for cancer in patients with systemic sclerosis: Data from the Spanish Scleroderma Registry (RESCLE).

AIM: Patients with systemic sclerosis (SSc) are at increased risk of cancer, a growing cause of non-SSc-related death among these patients. We analyzed the increased cancer risk among Spanish patients with SSc using standardized incidence ratios (SIRs) and identified independent cancer risk factors in this population. MATERIAL AND METHODS: Spanish Scleroderma Registry data were analyzed to determine the demographic characteristics of patients with SSc, and logistic regression was used to identify cancer risk factors. SIRs with 95% confidence intervals (CIs) relative to the general Spanish population were calculated. RESULTS: Of 1930 patients with SSc, 206 had cancer, most commonly breast, lung, hematological, and colorectal cancers. Patients with SSc had increased risks of overall cancer (SIR 1.48, 95% CI 1.36-1.60; P < 0.001), and of lung (SIR 2.22, 95% CI 1.77-2.73; P < 0.001), breast (SIR 1.31, 95% CI 1.10-1.54; P = 0.003), and hematological (SIR 2.03, 95% CI 1.52-2.62; P < 0.001) cancers. Cancer was associated with older age at SSc onset (odds ratio [OR] 1.22, 95% CI 1.01-1.03; P < 0.001), the presence of primary biliary cholangitis (OR 2.35, 95% CI 1.18-4.68; P = 0.015) and forced vital capacity <70% (OR 1.8, 95% CI 1.24-2.70; P = 0.002). The presence of anticentromere antibodies lowered the risk of cancer (OR 0.66, 95% CI 0.45-0.97; P = 0.036). CONCLUSIONS: Spanish patients with SSc had an increased cancer risk compared with the general population. Some characteristics, including specific autoantibodies, may be related to this increased risk.

Remdesivir in Very Old Patients (≥80 Years) Hospitalized with COVID-19: Real World Data from the SEMI-COVID-19 Registry.

(1) Background: Large cohort studies of patients with COVID-19 treated with remdesivir have reported improved clinical outcomes, but data on older patients are scarce. Objective: This work aims to assess the potential benefit of remdesivir in unvaccinated very old patients hospitalized with COVID-19; (2) Methods: This is a retrospective analysis of patients ≥ 80 years hospitalized in Spain between 15 July and 31 December 2020 (SEMI-COVID-19 Registry). Differences in 30-day all-cause mortality were adjusted using a multivariable regression analysis. (3) Results: Of the 4331 patients admitted, 1312 (30.3%) were ≥80 years. Very old patients treated with remdesivir (n: 140, 10.7%) had a lower mortality rate than those not treated with remdesivir (OR (95% CI): 0.45 (0.29−0.69)). After multivariable adjustment by age, sex, and variables associated with lower mortality (place of COVID-19 acquisition; degree of dependence; comorbidities; dementia; duration of symptoms; admission qSOFA; chest X-ray; D-dimer; and treatment with corticosteroids, tocilizumab, beta-lactams, macrolides, and high-flow nasal canula oxygen), the use of remdesivir remained associated with a lower 30-day all-cause mortality rate (adjusted OR (95% CI): 0.40 (0.22−0.61) (p < 0.001)). (4) Conclusions: Remdesivir may reduce mortality in very old patients hospitalized with COVID-19.

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.

Left ventricular diastolic dysfunction in systemic sclerosis: Clinical, immunological and survival differences in the Spanish RESCLE registry.

OBJECTIVES: Left ventricular diastolic dysfunction (LVDD) remains poorly studied in Systemic Sclerosis (SSc). To determine the prevalence and to define factors associated with LVDD and survival in a large cohort of patients with SSc. METHODS: An observational study was conducted with data from the multicentre Spanish Scleroderma Registry (RESCLE) to identify factors associated with LVDD and estimate survival. RESULTS: Out of 1517 patients, 319 (21.0%) had LVDD. The subset of sine scleroderma SSc was associated to LVDD (14.7% vs. 10.6%, p =0.048), whilst diffuse cutaneous SSc was more prevalent in non-LVDD (16.0 % vs. 21.2%, p =0.041). Multivariable analysis identified that LVDD was associated with older age at diagnosis of SSc (OR 1.05; 95% CI 1.04 to 1.06), longer time from diagnosis (OR 1.04; 95% CI 1.03 to 1.06), presence of telangiectasia (OR 1.42; 95% CI 1.08 to 1.88), treatment with calcium channel blockers (CCB) (OR 1.51; 95% CI 1.16 to 1.96), and inversely related to angiotensin-converting-enzyme inhibitors (ACEi) use (OR 0.59; 95% CI 0.44 to 0.80). SSc patients with LVDD had increased mortality (23.8 vs. 17.4%, p =0.010) and shortened survival from the first SSc symptom (p =0.040), even though it was not found to be an independent risk factor for death. CONCLUSIONS: LVDD is relatively common in SSc patients, and it is associated with worst prognosis, older age, longer time from diagnosis of SSc, presence of telangiectasia and vasodilator treatment.