Assessing the impact of long-term inhaled corticosteroid therapy on patients with COVID-19 and coexisting chronic lung disease: A multicenter retrospective cohort study.

Background: Patients with chronic lung disease (CLD), such as asthma or chronic obstructive pulmonary disease, were expected to have an increased risk of clinical manifestations and severity of COVID-19. However, these comorbidities have been reported less frequently than expected. Chronic treatment with inhaled corticosteroids (ICS) may impact the clinical course of COVID-19. The main objective of this study is to know the influence of chronic treatment with ICS on the prognosis of COVID-19 hospitalized patients with CLD. Methods: A multicenter retrospective cohort study was designed, including patients hospitalized with COVID-19. Epidemiological and clinical data were collected at admission and at seven days, and clinical outcomes were collected. Patients with CLD with and without chronic treatment with ICS were compared. Results: Two thousand five hundred ninety-eight patients were included, of which 1,171 patients had a diagnosis of asthma and 1,427 of COPD (53.37% and 41.41% with ICS, respectively). No differences were found in mortality, transfer to ICU, or development of moderate-severe ARDS. Patients with chronic ICS had a longer hospital stay in both asthma and COPD patients (9 vs. 8 days, p = 0.031 in asthma patients), (11 vs. 9 days, p = 0.018 in COPD patients); although they also had more comorbidity burden. Conclusions: Patients with chronic inhaled corticosteroids had longer hospital stays and more chronic comorbidities, measured by the Charlson comorbidity index, but they did not have more severe disease at admission, evaluated with qSOFA and PSI scores. Chronic treatment with inhaled corticosteroids had no influence on the prognosis of patients with chronic lung disease and COVID-19.

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%.

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.

The identification and management of interstitial lung disease in systemic sclerosis: evidence-based European consensus statements.

BACKGROUND: Systemic sclerosis-associated interstitial lung disease (ILD) carries a high mortality risk; expert guidance is required to aid early recognition and treatment. We aimed to develop the first expert consensus and define an algorithm for the identification and management of the condition through application of well established methods. METHODS: Evidence-based consensus statements for systemic sclerosis-associated ILD management were established for six domains (ie, risk factors, screening, diagnosis and severity assessment, treatment initiation and options, disease progression, and treatment escalation) using a modified Delphi process based on a systematic literature analysis. A panel of 27 Europe-based pulmonologists, rheumatologists, and internists with expertise in systemic sclerosis-associated ILD participated in three rounds of online surveys, a face-to-face discussion, and a WebEx meeting, followed by two supplemental Delphi rounds, to establish consensus and define a management algorithm. Consensus was considered achieved if at least 80% of panellists indicated agreement or disagreement. FINDINGS: Between July 1, 2018, and Aug 27, 2019, consensus agreement was reached for 52 primary statements and six supplemental statements across six domains of management, and an algorithm was defined for clinical practice use. The agreed statements most important for clinical use included: all patients with systemic sclerosis should be screened for systemic sclerosis-associated ILD using high-resolution CT; high-resolution CT is the primary tool for diagnosing ILD in systemic sclerosis; pulmonary function tests support screening and diagnosis; systemic sclerosis-associated ILD severity should be measured with more than one indicator; it is appropriate to treat all severe cases; no pharmacological treatment is an option for some patients; follow-up assessments enable identification of disease progression; progression pace, alongside disease severity, drives decisions to escalate treatment. INTERPRETATION: Through a robust modified Delphi process developed by a diverse panel of experts, the first evidence-based consensus statements were established on guidance for the identification and medical management of systemic sclerosis-associated ILD. FUNDING: An unrestricted grant from Boehringer Ingelheim International.