Acute Respiratory Events in Connective Tissue Disorders

Prediction of mortality in pneumonia patients with connective tissue disease treated with glucocorticoids or/and immunosuppressants by machine learning

Objectives

The assessment of accurate mortality risk is essential for managing pneumonia patients with connective tissue disease (CTD) treated with glucocorticoids or/and immunosuppressants. This study aimed to construct a nomogram for predicting 90-day mortality in pneumonia patients using machine learning.

Methods

Data were obtained from the DRYAD database. Pneumonia patients with CTD were screened. The samples were randomly divided into a training cohort (70%) and a validation cohort (30%). A univariate Cox regression analysis was used to screen for prognostic variables in the training cohort. Prognostic variables were entered into the least absolute shrinkage and selection operator (Lasso) and a random survival forest (RSF) analysis was used to screen important prognostic variables. The overlapping prognostic variables of the two algorithms were entered into the stepwise Cox regression analysis to screen the main prognostic variables and construct a model. Model predictive power was assessed using the C-index, the calibration curve, and the clinical subgroup analysis (age, gender, interstitial lung disease, diabetes mellitus). The clinical benefits of the model were assessed using a decision curve analysis (DCA). Similarly, the C-index was calculated and the calibration curve was plotted to verify the model stability in the validation cohort.

Results

A total of 368 pneumonia patients with CTD (training cohort: 247; validation cohort: 121) treated with glucocorticoids or/and immunosuppressants were included. The univariate Cox regression analysis obtained 19 prognostic variables. Lasso and RSF algorithms obtained eight overlapping variables. The overlapping variables were entered into a stepwise Cox regression to obtain five variables (fever, cyanosis, blood urea nitrogen, ganciclovir treatment, and anti-pseudomonas treatment), and a prognostic model was constructed based on the five variables. The C-index of the construction nomogram of the training cohort was 0.808. The calibration curve, DCA results, and clinical subgroup analysis showed that the model also had good predictive power. Similarly, the C-index of the model in the validation cohort was 0.762 and the calibration curve had good predictive value.

Conclusion

In this study, the nomogram developed performed well in predicting the 90-day risk of death in pneumonia patients with CTD treated with glucocorticoids or/and immunosuppressants.

Active vaccination campaign to increase seasonal influenza vaccination coverage: a monocenter experience in a cohort of Italian patients with systemic autoimmune diseases

Seasonal influenza is a frequent cause of hospitalization and mortality among patients with systemic autoimmune diseases. Despite this evidence, vaccination coverage is generally much lower than the minimum 75% target proposed by the WHO. Therefore, an active campaign was implemented in the years 2019/2020 and 2020/2021 within the Rheumatology Department of the Niguarda Hospital (Milan, Italy) to improve the vaccination coverage in patients with inflammatory arthritis. This study aims to evaluate the vaccination coverage in the 2019/2020 and 2020/2021 (active campaigns) seasons and to compare these results with the 2018/2019 season. A monocenter observational study was conducted among adult patients with rheumatoid arthritis, spondylarthritis, or psoriatic arthropathy, who were referred to the Rheumatology Department of the Niguarda Hospital. Patients were given a questionnaire to investigate previous years' vaccination coverage and to propose an influenza vaccine for the 2020/2021 season. Compared with 2018/2019, a trend for increase in vaccination coverage was reported in 2019/2020 season (+ 10.7%, p = 0.055; 45.5% of coverage) and a statistically significant increase was reported in 2020/2021 (+ 31.2%, p < 0.001; 65.9% of coverage). The increase was also significant when comparing the 2020/2021 and 2019/2020 seasons (+ 20.5%, p < 0.001). The greatest increase in vaccination coverage was observed among under-65-year-old patients. Obtained results support the implementation of active vaccination campaigns to increase vaccination coverage among patients with systemic autoimmune diseases and highlight the importance of external factors (such as the COVID-19 pandemic) in directing the patient to adopt preventive measures to avoid infections and related complications.

Metagenomic next-generation sequencing: A promising tool for diagnosis and treatment of suspected pneumonia in rheumatic patients with acute respiratory failure: Retrospective cohort study

Background

The effectiveness of metagenomic next-generation sequencing (mNGS) in respiratory pathogen detection and clinical decision-making in critically rheumatic patients remains largely unexplored.

Methods

A single-center retrospective study of 58 rheumatic patients who were admitted to ICU due to suspected pneumonia with acute respiratory failure if they underwent both bronchoalveolar lavage fluid specimen mNGS and combined microbiological tests (CMTs) was conducted to compare their diagnostic performance, using clinical composite diagnosis as the gold standard. Treatment modifications based on mNGS results were also reviewed.

Results

Forty-three patients were diagnosed with microbiologically confirmed pneumonia and 15 were considered as a non-infectious disease. mNGS outperformed CMTs in the accurate diagnosis of infectious and non-infectious lung infiltration (98.1% [57/58] vs. 87.9% [51/58], P = 0.031). A total of 94 causative pathogens were defined by the gold standard and 27 patients had polymicrobial pneumonia. The sensitivity of pathogen detection and complete concordance with the gold standard by mNGS exceeded those by CMTs (92.6% [87/94] vs. 76.6% [72/94], P < 0.001 and 72.1% [31/43] vs. 51.2% [22/43], P = 0.004, respectively). Moreover, 22 pathogens were detected only by mNGS and confirmed by orthogonal test. Accordingly, the etiological diagnosis changed in 19 cases, and the empirical treatment improved in 14 cases, including 8 cases of rescue treatment and 11 of antibiotics de-escalation. At the pathogen-type level, both methods were comparable for bacteria, but mNGS was advantageous to identify viruses (accuracy: 100% vs. 81%, P = 0.004). For Pneumocystis jirovecii detection, mNGS improved the sensitivity compared with Gomori’s methenamine silver stain (91.7% vs. 4.2%, P < 0.001) and was higher than polymerase chain reaction (79.2%), but the difference was not significant (P = 0.289). In terms of Aspergillus, the better sensitivity with a combination of culture and galactomannan test than that with mNGS was found (100% vs. 66.7%, P = 0.033).

Conclusions

mNGS has an excellent accuracy in etiological diagnosis and pathogen detection of suspected pneumonia in critically rheumatic patients, which has potential significance for clinical decision-making. Its superiority to different types of pathogens depends on the comprehensiveness of CMTs.

Management of progressive pulmonary fibrosis associated with connective tissue disease

INTRODUCTION

: Fibrotic interstitial lung disease (ILD) is a frequent and severe complication of connective tissue disease (CTD).

AREAS COVERED

: In this narrative review, we update the most relevant differential characteristics of fibrotic ILD associated with CTD (CTD-ILD) and propose a diagnostic and therapeutic approach based on a review of the articles published between 2002 and 2022 through PubMed.

EXPERT OPINION

: The subset of ILD, mainly the radiological/histological pattern and the degree of fibrotic component, usually determines the prognosis and therapeutic strategy for these patients. Some patients with CTD-ILD can develop progressive pulmonary fibrosis (PPF) with severe deterioration of lung function, rapid progression to chronic respiratory failure, and high mortality. PPF has been described in many CTDs, mainly in systemic sclerosis and rheumatoid arthritis, and requires a multidisciplinary diagnostic and therapeutic approach to improve patient outcomes.

Etiologies and outcomes of rheumatology patients with acute respiratory failure requiring intensive care: a single-center medical records review study of 259 patients

OBJECTIVE

The etiologies of acute respiratory failure in patients with systemic rheumatic diseases (SRDs) requiring intensive care remain unknown. This study was undertaken to investigate the etiologies and outcomes.

METHODS

A medical records review study was performed of 259 adult SRDs patients with respiratory failure admitted to medical ICU across a 5-year period. The etiologies were classified as infection, SRD exacerbation, and undetermined. The factors associated with ICU mortality were identified with multivariate logistic regression analysis.

RESULTS

The etiologies of respiratory failure included infection (n = 209, 80.7%), SRD exacerbation (n = 71, 27.4%), and undetermined (n = 21, 8.1%). The most common pathogen was Pneumocystis jirovecii (39.8%), followed by Aspergillus spp. (33.2%), and cytomegalovirus (23.2%). The ICU mortality rate was 59.8%. A high acute physiology and chronic health evaluation II score (OR 1.118, 95% CI 1.054 to 1.186, p < 0.001), a PaO₂/FiO₂ ratio < 100 mmHg (OR 3.918, 95% CI 2.199 to 6.892, p < 0.001), and a diagnosis of dermatomyositis/polymyositis (OR 4.898, 95% CI 1.949 to 12.309, p = 0.001), vasculitis (OR 3.007, 95% CI 1.237 to 7.309, p = 0.015), and Pneumocystis pneumonia (OR 2.345, 95% CI 1.168 to 4.705, p = 0.016) were associated with increased mortality.

CONCLUSIONS

Opportunistic infections and SRD exacerbation were the most common etiologies of acute respiratory failure in patients with SRDs requiring ICU admission, with high ICU mortality. Development of a standard protocol for differential diagnosis in this population might help initiate definitive therapy and improve clinical outcome. Key Points • Infections, especially with opportunistic infections, were the leading cause of acute respiratory failure in critically ill rheumatology patients, with high mortality. • Severity of illness, certain types of rheumatic diseases, and opportunistic fungal infections were associated with increased mortality. • Using a comprehensive diagnostic workup might help to confirm the infective etiology and improve outcome.