Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry

Impact of Risk Factors on COVID-19 Outcomes in Unvaccinated People With Rheumatic Diseases: A Comparative Analysis of Pandemic Epochs Using the COVID-19 Global Rheumatology Alliance Registry

OBJECTIVE

Approximately one third of individuals worldwide have not received a COVID-19 vaccine. Although studies have investigated risk factors linked to severe COVID-19 among unvaccinated people with rheumatic diseases (RDs), we know less about whether these factors changed as the pandemic progressed. We aimed to identify risk factors associated with severe COVID-19 in unvaccinated individuals in different pandemic epochs corresponding to major variants of concern.

METHODS

Patients with RDs and COVID-19 were entered into the COVID-19 Global Rheumatology Alliance Registry between March 2020 and June 2022. An ordinal logistic regression model (not hospitalized, hospitalized, and death) was used with date of COVID-19 diagnosis, age, sex, race and/or ethnicity, comorbidities, RD activity, medications, and the human development index (HDI) as covariates. The main analysis included all unvaccinated patients across COVID-19 pandemic epochs; subanalyses stratified patients according to RD types.

RESULTS

Among 19,256 unvaccinated people with RDs and COVID-19, those who were older, male, had more comorbidities, used glucocorticoids, had higher disease activity, or lived in lower HDI regions had worse outcomes across epochs. For those with rheumatoid arthritis, sulfasalazine and B-cell-depleting therapy were associated with worse outcomes, and tumor necrosis factor inhibitors were associated with improved outcomes. In those with connective tissue disease or vasculitis, B-cell-depleting therapy was associated with worse outcomes.

CONCLUSION

Risk factors for severe COVID-19 outcomes were similar throughout pandemic epochs in unvaccinated people with RDs. Ongoing efforts, including vaccination, are needed to reduce COVID-19 severity in this population, particularly in those with medical and social vulnerabilities identified in this study.

Critical evaluation of established risk prediction models for acute respiratory distress syndrome in adult patients: A systematic review and meta-analysis

AIM

To assess the performance of validated prediction models for acute respiratory distress syndrome (ARDS) by systematic review and meta-analysis.

METHODS

Eight databases (Medline, CINAHL, Embase, The Cochrane Library, CNKI, WanFang Data, Sinomed, and VIP) were searched up to March 26, 2023. Studies developed and validated a prediction model for ARDS in adult patients were included. Items on study design, incidence, derivation methods, predictors, discrimination, and calibration were collected. The risk of bias was assessed by the Prediction model Risk of Bias Assessment Tool. Models with a reported area under the curve of the receiver operating characteristic (AUC) metric were analyzed.

RESULTS

A total of 25 studies were retrieved, including 48 unique prediction models. Discrimination was reported in all studies, with AUC ranging from 0.701 to 0.95. Emerged AUC value of the logistic regression model was 0.837 (95% CI: 0.814 to 0.859). Besides, the value in the ICU group was 0.856 (95% CI: 0.812 to 0.899), the acute pancreatitis group was 0.863 (95% CI: 0.844 to 0.882), and the postoperation group was 0.835 (95% CI: 0.808 to 0.861). In total, 24 of the included studies had a high risk of bias, which was mostly due to the improper methods in predictor screening (13/24), model calibration assessment (9/24), and dichotomization of continuous predictors (6/24).

CONCLUSIONS

This study shows that most prediction models for ARDS are at high risk of bias, and the discrimination ability of the model is excellent. Adherence to standardized guidelines for model development is necessary to derive a prediction model of value to clinicians.

Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19

INTRODUCTION

The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P/F) ≤ 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P/F adjusted for this high altitude.

METHODS

This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogotá, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p <0.25. Then, these variables were automatically selected with a backward stepwise approach with a significance level of 0.1. The interaction terms and fractional polynomials were also examined in the final model. Multiple imputation procedures and bootstraps were used to obtain the coefficients with the best external validation. In addition, total adjustment of the model and logistic regression diagnostics were performed. The same methodology was used to develop a second model with the P/F adjusted for altitude. Finally, the areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves of the two models were compared.

RESULTS

A total of 2,210 subjects were included in the final analysis. The final model included 11 variables without interaction terms or nonlinear functions. The coefficients are presented excluding influential observations. The final equation for the model fit was g(x) = age(0.04819)+weight(0.00653)+height(-0.01856)+haemoglobin(-0.0916)+platelet count(-0.003614)+ creatinine(0.0958)+lactate dehydrogenase(0.001589)+sodium(-0.02298)+potassium(0.1574)+systolic pressure(-0.00308)+if moderate ARDS(0.628)+if severe ARDS(1.379), and the probability of in-hospital death was p (x) = e g (x)/(1+ e g (x)). The AUC of the ROC curve was 0.7601 (95% confidence interval (CI) 0.74-0, 78). The second model with the adjusted P/F presented an AUC of 0.754 (95% CI 0.73-0.77). No statistically significant difference was found between the AUC curves (p value = 0.6795).

CONCLUSION

This study presents a prediction model for patients with C-ARDS at 2,600 masl with easily available admission variables for early stratification of in-hospital mortality risk. Adjusting the P/F for 2,600 masl did not improve the predictive capacity of the model. We do not recommend adjusting the P/F for altitude.

Acute and postacute COVID-19 outcomes for patients with rheumatoid arthritis: lessons learned and emerging directions 3 years into the pandemic

PURPOSE OF REVIEW

To summarize the findings of studies investigating patients with rheumatoid arthritis (RA) and risk of acute and postacute COVID-19 outcomes 3 years into the pandemic.

RECENT FINDINGS

Most studies early in the pandemic included all patients with systemic autoimmune rheumatic diseases (SARDs), not only those with RA, due to limited sample size. Many of these studies found that patients with SARDs were at higher risk of COVID-19 infection and severe outcomes, including hospitalization, hyperinflammation, mechanical ventilation, and death. Studies performed later were able to focus on RA and found similar associations, while also identifying RA-specific factors such as immunosuppressive medications, disease activity/severity, and interstitial lung disease as risk factors for severe COVID-19. After COVID-19 vaccination, the risks for COVID-19 infection and severity were reduced for patients with RA, but a gap between the general population persisted, and some patients with RA are susceptible to breakthrough infection after vaccination. Preexposure prophylaxis, effective treatments, and changes in viral variants have also contributed to improved COVID-19 outcomes throughout the pandemic. Emerging data suggest that patients with RA may be at risk for postacute sequelae of COVID-19 (PASC).

SUMMARY

Although COVID-19 outcomes have improved over the pandemic for patients with RA, some experience poor acute and postacute outcomes after COVID-19. Clinicians and patients should remain vigilant about risk mitigation for infection and consider early treatment for RA patients with COVID-19. Future studies are needed to investigate clinical outcomes and mechanisms of PASC among patients with RA.