OP0251 IMPACT OF INTERSTITIAL LUNG DISEASE ON SEVERE COVID-19 OUTCOMES FOR PATIENTS WITH RHEUMATOID ARTHRITIS: A MULTICENTER STUDY

Background

RA has been associated with poor COVID-19 outcomes, but few studies have investigated outcomes in RA features such as interstitial lung disease.

Objectives

To assess COVID-19 outcomes in patients with RA overall, and those with and without ILD, compared to general population comparators.

Methods

A multicenter, retrospective cohort study was conducted at Mayo Clinic (19 hospitals and affiliated outpatient centers in 4 states) and Mass General Brigham (14 hospitals and affiliated outpatient centers in New England). Consecutive patients with RA meeting ACR/EULAR criteria and a positive COVID-19 test from March 1, 2020 through June 6, 2021 were matched 1:5 on age, sex, race, and COVID-19 test date with general population comparators without RA. RA features assessed included: RA-ILD per Bongartz criteria [1], duration, rheumatoid factor (RF), cyclic citrullinated peptide antibody (CCP), bone erosions, and treatments. The primary outcome was a composite of hospitalization or death following COVID-19 diagnosis. We used multivariable Cox regression to investigate the association of RA, and features such as ILD, with COVID-19 outcomes compared to matched comparators.

Results

We analyzed 582 patients with RA and 2892 comparators without RA, all with COVID-19. Mean age was 62 years, 51% were female, and 79% were White. Mean RA duration was 11 years, 67% were seropositive (52% RF+ and 54% CCP+), 27% had bone erosions, 28% were on steroids, and 79% were on DMARDs. 50/582 (9%) patients with RA had ILD.

The COVID-19 hospitalization or death rate for RA patients was higher than comparators (3.0 per 1,000 days [95% CI 2.5-3.6] vs. 1.9 per 1,000 days [95% CI 1.7-2.1], respectively). Overall, RA patients had a 53% higher risk of hospitalization or death than comparators after adjustment (95% CI 1.20-1.94).

Among those with RA-ILD, the hospitalization or death rate was significantly higher than comparators (10.9 [95% CI 6.7-15.2] vs. 2.5 per 1,000 days [1.8-3.2], respectively). RA-ILD was associated with nearly 3-fold higher risk for hospitalization or death than comparators (multivariable HR 2.84 [95% CI 1.64-4.91], Table 1). There was a significant interaction between RA/comparator status and presence/absence of ILD for risk of severe COVID-19 (p<0.001, Figure 1). The elevated risk for severe COVID-19 was similar for RA subgroups defined by serostatus or bone erosions.

Table 1.

Frequencies, proportions, and hazard ratios for COVID-19 outcomes, comparing all RA patients, and subgroups with or without RA-ILD, to matched comparators.

COVID-19 OutcomesAll RA Patients (n=582)RA-ILD (n=50)RA Patients without ILD (n=532)Comparators (n=2,892)Hospitalization, n (%)121 (21)24 (48)97 (18)402 (14)Unadjusted HR (95% CI)1.58 (1.27, 1.96)2.65 (1.71, 4.09)1.43 (1.12, 1.82)Ref.Adjusted* HR (95% CI)1.45 (1.14, 1.83)2.35 (1.38, 4.00)1.31 (1.00, 1.70)Ref.Death, n (%)26 (4)9 (18)17 (3)63 (2)Unadjusted HR (95% CI)1.72 (0.98, 3.01)5.88 (2.07, 16.71)1.13 (0.56, 2.29)Ref.Adjusted* HR (95% CI)1.24 (0.66, 2.32)13.94 (4.30, 45.18)0.75 (0.35, 1.63)Ref.Hospitalization or death, n (%)126 (22)25 (50)101 (19)419 (14)Unadjusted HR (95% CI)1.66 (1.33, 2.07)3.01 (1.93, 4.70)1.47 (1.14, 1.89)Ref.Adjusted* HR (95% CI)1.53 (1.20, 1.94)2.84 (1.64, 4.91)1.34 (1.02, 1.77)Ref.

*Adjusted for age, sex, race, and smoking

Figure 1.

Multivariable hazard ratios for the composite outcome of hospitalization or death from COVID-19, comparing all RA and subgroups by serostatus, bone erosions, and ILD to matched comparators without RA.

Conclusion

We confirmed that RA was associated with severe COVID-19 outcomes compared to the general population. We found evidence that ILD may be an effect modifier for the relationship between RA and severe COVID-19 outcomes, but RA subgroups defined by serostatus and bone erosions had similarly elevated risk. These findings suggest that ILD or its treatment may be a major contributor to severe COVID-19 outcomes in RA.

References

[1]Bongartz, T, et al, Arthritis Rheum. 2010 Jun;62(6):1583-91.

Disclosure of Interests

None declared

0533 Age-related changes in sleep disordered breathing in pediatric Prader Willi Syndrome patients

Introduction

Prader Willi Syndrome (PWS) is a rare genetic disorder characterized by infantile hypotonia, hyperphagia leading to early childhood obesity, and multiple sleep abnormalities including increased risk of obstructive sleep apnea, central sleep apnea, and excessive daytime sleepiness. PWS patients have been reported to have a shorter lifespan with respiratory related causes as a common cause of death. Limited data exists on PSGs in pediatric PWS patients. Our aim was to compare respiratory parameters in different age groups.

Methods

We conducted a retrospective chart review of pediatric patients with a genetically confirmed diagnosis of Prader Willi Syndrome from 2007 to 2015. In lab polysomnograms were scored using the AASM criteria for pediatric sleep studies. As central apneas are more commonly seen in infancy with PWS, we categorized patients into &lt; 1 years old and 1-19 years old for comparison.

Results

Fifty-one PSGs were reviewed of which 31 (60.7%) were males and 20 (39.3%) were females. Forty-one PSGs were initial studies and 11 were repeat studies. Age at time of sleep study ranged from 11 days-19 years old. 8 (15%) subjects were &lt; 1 years old and 44 (84%) were 1-19 years old. For patients &lt; 1 year old, mean obstructive hypopnea index (OAHI) was 5.65±3.7, central index (CI)2.2±2.5, mean SpO2(%) 98±.4, SpO2 nadir 86±5.8, and % of time with SpO2 &lt; 90% .16±.314. For patients 1-19 years old, mean (OAHI) was 8.7±13.4, (CI) 0.8±1.25, mean SpO2 96±3.0, SpO2 nadir 81±.10, and % of time with SpO2 &lt; 90% .03±.10. The OAHI trended up in the 1-19 year old group but results were not significant, CI decreased in the 1-19 year old group 2.2 vs 0.8 p &lt; .04.

Conclusion

Our study demonstrated similar results to prior studies in pediatric PWS with an increase in OAHI and decrease in CI with age. SPO2 nadir decreased in the 1-19 year old group but these results were not significant. Ongoing research at our center is looking at possible contributing factors including BMI percentile, GH therapy, and adenotonsillectomy to better understand our findings.

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0532 Defining Sleep Architecture in Pediatric Patients with Prader Willi Syndrome

Introduction

Prader Willi Syndrome (PWS) is a rare genetic disorder characterized by infantile hypotonia, hyperphagia leading to early childhood obesity, and short stature. PWS patients are at risk for multiple sleep abnormalities including increased risk of obstructive sleep apnea, central sleep apnea, and excessive daytime sleepiness. The limited studies reviewing PSGs in pediatric PWS patients showed varying results. Our study aim is to characterize sleep characteristics in pediatric patients with PWS.

Methods

We conducted a retrospective chart review of pediatric patients with a genetically confirmed diagnosis of Prader Willi Syndrome from 2007 to 2015. In lab polysomnograms were scored using the AASM criteria for pediatric sleep studies. Data was collected on sleep architecture parameters and compared to normative data available for pediatric polysomnography. Given large variability in sleep architecture during infancy, subjects were divided into two age groups (&lt; 1 years old, 1-19 years old).

Results

Fifty-one PSGs were reviewed of which 31 (60.7%) belong to males and 20 (39.3%) belong to females. Forty-one PSGs were initial studies and 11 were repeat studies. Age at the time of sleep study ranged from 11 days to 19 years old. 8 (15%) subjects were less than 1 years old and 44 (84%) were 1 year and older. For subjects less than one year old, mean sleep onset latency (min) was 21±33.4, REM onset latency (min) 35±27.2, SWS(%) 43.3±10.2, REM(%) 35.3±7.35, arousal index 9.7±11.9, wake after sleep onset (WASO) (min) 59.5±11.4 and sleep efficiency 82.4±9.4. For the 1-19 year age group, mean sleep onset latency (min) was 24.5±23.1, REM onset latency (min) 104± 59.9, SWS (%) 21.4±7.11, REM (%) 21.3±6.9, arousal index 7.3±5.4, WASO (min) 46.5±36.10 and sleep efficiency was 85.7±9.0.

Conclusion

In our population of PWS patients, REM onset latency was not decreased as shown in previous studies. Sleep efficiency was decreased. Other sleep parameters fell within normal range. Additional data on signs of excessive daytime sleepiness and sleep disordered breathing in this population is needed to understand if EDS persists with decreased sleep efficiency and otherwise normal sleep parameters and/or with OSA.

Support (If Any)

 

Radiogenomic analysis of primary breast cancer reveals [18F]-fluorodeoxglucose dynamic flux-constants are positively associated with immune pathways and outperform static uptake measures in associating with glucose metabolism

BACKGROUND

PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers.

METHODS

Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging.

RESULTS

A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance.

CONCLUSIONS

In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review

Background

In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes.

Objective

We performed a systematic review of the literature on consumer BP monitors that collect PGHD for managing hypertension to summarize their clinical impact on health and surrogate outcomes. We focused particularly on studies designed to measure the specific effect of using a BP monitor independent of cointerventions. We have also summarized the process and consumer experience outcomes.

Methods

An information specialist searched PubMed, MEDLINE, and Embase for controlled studies on consumer BP monitors published up to May 12, 2020. We assessed the risk of bias using an adapted 9-item appraisal tool and performed a narrative synthesis of the results.

Results

We identified 41 different types of BP monitors used in 49 studies included for review. Device engineers judged that 38 (92%) of those devices were similar to the currently available consumer BP monitors. The median sample size was 222 (IQR 101-416) participants, and the median length of follow-up was 6 (IQR 3-12) months. Of the included studies, 18 (36%) were designed to isolate the clinical effects of BP monitors; 6 of the 18 (33%) studies evaluated health outcomes (eg, mortality, hospitalizations, and quality of life), and data on those outcomes were unclear. The lack of clarity was due to low event rates, short follow-up duration, and risk of bias. All 18 studies that isolated the effect of BP monitors measured both systolic and diastolic BP and generally demonstrated a decrease of 2 to 4 mm Hg in systolic BP and 1 to 3 mm Hg in diastolic BP compared with non–BP monitor groups. Adherence to using consumer BP monitors ranged from 38% to 89%, and ease of use and satisfaction ratings were generally high. Adverse events were infrequent, but there were a few technical problems with devices (eg, incorrect device alerts).

Conclusions

Overall, BP monitors offer small benefits in terms of BP reduction; however, the health impact of these devices continues to remain unclear. Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers. Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers.

Estimating COVID-19 Hospitalizations in the United States with Surveillance Data Using a Bayesian Hierarchical Model: A Modeling Study

Background

In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important.

Objective

We aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19.

Methods

We estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data.

Results

We estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states.

Conclusions

Our novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.

First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report a measurement of the energy-dependent total charged-current cross section σ(E_{ν}) for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer (ν). Data corresponding to 5.3×10^{19} protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab booster neutrino beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy E_{ν} and reconstructed neutrino energy E_{ν}^{rec} and between the energy transfer ν and reconstructed hadronic energy E_{had}^{rec} are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the E_{had}^{rec} distributions between data and a MC prediction after constraining the reconstructed muon kinematic distributions, energy, and polar angle to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well modeled and underpins first-time measurements of both the total cross section σ(E_{ν}) and the differential cross section dσ/dν on argon.

Access to a Labile Monomeric Magnesium Radical by Ball-Milling

In order to isolate a monometallic Mg radical, the precursor (Am)MgI⋅(CAAC) (1) was prepared (Am=tBuC(N‐DIPP)₂, DIPP=2,6‐diisopropylphenyl, CAAC=cyclic (alkyl)(amino)carbene). Reduction of a solution of 1 in toluene with the reducing agent K/KI led to formation of a deep purple complex that rapidly decomposed. Ball‐milling of 1 with K/KI gave the low‐valent Mg^I complex (Am)Mg⋅(CAAC) (2) which after rapid extraction with pentane and crystallization was isolated in 15 % yield. Although a benzene solution of 2 decomposes rapidly to give Mg(Am)₂ (3) and unidentified products, the radical is stable in the solid state. Its crystal structure shows planar trigonal coordination at Mg. The extremely short Mg−C distance of 2.056(2) Å indicates strong Mg−CAAC bonding. Calculations and EPR measurements show that most of the spin density is in a π* orbital located at the C−N bond in CAAC, leading to significant C−N bond elongation. This is supported by calculated NPA charges in 2: Mg +1.73, CAAC −0.82. Similar metal‐to‐CAAC charge transfer was calculated for M⁰(CAAC)₂ and [M^I(CAAC)₂⁺] (M=Be, Mg, Ca) complexes in which the metal charges range from +1.50 to +1.70. Although the spin density of the radical is mainly located at the CAAC ligand, complex 2 reacts as a low‐valent Mg^I complex: reaction with a I₂ solution in toluene gave (Am)MgI⋅(CAAC) (1) as the major product.