Relationships Between Patient Race and Residential Race Context With Missed Human Immunodeficiency Virus Care Visits in the United States, 2010-2015

BACKGROUND

Racial inequities exist in retention in human immunodeficiency virus (HIV) care and multilevel analyses are needed to contextualize and address these differences. Leveraging data from a multisite clinical cohort of people with HIV (PWH), we assessed the relationships between patient race and residential characteristics with missed HIV care visits.

METHODS

Medical record and patient-reported outcome (PRO; including mental health and substance-use measures) data were drawn from 7 participating Center for AIDS Research Network of Integrated Clinical Systems (CNICS) sites including N = 20 807 PWH from January 2010 through December 2015. Generalized estimating equations were used to account for nesting within individuals and within census tracts in multivariable models assessing the relationship between race and missed HIV care visits, controlling for individual demographic and health characteristics and census tract characteristics.

RESULTS

Black PWH resided in more disadvantaged census tracts, on average. Black PWH residing in census tracts with higher proportion of Black residents were more likely to miss an HIV care visit. Non-Black PWH were less likely to miss a visit regardless of where they lived. These relationships were attenuated when PRO data were included.

CONCLUSIONS

Residential racial segregation and disadvantage may create inequities between Black PWH and non-Black PWH in retention in HIV care. Multilevel approaches are needed to retain PWH in HIV care, accounting for community, healthcare setting, and individual needs and resources.

Pain phenotyping and investigation of outcomes in physical therapy: An exploratory study in patients with low back pain

Phenotypes have been proposed as a method of characterizing subgroups based on biopsychosocial factors to identify responders to analgesic treatments. This study aimed to, first, confirm phenotypes in patients with low back pain receiving physical therapy based on an a priori set of factors used to derive subgroups in other pain populations. Second, an exploratory analysis examined if phenotypes differentiated pain and disability outcomes at four weeks of physical therapy. Fifty-five participants completed psychological questionnaires and pressure pain threshold (PPT). Somatization, anxiety, and depression domains of the Symptom-Checklist-90-Revised, and PPT, were entered into a hierarchical agglomerative cluster analysis with Ward's method to identify phenotypes. Repeated measures ANOVAs assessed pain ratings and disability by phenotype at four weeks. Three clusters emerged: 1) high emotional distress and pain sensitivity (n = 10), 2) low emotional distress (n = 34), 3) low pain sensitivity (n = 11). As an exploratory study, clusters did not differentiate pain ratings or disability after four weeks of physical therapy (p's>0.05). However, trends were observed as magnitude of change for pain varied by phenotype. This supports the characterization of homogenous subgroups based on a protocol conducted in the clinical setting with varying effect sizes noted by phenotype for short-term changes in pain. As an exploratory study, future studies should aim to repeat this trial in a larger sample of patients.

Quantifying and correcting slide-to-slide variation in multiplexed immunofluorescence images

MOTIVATION

Multiplexed imaging is a nascent single-cell assay with a complex data structure susceptible to technical variability that disrupts inference. These in situ methods are valuable in understanding cell-cell interactions, but few standardized processing steps or normalization techniques of multiplexed imaging data are available.

RESULTS

We implement and compare data transformations and normalization algorithms in multiplexed imaging data. Our methods adapt the ComBat and functional data registration methods to remove slide effects in this domain, and we present an evaluation framework to compare the proposed approaches. We present clear slide-to-slide variation in the raw, unadjusted data and show that many of the proposed normalization methods reduce this variation while preserving and improving the biological signal. Furthermore, we find that dividing multiplexed imaging data by its slide mean, and the functional data registration methods, perform the best under our proposed evaluation framework. In summary, this approach provides a foundation for better data quality and evaluation criteria in multiplexed imaging.

AVAILABILITY AND IMPLEMENTATION

Source code is provided at: https://github.com/statimagcoll/MultiplexedNormalization and an R package to implement these methods is available here: https://github.com/ColemanRHarris/mxnorm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Relationship Between Continuous Glucose Monitoring and OGTT in Youth and Young Adults With Cystic Fibrosis

CONTEXT

Early glucose abnormalities in people with cystic fibrosis (PwCF) are commonly detected by continuous glucose monitoring (CGM). Relationships between these CGM abnormalities and oral glucose tolerance testing (OGTT) in PwCF have not been fully characterized.

OBJECTIVE

This work aimed to determine the relationship between CGM and common OGTT-derived estimates of β-cell function, including C-peptide index and oral disposition index (oDI) and to explore whether CGM can be used to screen for OGTT-defined prediabetes and cystic fibrosis-related diabetes (CFRD).

METHODS

PwCF not on insulin and healthy controls aged 6 to 25 years were enrolled in a prospective study collecting OGTT and CGM. A subset underwent frequently sampled OGTTs (fsOGTT) with 7-point glucose, insulin, and C-peptide measurements. Pearson correlation coefficient was used to test the association between select CGM and fsOGTT measures. Receiver operating curve (ROC) analysis was applied to CGM variables to determine the cutoff optimizing sensitivity and specificity for detecting prediabetes and CFRD.

RESULTS

A total of 120 participants (controls = 35, CF = 85), including 69 with fsOGTTs, were included. CGM coefficient of variation correlated inversely with C-peptide index (Cpeptide30-Cpeptide0/Glucose30-Glucose0) (r = -0.45, P < .001) and oDIcpeptide (C-peptide index)(1/cpep0) (r = -0.48, P < .0001). In PwCF, CGM variables had ROC - areas under the curve ranging from 0.43 to 0.57 for prediabetes and 0.47 to 0.6 for CFRD.

CONCLUSION

Greater glycemic variability on CGM correlated with reduced β-cell function. However, CGM performed poorly at discriminating individuals with and without OGTT-defined CFRD and prediabetes. Prospective studies are now needed to determine how well the different tests predict clinically relevant nonglycemic outcomes in PwCF.

Designing and validating a Markov model for hospital-based addiction consult service impact on 12-month drug and non-drug related mortality

INTRODUCTION

Addiction consult services (ACS) engage hospitalized patients with opioid use disorder (OUD) in care and help meet their goals for substance use treatment. Little is known about how ACS affect mortality for patients with OUD. The objective of this study was to design and validate a model that estimates the impact of ACS care on 12-month mortality among hospitalized patients with OUD.

METHODS

We developed a Markov model of referral to an ACS, post-discharge engagement in SUD care, and 12-month drug-related and non-drug related mortality among hospitalized patients with OUD. We populated our model using Oregon Medicaid data and validated it using international modeling standards.

RESULTS

There were 6,654 patients with OUD hospitalized from April 2015 through December 2017. There were 114 (1.7%) drug-related deaths and 408 (6.1%) non-drug related deaths at 12 months. Bayesian logistic regression models estimated four percent (4%, 95% CI = 2%, 6%) of patients were referred to an ACS. Of those, 47% (95% CI = 37%, 57%) engaged in post-discharge OUD care, versus 20% not referred to an ACS (95% CI = 16%, 24%). The risk of drug-related death at 12 months among patients in post-discharge OUD care was 3% (95% CI = 0%, 7%) versus 6% not in care (95% CI = 2%, 10%). The risk of non-drug related death was 7% (95% CI = 1%, 13%) among patients in post-discharge OUD treatment, versus 9% not in care (95% CI = 5%, 13%). We validated our model by evaluating its predictive, external, internal, face and cross validity.

DISCUSSION

Our novel Markov model reflects trajectories of care and survival for patients hospitalized with OUD. This model can be used to evaluate the impact of other clinical and policy changes to improve patient survival.