Despite advances in antiretroviral treatment (ART), human immunodeficiency virus (HIV) can detrimentally affect everyday functioning. Neurocognitive impairment (NCI) and current depression are common in people with HIV (PWH) and can contribute to poor functional outcomes, but potential synergies between the two conditions are less understood. Thus, the present study aimed to compare the independent and combined effects of NCI and depression on everyday functioning in PWH. We predicted worse functional outcomes with comorbid NCI and depression than either condition alone.

PWH enrolled at the UCSD HIV Neurobehavioral Research Program were assessed for neuropsychological performance, depression severity (≤minimal, mild, moderate, or severe; Beck Depression Inventory-II), and self-reported everyday functioning.

Participants were 1,973 PWH (79% male; 66% racial/ethnic minority; Age: M = 48.6; Education: M = 13.0, 66% AIDS; 82% on ART; 42% with NCI; 35% BDI>13). ANCOVA models found effects of NCI and depression symptom severity on all functional outcomes (ps < .0001). With NCI and depression severity included in the same model, both remained significant (ps < .0001), although the effects of each were attenuated, and yielded better model fit parameters (i.e., lower AIC values) than models with only NCI or only depression.

Consistent with prior literature, NCI and depression had independent effects on everyday functioning in PWH. There was also evidence for combined effects of NCI and depression, such that their comorbidity had a greater impact on functioning than either alone. Our results have implications for informing future interventions to target common, comorbid NCI and depressed mood in PWH and thus reduce HIV-related health disparities.

Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. However, they lack specimen collection and diagnosis dates to assign location of onset. Algorithms to classify CDI onset location using claims data have been published, but the degree of misclassification is unknown.

We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016–2021 to Medicare beneficiaries with fee-for-service Part A/B coverage. We calculated sensitivity of ICD-10-CM codes in claims within ±28 days of EIP specimen collection. CDI was categorized as hospital, long-term care facility, or community-onset using three different Medicare claims-based algorithms based on claim type, ICD-10-CM code position, duration of hospitalization, and ICD-10-CM diagnosis code presence-on-admission indicators. We assessed concordance of EIP case classifications, based on chart review and specimen collection date, with claims case classifications using Cohen’s kappa statistic.

Of 12,671 CDI cases eligible for linkage, 9,032 (71%) were linked to a single, unique Medicare beneficiary. Compared to EIP, sensitivity of CDI ICD-10-CM codes was 81%; codes were more likely to be present for hospitalized patients (93.0%) than those who were not (56.2%). Concordance between EIP and Medicare claims algorithms ranged from 68% to 75%, depending on the algorithm used (κ = 0.56–0.66).

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

Duchenne muscular dystrophy is a devastating neuromuscular disorder characterized by the loss of dystrophin, inevitably leading to cardiomyopathy. Despite publications on prophylaxis and treatment with cardiac medications to mitigate cardiomyopathy progression, gaps remain in the specifics of medication initiation and optimization.

This document is an expert opinion statement, addressing a critical gap in cardiac care for Duchenne muscular dystrophy. It provides thorough recommendations for the initiation and titration of cardiac medications based on disease progression and patient response. Recommendations are derived from the expertise of the Advance Cardiac Therapies Improving Outcomes Network and are informed by established guidelines from the American Heart Association, American College of Cardiology, and Duchenne Muscular Dystrophy Care Considerations. These expert-derived recommendations aim to navigate the complexities of Duchenne muscular dystrophy-related cardiac care.

Comprehensive recommendations for initiation, titration, and optimization of critical cardiac medications are provided to address Duchenne muscular dystrophy-associated cardiomyopathy.

The management of Duchenne muscular dystrophy requires a multidisciplinary approach. However, the diversity of healthcare providers involved in Duchenne muscular dystrophy can result in variations in cardiac care, complicating treatment standardization and patient outcomes. The aim of this report is to provide a roadmap for managing Duchenne muscular dystrophy-associated cardiomyopathy, by elucidating timing and dosage nuances crucial for optimal therapeutic efficacy, ultimately improving cardiac outcomes, and improving the quality of life for individuals with Duchenne muscular dystrophy.

This document seeks to establish a standardized framework for cardiac care in Duchenne muscular dystrophy, aiming to improve cardiac prognosis.

Validate a public health model identifying patients at high risk for carbapenem-resistant Enterobacterales (CRE) on admission and evaluate performance across a healthcare network.

Retrospective case-control studies

Adults hospitalized with a clinical CRE culture within 3 days of admission (cases) and those hospitalized without a CRE culture (controls).

Using public health data from Atlanta, GA (1/1/2016–9/1/2019), we validated a CRE prediction model created in Chicago. We then closely replicated this model using clinical data from a healthcare network in Atlanta (1/1/2015–12/31/2021) (“Public Health Model”) and optimized performance by adding variables from the healthcare system (“Healthcare System Model”). We frequency-matched cases and controls based on year and facility. We evaluated model performance in validation datasets using area under the curve (AUC).

Using public health data, we matched 181 cases to 764,408 controls, and the Chicago model performed well (AUC 0.85). Using clinical data, we matched 91 cases to 384,013 controls. The Public Health Model included age, prior infection diagnosis, number of and mean length of stays in acute care hospitalizations (ACH) in the prior year. The final Healthcare System Model added Elixhauser score, antibiotic days of therapy in prior year, diabetes, admission to the intensive care unit in prior year and removed prior number of ACH. The AUC increased from 0.68 to 0.73.

A CRE risk prediction model using prior healthcare exposures performed well in a geographically distinct area and in an academic healthcare network. Adding variables from healthcare networks improved model performance.

Examine the relationship between patients’ race and prescriber antibiotic choice while accounting for differences in underlying illness and infection severity.

Retrospective cohort analysis.

Acute care facilities within an academic healthcare system.

Adult inpatients from January 2019 through June 2022 discharged from the Hospital Medicine Service with an ICD-10 Code for Pneumonia.

We describe variability in days of therapy of antimicrobials with activity against Pseudomonas aeruginosa (anti-Pseudomonas agents) or against MRSA (anti-MRSA agents), by patient’s race and ethnicity. We estimated the likelihood of receipt of any anti-Pseudomonas agents by race and modeled the effect of race on rate of use, adjusting for age, severity, and indication.

5,820 patients with 6,700 encounters were included. After adjusting for broad indication, severity, underlying illness, and age, use of anti-Pseudomonas agents were less likely among non-Hispanic Black patients than other race groups, although this effect was limited to younger patients (adjusted odds ratio [aOR] 0.45, 95% confidence interval [CI] 0.29, 0.70), and not older ones (aOR 0.98; 95% CI 0.85, 1.13); use of anti-MRSA agents were similar between groups. Among patients receiving any anti-Pseudomonas agents, Black patients received them for relatively lower proportion of their inpatient stay (incidence rate ratio 0.91; 95% CI 0.87, 0.96).

We found difference in use of anti-Pseudomonas agents between non-Hispanic Black patients and other patients that could not be easily explained by indications or underlying illness, suggesting unmeasured factors may be playing a role in treatment decisions.

Identifying persons with HIV (PWH) at increased risk for Alzheimer’s disease (AD) is complicated because memory deficits are common in HIV-associated neurocognitive disorders (HAND) and a defining feature of amnestic mild cognitive impairment (aMCI; a precursor to AD). Recognition memory deficits may be useful in differentiating these etiologies. Therefore, neuroimaging correlates of different memory deficits (i.e., recall, recognition) and their longitudinal trajectories in PWH were examined.

We examined 92 PWH from the CHARTER Program, ages 45–68, without severe comorbid conditions, who received baseline structural MRI and baseline and longitudinal neuropsychological testing. Linear and logistic regression examined neuroanatomical correlates (i.e., cortical thickness and volumes of regions associated with HAND and/or AD) of memory performance at baseline and multilevel modeling examined neuroanatomical correlates of memory decline (average follow-up = 6.5 years).

At baseline, thinner pars opercularis cortex was associated with impaired recognition (p = 0.012; p = 0.060 after correcting for multiple comparisons). Worse delayed recall was associated with thinner pars opercularis (p = 0.001) and thinner rostral middle frontal cortex (p = 0.006) cross sectionally even after correcting for multiple comparisons. Delayed recall and recognition were not associated with medial temporal lobe (MTL), basal ganglia, or other prefrontal structures. Recognition impairment was variable over time, and there was little decline in delayed recall. Baseline MTL and prefrontal structures were not associated with delayed recall.

Episodic memory was associated with prefrontal structures, and MTL and prefrontal structures did not predict memory decline. There was relative stability in memory over time. Findings suggest that episodic memory is more related to frontal structures, rather than encroaching AD pathology, in middle-aged PWH. Additional research should clarify if recognition is useful clinically to differentiate aMCI and HAND.

To examine the relationship between race and ethnicity and central line-associated bloodstream infections (CLABSI) while accounting for inherent differences in CLABSI risk related to central venous catheter (CVC) type.

Retrospective cohort analysis.

Acute care facilities within an academic healthcare system.

Adult inpatients from January 2012 through December 2017 with CVC present for ≥2 contiguous days.

We describe variability in demographics, comorbidities, CVC type/configuration, and CLABSI rate by patient’s race and ethnicity. We estimated the unadjusted risk of CLABSI for each demographic and clinical characteristic and then modelled the effect of race on time to CLABSI, adjusting for total parenteral nutrition use and CVC type. We also performed exploratory analysis replacing race and ethnicity with social vulnerability index (SVI) metrics.

32,925 patients with 57,642 CVC episodes met inclusion criteria, most of which (51,348, 89%) were among non-Hispanic White or non-Hispanic Black patients. CVC types differed between race/ethnicity groups. However, after adjusting for CVC type, configuration, and indication in an adjusted cox regression, the risk of CLABSI among non-Hispanic Black patients did not significantly differ from non-Hispanic White patients (adjusted hazard ratio [aHR] 1.19; 95% confidence interval [CI]: 0.94, 1.51). The odds of having a CLABSI among the most vulnerable SVI subset compared to the less vulnerable was no different (odds ratio [OR] 0.95; 95% CI: 0.75–1.2).

We did not find a difference in CLABSI risk between non-Hispanic White and non-Hispanic Black patients when adjusting for CLABSI risk inherent in type and configuration of CVC.

Among inpatients, peer-comparison of prescribing metrics is challenging due to variation in patient-mix and prescribing by multiple providers daily. We established risk-adjusted provider-specific antibiotic prescribing metrics to allow peer-comparisons among hospitalists.

Using clinical and billing data from inpatient encounters discharged from the Hospital Medicine Service between January 2020 through June 2021 at four acute care hospitals, we calculated bimonthly (every two months) days of therapy (DOT) for antibiotics attributed to specific providers based on patient billing dates. Ten patient-mix characteristics, including demographics, infectious disease diagnoses, and noninfectious comorbidities were considered as potential predictors of antibiotic prescribing. Using linear mixed models, we identified risk-adjusted models predicting the prescribing of three antibiotic groups: broad spectrum hospital-onset (BSHO), broad-spectrum community-acquired (BSCA), and anti-methicillin-resistant Staphylococcus aureus (Anti-MRSA) antibiotics. Provider-specific observed-to-expected ratios (OERs) were calculated to describe provider-level antibiotic prescribing trends over time.

Predictors of antibiotic prescribing varied for the three antibiotic groups across the four hospitals, commonly selected predictors included sepsis, COVID-19, pneumonia, urinary tract infection, malignancy, and age >65 years. OERs varied within each hospital, with medians of approximately 1 and a 75th percentile of approximately 1.25. The median OER demonstrated a downward trend for the Anti-MRSA group at two hospitals but remained relatively stable elsewhere. Instances of heightened antibiotic prescribing (OER >1.25) were identified in approximately 25% of the observed time-points across all four hospitals.

Our findings indicate provider-specific benchmarking among inpatient providers is achievable and has potential utility as a valuable tool for inpatient stewardship efforts.

The incubation period for Clostridioides difficile infection (CDI) is generally considered to be less than 1 week, but some recent studies suggest that prolonged carriage prior to disease onset may be common.

To estimate the incubation period for patients developing CDI after initial negative cultures.

In 3 tertiary care medical centers, we conducted a cohort study to identify hospitalized patients and long-term care facility residents with negative initial cultures for C. difficile followed by a diagnosis of CDI with or without prior detection of carriage. Cases were classified as healthcare facility-onset, community-onset, healthcare facility-associated, or community-associated and were further classified as probable, possible, or unlikely CDI. A parametric accelerated failure time model was used to estimate the distribution of the incubation period.

Of 4,179 patients with negative enrollment cultures and no prior CDI diagnosis within 56 days, 107 (2.6%) were diagnosed as having CDI, including 19 (17.8%) with and 88 (82.2%) without prior detection of carriage. When the data were censored to only include participants with negative cultures collected within 14 days, the estimated median incubation period was 6 days with 25% and 75% of estimated incubation periods occurring within 3 and 12 days, respectively. The observed estimated incubation period did not differ significantly for patients classified as probable, possible, or unlikely CDI.

Our findings are consistent with the previous studies that suggested the incubation period for CDI is typically less than 1 week and is less than 2 weeks in most cases.