Validation of an abbreviated version of the Denver HIV risk score for prediction of HIV infection in an urban ED

Performance of HIV Infection Prediction Models in Men Who Have Sex with Men: A Systematic Review and Meta-Analysis

Effective ways to identify and predict men who have sex with men (MSM) at substantial risk for HIV is a global priority. HIV risk assessment tools can improve individual risk awareness and subsequent health-seeking actions. We sought to identify and characterize the performance of HIV infection risk prediction models in MSM through systematic review and meta-analysis. PubMed, Embase, and The Cochrane Library were searched. Eighteen HIV infection risk assessment models with a total of 151,422 participants and 3643 HIV cases were identified, eight of which have been externally validated by at least one study (HIRI-MSM, Menza Score, SDET Score, Li Model, DHRS, Amsterdam Score, SexPro model, and UMRSS). The number of predictor variables in each model ranged from three to 12, age, the number of male sexual partners, unprotected receptive anal intercourse, recreational drug usage (amphetamines, poppers), and sexually transmitted infections were critical scoring variables. All eight externally validated models performed well in terms of discrimination, with the pooled area under the receiver operating characteristic curve (AUC) ranging from 0.62 (95%CI: 0.51 to 0.73, SDET Score) to 0.83 (95%CI: 0.48 to 0.99, Amsterdam Score). Calibration performance was only reported in 10 studies (35.7%, 10/28). The HIV infection risk prediction models showed moderate-to-good discrimination performance. Validation of prediction models across different geographic and ethnic environments is needed to ensure their real-world application.

Human-centered design development of mHealth patient-to-peer referral tool in the emergency department

Background

Given the steady increase of emergency department (ED) visits related to opioid overdoses, this study aims to determine the design and usability of an ED-centered mHealth patient-to-peer referral prototype tool that allows patients to refer peers to comprehensive HIV/HCV and opioid misuse prevention services.

Methods

Two iterative focus group discussion (FDG) sessions and one use-case session were conducted. Eligible participants who were ≥18 years, had a history of injection drug use (IDU), and had utilized the ED in the past year were recruited through the distribution of flyers at the study institution, including the study ED. Human-centered design process was completed by using participant feedback on perceived utility, usability/accessibility, tool design, and clarity/readability to fine-tune prototype version and drive subsequent discussion sessions.

Results

Sixteen consented individuals participated in at least one of the sessions. Feedback revealed that participants favored the inclusion of the webpage link on the referral card as means to bypass QR code if needed, more descriptions highlighting the exact services offered, and the fact that no personal information was required to complete the referral process. The prototype underwent several adjustments between user-centered FDG sessions, which ultimately ended in including features such as an online webpage with educational videos, SMS text-message communication system, and QR code usage into the final patient-to-peer referral tool prototype.

Conclusion

The findings of this study suggest a human-centered designed patient-to-peer referral tool could be a feasible approach to linking community members at risk of IDU to HIV/HCV and opioid use-related preventive services from ED patients.

HIV Testing at Visits to US Emergency Departments, 2018

BACKGROUND

An early HIV diagnosis improves patient outcomes, reduces the burden of undiagnosed HIV, and limits transmission. There is a need for an updated assessment of HIV testing rates in the emergency department (ED).

SETTING

The National Hospital Ambulatory Medical Care Survey sampling ED visits were weighted to give an estimate of ED visits across all US states in 2018.

METHODS

We analyzed patients aged 13-64 years without known HIV and estimated ED visits with HIV testing and then stratified by race, ethnicity, and region. Descriptive statistics and mapping were used to illustrate and compare patient, visit, and hospital characteristics for visits with HIV testing.

RESULTS

Of 83.0 million weighted visits to EDs in 2018 by patients aged 13-64 years without a known HIV infection (based on 13,237 National Hospital Ambulatory Medical Care Survey sample visits), HIV testing was performed in 1.05% of visits. HIV testing was more frequent for patients aged 13-34 years compared with that for patients aged 35-64 years (1.32% vs. 0.82%, P = 0.056), Black patients compared with that for White and other patients (1.73% vs. 0.79% and 0.41%, P = 0.002), Hispanic or Latino patients compared with that for non-Hispanic or Latino patients (2.18% vs. 0.84%, P = 0.001), and patients insured by Medicaid compared with that for patients insured by private or other insurance (1.71% vs. 0.64% and 0.96%, P = 0.003). HIV testing rates were the highest in the Northeast (1.72%), followed by the South (1.05%).

CONCLUSIONS

HIV testing occurred in a minority of ED visits. There are differences in rates of HIV testing by race, ethnicity, and location. Although rates of testing have increased, rates of ED-based HIV testing remain low.

Machine Learning-Based HIV Risk Estimation Using Incidence Rate Ratios

HIV/AIDS is an ongoing global pandemic, with an estimated 39 million infected worldwide. Early detection is anticipated to help improve outcomes and prevent further infections. Point-of-care diagnostics make HIV/AIDS diagnoses available both earlier and to a broader population. Wide-spread and automated HIV risk estimation can offer objective guidance. This supports providers in making an informed decision when considering patients with high HIV risk for HIV testing or pre-exposure prophylaxis (PrEP). We propose a novel machine learning method that allows providers to use the data from a patient's previous stays at the clinic to estimate their HIV risk. All features available in the clinical data are considered, making the set of features objective and independent of expert opinions. The proposed method builds on association rules that are derived from the data. The incidence rate ratio (IRR) is determined for each rule. Given a new patient, the mean IRR of all applicable rules is used to estimate their HIV risk. The method was tested and validated on the publicly available clinical database MIMIC-IV, which consists of around 525,000 hospital stays that included a stay at the intensive care unit or emergency department. We evaluated the method using the area under the receiver operating characteristic curve (AUC). The best performance with an AUC of 0.88 was achieved with a model consisting of 53 rules. A threshold value of 0.66 leads to a sensitivity of 98% and a specificity of 53%. The rules were grouped into drug abuse, psychological illnesses (e.g., PTSD), previously known associations (e.g., pulmonary diseases), and new associations (e.g., certain diagnostic procedures). In conclusion, we propose a novel HIV risk estimation method that builds on existing clinical data. It incorporates a wide range of features, leading to a model that is independent of expert opinions. It supports providers in making informed decisions in the point-of-care diagnostics process by estimating a patient's HIV risk.

Care of Sexual and Gender Minorities in the Emergency Department: A Scoping Review

STUDY OBJECTIVE

This scoping review was conducted to collate and summarize the published research literature addressing sexual and gender minority care in the emergency department (ED).

METHODS

Using PRISMA-ScR criteria, an electronic search was conducted of CINAHL, Embase, Ovid Medline, and Web of Science for all studies that were published after 1995 involving sexual and gender minorities, throughout all life stages, presenting to an ED. We excluded non-US and Canadian studies and editorials. Titles and abstracts were screened, and full-text review was performed independently with 4 reviewers. Abstraction focused on study design, demographics, and outcomes, and the resulting data were analyzed using an ad hoc iterative thematic analysis.

RESULTS

We found 972 unique articles and excluded 743 after title and abstract screening. The remaining 229 articles underwent full-text review, and 160 articles were included. Themes identified were HIV in sexual and gender minorities (n=61), population health (n=46), provider training (n=29), ED avoidance or barriers (n=23), ED use (n=21), and sexual orientation/gender identity information collection (n=9).

CONCLUSION

The current literature encompassing ED sexual and gender minority care cluster into 6 themes. There are considerable gaps to be addressed in optimizing culturally competent and equitable care in the ED for this population. Future research to address these gaps should include substantial patient stakeholder engagement in all aspects of the research process to ensure patient-focused outcomes congruent with sexual and gender minority values and preferences.

Derivation and Validation of an HIV Risk Prediction Score Among Gay, Bisexual, and Other Men Who Have Sex With Men to Inform PrEP Initiation in an STD Clinic Setting

BACKGROUND

Clinicians and health departments would ideally undertake targeted efforts to promote HIV pre-exposure prophylaxis (PrEP) and frequent HIV testing using data-based criteria to identify populations at elevated risk for HIV. We developed an HIV risk prediction score for men who have sex with men (MSM) to identify individuals at substantial risk for HIV acquisition.

METHODS

We created a retrospective cohort of MSM who tested HIV-negative at the sexually transmitted disease clinic in Seattle, WA, from 2001 to 2015, and identified seroconversions using HIV surveillance data. We split the cohort randomly 2:1 into derivation and validation data sets, and used Cox proportional hazards to estimate the hazard of acquiring HIV associated with behavioral and clinical predictors, and the Akaike information criterion to determine which variables to retain in our model.

RESULTS

Among 16,448 MSM, 640 seroconverted over a 14.3-year follow-up period. The best prediction model included 13 variables and had an area under the receiver operating characteristic curve of 0.73 (95% confidence interval: 0.71 to 0.76), 76% sensitivity, and 63% specificity at a score cutoff ≥11. A simplified model restricted to 2011-2015 included 4 predictors [methamphetamine use, condomless receptive anal intercourse (CRAI), ≥10 partners, and current diagnosis or self-reported gonorrhea/syphilis in the past year]. This model, the Seattle PrEP Score, had an area under the receiver operating characteristic curve of 0.69 (95% confidence interval: 0.64 to 0.73), 62% sensitivity, and 70% specificity. One-year incidence was 0.5% for a score of 0, 0.7% for a score of 1, and 2.1% for scores ≥2.

CONCLUSIONS

The Seattle PrEP Score was predictive of HIV acquisition and could help clinicians and public health agencies identify MSM who could benefit from PrEP and frequent HIV testing.

Development and Validation of a Sociodemographic and Behavioral Characteristics-Based Risk-Score Algorithm for Targeting HIV Testing Among Adults in Kenya

To inform targeted HIV testing, we developed and externally validated a risk-score algorithm that incorporated behavioral characteristics. Outpatient data from five health facilities in western Kenya, comprising 19,458 adults ≥ 15 years tested for HIV from September 2017 to May 2018, were included in univariable and multivariable analyses used for algorithm development. Data for 11,330 adults attending one high-volume facility were used for validation. Using the final algorithm, patients were grouped into four risk-score categories: ≤ 9, 10-15, 16-29 and ≥ 30, with increasing HIV prevalence of 0.6% [95% confidence interval (CI) 0.46-0.75], 1.35% (95% CI 0.85-1.84), 2.65% (95% CI 1.8-3.51), and 15.15% (95% CI 9.03-21.27), respectively. The algorithm's discrimination performance was modest, with an area under the receiver-operating-curve of 0.69 (95% CI 0.53-0.84). In settings where universal testing is not feasible, a risk-score algorithm can identify sub-populations with higher HIV-risk to be prioritized for HIV testing.

A Model for Syphilis Screening in the Emergency Department

The incidence of syphilis infections is on the rise, particularly among African American men and men who have sex with men, and it is reaching epidemic levels in these communities throughout the United States. Although syphilis is relatively inexpensive to treat and cure and is a predictor for HIV incidence among men and transgender women who have sex with men, rates of co-screening for syphilis are low in the emergency department setting, with a dearth of literature on this topic since the 1990s and early 2000s. In this case study, we describe an operational model for routine syphilis screening implemented in June 2017 at the University Hospitals Cleveland Medical Center in Cleveland, Ohio. We describe the advantages of screening using a reverse testing algorithm rather than the traditional method and the necessity of partnering with the Cleveland Department of Public Health for both diagnostic and follow-up logistics.

Clinical knowledge of human immunodeficiency virus and sexually transmitted infections among emergency medicine providers

Introduction

This study examines the association of the domains of knowledge for HIV and sexually transmitted infections (STIs) among emergency medicine providers (EP).

Methods

From February 2018 to March 2018, 75 EP (physicians, residents, and advanced practice providers) completed an anonymous, self-administered survey. The primary outcome of strength of correlation between HIV and STI sections of the survey was analyzed using Spearman’s rank-order coefficient.

Results

Respondents were physicians (54.6%), male (56%), Caucasian (83.7%), with eight years in practice (IQR: 2,16). Spearman’s correlation of HIV and STIs showed a weak positive correlation ( r = 0.35, p = 0.002). There was no association between HIV scores and provider type ( p = 0.67) or provider gender ( p = 0.89) as well as no association between STI scores and provider type ( p = 0.10) or provider gender ( p = 0.79).

Conclusion

The results of our study reveal that when presented with a patient at high risk for undiagnosed HIV or with undiagnosed symptomatic HIV infection, most providers either do not test or do not have HIV in the differential diagnosis. Similarly, knowledge of STIs is only weakly correlated with knowledge of HIV risk factors and symptomatic HIV infection. Further research and screening efforts may benefit by focusing on HIV education among emergency medicine providers.

Risk Prediction Score for HIV Infection: Development and Internal Validation with Cross-Sectional Data from Men Who Have Sex with Men in China

Receptive anal intercourse, multiple partners, condomless sex, sexually transmitted infections (STIs), and drug/alcohol addiction are familiar factors that correlate with increased human immunodeficiency virus (HIV) risk among men who have sex with men (MSM). To improve estimation to HIV acquisition, we created a composite score using questions from routine survey of 3588 MSM in Beijing, China. The HIV prevalence was 13.4%. A risk scoring tool using penalized maximum likelihood multivariable logistic regression modeling was developed, deploying backward step-down variable selection to obtain a reduced-form model. The full penalized model included 19 sexual predictors, while the reduced-form model had 12 predictors. Both models calibrated well; bootstrap-corrected c-indices were 0.70 (full model) and 0.71 (reduced-form model). Non-Beijing residence, short-term living in Beijing, illegal drug use, multiple male sexual partners, receptive anal sex, inconsistent condom use, alcohol consumption before sex, and syphilis infection were the strongest predictors of HIV infection. Discriminating higher-risk MSM for targeted HIV prevention programming using a validated risk score could improve the efficiency of resource deployment for educational and risk reduction programs. A valid risk score can also identify higher risk persons into prevention and vaccine clinical trials, which would improve trial cost-efficiency.

The impact of nurse-driven targeted HIV screening in 8 emergency departments: study protocol for the DICI-VIH cluster-randomized two-period crossover trial

BACKGROUND

In 2010, to reduce late HIV diagnosis, the French national health agency endorsed non-targeted HIV screening in health care settings. Despite these recommendations, non-targeted screening has not been implemented and only physician-directed diagnostic testing is currently performed. A survey conducted in 2010 in 29 French Emergency Departments (EDs) showed that non-targeted nurse-driven screening was feasible though only a few new HIV diagnoses were identified, predominantly among high-risk groups. A strategy targeting high-risk groups combined with current practice could be shown to be feasible, more efficient and cost-effective than current practice alone.

METHODS/DESIGN

DICI-VIH (acronym for nurse-driven targeted HIV screening) is a multicentre, cluster-randomized, two-period crossover trial. The primary objective is to compare the effectiveness of 2 strategies for diagnosing HIV among adult patients visiting EDs: nurse-driven targeted HIV screening combined with current practice (physician-directed diagnostic testing) versus current practice alone. Main secondary objectives are to compare access to specialist consultation and how early HIV diagnosis occurs in the course of the disease between the 2 groups, and to evaluate the implementation, acceptability and cost-effectiveness of nurse-driven targeted screening. The 2 strategies take place during 2 randomly assigned periods in 8 EDs of metropolitan Paris, where 42 % of France's new HIV patients are diagnosed every year. All patients aged 18 to 64, not presenting secondary to HIV exposure are included. During the intervention period, patients are invited to fill a 7-item questionnaire (country of birth, sexual partners and injection drug use) in order to select individuals who are offered a rapid test. If the rapid test is reactive, a follow-up visit with an infectious disease specialist is scheduled within 72 h. Assuming an 80 % statistical power and a 5 % type 1 error, with 1.04 and 3.38 new diagnoses per 10,000 patients in the control and targeted groups respectively, a sample size of 140,000 patients was estimated corresponding to 8,750 patients per ED and per period. Inclusions started in June 2014. Results are expected by mid-2016.

DISCUSSION

The DICI-VIH study is the first large randomized controlled trial designed to assess nurse-driven targeted HIV screening. This study can provide valuable information on HIV screening in health care settings.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02127424 (29 April 2014).

Development and validation of the San Diego Early Test Score to predict acute and early HIV infection risk in men who have sex with men

BACKGROUND

Although men who have sex with men (MSM) represent a dominant risk group for human immunodeficiency virus (HIV), the risk of HIV infection within this population is not uniform. The objective of this study was to develop and validate a score to estimate incident HIV infection risk.

METHODS

Adult MSM who were tested for acute and early HIV (AEH) between 2008 and 2014 were retrospectively randomized 2:1 to a derivation and validation dataset, respectively. Using the derivation dataset, each predictor associated with an AEH outcome in the multivariate prediction model was assigned a point value that corresponded to its odds ratio. The score was validated on the validation dataset using C-statistics.

RESULTS

Data collected at a single HIV testing encounter from 8326 unique MSM were analyzed, including 200 with AEH (2.4%). Four risk behavior variables were significantly associated with an AEH diagnosis (ie, incident infection) in multivariable analysis and were used to derive the San Diego Early Test (SDET) score: condomless receptive anal intercourse (CRAI) with an HIV-positive MSM (3 points), the combination of CRAI plus ≥5 male partners (3 points), ≥10 male partners (2 points), and diagnosis of bacterial sexually transmitted infection (2 points)-all as reported for the prior 12 months. The C-statistic for this risk score was >0.7 in both data sets.

CONCLUSIONS

The SDET risk score may help to prioritize resources and target interventions, such as preexposure prophylaxis, to MSM at greatest risk of acquiring HIV infection. The SDET risk score is deployed as a freely available tool at http://sdet.ucsd.edu.