Utility of clinical assessment, imaging, and cryptococcal antigen titer to predict AIDS-related complicated forms of cryptococcal meningitis

<p>Abstract</p> <p>Background</p> <p>This study aimed to evaluate the prevalence and predictors of AIDS-related complicated cryptococcal meningitis. The outcome was complicated cryptococcal meningitis: prolonged (≥ 14 days) altered mental status, persistent (≥ 14 days) focal neurologic findings, cerebrospinal fluid (CSF) shunt placement or death. Predictor variable operating characteristics were estimated using receiver operating characteristic curve (ROC) analysis. Multivariate analysis identified independent predictors of the outcome.</p> <p>Results</p> <p>From 1990-2009, 82 patients with first episode of cryptococcal meningitis were identified. Of these, 14 (17%) met criteria for complicated forms of cryptococcal meningitis (prolonged altered mental status 6, persistent focal neurologic findings 7, CSF surgical shunt placement 8, and death 5). Patients with complicated cryptococcal meningitis had higher frequency of baseline focal neurological findings, head computed tomography (CT) abnormalities, mean CSF opening pressure, and cryptococcal antigen (CRAG) titers in serum and CSF. ROC area of log₂serum and CSF CRAG titers to predict complicated forms of cryptococcal meningitis were comparable, 0.78 (95%CI: 0.66 to 0.90) vs. 0.78 (95% CI: 0.67 to 0.89), respectively (χ², p = 0.95). The ROC areas to predict the outcomes were similar for CSF pressure and CSF CRAG titers. In a multiple logistic regression model, the following were significant predictors of the outcome: baseline focal neurologic findings, head CT abnormalities and log₂CSF CRAG titer.</p> <p>Conclusions</p> <p>During initial clinical evaluation, a focal neurologic exam, abnormal head CT and large cryptococcal burden measured by CRAG titer are associated with the outcome of complicated cryptococcal meningitis following 2 weeks from antifungal therapy initiation.</p

Mesothelioma in an HIV/AIDS patient without history of asbestos exposure: possible role for immunosuppression in mesothelioma: a case report

We describe a 41-year-old African-American male who initially presented in respiratory distress. He had a positive history of asthma, cigarette smoking, and only recent possible asbestos exposure six months prior to onset of symptoms. Mesothelioma was suspected after chest radiography and PET-CT, and confirmed by immunohistochemical tissue analysis. We postulate that immunosuppression enhances susceptibility to mesothelioma, since weakened immune systems are present in both HIV/AIDS patients like this 41-year-old man, and elderly patients who compose the population that classically presents with mesothelioma. Furthermore, immunosuppression may be a prerequisite to the development of mesothelioma

Denial of Risk Behavior Does Not Exclude Asymptomatic Anorectal Sexually Transmitted Infection in HIV-Infected Men

BACKGROUND: The Centers for Disease Control recommend screening for asymptomatic sexually transmitted infection (STI) among HIV-infected men when there is self-report of unprotected anal-receptive exposure. The study goals were: (1) to estimate the validity and usefulness for screening policies of self-reported unprotected anal-receptive exposure as a risk indicator for asymptomatic anorectal infection with Neisseria gonorrhoeae (GC) and/or Chlamydia trachomatis (CT). (2) to estimate the number of infections that would be missed if anal diagnostic assays were not performed among patients who denied unprotected anorectal exposure in the preceding month. METHODS AND FINDINGS: Retrospective analysis in HIV primary care and high resolution anoscopy (HRA) clinics. HIV-infected adult men were screened for self-reported exposure during the previous month at all primary care and HRA appointments. Four sub-cohorts were defined based on microbiology methodology (GC culture and CT direct fluorescent antibody vs. GC/CT nucleic acid amplification test) and clinical setting (primary care vs. HRA). Screening question operating characteristics were estimated using contingency table methods and then pooled across subcohorts. Among 803 patients, the prevalence of anorectal GC/CT varied from 3.5-20.1% in the 4 sub-cohorts. The sensitivity of the screening question for self-reported exposure to predict anorectal STI was higher in the primary care than in the HRA clinic, 86-100% vs. 12-35%, respectively. The negative predictive value of the screening question to predict asymptomatic anorectal STI was > or = 90% in all sub-cohorts. In sensitivity analyses, the probability of being an unidentified case among those denying exposure increased from 0.4-8.1% in the primary care setting, and from 0.9-18.8% in the HRA setting as the prevalence varied from 1-20%. CONCLUSION: As STI prevalence increases, denial of unprotected anal-receptive exposure leads to an increasingly unacceptable proportion of unidentified asymptomatic anorectal STI if used as a criterion not to obtain microbiologic assays

Randomized Trial of a Health Coaching Intervention to Enhance Retention in Care: California Collaborative Treatment Group 594.

Poor linkage, engagement and retention remain significant barriers in achieving HIV treatment goals in the US. HIV-infected persons entering or re-entering care across three Southern California academic HIV clinics, were randomized (1:1) to an Active, Linkage, Engagement, Retention and Treatment (ALERT) specialist for outreach and health coaching, or standard of care (SOC). The primary outcome of time to loss to follow up (LTFU) was compared using Cox proportional hazards regression modeling. No differences in the median time to LTFU (81.7 for ALERT versus 93.6&nbsp;weeks for SOC; HR 1.27; p = 0.40), or time to ART initiation was observed (N = 116). Although, ALERT participants demonstrated worsening depressive symptomatology from baseline to week 48 compared to SOC (p = 0.02). The ALERT intervention did not improve engagement and retention in HIV care over SOC. Further studies are&nbsp;needed to determine how best to apply resources to improve retention and engagement

COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes.

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) codes. COVID-19 TestNorm was developed and evaluated using 568 test names collected from 8 healthcare systems. Our results show that it could achieve an accuracy of 97.4% on an independent test set. COVID-19 TestNorm is available as an open-source package for developers and as an online Web application for end users (https://clamp.uth.edu/covid/loinc.php). We believe that it will be a useful tool to support secondary use of EHRs for research on COVID-19

Estimating the Accuracy of Anal Cytology in the Presence of an Imperfect Reference Standard

Background: The study aim is to estimate sensitivity and specificity of anal cytology for histologic HSIL in analyses adjusted for the imperfect biopsy reference standard. Methods and Principal Findings: Retrospective cohort study of an anal dysplasia screening program for HIV infected adults. We estimated the prevalence of histologic HSIL by concurrent cytology category and the associated cytology ROC area. Cytology operating characteristics for HSIL were estimated and adjusted for the imperfect reference standard by 3 methodologies. The study cohort included 261 patients with 3 available measures: (1) referral cytology; (2) HRA cytology; and (3) HRA directed biopsy. The prevalence of biopsy HSIL varied according to the concurrent HRA cytology result: 64.5

Development and implementation of an automated electronic health record-linked registry for emergency general surgery.

INTRODUCTION: Despite adoption of the emergency general surgery (EGS) service by hospitals nationally, quality improvement (QI) and research for this patient population are challenging because of the lack of population-specific registries. Past efforts have been limited by difficulties in identifying EGS patients within institutions and labor-intensive approaches to data capture. Thus, we created an automated electronic health record (EHR)-linked registry for EGS. METHODS: We built a registry within the Epic EHR at University of California San Diego for the EGS service. Existing EHR labels that identified patients seen by the EGS team were used to create our automated inclusion rules. Registry validation was performed using a retrospective cohort of EGS patients in a 30-month period and a 1-month prospective cohort. We created quality metrics that are updated and reported back to clinical teams in real time and obtained aggregate data to identify QI and research opportunities. A key metric tracked is clinic schedule rate, as we care that discontinuity postdischarge for the EGS population remains a challenge. RESULTS: Our registry captured 1,992 patient encounters with 1,717 unique patients in the 30-month period. It had a false-positive EGS detection rate of 1.8%. In our 1-month prospective cohort, it had a false-positive EGS detection rate of 0% and sensitivity of 85%. For quality metrics analysis, we found that EGS patients who were seen as consults had significantly lower clinic schedule rates on discharge compared with those who were admitted to the EGS service (85% vs. 60.7%, p &lt; 0.001). CONCLUSION: An EHR-linked EGS registry can reliably conduct capture data automatically and support QI and research. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III

A learning health system approach to COVID‐19 exposure notification system rollout

IntroductionDigital exposure notification (EN) approaches may offer considerable advantages over traditional contact tracing in speed, scale, efficacy, and confidentiality in pandemic control. We applied the science of learning health systems to test the effect of framing and digital means, email vs Short Message Service (SMS), on EN adoption among patients of an academic health center.MethodsWe tested three communication approaches of the Apple and Google EN system in a rapid learning cycle involving 15 000 patients pseudorandomly assigned to three groups. The patients in the first group received a 284-word email that presented EN as a tool that can help slow the spread. The patients in the second group received a 32-word SMS that described EN as a new tool to help slow the spread (SlowTheSpreadSMS). Patients in the third group received a 47-word SMS that depicted the system as a new digital tool that can empower them to protect their family and friends (EmpowerSMS). A brief four-question anonymous survey of adoption was included in a reminder message sent 2 days after the initial outreach.ResultsOne hundred and sixty people responded to the survey within 1 week: 2.33% from EmpowerSMS, 0.97% from SlowTheSpreadSMS, and 0.53% from emails; 29 (41.43%), 24 (41.38%), and 11 (34.38%) reported having adopted EN from each group, respectively. Patient reported barriers to adoption included iOS version incompatibility, privacy concerns, and low trust of government agencies or companies like Apple and Google. Patients recommended that healthcare systems play an active role in disseminating information about this tool. Patients also recommended advertising on social media and providing reassurance about privacy.ConclusionsThe EmpowerSMS resulted in relatively more survey responses. Both SMS groups had slightly higher, but not statistically significant EN adoption rates compared to email. Findings from the pilot not only informed operational decision-making in our health system but also contributed to EN rollout planning in our State

Generative artificial intelligence responses to patient messages in the electronic health record: early lessons learned

BackgroundElectronic health record (EHR)-based patient messages can contribute to burnout. Messages with a negative tone are particularly challenging to address. In this perspective, we describe our initial evaluation of large language model (LLM)-generated responses to negative EHR patient messages and contend that using LLMs to generate initial drafts may be feasible, although refinement will be needed.MethodsA retrospective sample (n = 50) of negative patient messages was extracted from a health system EHR, de-identified, and inputted into an LLM (ChatGPT). Qualitative analyses were conducted to compare LLM responses to actual care team responses.ResultsSome LLM-generated draft responses varied from human responses in relational connection, informational content, and recommendations for next steps. Occasionally, the LLM draft responses could have potentially escalated emotionally charged conversations.ConclusionFurther work is needed to optimize the use of LLMs for responding to negative patient messages in the EHR