Objective: The practice of evidence-based medicine can be challenging when relevant data are lacking or difficult to contextualize for a specific patient. Large language models (LLMs) could potentially address both challenges by summarizing published literature or generating new studies using real-world data.
Materials and Methods: We submitted 50 clinical questions to five LLM-based systems: OpenEvidence, which uses an LLM for retrieval-augmented generation (RAG); ChatRWD, which uses an LLM as an interface to a data extraction and analysis pipeline; and three general-purpose LLMs (ChatGPT-4, Claude 3 Opus, Gemini 1.5 Pro). Nine independent physicians evaluated the answers for relevance, quality of supporting evidence, and actionability (i.e., sufficient to justify or change clinical practice).
Results: General-purpose LLMs rarely produced relevant, evidence-based answers (2–10% of questions). In contrast, RAG-based and agentic LLM systems, respectively, produced relevant, evidence-based answers for 24% (OpenEvidence) to 58% (ChatRWD) of questions. OpenEvidence produced actionable results for 48% of questions with existing evidence, compared to 37% for ChatRWD and <5% for the general-purpose LLMs. ChatRWD provided actionable results for 52% of questions that lacked existing literature compared to <10% for other LLMs.
Discussion: Special-purpose LLM systems greatly outperformed general-purpose LLMs in producing answers to clinical questions. Retrieval-augmented generation-based LLM (OpenEvidence) performed well when existing data were available, while only the agentic ChatRWD was able to provide actionable answers when preexisting studies were lacking.
Conclusion: Synergistic systems combining RAG-based evidence summarization and agentic generation of novel evidence could improve the availability of pertinent evidence for patient care.

Context: Patients with culture-negative pulmonary TB (PTB) can face delays in diagnosis that worsen outcomes and lead to ongoing transmission. An understanding of current trends and characteristics of culture-negative PTB can support earlier detection and access to care.
Objective: Describe epidemiology of culture-negative PTB.
Design, setting, participants: We utilized Alameda County TB surveillance data from 2010 to 2019. Culture-negative PTB cases met clinical but not laboratory criteria for PTB per US National Tuberculosis Surveillance System definitions. We calculated trends in annual incidence and proportion of culture-negative PTB using Poisson and weighted linear regression, respectively. We further compared demographic and clinical characteristics among culture-negative versus culture-positive PTB cases.
Results: During 2010-2019, there were 870 cases of PTB, of which 152 (17%) were culture-negative. The incidence of culture-negative PTB declined by 76%, from 1.9/100 000 to 0.46/100 000 (P for trend <.01), while the incidence of culture-positive PTB reduced by 37% (6.5/100 000 to 4.1/100 000, P for trend =.1). Culture-negative PTB case-patients were more likely than culture-positive PTB case-patients to be younger (7.9% were children <15 years old vs 1.1%; P < .01), recent immigrants within 5 years of arrival (38.2% vs 25.5%; P < .01), and have a TB contact (11.2% vs 2.9%; P < .01). Culture-negative PTB case-patients were less likely than culture-positive PTB case-patients to be evaluated because of TB symptoms (57.2% vs 74.7%; P < .01) or have cavitation on chest imaging (13.1% vs 38.8%; P < .01). At the same time culture-negative PTB case-patients were less likely to die during TB treatment (2.0% vs 9.6%; P < .01).
Conclusions: The incidence of culture-negative PTB disproportionately declined compared with culture-positive TB and raises concern for gaps in detection. Expansion of screening programs for recent immigrants and TB contacts and greater recognition of risk factors may increase detection of culture-negative PTB.

Context: Patients with culture-negative pulmonary TB (PTB) can face delays in diagnosis that worsen outcomes and lead to ongoing transmission. An understanding of current trends and characteristics of culture-negative PTB can support earlier detection and access to care.
Objective: Describe epidemiology of culture-negative PTB.
Design, setting, participants: We utilized Alameda County TB surveillance data from 2010 to 2019. Culture-negative PTB cases met clinical but not laboratory criteria for PTB per US National Tuberculosis Surveillance System definitions. We calculated trends in annual incidence and proportion of culture-negative PTB using Poisson and weighted linear regression, respectively. We further compared demographic and clinical characteristics among culture-negative versus culture-positive PTB cases.
Results: During 2010-2019, there were 870 cases of PTB, of which 152 (17%) were culture-negative. The incidence of culture-negative PTB declined by 76%, from 1.9/100 000 to 0.46/100 000 (P for trend <.01), while the incidence of culture-positive PTB reduced by 37% (6.5/100 000 to 4.1/100 000, P for trend =.1). Culture-negative PTB case-patients were more likely than culture-positive PTB case-patients to be younger (7.9% were children <15 years old vs 1.1%; P < .01), recent immigrants within 5 years of arrival (38.2% vs 25.5%; P < .01), and have a TB contact (11.2% vs 2.9%; P < .01). Culture-negative PTB case-patients were less likely than culture-positive PTB case-patients to be evaluated because of TB symptoms (57.2% vs 74.7%; P < .01) or have cavitation on chest imaging (13.1% vs 38.8%; P < .01). At the same time culture-negative PTB case-patients were less likely to die during TB treatment (2.0% vs 9.6%; P < .01).
Conclusions: The incidence of culture-negative PTB disproportionately declined compared with culture-positive TB and raises concern for gaps in detection. Expansion of screening programs for recent immigrants and TB contacts and greater recognition of risk factors may increase detection of culture-negative PTB.

Recovery from enteric bacterial illness often includes a phase of organismal shedding over a period of days to months. The monitoring of this process through laboratory testing forms the foundation of public health action to prevent further transmission. Regulations in most jurisdictions in the United States exclude individuals who continue to shed certain organisms from sensitive occupations and situations, such as food handling, providing direct patient care, or attending day care. The burden that this creates for recovering patients and their families/coworkers is great, so any effort to provide efficiency to the testing process would be of significant benefit. We sought to assess the ability of PCR for the detection of Salmonella enterica shedding and to compare that ability to culture-based testing. PCR would be faster than culture and would allow results to be generated more quickly. Herein, we show data that indicate that, while PCR and culture testing agree in the majority of cases, there are incidents of discordance between the two tests, whereupon PCR shows positive results when culture indicates lack of detectable viable organisms. Using culture-based testing as the standard, the negative predictive value of PCR was found to be 100%, while the positive predictive value was 79%. The nature of this discordance is briefly investigated. We found that it is possible that PCR may not only detect nonviable organisms in stool but also viable organisms that remain undetectable by standard culture methods.

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BACKGROUND
Substance use is highly prevalent among men who have sex with men (MSM) and is associated with individual-level sexual risk behaviors. However, few studies have explored the relationship between substance use and HIV risk behaviors within partnerships.
METHODS
We examined partner-level data between MSM participants (n = 23) and their sexual partners (n = 52). We used multivariable generalized estimating equations (GEE) logistic regression to assess the relationship between partner-level substance use during their last sexual encounter with each partner, and engaging in condomless anal intercourse (CAI) and serodiscordant CAI.
RESULTS
In multivariable analyses, participants had significantly higher adjusted odds ratio (AOR) of CAI when the participant (AOR = 22.2, 95%CI = 2.5-199.5) or their partners used any drugs (AOR = 21.8, 95%CI = 3.3-144.3); their partners (AOR = 5.7, 95%CI = 1.7-19.3) or both participant and partner had concordant use of methamphetamine (AOR = 10.5, 95%CI = 2.2-50.6); or when both used poppers (AOR = 11.4, 95%CI = 1.5-87). There were higher odds of SDCAI if the participant binge drank (AOR = 4, 95%CI = 1.01-15.8), used more than one substance (AOR = 15.8, 95%CI = 1.9-133), or used other drugs (AOR = 4.8, 95%CI = 1.3-18.4); if their partner used poppers (AOR = 7.6, 95%CI = 1.5-37.6), or used more than one substance (AOR = 7.9, 95%CI = 1.9-34.1); and when both participant and partner had concordant use of poppers (AOR = 4.4, 95%CI = 1.2-16.8).
CONCLUSIONS
This study observed significant relationship between substance use and HIV risk behaviors within partnerships. Specifically, when either the participant, the partner, or both used any drugs there was an increased odds of sexual risk behaviors. Findings suggest that partner-level substance use behaviors should be taken in account when developing sexual risk reduction interventions.