Confronting the Disruption of the Infectious Diseases Workforce by Artificial Intelligence: What This Means for Us and What We Can Do About It.

With the rapid advancement of artificial intelligence (AI), the field of infectious diseases (ID) faces both innovation and disruption. AI and its subfields including machine learning, deep learning, and large language models can support ID clinicians' decision making and streamline their workflow. AI models may help ensure earlier detection of disease, more personalized empiric treatment recommendations, and allocation of human resources to support higher-yield antimicrobial stewardship and infection prevention strategies. AI is unlikely to replace the role of ID experts, but could instead augment it. However, its limitations will need to be carefully addressed and mitigated to ensure safe and effective implementation. ID experts can be engaged in AI implementation by participating in training and education, identifying use cases for AI to help improve patient care, designing, validating and evaluating algorithms, and continuing to advocate for their vital role in patient care.

Severe COVID-19 in Vaccinated Adults With Hematologic Cancers in the Veterans Health Administration.

Importance: With SARS-CoV-2 transforming into an endemic disease and with antiviral treatments available, it is important to establish which patients remain at risk of severe COVID-19 despite vaccination. Objective: To quantify the associations of clinical and demographic variables with odds of severe COVID-19 among patients with hematologic cancers. Design, Setting, and Participants: This case-control study included all patients with hematologic malignant neoplasms in the national Veterans Health Administration (VHA) who had documented SARS-CoV-2 infection after vaccination. Groups of patients with severe (cases) vs nonsevere (controls) COVID-19 were compared. Data were collected between January 1, 2020, and April 5, 2023, with data on infection collected between January 1, 2021, and September 30, 2022. All patients with diagnostic codes for hematologic malignant neoplasms who had documented vaccination followed by documented SARS-CoV-2 infection and for whom disease severity could be assessed were included. Data were analyzed from July 28 to December 30, 2023. Exposures: Clinical (comorbidities, predominant viral variant, treatment for malignant neoplasm, booster vaccination, and antiviral treatment) and demographic (age and sex) variables shown in prior studies to be associated with higher or lower rates of severe COVID-19. Comorbidities included Alzheimer disease or dementia, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, heart failure, and peripheral vascular disease. Main Outcome and Measures: The main outcome was severe COVID-19 compared with nonsevere SARS-CoV-2 infection. Severe COVID-19 was defined as death within 28 days, mechanical ventilation, or hospitalization with use of dexamethasone or evidence of hypoxemia or use of supplemental oxygen. Multivariable logistic regression was used to estimate the associations of demographic and clinical variables with the odds of severe COVID-19, expressed as adjusted odds ratios (aORs) with 95% CIs. Results: Among 6122 patients (5844 [95.5%] male, mean [SD] age, 70.89 [11.57] years), 1301 (21.3%) had severe COVID-19. Age (aOR per 1-year increase, 1.05; 95% CI, 1.04-1.06), treatment with antineoplastic or immune-suppressive drugs (eg, in combination with glucocorticoids: aOR, 2.32; 95% CI, 1.93-2.80), and comorbidities (aOR per comorbidity, 1.35; 95% CI, 1.29-1.43) were associated with higher odds of severe disease, whereas booster vaccination was associated with lower odds (aOR, 0.73; 95% CI, 0.62-0.86). After oral antiviral drugs became widely used in March 2022, 20 of 538 patients (3.7%) with SARS-CoV-2 infection during this period had progression to severe COVID-19. Conclusions and Relevance: In this case-control study of patients with hematologic cancers, odds of severe COVID-19 remained high through mid-2022 despite vaccination, especially in patients requiring treatment.

Immunomodulators for immunocompromised patients hospitalized for COVID-19: a meta-analysis of randomized controlled trials.

Background: Although immunomodulators have established benefit against the new coronavirus disease (COVID-19) in general, it is uncertain whether such agents improve outcomes without increasing the risk of secondary infections in the specific subgroup of previously immunocompromised patients. We assessed the effect of immunomodulators on outcomes of immunocompromised patients hospitalized for COVID-19. Methods: The protocol was prospectively registered with PROSPERO (CRD42022335397). MEDLINE, Cochrane Central Register of Controlled Trials and references of relevant articles were searched up to 01-06-2022. Authors of potentially eligible randomized controlled trials were contacted to provide data on immunocompromised patients randomized to immunomodulators vs control (i.e., placebo or standard-of-care). Findings: Eleven randomized controlled trials involving 397 immunocompromised patients hospitalized for COVID-19 were included. Ten trials had low risk of bias. There was no difference between immunocompromised patients randomized to immunomodulators vs control regarding mortality [30/182 (16.5%) vs 41/215 (19.1%); RR 0.93, 95% CI 0.61-1.41; p = 0.74], secondary infections (RR 1.00, 95% CI 0.64-1.58; p = 0.99) and change in World Health Organization ordinal scale from baseline to day 15 (weighed mean difference 0.27, 95% CI -0.09-0.63; p = 0.15). In subgroup analyses including only patients with hematologic malignancy, only trials with low risk of bias, only trials administering IL-6 inhibitors, or only trials administering immunosuppressants, there was no difference between comparators regarding mortality. Interpretation: Immunomodulators, compared to control, were not associated with harmful or beneficial outcomes, including mortality, secondary infections, and change in ordinal scale, when administered to immunocompromised patients hospitalized for COVID-19. Funding: Hellenic Foundation for Research and Innovation.

Underuse of Antiviral Drugs to Prevent Progression to Severe COVID-19 - Veterans Health Administration, March-September 2022.

Antiviral drugs reduce the rate of progression to severe COVID-19 when given to patients with mild-to-moderate disease within 5 days of symptom onset. Despite being recommended for patients at high risk for progression to severe COVID-19 because of age or chronic conditions, reported antiviral use among the general adult population has been ≤35%. To ascertain reasons for underuse of antiviral medications to prevent severe COVID-19 and propose interventions accordingly, a detailed review was conducted of 110 Veterans Health Administration patients with mild-to-moderate infection at high risk for progression because of underlying conditions (organ transplantation or hematologic malignancies) who did not receive an antiviral drug. Among these 110 patients, all of whom had received COVID-19 vaccine, 22 (20.0%) were offered treatment but declined, and 88 (80.0%) were not offered treatment. Among the 88 patients not offered treatment, provider reasons included symptom duration of >5 days (22.7%), concern about possible drug interactions (5.7%), or absence of symptoms (22.7%); however, among nearly one half (43 of 88; 48.9%) of these patients, no reason other than mild symptoms was given. Among 24 (55.8%) of those 43 patients, follow-up was limited to telephone calls to report test results and inquire about symptom evolution, with no documentation of treatment being offered. These findings suggest that education of patients, providers, and medical personnel tasked with follow-up calls, combined with advance planning in the event of a positive test result, might improve the rate of recommended antiviral medication use to prevent severe COVID-19-associated illness, including death.

Risk of severe coronavirus disease 2019 despite vaccination in patients requiring treatment with immune-suppressive drugs: A nationwide cohort study of US Veterans.

BACKGROUND: Patients taking immune-suppressive drugs are at increased risk of severe coronavirus disease 2019 (COVID-19), not fully ameliorated by vaccination. We assessed the contributions of clinical and demographic factors to the risk of severe disease despite vaccination in patients taking immune-suppressive medications for solid organ transplantation (SOT), rheumatoid arthritis (RA), inflammatory bowel disease (IBD), or psoriasis. METHODS: Veterans Health Administration electronic health records were used to identify patients diagnosed with RA, IBD, psoriasis, or SOT who had been vaccinated against severe acute respiratory syndrome coronavirus 2, were subsequently infected, and had received immune-suppressive drugs within 3 months before infection. The association of severe (defined as hypoxemia, mechanical ventilation, dexamethasone use, or death) versus non-severe COVID-19 with the use of immune-suppressive and antiviral drugs and clinical covariates was assessed by multivariable logistic regression. RESULTS: Severe COVID-19 was more common in patients with SOT (230/1011, 22.7%) than RA (173/1355, 12.8%), IBD (51/742, 6.9%), or psoriasis (82/1125, 7.3%). Age was strongly associated with severe COVID-19, adjusted odds ratio (aOR) of 1.04 (CI 1.03-1.05) per year. Comorbidities indicating chronic brain, heart, lung, or kidney damage were also associated with severity, aOR 1.35-2.38. The use of glucocorticoids was associated with increased risk (aOR 1.66, CI 1.39-2.18). Treatment with antivirals was associated with reduced severity, for example, aOR 0.28 (CI 0.13-0.62) for nirmatrelvir/ritonavir. CONCLUSION: The risk of severe COVID-19 despite vaccination is substantial in patients taking immune-suppressive drugs, more so in patients with SOT than in patients with inflammatory diseases. Age and severe comorbidities contribute to risk, as in the general population. Oral antivirals were very beneficial but not widely used.

Development and Validation of an Electronic Adverse Event Model for Patient Safety Surveillance in Interventional Radiology.

BACKGROUND: Comprehensive adverse event (AE) surveillance programs in interventional radiology (IR) are rare. Our aim was to develop and validate a retrospective electronic surveillance model to identify outpatient IR procedures that are likely to have an AE, to support patient safety and quality improvement. METHODS: We identified outpatient IR procedures performed in the period from October 2017 to September 2019 from the Veterans Health Administration (n = 135,283) and applied electronic triggers based on posyprocedure care to flag cases with a potential AE. From the trigger-flagged cases, we randomly sampled n = 1,500 for chart review to identify AEs. We also randomly sampled n = 600 from the unflagged cases. Chart-reviewed cases were merged with patient, procedure, and facility factors to estimate a mixed-effects logistic regression model designed to predict whether an AE occurred. Using model fit and criterion validity, we determined the best predicted probability threshold to identify cases with a likely AE. We reviewed a random sample of 200 cases above the threshold and 100 cases from below the threshold from October 2019 to March 2020 (n = 20,849) for model validation. RESULTS: In our development sample of mostly trigger-flagged cases, 444 of 2,096 cases (21.8%) had an AE. The optimal predicted probability threshold for a likely AE from our surveillance model was >50%, with positive predictive value of 68.9%, sensitivity of 38.3%, and specificity of 95.3%. In validation, chart-reviewed cases with AE probability >50% had a positive predictive value of 63% (n = 203). For the period from October 2017 to March 2020, the model identified approximately 70 IR cases per month that were likely to have an AE. CONCLUSIONS: This electronic trigger-based approach to AE surveillance could be used for patient-safety reporting and quality review.

Harm reduction stories: leveraging graphic medicine to engage veterans in substance use services within the VA.

BACKGROUND: Harm reduction strategies can decrease morbidity and mortality associated with substance use. Various barriers limit conversation around substance use between clinicians and patients. Graphic medicine techniques can inform and encourage patient-centered conversations about substance use. We describe the co-development of a harm reduction-focused graphic medicine comic that depicts the infectious risks associated with injection drug use and patient-centered approaches to providing education about potential risk mitigation strategies. METHODS: We formed a co-design group of veterans with lived experience with substance use, physicians, health services researchers, and community-based harm reduction leaders. Over the course of ten sessions, the co-design team developed a storyline and key messages, reviewed draft content and worked with a graphic designer to develop a comic incorporating the veterans' input. During each session, co-design leads presented drafts of the comic and invited feedback from the group. The comic was edited and adapted via this iterative process. RESULTS: The comic depicts a fictionalized clinical vignette in which a patient develops an injection-related abscess and presents to their primary care provider. The dialogue highlights key healthcare principles, including patient autonomy and agency, and highlights strategies for safer use, rather than emphasizing abstinence. Feedback from co-design group participants highlights lessons learned during the development process. DISCUSSION: Graphic medicine is ideally suited for a patient-centered curriculum about harm reduction. This project is one of several interventions that will be integrated into VA facilities nationally to support incorporation of harm reduction principles into the care of persons who inject drugs.

Factors associated with uptake of guideline-recommended cardiovascular implantable electronic device management: a nationwide, retrospective cohort study.

Clinical guidelines recommend device removal for cardiovascular implantable electronic device (CIED) infection management. In this retrospective, nationwide cohort, 60.8% of CIED infections received guideline-concordant care. One-year mortality was higher among those without procedural management (25% vs 16%). Factors associated with receipt of device procedures included pocket infections and positive microbiology.

Engaging patients in antimicrobial stewardship: co-designed educational tool to improve periprocedural care through de-implementation of guideline-discordant antimicrobial use.

Effective de-implementation models often include replacement of an ineffective practice with an alternative. We co-developed patient education materials as a replacement strategy for inappropriate post-procedural antibiotics in cardiac device procedures. Lessons learned and developed materials may be used to promote infection prevention in other periprocedural settings.

Pandemic scientific data sharing recommendations: examining and re-imagining pre-print servers after the end of the world-wide emergency.

Early in the pandemic, pre-print servers sped rapid evidence sharing. A collaborative of major medical journals supported their use to ensure equitable access to scientific advancements. In the intervening three years, we have made major advancements in the prevention and treatment of COVID-19 and learned about the benefits and limitations of pre-prints as a mechanism for sharing and disseminating scientific knowledge. Pre-prints increase attention, citations, and ultimately impact policy, often before findings are verified. Evidence suggests that pre-prints have more spin relative to peer-reviewed publications. Clinical trial findings posted on pre-print servers do not change substantially following peer-review, but other study types (e.g., modeling and observational studies) often undergo substantial revision or are never published. Nuanced policies about sharing results are needed to balance rapid implementation of true and important advancements with accuracy. Policies recommending immediate posting of COVID-19-related research should be re-evaluated, and standards for evaluation and sharing of unverified studies should be developed. These may include specifications about what information is included in pre-prints and requirements for certain data quality standards (e.g., automated review of images and tables); requirements for code release and sharing; and limiting early postings to methods, results, and limitations sections. Academic publishing needs to innovate and improve, but assessments of evidence quality remains a critical part of the scientific discovery and dissemination process.

Embracing dynamic public health policy impacts in infectious diseases responses: leveraging implementation science to improve practice.

Rationale: The host-pathogen relationship is inherently dynamic and constantly evolving. Applying an implementation science lens to policy evaluation suggests that policy impacts are variable depending upon key implementation outcomes (feasibility, acceptability, appropriateness costs) and conditions and contexts. COVID-19 case study: Experiences with non-pharmaceutical interventions (NPIs) including masking, testing, and social distancing/business and school closures during the COVID-19 pandemic response highlight the importance of considering public health policy impacts through an implementation science lens of constantly evolving contexts, conditions, evidence, and public perceptions. As implementation outcomes (feasibility, acceptability) changed, the effectiveness of these interventions changed thereby altering public health policy impact. Sustainment of behavioral change may be a key factor determining the duration of effectiveness and ultimate impact of pandemic policy recommendations, particularly for interventions that require ongoing compliance at the level of the individual. Practical framework for assessing and evaluating pandemic policy: Updating public health policy recommendations as more data and alternative interventions become available is the evidence-based policy approach and grounded in principles of implementation science and dynamic sustainability. Achieving the ideal of real-time policy updates requires improvements in public health data collection and analysis infrastructure and a shift in public health messaging to incorporate uncertainty and the necessity of ongoing changes. In this review, the Dynamic Infectious Diseases Public Health Response Framework is presented as a model with a practical tool for iteratively incorporating implementation outcomes into public health policy design with the aim of sustaining benefits and identifying when policies are no longer functioning as intended and need to be adapted or de-implemented. Conclusions and implications: Real-time decision making requires sensitivity to conditions on the ground and adaptation of interventions at all levels. When asking about the public health effectiveness and impact of non-pharmaceutical interventions, the focus should be on when, how, and for how long they can achieve public health impact. In the future, rather than focusing on models of public health intervention effectiveness that assume static impacts, policy impacts should be considered as dynamic with ongoing re-evaluation as conditions change to meet the ongoing needs of the ultimate end-user of the intervention: the public.

Maintaining the Utility of Coronavirus Disease 2019 Pandemic Severity Surveillance: Evaluation of Trends in Attributable Deaths and Development and Validation of a Measurement Tool.

BACKGROUND: Death within a specified time window following a positive SARS-CoV-2 test is used by some agencies for attributing death to COVID-19. With Omicron variants, widespread immunity, and asymptomatic screening, there is cause to re-evaluate COVID-19 death attribution methods and develop tools to improve case ascertainment. METHODS: All patients who died following microbiologically confirmed SARS-CoV-2 in the Veterans Health Administration (VA) and at Tufts Medical Center (TMC) were identified. Records of selected vaccinated VA patients with positive tests in 2022, and of all TMC patients with positive tests in 2021-2022, were manually reviewed to classify deaths as COVID-19-related (either directly caused by or contributed to), focused on deaths within 30 days. Logistic regression was used to develop and validate a surveillance model for identifying deaths in which COVID-19 was causal or contributory. RESULTS: Among vaccinated VA patients who died ≤30 days after a positive test in January-February 2022, death was COVID-19-related in 103/150 cases (69%) (55% causal, 14% contributory). In June-August 2022, death was COVID-19-related in 70/150 cases (47%) (22% causal, 25% contributory). Similar results were seen among the 71 patients who died at TMC. A model including hypoxemia, remdesivir, and anti-inflammatory drugs had positive and negative predictive values of 0.82-0.95 and 0.64-0.83, respectively. CONCLUSIONS: By mid-2022, "death within 30 days" did not provide an accurate estimate of COVID-19-related death in 2 US healthcare systems with routine admission screening. Hypoxemia and use of antiviral and anti-inflammatory drugs-variables feasible for reporting to public health agencies-would improve classification of death as COVID-19-related.

The integration of harm reduction services in the Veterans Health Administration (VHA): a qualitative analysis of barriers and facilitators.

BACKGROUND: Substance use is common among U.S. military veterans and veterans are at high risk for negative consequences associated with substance use, such as injection-related infections and overdose. Although harm reduction services (HRS) are highly evidence-based, implementation in traditional healthcare settings has been limited. This formative, qualitative study sought to identify barriers and facilitators to the integration of HRS and identify appropriate implementation strategies to support the optimized integration of a comprehensive bundle of HRS in the Veterans Health Administration (VHA). METHODS: Semi-structured interviews explored how harm reduction is currently understood by VHA providers and elicited input on perceived facilitators and barriers to implementation. Data were analyzed using a directed content analysis and the Practical, Robust Implementation and Sustainability Model (PRISM) implementation framework was used to organize findings. Results were then mapped to relevant implementation strategies using the Consolidated Framework for Implementation Research - Expert Recommendations for Implementing Change (CFIR - ERIC) tool. RESULTS: 15 interviews with VHA providers were conducted across 5 sites. Respondents reported that current HRS are fragmented and dependent on the knowledge, time, and comfort level of individual providers. Stigma around substance use at the patient, provider, and institutional levels was noted to be a key barrier to HRS adoption. Based on identified barriers and facilitators, strategies that may be effective for increasing adoption of HRS include engagement of champions, communication and educational strategies, and adaptation of existing infrastructure. CONCLUSIONS: Many of the barriers identified in this formative study may be addressed using evidence-based implementation strategies. Additional research is needed to identify implementation strategies that are effective for addressing stigma, which is perceived to be a persistent challenge to the provision of integrated harm reduction services.

Improving COVID-19 Disease Severity Surveillance Measures: Statewide Implementation Experience.

Measurement of the burden of COVID-19 on U.S. hospitals has been an important element of the public health response to the pandemic. However, because of variation in testing density and policies, the metric is not standardized across facilities. Two types of burdens exist, one related to the infection control measures that patients who test positive for SARS-CoV-2 require and one from the care of severely ill patients receiving treatment of COVID-19. With rising population immunity from vaccination and infection, as well as the availability of therapeutics, severity of illness has declined. Prior research showed that dexamethasone administration was highly correlated with other disease severity metrics and sensitive to the changing epidemiology associated with the emergence of immune-evasive variants.On 10 January 2022, the Massachusetts Department of Public Health began requiring hospitals to expand surveillance to include reports of both the total number of "COVID-19 hospitalizations" daily and the number of inpatients who received dexamethasone at any point during their hospital stay. All 68 acute care hospitals in Massachusetts submitted COVID-19 hospitalization and dexamethasone data daily to the Massachusetts Department of Public Health over a 1-year period. A total of 44 196 COVID-19 hospitalizations were recorded during 10 January 2022 to 9 January 2023, of which 34% were associated with dexamethasone administration. The proportion of patients hospitalized with COVID-19 who had received dexamethasone was 49.6% during the first month of surveillance and decreased to a monthly average of approximately 33% by April 2022, where it has remained since (range, 28.7% to 33%).Adding a single data element to mandated reporting to estimate the frequency of severe COVID-19 in hospitalized patients was feasible and provided actionable information for health authorities and policy makers. Updates to surveillance methods are necessary to match data collection with public health response needs.

A Novel Informatics Tool to Detect Periprocedural Antibiotic Allergy Adverse Events for Near Real-time Surveillance to Support Audit and Feedback.

Importance: Standardized processes for identifying when allergic-type reactions occur and linking reactions to drug exposures are limited. Objective: To develop an informatics tool to improve detection of antibiotic allergic-type events. Design, Setting, and Participants: This retrospective cohort study was conducted from October 1, 2015, to September 30, 2019, with data analyzed between July 1, 2021, and January 31, 2022. The study was conducted across Veteran Affairs hospitals among patients who underwent cardiovascular implantable electronic device (CIED) procedures and received periprocedural antibiotic prophylaxis. The cohort was split into training and test cohorts, and cases were manually reviewed to determine presence of allergic-type reaction and its severity. Variables potentially indicative of allergic-type reactions were selected a priori and included allergies entered in the Veteran Affair's Allergy Reaction Tracking (ART) system (either historical [reported] or observed), allergy diagnosis codes, medications administered to treat allergic reactions, and text searches of clinical notes for keywords and phrases indicative of a potential allergic-type reaction. A model to detect allergic-type reaction events was iteratively developed on the training cohort and then applied to the test cohort. Algorithm test characteristics were assessed. Exposure: Preprocedural and postprocedural prophylactic antibiotic administration. Main Outcomes and Measures: Antibiotic allergic-type reactions. Results: The cohort of 36 344 patients included 34 703 CIED procedures with antibiotic exposures (mean [SD] age, 72 [10] years; 34 008 [98%] male patients); median duration of postprocedural prophylaxis was 4 days (IQR, 2-7 days; maximum, 45 days). The final algorithm included 7 variables: entries in the Veteran Affair's hospitals ART, either historic (odds ratio [OR], 42.37; 95% CI, 11.33-158.43) or observed (OR, 175.10; 95% CI, 44.84-683.76); PheCodes for "symptoms affecting skin" (OR, 8.49; 95% CI, 1.90-37.82), "urticaria" (OR, 7.01; 95% CI, 1.76-27.89), and "allergy or adverse event to an antibiotic" (OR, 11.84, 95% CI, 2.88-48.69); keyword detection in clinical notes (OR, 3.21; 95% CI, 1.27-8.08); and antihistamine administration alone or in combination (OR, 6.51; 95% CI, 1.90-22.30). In the final model, antibiotic allergic-type reactions were identified with an estimated probability of 30% or more; positive predictive value was 61% (95% CI, 45%-76%); and sensitivity was 87% (95% CI, 70%-96%). Conclusions and Relevance: In this retrospective cohort study of patients receiving periprocedural antibiotic prophylaxis, an algorithm with a high sensitivity to detect incident antibiotic allergic-type reactions that can be used to provide clinician feedback about antibiotic harms from unnecessarily prolonged antibiotic exposures was developed.