Infection Risk Assessment Research Articles

P-256. Development of Novel Clutter and Cleanliness Scales for Infection Prevention and Control in U.S. Home Healthcare Settings

Abstract Background In the U.S., homebound older adults often have multiple chronic conditions thereby increasing their infection risk. For those receiving home health care (HHC), environmental hazards in the home can not only exacerbate infection risk but can also impede effective infection prevention and control (IPC) practices for HHC clinicians, patients and their caregivers. Timely and accurate assessment of environmental risks are crucial. Yet, no tools exist specifically for HHC clinicians to assess infection risk factors in the home environment. To fill this gap, we developed scales to measure clutter and cleanliness in HHC patients’ homes. The clutter and cleanliness rating scale. Methods First, we reviewed existing clutter and cleanliness scales, noting that most validated scales focused on hoarding. We adapted these scales and developed observational items focused on IPC in the home environment. During pilot testing with 15 HHC patients and caregivers from an urban HHC agency, we used a uniform rating scale for both clutter and cleanliness items, which posed challenges due to variable home environments and interviewer biases. Following pilot testing, we refined the scales based on interviewer feedback. To improve coding consistency, interviewers received training using a procedural manual and completed a home observation quiz with example pictures. Results Our revised observational items now have distinct rating scales for cleanliness and clutter. Clutter is rated on percentages of free space to reduce subjectivity, and cleanliness is rated on a scale of visible clean to not clean (Table 1). Even with refinement, there was still difficulty achieving consistent ratings among interviewers, specifically with the middle scale points (mostly and moderately clean; some and moderate clutter). However, after scale revisions and interviewer trainings, home observation quiz responses among interviewers achieved at least 80% consistency. Conclusion Our scales represent the first observational items designed to assess home cleanliness and clutter for IPC purposes. If widely adopted, these scales could enable HHC clinicians to effectively assess environmental hazards, informing patient/caregiver educational needs and enhancing patient safety by reducing infection risks. Disclosures All Authors: No reported disclosures

P1283 Adherence to Infectious Disease Assessment at Baseline in Patients with Inflammatory Bowel Disease: A Retrospective Study from a Medical Center

Abstract Background The prevalence of inflammatory bowel disease (IBD) in Taiwan is increasing, and with a growing understanding of the disease, treatment options for IBD have expanded beyond the use of 5-aminosalicylic acid (5-ASA), immunomodulators, and steroids to include a variety of biologics. However, during the course of medical treatment for IBD patients, the risk of infectious diseases may arise. Therefore, conducting a baseline assessment for infections in IBD patients is crucial. Thus, we conducted this retrospective study on IBD patients at a medical center to assess physicians’ adherence to infection risk assessments in IBD patients. Methods This retrospective study enrolled IBD patients from Changhua Christian Hospital from 1995 to 2024 and collected relevant data, including age, gender, IBD classification, types of medications used, and whether testing for HBV, HCV, TB, VZV, and measles was performed. Additionally, we conducted an analysis of factors related to IBD patients who underwent these tests. Results This study enrolled a total of 338 patients, with an average age of 45.9 ± 16.1 years. Among them, 62.7% (212/338) were male, and 67.8% had ulcerative colitis (UC). Additionally, 72.5% of the patients were treated by an IBD specialist. Of the patients, 95.0% were tested for HBsAg, 75.1% for anti-HBc IgG, 95.0% for anti-HCV, 49.1% for IGRA, 31.4% for anti-VZV IgG, and 16.3% for anti-measles IgG. UC patients were significantly less likely to be assessed for TB, while physicians specializing in IBD were significantly more likely to evaluate for VZV and measles compared to general physicians. In terms of medication use, 5-ASA did not show any significant difference in infection assessments. However, patients using immunomodulators, steroids, or biologics had a significantly higher rate of TB evaluation, whereas the proportion of patients assessed for VZV, and measles remained significantly low, regardless of the type of medication used. Conclusion In conclusion, this study highlights gaps in infection risk assessment among IBD patients. While testing rates for HBV and HCV were high, there was a notable variation in the evaluation of TB, VZV, and measles, particularly among non-IBD specialty physicians. Additionally, the use of immunomodulators, steroids, or biologics was associated with a higher rate of TB evaluation, but VZV and measles assessments remained consistently low across all medication groups. These findings underscore the need for more comprehensive infection screening, especially for VZV and measles, to improve patient safety in IBD management.

A nomogram for the prediction of co-infection in MDA5 dermatomyositis: A rapid clinical assessment model.

Patients with anti-melanoma differentiation-associated gene 5-positive dermatomyositis (MDA5 DM) are prone to infections, but there is a lack of rapid methods to assess infection risk, which greatly affects patient prognosis. This study aims to analyze the clinical features of MDA5 DM patients systematically and develop a predictive model for infections. Retrospective analysis was performed on clinical data from 118 hospitalized patients with MDA5 DM. According to the results of pathogen detection and clinical manifestations, the patients were divided into infected group and non-infected group. LASSO analysis and multivariate logistic regression were used to establish the prediction model of infection in MAD5 DM patients. The resulting model was visualized using a Nomogram. We used methods such as Receiver Operating Characteristic (ROC) curve analysis, Area Under the Curve (AUC) calculation to evaluate the model. The Cough, interstitial lung disease, moist rales, positive anti-RO-52, carcinoembryonic antigen, triglyceride, hydroxybutyrate dehydrogenase and erythrocyte sedimentation rate were significantly associated with infection risk in MDA5 DM patients. A prediction model was developed using these eight risk factors, achieving an AUC of 0.851 in determining co-infection status. Further analysis based on infection site and pathogen classification demonstrated strong discrimination performance of the model in identifying pulmonary infection (AUC: 0.844) and fungal infection (AUC: 0.822). This study aimed to develop a clinical prediction model and visualize it using Nomogram to assess the risk of infection in MDA5 DM. The model provides an effective tool for determining infection status in patients and serves as a reference for formulating clinical medication regimens.

Incidence and Risk of Infections in Patients With Radiographic Axial Spondyloarthritis Receiving Biologic Therapies: A Prospective Observational Study Using the KOBIO Registry.

This study aimed to assess the occurrence of infection and risk factors among patients with radiographic axial spondyloarthritis (r-axSpA) treated with biologics in a real-world setting. This prospective observational cohort study included patients with r-axSpA from the Korean College of Rheumatology Biologics (KOBIO) registry who initiated or switched to a biologic agent between December 2012 and December 2023. The primary outcome was the first occurrence of any infection, ranging from mild to severe, classified by organ system. The infection rates per 1000 person-years (PY), with 95% CI, were calculated using the Poisson distribution method. Cox proportional hazard regression models-adjusted for confounders-estimated hazard ratios for infection risk, considering only the first infection event. This analysis included 2129 patients with a total of 7107.67 PY of follow-up. The predominant infections observed were of the upper and lower respiratory tract (25.89/1000 PY), followed by herpes zoster (HZ; 6.13/1000 PY). Multivariate Cox regression analysis revealed significant risk factors for infection, including advanced age, ischemic heart disease (IHD), diabetes mellitus (DM) with complications, chronic kidney disease (CKD), and peripheral arthritis. In contrast, male sex was identified as a protective factor against the development of infections. The infection rate was 39.39 events/1000 PY, with respiratory tract infections being most common, followed by HZ. Significant risk factors for the occurrence of infection in patients with r-axSpA treated with biologics included advanced age, female sex, IHD, DM with complications, CKD, and peripheral arthritis. These findings emphasize infection risk assessment, particularly in high-risk patients, to optimize the safety of biologic therapy in r-axSpA.

Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China.

In this retrospective analysis, we explored the clinical characteristics and risk factors of secondary infections in patients with severe heatstroke with the aim to gain epidemiological insights and identify risk factors for secondary infections. The study included 129 patients with severe heatstroke admitted to the General Hospital of the Southern Theater Command of the PLA between January 1, 2011, and December 31, 2021. Patients were divided into an infection group (n = 24) and a non-infection group (n = 105) based on infection occurrence within 48 h of intensive care unit (ICU) admission. Clinical indicators, infection indicators, and clinical outcomes within 24 h of ICU admission were collected and compared between the groups. Independent risk factors for infection in patients with severe heatstroke were analyzed using univariate and multivariate analyses. A nomogram model was constructed, evaluated, and validated. Among the 129 patients with heatstroke, 24 developed secondary infections. Infections occurred between days 3 and 10 post-ICU admission, primarily affecting the lungs. Multivariate analysis identified vasopressor use, serum creatinine level, and gastrointestinal dysfunction at admission as independent risk factors, while elevated lymphocyte count (odds ratio [OR] = 0.167; 95% confidence interval [CI] 0.049-0.572; P = 0.004) was protective against severe heatstroke. Infected patients required longer durations of mechanical ventilation (OR = 2.764; 95% CI, 1.735-4.405; P = 0.044) and total hospital stay than those in the non-infection group. The nomogram model demonstrated clinical feasibility. Increased lymphocyte count is an independent protective factor against infections in patients with severe heatstroke. Vasopressor use, gastrointestinal dysfunction, and elevated serum creatinine levels are independent risk factors. These indicators can aid clinicians in assessing infection risk in patients with severe heatstroke.

Current and emerging tools for simultaneous assessment of infection and rejection risk in transplantation.

Infection and rejection are major complications that impact transplant longevity and recipient survival. Balancing their risks is a significant challenge for clinicians. Current strategies aimed at interrogating the degree of immune deficiency or activation and their attendant risks of infection and rejection are imprecise. These include immune (cell counts, function and subsets, immunoglobulin levels) and non-immune (drug levels, viral loads) markers. The shared risk factors between infection and rejection and the bidirectional and intricate relationship between both entities further complicate transplant recipient care and decision-making. Understanding the dynamic changes in the underlying net state of immunity and the overall risk of both complications in parallel is key to optimizing outcomes. The allograft biopsy is the current gold standard for the diagnosis of rejection but is associated with inherent risks that warrant careful consideration. Several biomarkers, in particular, donor derived cell-free-DNA and urinary chemokines (CXCL9 and CXCL10), show significant promise in improving subclinical and clinical rejection risk prediction, which may reduce the need for allograft biopsies in some situations. Integrating conventional and emerging risk assessment tools can help stratify the individual's short- and longer-term infection and rejection risks in parallel. Individuals identified as having a low risk of rejection may tolerate immunosuppression wean to reduce medication-related toxicity. Serial monitoring following immunosuppression reduction or escalation with minimally invasive tools can help mitigate infection and rejection risks and allow for timely diagnosis and treatment of these complications, ultimately improving allograft and patient outcomes.

Modelling indoor airborne transmission combining architectural design and people movement using the VIRIS simulator and web app

A Viral Infection Risk Indoor Simulator (VIRIS) has been developed to quickly assess and compare mitigations for airborne disease spread. This agent-based simulator combines people movement in an indoor space, viral transmission modelling and detailed architectural design, and it is powered by topologicpy, an open-source Python library. VIRIS generates very fast predictions of the viral concentration and the spatiotemporal infection risk for individuals as they move through a given space. The simulator is validated with data from a courtroom superspreader event. A sensitivity study for unknown parameter values is also performed. We compare several non-pharmaceutical interventions (NPIs) issued in UK government guidance, for two indoor settings: a care home and a supermarket. Additionally, we have developed the user-friendly VIRIS web app that allows quick exploration of diverse scenarios of interest and visualisation, allowing policymakers, architects and space managers to easily design or assess infection risk in an indoor space.

Questions on travel and sexual behaviours negatively impact ethnic minority donor recruitment: Effect of negative word-of-mouth and avoidance.

Donor selection questions differentially impacting ethnic minorities can discourage donation directly or via negative word-of-mouth. We explore the differential impact of two blood safety questions relating to (i) sexual contacts linked to areas where human immunodeficiency virus (HIV) rates are high and (ii) travelling to areas where malaria is endemic. Epidemiological data are used to assess infection risk and the need for these questions. We report two studies. Study 1 is a behavioural study on negative word-of-mouth and avoiding donation among ethnic minorities (n = 981 people from National Health Service Blood and Transplant (NHSBT) and the general population: 761 were current donors). Study 2 is an epidemiology study (utilizing NHSBT/UK Health Security Agency (UKHSA) surveillance data on HIV-positive donations across the UK blood services between1996 and 2019) to assess whether the sexual risk question contributes to reducing HIV risk and whether travel deferral was more prevalent among ethnic minorities (2015-2019). Studies 1 and 2 provide complementary evidence on the behavioural impact to support policy implications. A high proportion of people from ethnic minorities were discouraged from donating and expressed negative word-of-mouth. This was mediated by perceived racial discrimination within the UK National Health Service. The number of donors with HIV who the sexual contact question could have deferred was low, with between 8% and 9.3% of people from ethnic minorities deferred on travel compared with 1.7% of White people. Blood services need to consider ways to minimize negative word-of-mouth, remove questions that are no longer justified on evidence and provide justification for those that remain.

A novel spatio-temporal prediction model of epidemic spread integrating cellular automata with agent-based modeling

Since 2019, major infectious disease outbreaks have placed tremendous pressure on global public health systems, triggering extensive research on the predictive modeling of infectious diseases. Cellular Automaton (CA) is primarily used in the spatial prediction of infectious diseases to establish a model to for simulating the interaction between different regions and the infection risk to simulate the transmission process of the disease and predict its development trend. However, CA models are governed by initial fixed rules and local interactions, and often fail to capture the complex dynamics of epidemic transmission, which are influenced by factors such as public behavior and government intervention. In view of these limitations, we propose a factorial simulation model for the spatial spread of epidemics, the CA-ABM, which divides agents into three categories–public, government, and hospital agents–to comprehensively express the macro factors that affect the development of epidemics. Agent-Based Modeling (ABM) influences the transition rules of the CA through agent choices, constraints and supporting behaviors. Focusing on the COVID-19 pandemic in mainland China from February 6 to March 20, 2020, we simulate its spread. The results showed an average improvement of 8.4 % in prediction accuracy, with few errors, RMSE under 200, and R2 values over 0.9 in most provinces, demonstrating strong macro-scale stability. This approach helps regions to understand influencing factors and enables targeted infection risk assessment and prevention. In addition, scenario analysis based on CA-ABM model changes epidemic decision-making from “prediction-response” to “scenario-response” and provides theoretical reference for future epidemic management.

Prevalence and genetic diversity of Anaplasma phagocytophilum in wild small mammals from western Yunnan province, China.

Anaplasma phagocytophilum (A. phagocytophilum) is an emerging zoonotic pathogen causing human granulocytic anaplasmosis, linked to small mammal reservoirs that harbor various zoonotic pathogens, underscoring their importance in public health and ecology. This study seeks to determine the prevalence of A. phagocytophilum in small mammals using PCR, then sequence and genotype positive samples, and assess infection risk factors. Small mammals were seasonally captured and a nested polymerase chain reaction (nested-PCR) was conducted targeting the 16S rRNA gene on spleen samples to detect A. phagocytophilum infection from three counties in western Yunnan province, China. Positive samples were sequenced and genotyped, revealing genetic diversity and regional clustering of the pathogen. A total of 1,605 small mammals belonging to 30 species, 18 genera, 6 families, 3 orders were captured seasonally and screened in this region, yielding a 0.93% infection rate with A. phagocytophilum (15/1605). Significant variations in infection rates were observed across different species, counties, and habitats. The 16Sr RNA genes of A. phagocytophilum were categorized into two distinct clades, indicating notable genetic diversity. The identification of genetic variants in spleen samples underscores the potential public health risk and the critical importance of the One Health approach in disease surveillance. Our findings emphasize the necessity for continuous monitoring and highlight the value of nested-PCR testing on spleen samples for accurate prevalence assessment.

Modeling the health impact of wastewater contamination events in drinking water networks

Pathogen intrusion in drinking water systems can pose severe health risks. To better prepare in planning and responding to such events, computational models that capture the intrusion and health impact dynamics are needed. This study presents a novel benchmark testbed that integrates current knowledge on pathogen transport and fate in chlorinated systems and can assess infection risk from contamination events. The model considers organic matter degradation, chlorine decay mechanisms, pathogen inactivation kinetics, as well as stochastic water demands.We studied modeling of wastewater intrusion events that can occur anywhere within a chlorinated and non-chlorinated network. We applied the Quantitative Microbial Risk Assessment framework focusing on three pathogens: enterovirus, Campylobacter, and Cryptosporidium, and their respective dose-response models. Synthetic household-level water demand time series were used to model the individual water consumption timing and calculate the infection risk (exposure via ingestion).Model outcomes indicate that while chlorination aids mitigation, larger contaminations can still lead to infections due to chlorine resistance (for Cryptosporidium) and chlorine depletion at the contamination point. In our example scenarios, chlorine-susceptible pathogens infected 0.78–26.6% of the downstream population, while chlorine-resistant ones infected the entire downstream population. Enterovirus infection risk is higher, despite the concentrations in the contamination source being lower, due to the lower susceptibility to chlorine than Campylobacter. In non-chlorinated networks, the modeled wastewater contamination events led to 11–46% infection risk in the total population, depending on the contamination location. Hydraulic uncertainty had a limited influence on infection risk. Furthermore, Campylobacter's infection risk is more sensitive to the initial concentration in the contamination source whereas enterovirus infection risk to the inactivation rate. The model further indicates that the time window for effective mitigation of the magnitude of a waterborne outbreak is short (within hours).

Quantifying multi-virion aerosols in respiratory infection transmission

Infectious aerosols are expired in various sizes, and the number of contained virions is expected to significantly vary among expired aerosols. To evaluate the effect of the number of contained virions on infection risk, multi-virion aerosols in expired air should be first quantified. In this study, we categorised expired aerosols into traditional aerosol size bins and aerosols containing different number of virions. We quantified the number of virions in aerosols of each size bin and estimated the size distribution of aerosols which contain a certain number of virions when the viral load is known. This analysis helped us to determine the relationship between multi-size aerosols and multi-virion aerosols. Our findings indicate that for long-range airborne transmission, the airborne transmission droplets derived from four COVID-19 outbreak venues contain at most one infectious virion, supporting the one-virion assumption for the considered viral load ranges. However, for short-range airborne transmission, the impact of multi-virion aerosols on infection risk must be considered. Our quantification of multi-virion aerosols for the first time lays the groundwork for incorporating the multi-virion assumption into infection risk assessments.

COVID-19 Risk Assessment Among Vulnerable Small Business Owners in El Paso County, Texas.

Our objective was to deliver actionable, worksite-specific COVID-19 risk assessments and mitigation strategies tailored to vulnerable workers in one of the highest-risk areas in the US. Four trained, bilingual (English/Spanish) community health workers (CHWs) recruited small businesses (ie, ≤20 employees) across various industries and executed novel on-site infectious disease risk assessment surveys of at least one employer and one employee. Of 102 participating businesses (95% Hispanic-owned), 96% were characterized as "high risk" or "very high risk" for disease transmission. All businesses reported implementing at least one practice to reduce disease transmission; however, almost half of businesses lacked at least 13 of the 17 controls identified to mitigate risk. Tailored, culturally sensitive outreach led by CHWs identified and educated businesses on critical hazards, and these methods may be transferable to similar communities.

TLR9 gene polymorphism confers risk to Helicobacter pylori infection in Jiangsu, China and its inspiration for precision nursing car.

The number of studies which investigate the association between TLR9 gene polymorphism and Helicobacter pylori (H.pylori) infection is low and their results are not consistent. To get a better understanding of the association between TLR9 gene polymorphism and H.pylori infection, providing basis and risk assessment for precision nursing for hospital nurses. A total of 630 normal physical examination subjects were collected including 240 H.pylori (+) and 390 H.pylori (-) subjects. PCR-RFLP was applied to investigate the present polymorphism. At the same time, the meta-analysis was performed between TLR9 gene polymorphism and H.pylori infection risk. Three genotypes (TT, TC, and CC) were observed for TLR9 gene rs187084 polymorphism. CC genotype and C allele were responsible for the significant associations (all P< 0.05). Meta-analysis found no significant associations were found by any genetic models (all P> 0.05). TLR9 polymorphism has a crucial role in H.pylori infection risk and CC genotype confers increased risk to H.pylori infection in the Southern Chinese population. After understanding the influence of TLR9 gene polymorphism on H.pylori infection, nurses can improve the risk assessment of Helicobacter pylori infection and provide health education more personally.

Risk assessment of infection of COVID-19 contacts based on scenario simulation.

We constructed a rapid infection risk assessment model for contacts of COVID-19. The improved Wells-Riley model was used to estimate the probability of infection for contacts of COVID-19 in the same place and evaluate their risk grades. We used COVID-19 outbreaks that were documented to validate the accuracy of the model. We analyzed the relationship between controllable factors and infection probability and constructed common scenarios to analyze the infection risk of contacts in different scenarios. The model showed the robustness of the fitting (mean relative error = 5.89%, mean absolute error = 2.03%, root mean squared error = 2.03%, R2 = 0.991). We found that improving ventilation from poorly ventilated to naturally ventilated and wearing masks can reduce the probability of infection by about two times. Contacts in places of light activity, loud talking or singing, and heavy exercise, oral breathing (e.g., gyms, KTV, choirs) were at higher risk of infection. The model constructed in this study can quickly and accurately assess the infection risk grades of COVID-19 contacts. Simply opening doors and windows for ventilation can significantly reduce the risk of infection in certain places. The places of light activity, loud talking or singing, and heavy exercise, oral breathing, should pay more attention to prevent and control transmission of the epidemic.

2024 Clinical Practice Guideline Update by the Infectious Diseases Society of America on Complicated Intra-abdominal Infections: Diagnostic Imaging of Suspected Acute Appendicitis in Adults, Children, and Pregnant People.

This paper is part of a clinical practice guideline update on the risk assessment, diagnostic imaging, and microbiological evaluation of complicated intra-abdominal infections in adults, children, and pregnant people, developed by the Infectious Diseases Society of America (IDSA). In this paper, the panel provides recommendations for diagnostic imaging of suspected acute appendicitis. The panel's recommendations are based on evidence derived from systematic literature reviews and adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach.

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods

BackgroundNosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) systems are constructed in each hospital; while these data are only used as real-time surveillance but fail to realize the prediction and early warning function. Study is to screen effective predictors from the routine NIS data, through integrating the multiple risk factors and Machine learning (ML) methods, and eventually realize the trend prediction and risk threshold of Incidence of Nosocomial infection (INI).MethodsWe selected two representative hospitals in southern and northern China, and collected NIS data from 2014 to 2021. Thirty-nine factors including hospital operation volume, nosocomial infection, antibacterial drug use and outdoor temperature data, etc. Five ML methods were used to fit the INI prediction model respectively, and to evaluate and compare their performance.ResultsCompared with other models, Random Forest showed the best performance (5-fold AUC = 0.983) in both hospitals, followed by Support Vector Machine. Among all the factors, 12 indicators were significantly different between high-risk and low-risk groups for INI (P < 0.05). After screening the effective predictors through importance analysis, prediction model of the time trend was successfully constructed (R2 = 0.473 and 0.780, BIC = -1.537 and -0.731).ConclusionsThe number of surgeries, antibiotics use density, critical disease rate and unreasonable prescription rate and other key indicators could be fitted to be the threshold predictions of INI and quantitative early warning.

2024 Clinical Practice Guideline Update by the Infectious Diseases Society of America on Complicated Intra-abdominal Infections: Diagnostic Imaging of Suspected Acute Intra-abdominal Abscess in Adults, Children, and Pregnant People.

This article is part of a clinical practice guideline update on the risk assessment, diagnostic imaging, and microbiological evaluation of complicated intra-abdominal infections in adults, children, and pregnant people, developed by the Infectious Diseases Society of America. In this article, the panel provides recommendations for diagnostic imaging of suspected acute intra-abdominal abscess. The panel's recommendations are based on evidence derived from systematic literature reviews and adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach.

2024 Clinical Practice Guideline Update by the Infectious Diseases Society of America on Complicated Intra-abdominal Infections: Utility of Intra-abdominal Fluid Cultures in Adults, Children, and Pregnant People.

This paper is part of a clinical practice guideline update on the risk assessment, diagnostic imaging, and microbiological evaluation of complicated intra-abdominal infections in adults, children, and pregnant people, developed by the Infectious Diseases Society of America. In this paper, the panel provides recommendations for obtaining cultures of intra-abdominal fluid in patients with known or suspected intra-abdominal infection. The panel's recommendations are based on evidence derived from systematic literature reviews and adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.

2024 Clinical Practice Guideline Update by the Infectious Diseases Society of America on Complicated Intraabdominal Infections: Diagnostic Imaging of Suspected Acute Cholecystitis and Acute Cholangitis in Adults, Children, and Pregnant People.

This article is part of a clinical practice guideline update on the risk assessment, diagnostic imaging, and microbiological evaluation of complicated intraabdominal infections in adults, children, and pregnant people, developed by the Infectious Diseases Society of America. In this article, the panel provides recommendations for diagnostic imaging of suspected acute cholecystitis and acute cholangitis. The panel's recommendations are based on evidence derived from systematic literature reviews and adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.