Vaccine-induced immune thrombocytopenia and thrombosis (VITT) is a newly recognized syndrome mediated by anti-platelet factor 4 antibodies induced by Covid-19 adenovirus-vectored vaccines including ChAdOx1 nCoV-19 and Ad26.COV2.S. This study validated a proposed Brighton Collaboration case definition for VITT. A data collection form was developed and used to capture the variations in VITT criteria and assess their level of diagnostic certainty from adjudicated positive VITT case datasheets in Germany (n = 71), UK (n = 220), Australia (n = 203), and Taiwan (n = 56). We observed high prevalence of each component of the proposed VITT definition in positive cases (84%-100%), except for the occurrence of thrombosis or thromboembolism criterion in only 34% of VITT cases in Taiwan. The sensitivity of this proposed definition was 100% for Germany and UK, 92% for Australia, and 89% for Taiwan cases. These findings support the validity of this case definition for VITT.

BACKGROUND: Human respiratory syncytial virus (hRSV) is a leading cause of acute lower respiratory tract infection in frail individuals, including children, the elderly and immunocompromised people, with mild to severe symptoms. World Health Organization claims hRSV causes most elderly influenza-like illnesses (ILI) and severe acute respiratory infections (SARI). In this study, different case definitions for hRSV surveillance were examined for accuracy.
METHODS: The following search query (\'Respiratory Syncytial Virus\' OR \'RSV\' OR \'hRSV\' AND \'case definition\') was used on PubMed/MEDLINE and Scopus with a 15-year-old baseline age restriction to conduct a systematic literature review.
RESULTS: Of 12 records, 58% employed the SARI definition, 50% the ILI definition and 42% the acute respiratory infection (ARI) definition, with some overlap. In young adults (18-64 years old), most studies show RSV prevalence between 6.25 and 72.54 cases per 1000 per year, and 19.23 to 98.5 in older adults. The outpatient ARI and hospitalized SARI criteria are particularly sensitive and specific.
CONCLUSIONS: Disease burden measurement requires a clear case definition; however, current literature is questionable. Currently, hRSV surveillance uses numerous case definitions with debatable accuracy. The epidemiology, clinical characteristics, and disease burden of hRSV are difficult to characterize without a standard surveillance case definition.

BACKGROUND: In 2020, the Council of State and Territorial Epidemiologists (CSTE) pertussis case definition was modified; the main change was classifying polymerase chain reaction (PCR)-positive cases as confirmed, regardless of cough duration. Pertussis data reported through Enhanced Pertussis Surveillance (EPS) in 7 sites and the National Notifiable Diseases Surveillance System (NNDSS) were used to evaluate the impact of the new case definition.
METHODS: We compared the number of EPS cases with cough onset in 2020 to the number that would have been reported based on the prior (2014) CSTE case definition. To assess the impact of the change nationally, the proportion of EPS cases newly reportable under the 2020 CSTE case definition was applied to 2020 NNDSS data to estimate how many additional cases were captured nationally.
RESULTS: Among 442 confirmed and probable cases reported to EPS states in 2020, 42 (9.5%) were newly reportable according to the 2020 case definition. Applying this proportion to the 6124 confirmed and probable cases reported nationally in 2020, we estimated that the new definition added 582 cases. Had the case definition not changed, reported cases in 2020 would have decreased by 70% from 2019; the observed decrease was 67%.
CONCLUSIONS: Despite a substantial decrease in reported pertussis cases in the setting of coronavirus disease 2019 (COVID-19), our data show that the 2020 pertussis case definition change resulted in additional case reporting compared with the previous case definition, providing greater opportunities for public health interventions such as prophylaxis of close contacts.

Background: Our aim is to propose a framework for the development of a research case definition of lipedema, based on current available literature and those observations that can be applied to future lipedema research with the intent to standardize and strengthen the scientific evidence base. Methods and Results: We conducted a narrative review of the literature, and identified consensus characteristics and disputed characteristics that could be included in a research case definition of lipedema. After considering the strength of the evidence and how each characteristic might be measured in a research study, we recommended an approach for the development of a research case definition of lipedema that would be based on consideration of five agreed-upon characteristics, and five disputed, or less substantiated, characteristics as additional evidence to enhance specificity. Conclusions: We present a case definition framework for lipedema drawn from the scientific literature that can be applied to future studies on lipedema. Utilizing this framework should help to increase the sensitivity and specificity of case definition and provide an opportunity for meta-analysis of clinical studies and facilitate future research intercomparisons.

Health care-associated infection (HAI) surveillance is vital for safety in health care settings. It helps identify infection risk factors, enhancing patient safety and quality improvement. However, HAI surveillance is complex, demanding specialized knowledge and resources. This study investigates the use of artificial intelligence (AI), particularly generative large language models, to improve HAI surveillance.
We assessed 2 AI agents, OpenAI\'s chatGPT plus (GPT-4) and a Mixtral 8×7b-based local model, for their ability to identify Central Line-Associated Bloodstream Infection (CLABSI) and Catheter-Associated Urinary Tract Infection (CAUTI) from 6 National Health Care Safety Network training scenarios. The complexity of these scenarios was analyzed, and responses were matched against expert opinions.
Both AI models accurately identified CLABSI and CAUTI in all scenarios when given clear prompts. Challenges appeared with ambiguous prompts including Arabic numeral dates, abbreviations, and special characters, causing occasional inaccuracies in repeated tests.
The study demonstrates AI\'s potential in accurately identifying HAIs like CLABSI and CAUTI. Clear, specific prompts are crucial for reliable AI responses, highlighting the need for human oversight in AI-assisted HAI surveillance.
AI shows promise in enhancing HAI surveillance, potentially streamlining tasks, and freeing health care staff for patient-focused activities. Effective AI use requires user education and ongoing AI model refinement.

UNASSIGNED: Enteric infections and their chronic sequelae are a major cause of disability and death. Despite the increasing use of administrative health data in measuring the burden of chronic diseases in the population, there is a lack of validated International Classification of Disease (ICD) code-based case definitions, particularly in the Canadian context. Our objective was to validate ICD code definitions for sequelae of enteric infections in Canada: acute kidney injury (AKI); hemolytic uremic syndrome (HUS); thrombotic thrombocytopenic purpura (TTP); Guillain-Barré syndrome/Miller-Fisher syndrome (GBS/MFS); chronic inflammatory demyelinating polyneuropathy (CIDP); ankylosing spondylitis (AS); reactive arthritis; anterior uveitis; Crohn\'s disease, ulcerative colitis, celiac disease, erythema nodosum (EN); neonatal listeriosis (NL); and Graves\' disease (GD).
UNASSIGNED: We used a multi-step approach by conducting a literature review to identify existing validated definitions, a clinician assessment of the validated definitions, a chart review to verify proposed definitions and a final clinician review. We measured the sensitivity and positive predictive value (PPV) of proposed definitions.
UNASSIGNED: Forty studies met inclusion criteria. We identified validated definitions for 12 sequelae; clinicians developed three (EN, NL, GD). We reviewed 181 charts for 6 sequelae (AKI, HUS, TTP, GBS/MFS, CIDP, AS). Sensitivity (42.8%-100%) and PPV (63.6%-100%) of ICD code definitions varied. Six definitions were modified by clinicians following the chart review (AKI, TTP, GBS/MFS, CIDP, AS, reactive arthritis) to reflect coding practices, increase specificity or sensitivity, and address logistical constraints.
UNASSIGNED: The multi-step design to derive ICD code definitions provided flexibility to identify existing definitions, to improve their sensitivity and PPV and adapt them to the Canadian context.

OBJECTIVE: Although respiratory syncytial virus (RSV) is a leading cause of acute respiratory infections (ARIs), it is unclear which of the case definitions that prompt swab collection predicts RSV best. We aimed to profile RSV-positive adults and to identify possible RSV case definitions.
METHODS: This individual-based pooled analysis was based on influenza-like illness (ILI) surveillance conducted among Italian outpatient adults. All samples were tested for influenza, RSV and other respiratory viruses.
RESULTS: RSV was detected in 5.2% of the 1240 ILI adults tested. The prevalence of fever/feverishness was significantly lower (83.3%) in individuals positive for RSV and those negative for both viruses (79.4%) than in influenza-positive subjects (96.2%). Conversely, 98.3% of RSV-positive adults reported cough. Compared with subjects who tested negative, the adjusted relative risk ratio of cough in RSV-positive subjects was much higher than in influenza-positive subjects (6.89 vs 2.79). Using ARI with cough as the RSV case definition increased specificity.
CONCLUSIONS: As fever/feverishness is more common among influenza than RSV cases, ILI-based surveillance may underestimate RSV incidence in adult outpatients. While broad ARI definitions are useful for routine RSV surveillance, their low specificity may hamper vaccine effectiveness studies. The use of further ARI qualifiers like cough increases specificity.

This report introduces a Brighton Collaboration (BC) case definition for autoimmune hepatitis (AIH), which has been classified as a priority adverse event of special interest (AESI), as there were possible cases seen following COVID-19 vaccination. The case definition was developed by a group of subject matter and BC process experts to facilitate safety data comparability across pre- and post-licensure clinical trials, as well as pharmacovigilance activities in multiple settings with diverse resources and healthcare access. The usual BC case definition development process was followed in an expedited manner, and took two months to complete, including finalising the manuscript for publication, instead of the usual 1 year development time. It includes a systematic review of the literature and an expert consensus to define levels of diagnostic certainty for AIH, and provides specific guidelines for data collection and analysis. Histology, serological and biochemical tests and exclusion of alternate diagnosis were considered necessary to define the levels of certainty (definitive, probable and possible). AEFI reports of suspected AIH were independently classified by the WG members to test its useability and these classifications were used to finalise the case definition. The document underwent peer review by external AIH experts and a Reference Group of vaccine safety stakeholders in high-, low- and middle-income countries to ensure case definition useability, applicability, and scientific integrity. The expedited process can be replicated for development of other standardised case definitions for priority AESIs for endemics and epidemics. While applicable to cases reported following immunisation, the case definition is independent of lapsed time following vaccination and, as such, can also be used to determine background incidence for vaccinated and unvaccinated control groups in studies of causal association. While use of this case definition is also appropriate for the study of safety of other products including drugs, it is not meant to guide clinical case management.

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BackgroundCommunity-associated Clostridioides difficile infections (CA-CDI) have increased worldwide. Patients with CDI-related symptoms occurring < 48 hours after hospitalisation and no inpatient stay 12 weeks prior are classified as CA-CDI, regardless of hospital day attendances 3 months before CDI onset. Healthcare-associated (HA) CDIs include those with symptom onset ≥ 48 hours post hospitalisation.AimTo consider an incubation period more reflective of CDI, and changing healthcare utilisation, we measured how varying surveillance specifications to categorise patients according to their CDI origin resulted in changes in patients\' distribution among CDI origin categories.MethodsNew CDI cases between 2012-2021 from our hospital were reviewed. For patients with CA-CDI, hospital day attendances in the 3 months prior were recorded. CA-CDI patients with hospital day attendances and recently discharged CDI patients (RD-CDI; CDI onset 4-12 weeks after discharge) were combined into a new \'healthcare-exposure\' category (HE-CDI). Time from hospitalisation to disease onset was varied and the midpoint between optimal and balanced cut-offs was used instead of 48 hours to categorise HA-CDI.ResultsOf 1,047 patients, 801 (76%) were HA-CDI, 205 (20%) CA-CDI and 41 (4%) were RD-CDI. Of the CA-CDI cohort, 45 (22%) met recent HE-CDI criteria and, when reassigned, reduced CA-CDI to 15%. Sensitivity analysis indicated a day 4 cut-off for assigning HA-CDI. Applying this led to 46 HA-CDI reassigned as CA-CDI. Applying both HE and day 4 criteria led to 72% HA-CDI, 20% CA-CDI, and 8% HE-CDI (previously RD-CDI).ConclusionCDI surveillance specifications reflecting healthcare exposure and an incubation period more characteristic of C. difficile may improve targeted CDI prevention interventions.