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Background: Biopsy-proven breast lesions such as atypical ductal hyperplasia (ADH) or atypical lobular hyperplasia (ALH), lobular carcinoma in situ (LCIS) and flat epithelial atypia (FEA) increase subsequent risk of breast cancer (BC), but long-term risk has not been synthesized. A systematic review was conducted to quantify future risk of breast cancer accounting for time since diagnosis of these high-risk lesions. Methods: A systematic search of literature from 2000 was performed to identify studies reporting BC as an outcome following core-needle or excision biopsy histology diagnosis of ADH, ALH, LCIS, lobular neoplasia (LN) or FEA. Meta-analyses were conducted to estimate cumulative BC incidence at five-yearly intervals following initial diagnosis for each histology type. Results: Seventy studies reporting on 47,671 subjects met eligibility criteria. BC incidence at five years post-diagnosis with a high-risk lesion was estimated to be 9.3 % (95 % CI 6.9–12.5 %) for LCIS, 6.6 % (95 % CI 4.4–9.7 %) for ADH, 9.7 % (95 % CI 5.3–17.2 %) for ALH, 8.6 % (95 % CI 6.5–11.4 %) for LN, and 3.8 % (95 % CI 1.2–11.7 %) for FEA. At ten years post-diagnosis, BC incidence was estimated to be 11.8 % (95 % CI 9.0–15.3 %) for LCIS, 13.9 % (95 % CI 7.8–23.6 %) for ADH, 15.4 % (95 % CI 7.2–29.3 %) for ALH, 17.0 % (95 % CI 7.2–35.3 %) for LN and 7.2 % (95 % CI 2.2–21.2 %) for FEA. Conclusion: Our findings demonstrate increased BC risk sustained over time since initial diagnosis of high-risk breast lesions, varying by lesion type, with relatively less evidence for FEA.

Introduction Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus that causes encephalitis and other morbidity in Southeast Asia. Since February 2022, geographically dispersed JEV human, animal and vector detections occurred on the Australian mainland for the first time. This study will determine the prevalence of JEV-specific antibodies in human blood with a focus on populations at high risk of JEV exposure and determine risk factors associated with JEV seropositivity by location, age, occupation and other factors.Method Samples are collected using two approaches: from routine blood donors (4153 samples), and active collections targeting high-risk populations (convenience sampling). Consent-based sampling for the latter includes a participant questionnaire on demographic, vaccination and exposure data. Samples are tested for JEV-specific total antibody using a defined epitope-blocking ELISA, and total antibody to Australian endemic flaviviruses Murray Valley encephalitis and Kunjin viruses.Analysis Two analytic approaches will occur: descriptive estimates of seroprevalence and multivariable logistic regression using Bayesian hierarchical models. Descriptive analyses will include unadjusted analysis of raw data with exclusions for JEV-endemic country of birth, travel to JEV-endemic countries, prior JEV-vaccination, and sex-standardised and age-standardised analyses. Multivariable logistic regression will determine which risk factors are associated with JEV seropositivity likely due to recent transmission within Australia and the relative contribution of each factor when accounting for effects within the model.Ethics National Mutual Acceptance ethical approval was obtained from the Sydney Children’s Hospitals Network Human Research Ethics Committee (HREC). Local approvals were planned to be sought in each jurisdiction, as per local ethics processes. Ethical approval was also obtained from the Australian Red Cross Lifeblood HREC.Dissemination Findings will be communicated to participants and their communities, and human and animal health stakeholders and policy-makers iteratively and after final analyses. Understanding human infection rates will inform procurement and targeted allocation of limited JEV vaccine, and public health strategies and communication campaigns, to at-risk populations.

Background: Diabetes is a common condition that often requires increasing intensity of glucose lowering regimens. We describe the population trends in the intensity of regimens, and associations of achieved HbA1c and treatment persistence. Methods: We performed an episode-based analysis of the EXTEND-45 dataset, assessing trends in glucose lowering therapy and the associated outcomes of HbA1c and treatment persistence. Trends from 2009 to 2014 were assessed for each intensity level of a glucose lowering therapy regimen, according to the year prescribed. Episodes were defined as the length of time that an individual adhered to a regimen through ongoing prescription, and this was used as to define persistence. Mean HbA1c were calculated for each episode. Persistence and HbA1c were compared across the different regimens of treatment intensity. Results: The intensity of glucose lowering therapy remained stable over time with around one third of episodes utilising a single glucose lowering agent. Mean HbA1c was higher for insulin-based treatment (mean 7.9 % SD = 1.3 %), and lowest for episodes of no glucose lowering treatment (mean 6.3 % (SD = 0.8 %). Around half of participants achieved glycemic targets of 7 %. While there was considerable variation in persistence, the median persistence was around 3 months (94 days, IQR 51–201 days). Conclusions: Therapeutic intensity for diabetes has remained stable over 9 years. Whilst there was considerable variability in persistence with glucose lowering regimens, the mean duration of all regimens was less than a year. Requirement for higher intensity treatment with insulin was related to poorer glycemic control.

BackgroundSepsis is a severe condition associated with extensive morbidity and mortality worldwide. Pediatric, neonatal, and maternal patients represent a considerable proportion of the sepsis burden. Identifying sepsis cases as early as possible is a key pillar of sepsis management and has prompted the development of sepsis identification rules and algorithms that are embedded in computerized clinical decision support (CCDS) systems. ObjectiveThis scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of pediatric, neonatal, and maternal inpatients at risk of sepsis. MethodsMEDLINE, Embase, CINAHL, Cochrane, Latin American and Caribbean Health Sciences Literature (LILACS), Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and ProQuest Dissertations and Theses Global (PQDT) were searched by using a search strategy that incorporated terms for sepsis, clinical decision support, and early detection. Title, abstract, and full-text screening was performed by 2 independent reviewers, who consulted a third reviewer as needed. One reviewer performed data charting with a sample of data. This was checked by a second reviewer and via discussions with the review team, as necessary. ResultsA total of 33 studies were included in this review—13 (39%) pediatric studies, 18 (55%) neonatal studies, and 2 (6%) maternal studies. All studies were published after 2011, and 27 (82%) were published from 2017 onward. The most common outcome investigated in pediatric studies was the accuracy of sepsis identification (9/13, 69%). Pediatric CCDS systems used different combinations of 18 diverse clinical criteria to detect sepsis across the 13 identified studies. In neonatal studies, 78% (14/18) of the studies investigated the Kaiser Permanente early-onset sepsis risk calculator. All studies investigated sepsis treatment and management outcomes, with 83% (15/18) reporting on antibiotics-related outcomes. Usability and cost-related outcomes were each reported in only 2 (6%) of the 31 pediatric or neonatal studies. Both studies on maternal populations were short abstracts. ConclusionsThis review found limited research investigating CCDS systems to support the early detection of sepsis among pediatric, neonatal, and maternal patients, despite the high burden of sepsis in these vulnerable populations. We have highlighted the need for a consensus definition for pediatric and neonatal sepsis and the study of usability and cost-related outcomes as critical areas for future research. International Registered Report Identifier (IRRID)RR2-10.2196/24899

BackgroundSepsis is a significant cause of morbidity and mortality worldwide. Early detection of sepsis followed promptly by treatment initiation improves patient outcomes and saves lives. Hospitals are increasingly using computerized clinical decision support (CCDS) systems for the rapid identification of adult patients with sepsis. ObjectiveThis scoping review aims to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of adult inpatients with sepsis. MethodsThe protocol for this scoping review was previously published. A total of 10 electronic databases (MEDLINE, Embase, CINAHL, the Cochrane database, LILACS [Latin American and Caribbean Health Sciences Literature], Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and PQDT [ProQuest Dissertations and Theses]) were comprehensively searched using terms for sepsis, CCDS, and detection to identify relevant studies. Title, abstract, and full-text screening were performed by 2 independent reviewers using predefined eligibility criteria. Data charting was performed by 1 reviewer with a second reviewer checking a random sample of studies. Any disagreements were discussed with input from a third reviewer. In this review, we present the results for adult inpatients, including studies that do not specify patient age. ResultsA search of the electronic databases retrieved 12,139 studies following duplicate removal. We identified 124 studies for inclusion after title, abstract, full-text screening, and hand searching were complete. Nearly all studies (121/124, 97.6%) were published after 2009. Half of the studies were journal articles (65/124, 52.4%), and the remainder were conference abstracts (54/124, 43.5%) and theses (5/124, 4%). Most studies used a single cohort (54/124, 43.5%) or before-after (42/124, 33.9%) approach. Across all 124 included studies, patient outcomes were the most frequently reported outcomes (107/124, 86.3%), followed by sepsis treatment and management (75/124, 60.5%), CCDS usability (14/124, 11.3%), and cost outcomes (9/124, 7.3%). For sepsis identification, the systemic inflammatory response syndrome criteria were the most commonly used, alone (50/124, 40.3%), combined with organ dysfunction (28/124, 22.6%), or combined with other criteria (23/124, 18.5%). Over half of the CCDS systems (68/124, 54.8%) were implemented alongside other sepsis-related interventions. ConclusionsThe current body of literature investigating the implementation of CCDS systems for the early detection of adult inpatients with sepsis is extremely diverse. There is substantial variability in study design, CCDS criteria and characteristics, and outcomes measured across the identified literature. Future research on CCDS system usability, cost, and impact on sepsis morbidity is needed. International Registered Report Identifier (IRRID)RR2-10.2196/24899

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time.Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001-2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined.Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component.Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

With the rising incidence of type II diabetes mellitus (DM II) worldwide, methods to identify high-risk geographical areas have become increasingly important. In this comprehensive review following Cochrane Collaboration guidelines, we outline spatial methods, outcomes and covariates used in all spatial studies involving outcomes of DM II. A total of 1894 potentially relevant citations were identified. Studies were included if spatial methods were used to explore outcomes of DM II or type I and 2 diabetes combined. Descriptive tables were used to summarize information from included studies. Ten spatial studies conducted in the USA, UK and Europe met selection criteria. Three studies used Bayesian generalized linear mixed modelling (GLMM), three used classic generalized linear modelling, one used classic GLMM, two used geographic information systems mapping tools and one compared case:provider ratios across regions. Spatial studies have been effective in identifying high-risk areas and spatial factors associated with DM II outcomes in the USA, UK and Europe, and would be useful in other parts of the world for allocation of additional services to detect and manage DM II early.

Objectives. We compared postoperative analgesic requirements between women with early stage endometrial cancer treated by total abdominal hysterectomy (TAH) or total laparoscopic hysterectomy (TLH). Methods. 760 patients with apparent stage I endometrial cancer were treated in the international, multicentre, prospective randomised trial (LACE) by TAH (n=353) or TLH (n=407) (2005–2010). Epidural, opioid, and nonopioid analgesic requirements were collected until ten months after surgery. Results. Baseline demographics and analgesic use were comparable between treatment arms. TAH patients were more likely to receive epidural analgesia than TLH patients (33% versus 0.5%, P