Renal Pathology of Ciliopathies.

Renal ciliopathies are a group of genetic disorders that affect the function of the primary cilium in the kidney, as well as other organs. Since primary cilia are important for regulation of cell signaling pathways, ciliary dysfunction results in a range of clinical manifestations, including renal failure, cyst formation, and hypertension. We summarize the current understanding of the pathophysiological and pathological features of renal ciliopathies in childhood, including autosomal dominant and recessive polycystic kidney disease, nephronophthisis, and Bardet-Biedl syndrome, as well as skeletal dysplasia associated renal ciliopathies. The genetic basis of these disorders is now well-established in many cases, with mutations in a large number of cilia-related genes such as PKD1, PKD2, BBS, MKS, and NPHP being responsible for the majority of cases. Renal ciliopathies are broadly characterized by development of interstitial fibrosis and formation of multiple renal cysts which gradually enlarge and replace normal renal tissue, with each condition demonstrating subtle differences in the degree, location, and age-related development of cysts and fibrosis. Presentation varies from prenatal diagnosis of congenital multisystem syndromes to an asymptomatic childhood with development of complications in later adulthood and therefore clinicopathological correlation is important, including increasing use of targeted genetic testing or whole genome sequencing, allowing greater understanding of genetic pathophysiological mechanisms.

Body weight-based iodinated contrast immersion timing for human fetal postmortem microfocus computed tomography.

Objectives: The aim of this study was to evaluate the length of time required to achieve full iodination using potassium tri-iodide as a contrast agent, prior to human fetal postmortem microfocus computed tomography (micro-CT) imaging. Methods: Prospective assessment of optimal contrast iodination was conducted across 157 human fetuses (postmortem weight range 2-298 g; gestational age range 12-37 weeks), following micro-CT imaging. Simple linear regression was conducted to analyse which fetal demographic factors could produce the most accurate estimate for optimal iodination time. Results: Postmortem body weight (r2 = 0.6435) was better correlated with iodination time than gestational age (r2 = 0.1384), producing a line of best fit, y = [0.0304 × body weight (g)] - 2.2103. This can be simplified for clinical use whereby immersion time (days) = [0.03 × body weight (g)] - 2.2. Using this formula, for example, a 100-g fetus would take 5.2 days to reach optimal contrast enhancement. Conclusions: The simplified equation can now be used to provide estimation times for fetal contrast preparation time prior to micro-CT imaging and can be used to manage service throughput and parental expectation for return of their fetus. Advances in knowledge: A simple equation from empirical data can now be used to estimate preparation time for human fetal postmortem micro-CT imaging.

The value of standards for health datasets in artificial intelligence-based applications.

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative).

Maternal PlGF and umbilical Dopplers predict pregnancy outcomes at diagnosis of early-onset fetal growth restriction.

BACKGROUNDSevere, early-onset fetal growth restriction (FGR) causes significant fetal and neonatal mortality and morbidity. Predicting the outcome of affected pregnancies at the time of diagnosis is difficult, thus preventing accurate patient counseling. We investigated the use of maternal serum protein and ultrasound measurements at diagnosis to predict fetal or neonatal death and 3 secondary outcomes: fetal death or delivery at or before 28+0 weeks, development of abnormal umbilical artery (UmA) Doppler velocimetry, and slow fetal growth.METHODSWomen with singleton pregnancies (n = 142, estimated fetal weights [EFWs] below the third centile, less than 600 g, 20+0 to 26+6 weeks of gestation, no known chromosomal, genetic, or major structural abnormalities) were recruited from 4 European centers. Maternal serum from the discovery set (n = 63) was analyzed for 7 proteins linked to angiogenesis, 90 additional proteins associated with cardiovascular disease, and 5 proteins identified through pooled liquid chromatography and tandem mass spectrometry. Patient and clinician stakeholder priorities were used to select models tested in the validation set (n = 60), with final models calculated from combined data.RESULTSThe most discriminative model for fetal or neonatal death included the EFW z score (Hadlock 3 formula/Marsal chart), gestational age, and UmA Doppler category (AUC, 0.91; 95% CI, 0.86-0.97) but was less well calibrated than the model containing only the EFW z score (Hadlock 3/Marsal). The most discriminative model for fetal death or delivery at or before 28+0 weeks included maternal serum placental growth factor (PlGF) concentration and UmA Doppler category (AUC, 0.89; 95% CI, 0.83-0.94).CONCLUSIONUltrasound measurements and maternal serum PlGF concentration at diagnosis of severe, early-onset FGR predicted pregnancy outcomes of importance to patients and clinicians.TRIAL REGISTRATIONClinicalTrials.gov NCT02097667.FUNDINGThe European Union, Rosetrees Trust, Mitchell Charitable Trust.

Use of super resolution reconstruction MRI for surgical planning in Placenta accreta spectrum disorder: Case series.

INTRODUCTION: Comprehensive imaging using ultrasound and MRI of placenta accreta spectrum (PAS) aims to prevent catastrophic haemorrhage and maternal death. Standard MRI of the placenta is limited by between-slice motion which can be mitigated by super-resolution reconstruction (SRR) MRI. We applied SRR in suspected PAS cases to determine its ability to enhance anatomical placental assessment and predict adverse maternal outcome. METHODS: Suspected PAS patients (n = 22) underwent MRI at a gestational age (weeks + days) of (32+3±3+2, range (27+1-38+6)). SRR of the placental-myometrial-bladder interface involving rigid motion correction of acquired MRI slices combined with robust outlier detection to reconstruct an isotropic high-resolution volume, was achieved in twelve. 2D MRI or SRR images alone, and paired data were assessed by four radiologists in three review rounds. All radiologists were blinded to results of the ultrasound, original MR image reports, case outcomes, and PAS diagnosis. A Random Forest Classification model was used to highlight the most predictive pathological MRI markers for major obstetric haemorrhage (MOH), bladder adherence (BA), and placental attachment depth (PAD). RESULTS: At delivery, four patients had placenta praevia with no abnormal attachment, two were clinically diagnosed with PAS, and six had histopathological PAS confirmation. Pathological MRI markers (T2-dark intraplacental bands, and loss of retroplacental T2-hypointense line) predicting MOH were more visible using SRR imaging (accuracy 0.73), in comparison to 2D MRI or paired imaging. Bladder wall interruption, predicting BA, was only easily detected by paired imaging (accuracy 0.72). Better detection of certain pathological markers predicting PAD was found using 2D MRI (placental bulge and myometrial thinning (accuracy 0.81)), and SRR (loss of retroplacental T2-hypointense line (accuracy 0.82)). DISCUSSION: The addition of SRR to 2D MRI potentially improved anatomical assessment of certain pathological MRI markers of abnormal placentation that predict maternal morbidity which may benefit surgical planning.

Evaluation of the feasibility, diagnostic yield, and clinical utility of rapid genome sequencing in infantile epilepsy (Gene-STEPS): an international, multicentre, pilot cohort study.

BACKGROUND: Most neonatal and infantile-onset epilepsies have presumed genetic aetiologies, and early genetic diagnoses have the potential to inform clinical management and improve outcomes. We therefore aimed to determine the feasibility, diagnostic yield, and clinical utility of rapid genome sequencing in this population. METHODS: We conducted an international, multicentre, cohort study (Gene-STEPS), which is a pilot study of the International Precision Child Health Partnership (IPCHiP). IPCHiP is a consortium of four paediatric centres with tertiary-level subspecialty services in Australia, Canada, the UK, and the USA. We recruited infants with new-onset epilepsy or complex febrile seizures from IPCHiP centres, who were younger than 12 months at seizure onset. We excluded infants with simple febrile seizures, acute provoked seizures, known acquired cause, or known genetic cause. Blood samples were collected from probands and available biological parents. Clinical data were collected from medical records, treating clinicians, and parents. Trio genome sequencing was done when both parents were available, and duo or singleton genome sequencing was done when one or neither parent was available. Site-specific protocols were used for DNA extraction and library preparation. Rapid genome sequencing and analysis was done at clinically accredited laboratories, and results were returned to families. We analysed summary statistics for cohort demographic and clinical characteristics and the timing, diagnostic yield, and clinical impact of rapid genome sequencing. FINDINGS: Between Sept 1, 2021, and Aug 31, 2022, we enrolled 100 infants with new-onset epilepsy, of whom 41 (41%) were girls and 59 (59%) were boys. Median age of seizure onset was 128 days (IQR 46-192). For 43 (43% [binomial distribution 95% CI 33-53]) of 100 infants, we identified genetic diagnoses, with a median time from seizure onset to rapid genome sequencing result of 37 days (IQR 25-59). Genetic diagnosis was associated with neonatal seizure onset versus infantile seizure onset (14 [74%] of 19 vs 29 [36%] of 81; p=0·0027), referral setting (12 [71%] of 17 for intensive care, 19 [44%] of 43 non-intensive care inpatient, and 12 [28%] of 40 outpatient; p=0·0178), and epilepsy syndrome (13 [87%] of 15 for self-limited epilepsies, 18 [35%] of 51 for developmental and epileptic encephalopathies, 12 [35%] of 34 for other syndromes; p=0·001). Rapid genome sequencing revealed genetic heterogeneity, with 34 unique genes or genomic regions implicated. Genetic diagnoses had immediate clinical utility, informing treatment (24 [56%] of 43), additional evaluation (28 [65%]), prognosis (37 [86%]), and recurrence risk counselling (all cases). INTERPRETATION: Our findings support the feasibility of implementation of rapid genome sequencing in the clinical care of infants with new-onset epilepsy. Longitudinal follow-up is needed to further assess the role of rapid genetic diagnosis in improving clinical, quality-of-life, and economic outcomes. FUNDING: American Academy of Pediatrics, Boston Children's Hospital Children's Rare Disease Cohorts Initiative, Canadian Institutes of Health Research, Epilepsy Canada, Feiga Bresver Academic Foundation, Great Ormond Street Hospital Charity, Medical Research Council, Murdoch Children's Research Institute, National Institute of Child Health and Human Development, National Institute for Health and Care Research Great Ormond Street Hospital Biomedical Research Centre, One8 Foundation, Ontario Brain Institute, Robinson Family Initiative for Transformational Research, The Royal Children's Hospital Foundation, University of Toronto McLaughlin Centre.

Identification of bacterial pathogens in sudden unexpected death in infancy and childhood using 16S rRNA gene sequencing.

Background: Sudden unexpected death in infancy (SUDI) is the most common cause of post-neonatal death in the developed world. Following an extensive investigation, the cause of ~40% of deaths remains unknown. It is hypothesized that a proportion of deaths are due to an infection that remains undetected due to limitations in routine techniques. This study aimed to apply 16S rRNA gene sequencing to post-mortem (PM) tissues collected from cases of SUDI, as well as those from the childhood equivalent (collectively known as sudden unexpected death in infancy and childhood or SUDIC), to investigate whether this molecular approach could help identify potential infection-causing bacteria to enhance the diagnosis of infection. Methods: In this study, 16S rRNA gene sequencing was applied to de-identified frozen post-mortem (PM) tissues from the diagnostic archive of Great Ormond Street Hospital. The cases were grouped depending on the cause of death: (i) explained non-infectious, (ii) infectious, and (iii) unknown. Results and conclusions: In the cases of known bacterial infection, the likely causative pathogen was identified in 3/5 cases using bacterial culture at PM compared to 5/5 cases using 16S rRNA gene sequencing. Where a bacterial infection was identified at routine investigation, the same organism was identified by 16S rRNA gene sequencing. Using these findings, we defined criteria based on sequencing reads and alpha diversity to identify PM tissues with likely infection. Using these criteria, 4/20 (20%) cases of unexplained SUDIC were identified which may be due to bacterial infection that was previously undetected. This study demonstrates the potential feasibility and effectiveness of 16S rRNA gene sequencing in PM tissue investigation to improve the diagnosis of infection, potentially reducing the number of unexplained deaths and improving the understanding of the mechanisms involved.

Less-invasive autopsy for early pregnancy loss.

Autopsy investigations provide valuable information regarding fetal death that can assist in the parental bereavement process, and influence future pregnancies, but conventional autopsy is often declined by parents because of its invasive approach. This has led to the development of less-invasive autopsy investigations based on imaging technology to provide a more accessible and acceptable choice for parents when investigating their loss. Whilst the development and use of more conventional clinical imaging techniques (radiographs, CT, MRI, US) are well described in the literature for fetuses over 20 weeks of gestational age, these investigations have limited diagnostic accuracy in imaging smaller fetuses. Techniques such as ultra-high-field MRI (>3T) and micro-focus computed tomography have been shown to have higher diagnostic accuracy whilst still being acceptable to parents. By further developing and increasing the availability of these more innovative imaging techniques, parents will be provided with a greater choice of acceptable options to investigate their loss, which may in turn increase their uptake. We provide a narrative review focussing on the development of high-resolution, non-invasive imaging techniques to evaluate early gestational pregnancy loss.

Routine placental histopathology findings from women testing positive for SARS-CoV-2 during pregnancy: Retrospective cohort comparative study.

OBJECTIVE: To assess the impact of maternal Coronavirus disease 2019 (COVID-19) infection on placental histopathological findings in an unselected population and evaluate the potential effect on the fetus, including the possibility of vertical transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). DESIGN: Retrospective cohort comparative study of placental histopathological findings in patients with COVID-19, compared with controls. SETTING: During the COVID-19 pandemic, placentas were studied from women at University College Hospital London who reported and/or tested positive for COVID-19. POPULATION: Of 10 508 deliveries, 369 (3.5%) women had COVID-19 during pregnancy, with placental histopathology available for 244 women. METHODS: Retrospective review of maternal and neonatal characteristics, where placental analysis had been performed. This was compared with available, previously published, histopathological findings from placentas of unselected women. MAIN OUTCOME MEASURES: Frequency of placental histopathological findings and relevant clinical outcomes. RESULTS: Histological abnormalities were reported in 117 of 244 (47.95%) cases, with the most common diagnosis being ascending maternal genital tract infection. There was no statistically significant difference in the frequency of most abnormalities compared with controls. There were four cases of COVID-19 placentitis (1.52%, 95% CI 0.04%-3.00%) and one possible congenital infection, with placental findings of acute maternal genital tract infection. The rate of fetal vascular malperfusion (FVM), at 4.5%, was higher compared with controls (p = 0.00044). CONCLUSIONS: In most cases, placentas from pregnant women infected with SARS-CoV-2 virus do not show a significantly increased frequency of pathology. Evidence for transplacental transmission of SARS-CoV-2 is lacking from this cohort. There is a need for further study into the association between FVM, infection and diabetes.

Rapid desensitization through immunoadsorption during cardiopulmonary bypass. A novel method to facilitate human leukocyte antigen incompatible heart transplantation.

BACKGROUND: Anti-human leukocyte antigen (HLA)-antibody production represents a major barrier to heart transplantation, limiting recipient compatibility with potential donors and increasing the risk of complications with poor waiting-list outcomes. Currently there is no consensus to when desensitization should take place, and through what mechanism, meaning that sensitized patients must wait for a compatible donor for many months, if not years. We aimed to determine if intraoperative immunoadsorption could provide a potential desensitization methodology. METHODS: Anti-HLA antibody-containing whole blood was added to a Cardiopulmonary bypass (CPB) circuit set up to mimic a 20 kg patient undergoing heart transplantation. Plasma was separated and diverted to a standalone, secondary immunoadsorption system, with antibody-depleted plasma returned to the CPB circuit. Samples for anti-HLA antibody definition were taken at baseline, when combined with the CPB prime (on bypass), and then every 20 min for the duration of treatment (total 180 min). RESULTS: A reduction in individual allele median fluorescence intensity (MFI) to below clinically relevant levels (<1000 MFI), and in the majority of cases below the lower positive detection limit (<500 MFI), even in alleles with a baseline MFI >4000 was demonstrated. Reduction occurred in all cases within 120 min, demonstrating efficacy in a time period usual for heart transplantation. Flowcytometric crossmatching of suitable pseudo-donor lymphocytes demonstrated a change from T cell and B cell positive channel shifts to negative, demonstrating a reduction in binding capacity. CONCLUSIONS: Intraoperative immunoadsorption in an ex vivo setting demonstrates clinically relevant reductions in anti-HLA antibodies within the normal timeframe for heart transplantation. This method represents a potential desensitization technique that could enable sensitized children to accept a donor organ earlier, even in the presence of donor-specific anti-HLA antibodies.

Engaging children and young people on the potential role of artificial intelligence in medicine.

INTRODUCTION: There is increasing interest in Artificial Intelligence (AI) and its application to medicine. Perceptions of AI are less well-known, notably amongst children and young people (CYP). This workshop investigates attitudes towards AI and its future applications in medicine and healthcare at a specialised paediatric hospital using practical design scenarios. METHOD: Twenty-one members of a Young Persons Advisory Group for research contributed to an engagement workshop to ascertain potential opportunities, apprehensions, and priorities. RESULTS: When presented as a selection of practical design scenarios, we found that CYP were more open to some applications of AI in healthcare than others. Human-centeredness, governance and trust emerged as early themes, with empathy and safety considered as important when introducing AI to healthcare. Educational workshops with practical examples using AI to help, but not replace humans were suggested to address issues, build trust, and effectively communicate about AI. CONCLUSION: Whilst policy guidelines acknowledge the need to include children and young people to develop AI, this requires an enabling environment for human-centred AI involving children and young people with lived experiences of healthcare. Future research should focus on building consensus on enablers for an intelligent healthcare system designed for the next generation, which fundamentally, allows co-creation. IMPACT: Children and young people (CYP) want to be included to share their insights about the development of research on the potential role of Artificial Intelligence (AI) in medicine and healthcare and are more open to some applications of AI than others. Whilst it is acknowledged that a research gap on involving and engaging CYP in developing AI policies exists, there is little in the way of pragmatic and practical guidance for healthcare staff on this topic. This requires research on enabling environments for ongoing digital cooperation to identify and prioritise unmet needs in the application and development of AI.

Oxygen delivery in pediatric cardiac surgery and its association with acute kidney injury using machine learning.

OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CPB) is a frequently reported complication. In this study we aimed to determine the oxygen delivery indexed to body surface area (Do2i) threshold associated with postoperative AKI in pediatric patients during CPB, and whether it remains clinically important in the context of other known independent risk factors. METHODS: A single-institution, retrospective study, encompassing 396 pediatric patients, who underwent heart surgery between April 2019 and April 2021 was undertaken. Time spent below Do2i thresholds were compared to determine the critical value for all stages of AKI occurring within 48 hours of surgery. Do2i threshold was then included in a classification analysis with known risk factors including nephrotoxic drug usage, surgical complexity, intraoperative data, comorbidities and ventricular function data, and vasoactive inotrope requirement to determine Do2i predictive importance. RESULTS: Logistic regression models showed cumulative time spent below a Do2i value of 350 mL/min/m2 was associated with AKI. Random forest models, incorporating established risk factors, showed Do2i threshold still maintained predictive importance. Patients who developed post-CPB AKI were younger, had longer CPB and ischemic times, and required higher inotrope support postsurgery. CONCLUSIONS: The present data support previous findings that Do2i during CPB is an independent risk factor for AKI development in pediatric patients. Furthermore, the data support previous suggestions of a higher threshold value in children compared with that in adults and indicate that adjustments in Do2i management might reduce incidence of postoperative AKI in the pediatric cardiac surgery population.

Intraoperative Needle Tip Tracking with an Integrated Fibre-Optic Ultrasound Sensor.

Ultrasound is an essential tool for guidance of many minimally-invasive surgical and interventional procedures, where accurate placement of the interventional device is critical to avoid adverse events. Needle insertion procedures for anaesthesia, fetal medicine and tumour biopsy are commonly ultrasound-guided, and misplacement of the needle may lead to complications such as nerve damage, organ injury or pregnancy loss. Clear visibility of the needle tip is therefore critical, but visibility is often precluded by tissue heterogeneities or specular reflections from the needle shaft. This paper presents the in vitro and ex vivo accuracy of a new, real-time, ultrasound needle tip tracking system for guidance of fetal interventions. A fibre-optic, Fabry-Pérot interferometer hydrophone is integrated into an intraoperative needle and used to localise the needle tip within a handheld ultrasound field. While previous, related work has been based on research ultrasound systems with bespoke transmission sequences, the new system-developed under the ISO 13485 Medical Devices quality standard-operates as an adjunct to a commercial ultrasound imaging system and therefore provides the image quality expected in the clinic, superimposing a cross-hair onto the ultrasound image at the needle tip position. Tracking accuracy was determined by translating the needle tip to 356 known positions in the ultrasound field of view in a tank of water, and by comparison to manual labelling of the the position of the needle in B-mode US images during an insertion into an ex vivo phantom. In water, the mean distance between tracked and true positions was 0.7 ± 0.4 mm with a mean repeatability of 0.3 ± 0.2 mm. In the tissue phantom, the mean distance between tracked and labelled positions was 1.1 ± 0.7 mm. Tracking performance was found to be independent of needle angle. The study demonstrates the performance and clinical compatibility of ultrasound needle tracking, an essential step towards a first-in-human study.

Establishing risk factors and outcomes for congenital hypothyroidism with gland in situ using population-based data linkage methods: study protocol.

INTRODUCTION: There has been an increase in the birth prevalence of congenital hypothyroidism (CH) since the introduction of newborn screening, both globally and in the UK. This increase can be accounted for by an increase in CH with gland in situ (CH-GIS). It is not known why CH-GIS is becoming more common, nor how it affects the health, development and learning of children over the long term. Our study will use linked administrative health, education and clinical data to determine risk factors for CH-GIS and describe long-term health and education outcomes for affected children. METHODS AND ANALYSIS: We will construct a birth cohort study based on linked, administrative data to determine what factors have contributed to the increase in the birth prevalence of CH-GIS in the UK. We will also set up a follow-up study of cases and controls to determine the health and education outcomes of children with and without CH-GIS. We will use logistic/multinomial regression models to establish risk factors for CH-GIS. Changes in the prevalence of risk factors over time will help to explain the increase in birth prevalence of CH-GIS. Multivariable generalised linear models or Cox proportional hazards regression models will be used to assess the association between type of CH and school performance or health outcomes. ETHICS AND DISSEMINATION: This study has been approved by the London Queen Square Research Ethics Committee and the Health Research Authority's Confidentiality Advisory Group CAG. Approvals are also being sought from each data provider. Obtaining approvals from CAG, data providers and information governance bodies have caused considerable delays to the project. Our methods and findings will be published in peer-reviewed journals and presented at academic conferences.

Machine learning forecasting for COVID-19 pandemic-associated effects on paediatric respiratory infections.

OBJECTIVE: The COVID-19 pandemic and subsequent government restrictions have had a major impact on healthcare services and disease transmission, particularly those associated with acute respiratory infection. This study examined non-identifiable routine electronic patient record data from a specialist children's hospital in England, UK, examining the effect of pandemic mitigation measures on seasonal respiratory infection rates compared with forecasts based on open-source, transferable machine learning models. METHODS: We performed a retrospective longitudinal study of respiratory disorder diagnoses between January 2010 and February 2022. All diagnoses were extracted from routine healthcare activity data and diagnosis rates were calculated for several diagnosis groups. To study changes in diagnoses, seasonal forecast models were fit to prerestriction period data and extrapolated. RESULTS: Based on 144 704 diagnoses from 31 002 patients, all but two diagnosis groups saw a marked reduction in diagnosis rates during restrictions. We observed 91%, 89%, 72% and 63% reductions in peak diagnoses of 'respiratory syncytial virus', 'influenza', 'acute nasopharyngitis' and 'acute bronchiolitis', respectively. The machine learning predictive model calculated that total diagnoses were reduced by up to 73% (z-score: -26) versus expected during restrictions and increased by up to 27% (z-score: 8) postrestrictions. CONCLUSIONS: We demonstrate the association between COVID-19 related restrictions and significant reductions in paediatric seasonal respiratory infections. Moreover, while many infection rates have returned to expected levels postrestrictions, others remain supressed or followed atypical winter trends. This study further demonstrates the applicability and efficacy of routine electronic record data and cross-domain time-series forecasting to model, monitor, analyse and address clinically important issues.

Artificial intelligence for radiological paediatric fracture assessment: a systematic review.

BACKGROUND: Majority of research and commercial efforts have focussed on use of artificial intelligence (AI) for fracture detection in adults, despite the greater long-term clinical and medicolegal implications of missed fractures in children. The objective of this study was to assess the available literature regarding diagnostic performance of AI tools for paediatric fracture assessment on imaging, and where available, how this compares with the performance of human readers. MATERIALS AND METHODS: MEDLINE, Embase and Cochrane Library databases were queried for studies published between 1 January 2011 and 2021 using terms related to 'fracture', 'artificial intelligence', 'imaging' and 'children'. Risk of bias was assessed using a modified QUADAS-2 tool. Descriptive statistics for diagnostic accuracies were collated. RESULTS: Nine eligible articles from 362 publications were included, with most (8/9) evaluating fracture detection on radiographs, with the elbow being the most common body part. Nearly all articles used data derived from a single institution, and used deep learning methodology with only a few (2/9) performing external validation. Accuracy rates generated by AI ranged from 88.8 to 97.9%. In two of the three articles where AI performance was compared to human readers, sensitivity rates for AI were marginally higher, but this was not statistically significant. CONCLUSIONS: Wide heterogeneity in the literature with limited information on algorithm performance on external datasets makes it difficult to understand how such tools may generalise to a wider paediatric population. Further research using a multicentric dataset with real-world evaluation would help to better understand the impact of these tools.

Causes of Sudden Unexpected Death in Childhood: Autopsy Findings from a Specialist Centre.

OBJECTIVES: To investigate the aetiologies of sudden unexpected death from natural causes in children aged 1-18 years by retrospective examination of autopsy records from a single centre. MATERIALS AND METHODS: The post-mortem findings from 548 children (1996-2015) were examined. Details were entered into an established research database and categorized according to >400 pre-defined criteria. RESULTS: There were 265 previously apparently healthy children and 283 with pre-existing, potentially life-limiting, conditions. There were more males than females (M:F 1.4:1), and deaths were more frequent in the winter. Infection was commonest accounting for 43% of all deaths. Non-infectious diseases were identified as cause of death in 28%, and 29% of all deaths were unexplained. There was no significant difference in the proportions of deaths in each category between the previously healthy children and those with pre-existing conditions. CONCLUSION: Sudden unexpected death is a rare presentation of death in childhood and those with pre-existing conditions may be more at risk. Standardisation of the post-mortem procedure in such cases may result in more ancillary investigations performed as routine and may reduce the number of cases that are 'unexplained'.

Intussusception and COVID-19 in Infants: Evidence for an Etiopathologic Correlation.

Nonrespiratory conditions related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been largely described. Ileocolic intussusception has been reported in association with SARS-CoV-2 infection in 10 children, raising the possibility of an etiopathologic role for the virus, but none of these cases documented tissue pathology that would have supported SARS-CoV-2 intestinal inflammation. We report 2 cases of intussusception in patients with SARS-CoV-2 infection who were treated at different pediatric tertiary centers in Europe and provide evidence of the presence of the virus in mesenteric and intestinal tissues of the patients.