An increased risk of intussusception has been reported following rotavirus vaccination. We sought to determine whether introduction of rotavirus vaccination in England in July 2013 was associated ...with a change in the burden of total and age group-specific childhood hospital admissions for intussusception.
We identified all children aged 0–36 months admitted to hospitals in England with intussusception using the Hospital Episode Statistics dataset. We performed a retrospective ecological analysis comparing hospital admission rates for intussusception during the periods before (2008/2009–2012/2013) and after (2014/2015–2017/2018) introduction of rotavirus vaccination using modified Poisson regression and interrupted time series analysis. Length of hospital stay and clinical outcomes were also examined.
The mean annual admission rate for intussusception in infants over the ten-year study period was 31.5 per 100,000 person-years. An increase in the admission rate in the 8–16 weeks age group (RR 1.46, 95% CI 1.12–1.91), those receiving vaccination, was compensated for by decreases in the 17–24 weeks (RR 0.77, 0.63–0.94), 25–32 weeks (RR 0.71, 0.59–0.86) and 41–52 weeks (RR 0.80, 0.66–0.98) age groups. Using interrupted time series analysis, we observed a significant decrease in incidence in the 0–12 months age group (RR 0.80, 0.67–0.96), but not in the overall 0–36 months age group (RR 1.09, 0.98–1.20). There was no significant change in the proportion of children requiring surgical intervention or with major complications of intussusception. Length of hospital stay decreased among infants receiving surgery for intussusception.
Our results suggest that introduction of rotavirus vaccination in England has resulted in a downward shift in the age at which intussusception occurs in infants, with no overall increase in hospital admission rate or disease severity. These findings support the view that the benefits of rotavirus vaccination outweigh the small increased risk of intussusception in the early post-vaccination period.
IntroductionWhile still a ubiquitous disease of childhood, chickenpox has been effectively controlled in many countries through the use of vaccination. Previous health economic assessment of the use ...of these vaccines in the UK were based on limited quality of life data and only routinely collected epidemiological outcomes.Methods and analysisThis two armed study will carry prospective surveillance of hospital admissions and recruit from community settings to measure the acute quality of life loss caused by paediatric chickenpox both in the UK and in Portugal. The quality of life effects on children and their primary and secondary caregivers will be assessed using the EuroQol EQ-5D with the Child Health Utility instrument (CHU-9) in addition for children. Results will be used to derive quality-adjusted life year loss estimates for cases of simple varicella and the secondary complications.Ethics and disseminationWe have received National Health Service ethical approval (REC ref: 18/ES/0040) for the inpatient arm, university ethical approval (University of Bristol ref: 60721) for the community arm and 10 sites currently are recruiting in the UK and 14 in Portugal. Informed consent is obtained from the parent(s). Results will be disseminated in peer-reviewed publications.Trial registration numberISRCTN15017985.
ObjectiveEstimating weight is essential in order to prepare appropriate sized equipment and doses of resuscitation drugs in cases where children are critically ill or injured. Many methods exist with ...varying degrees of complexity and accuracy. The most recent version of the Advanced Paediatric Life Support (APLS) course has changed their teaching from an age-based calculation method to the use of a reference table. We aimed to evaluate the potential implications of this change.MethodUsing a bespoke online simulation platform we assessed the ability of acute paediatric staff to apply different methods of weight estimation. Comparing the time taken, rate and magnitude of errors were made using the APLS single and triple age-based formulae, Best Guess and reference table methods. To add urgency and an element of cognitive stress, a time-based competitive component was included.Results57 participants performed a total of 2240 estimates of weight. The reference table was the fastest (25 (22–28) vs 35 (31–38) to 48 (43–51) s) and most preferred, but errors were made using all methods. There was no significant difference in the percentage accuracy between methods (93%–97%) but the magnitude of errors made was significantly smaller using the three APLS formulae 10% (6.5–21) compared with reference table (69% (34–133)) mainly from month/year table confusion.ConclusionIn this exploratory study under psychological stress none of the methods of weight estimation were free from error. Reference tables were the fastest method and also had the largest errors and should be designed to minimise the risk of picking errors.
Improved sensitivity and efficiency of detection and quantification of carriage of Neisseria meningitidis (Nm) in young people is important for evaluation of the impact of vaccines upon transmission ...and associated population-wide effects. Saliva collection is quick, non-invasive and facilitates frequent sampling, but has been reported to yield low sensitivity by culture. We re-evaluated this approach in a follow-up cross sectional study using direct and culture-amplified PCR.
In April 2016 we collected paired oropharyngeal swabs (OPS) and saliva samples from 1005 healthy students in Portugal into STGG broth and stored them at -80°C until DNA extraction and batched qPCR analysis. Samples were also cultured on GC agar plates for 72h and PCR done on DNA extracts from overall growth. Nm isolates were also sought from a selection of 50 samples. qPCR amplification targets were superoxide dismutase sodC and capsular locus/genogroup-specific genes (B, C, W, X and Y) and, for cultured isolates only, porA. Cycle threshold values of ≤36 were considered positive.
556 tests (460 samples, 363 subjects, 36.1%) were positive for Nm (sodC) and 65 (45, 36, 3.6%) for MenB. More salivas were positive by direct sodC qPCR (211, 21.0%) than OPS (126, 12.5%) but fewer were positive by culture-amplified qPCR (94 vs. 125). For both sample types, many that were negative on direct qPCR came positive on culture-amplification and Nm was consistently isolated from salivas in which culture amplified the PCR signal. Using both methods on both samples yielded 36.1% Nm and 5.5% encapsulated Nm carriage rates while direct qPCR on OPS alone detected 12.5% and 2.2%.
Detectable MenB carriage rates (2.9%) were lower than 4 years earlier (6.8%) in this population (p = 0.0003). Viable meningococci were often present in saliva. Although evidence of encapsulated Nm was less frequent in saliva than OPS, collection is more acceptable to subjects allowing more frequent sampling. Use of culture-amplification increases detection sensitivity in both sample types, especially when combined with direct PCR. Combining these samples and/or methodologies could greatly enhance the power of carriage studies to detect the impact of vaccines upon carriage and transmission.
Infectious diarrhoea is a common disease of childhood. It is estimated to be responsible for over 1.3 million deaths per year, predominantly in resource-poor countries. In wealthy nations, it causes ...significant morbidity, healthcare burden and associated cost. In both scenarios, the most common cause is rotavirus. This article reviews the experience of primary prevention of rotavirus disease through immunisation and considers the case for extending vaccine use further in Europe and globally.
ObjectivesIn our tertiary paediatric emergency department children waiting over 12 hours after a decision to admit (’12 hour trolley breech’) was previously a near ‘never event’, with only 2 between ...2015 and 2020. In the post-pandemic period NHS performance has increasingly struggled.1 For many departments – including our own – 12hr breeches have become a daily occurrence. Logging and reporting these episodes is a core part of our governance, safety and quality processes. But in contrast to our separate ‘adult’ department, we have limited administrative and non-clinical support. Datix2 reporting became a large burden for our clinical team to complete, often staying post shift to complete forms, or with some episodes going unreported. As this information was already electronically captured, we attempted to develop a more efficient process.MethodsUsing the free opensource R3 and RSelenium package4 we developed code to check our EPR (CareFlow) to identify if, when and how many 12hr breeches had occurred then without user-intervention – complete and submit the appropriate Datix form, link to the risk-register, and close it. We estimated how much time the Datix ‘robot’ saved and if there were other safety/performance issues it could process.ResultsBetween Oct 22-Jan 23 there were 284 12hr breeches in our children’s emergency department. Timing experienced nurses, we found identification and entry for each, when done manually was a simple but monotonous task taking >10 minutes per form (plus frequent coffee breaks!). Reporting and closing them automatically using ‘the robot’ saved a minimum of 47 hours of clinical time. Further iterations of ‘the robot’ were developed to submit daily performance Datix reports highlighting when we had not achieved our internal standards: of time to triage; time to assessment; crowding; and exit block – again linked as evidence against our risk-register. Further adaptations to the robot will report nurse:patient ratios and the new 12hrs since arrival breech.ConclusionAutomating the completion of Datix forms recording 12hr breeches in the emergency department has successfully raised the visibility of our most significant performance challenges and increased scrutiny of divisional performance within our Trust. Using this technique has levelled the playing field to allow us to ‘play the game’. It has the potential to allow departments with minimal admin support to accurately report their data driven incidents and demonstrate the need for further investment. Our code can easily be replicated in any department using Datix.Referenceshttps://digital.nhs.uk/data-and-information/publications/statistical/hospital-accident--emergency-activity/2021-22/performance-timeshttps://www.rldatix.com/en-uke/R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/https://docs.ropensci.org/RSelenium/
ObjectivesEmergency Department (ED) patient wait-times have been progressively increasing. Targets set clear expectations for health service users but nationally the NHS has failed to meet its ...wait-time targets in any year since 2013/14.1 Research has shown that patient dissatisfaction can lead to violence towards staff, often because of patients’ relative’s unmet expectations.2 Research has concluded that managing perceptions of wait-times may be a more effective strategy at increasing patient satisfaction than decreasing actual wait-times.3Previous studies have modelled ED wait-times4–6 but none were conducted in a paediatric setting. Of these, one study4 attempted to predict future wait-times and achieved 52.47% accuracy but used discharge diagnoses as a variable making it difficult to implement in practice.This study aims to use multiple regression modelling to accurately predict how long it will take a child to be seen in an ED and use this information to manage expectations of wait-times.MethodsWe used anonymised routinely collected administrative data from all presentations to the Accident and Emergency Department of the Bristol Royal Hospital for Children during 2022. Using R, we randomly allocated 80% of the data to a training set and the remainder to a testing set. We used the training set to develop a multiple regression model, based on assigned triage category and measures of how busy the department was.Understanding that patients are satisfied being seen sooner than their predicted wait-time, we considered the result to be unsuccessful if their predicted wait-time was longer than 30 minutes of their actual wait-time. We assessed the accuracy of the model by applying it to our reserved test data. Confidence intervals were calculated by 1000 bootstrap iterations.ResultsFrom 48,540 ED presentations, the median patient wait-time after triage was 65 minutes (IQR 34–122). Our model was able to predict 77.4% (95% CI: 76.5–78.2%) attendances successfully. Triage category, wait-time of last patient, number of patients waiting to be seen and number of patients waiting for a bed had the most significant impact on prediction of wait-times (all p<0.005).ConclusionTailored models created using a department’s routine data can be used to give individualised predictions for wait-times which can be given to patients to manage their expectations and may improve patient satisfaction. We are currently refining this model with machine learning and will develop a method to distribute this information to ED attendees.ReferencesNHS. A&E Attendances and Emergency Admissions Internet. United Kingfrom: NHS; 2023 cited 2023 Jan 24. https://www.england.nhs.uk/statistics/statistical-work-areas/ae-waiting-times-and-activity/Yıldız I, Yıldız F. Pediatric emergency nurses’ workplace violence experiences: A qualitative study. Int Emerg Nursinternet. 2022 Mar 23 cited 2023 Jan 24; 62. https://pubmed.ncbi.nlm.nih.gov/35339106/Thompson DA, Yarnold PR, Williams DR, Adams SL. Effects of actual waiting time, perceived waiting time, information delivery, and expressive quality on patient satisfaction in the emergency department. Ann Emerg Med internet. 1996 Dec cited 2023 Jan 24;28(6): 657–65. https://www.sciencedirect.com/science/article/abs/pii/S0196064496700902Ataman MG, Sarıeyer G. Predicting waiting and treatment times in emergency departments using ordinal logistic regression models. Am J Emerg Med internet. 2021 Mar 01 cited 2023 Jan 24;46: 45–50. https://pubmed.ncbi.nlm.nih.gov/33721589/Walker K, Jiarpakdee J, Loupis A, Tantithamthavorjn C, Joe K, Ben-Meir M, et al. Emergency medicine patient wait time multivariable prediction models: a multicentre derivation and validation study. Emerg Med J 2022 May cited 2023 Jan 24;39(5):386–93. https://pubmed.ncbi.nlm.nih.gov/34433615/Ding R, McCarthy ML, Desmond JS, Lee JS, Aronsky D, Zeger SL. Characterizing waiting room time, treatment time, and boarding time in the emergency department using quantile regression. Acad Emerg Med. 2010 Aug cited 2023 Jan 24;17(8): 813–23. https://pubmed.ncbi.nlm.nih.gov/20670318/
AbstractObjectiveTo determine whether artificial intelligence (AI) can generate plausible and engaging titles for potential Christmas research articles in The BMJ.DesignObservational ...study.SettingEurope, Australia, and Africa.Participants1 AI technology (Generative Pre-trained Transformer 3, GPT-3) and 25 humans.Main outcome measuresPlausibility, attractiveness, enjoyability, and educational value of titles for potential Christmas research articles in The BMJ generated by GPT-3 compared with historical controls.ResultsAI generated titles were rated at least as enjoyable (159/250 responses (64%) v 346/500 responses (69%); odds ratio 0.9, 95% confidence interval 0.7 to 1.2) and attractive (176/250 (70%) v 342/500 (68%); 1.1, 0.8 to 1.4) as real control titles, although the real titles were rated as more plausible (182/250 (73%) v 238/500 (48%); 3.1, 2.3 to 4.1). The AI generated titles overall were rated as having less scientific or educational merit than the real controls (146/250 (58%) v 193/500 (39%); 2.0, 1.5 to 2.6); this difference, however, became non-significant when humans curated the AI output (146/250 (58%) v 123/250 (49%); 1.3, 1.0 to 1.8). Of the AI generated titles, the most plausible was “The association between belief in conspiracy theories and the willingness to receive vaccinations,” and the highest rated was “The effects of free gourmet coffee on emergency department waiting times: an observational study.”ConclusionsAI can generate plausible, entertaining, and scientifically interesting titles for potential Christmas research articles in The BMJ; as in other areas of medicine, performance was enhanced by human intervention.
AimsThe meningococcal B vaccine, which was introduced to the routine vaccine schedule in the UK in September 2015, has been linked with fever post-administration with estimates of fever occurring in ...over 50% of children who receive the vaccine. The first dose of the vaccine is given at 2 months old. Fever in children under 3 months is a red flag symptom for sepsis according to the National Institute for Health and Care Excellence guidelines and may warrant further investigations including a lumbar puncture.The objective of this study is to review whether the introduction of the meningococcal B vaccine has increased rates of lumbar punctures in children aged one to three months admitted to hospitals in England.MethodsChildren aged 29 to 90 days, who had a lumbar puncture during a hospital admission in England, between financial years 2010/11 and 2019/20 were identified using the Hospital Episodes Statistics (HES) dataset. Rates of lumbar puncture were calculated using population estimates from the Office of National Statistics. ICD-10 codes for meningitis were identified and rates of meningitis as the primary diagnosis, using the first diagnostic code from the HES dataset, were calculated.ResultsAs shown in figures 1 and 2, rates of lumbar puncture have increased over the last decade. The highest rates occurred in the financial year 2016/17 with a rate of 4581 lumbar punctures per 100,000 person-years (4460,4706 95%CI). This was the year following the introduction of the meningococcal vaccine, suggesting that the introduction of the meningococcal B vaccine may be linked to increased lumbar puncture rates. Rates have then reduced in subsequent years. This may be due to increased recognition of vaccines as a cause of fever or greater use of antipyretic medications at the time of vaccination. The median length of admission for infants aged 29 to 90 days was 3 days (2,4 IQR).The cause of the general increase in lumbar puncture rates over the last decade is unclear. One possible cause is improved coding of lumbar punctures rather than a genuine increase in rates.Rates of meningitis have however remained relatively static over this time period as shown in figures 1 and 2. Rates have ranged between 75 and 92 cases per 100,000 person-years in one–to-three-month-old infants in England.Abstract 1283 Figure 1Graph to show the change in rates of lumbar puncture and primary diagnosis of meningitis in 29-to-90-days olds in England from financial years 2010/11 to 2019/20Abstract 1283 Figure 2Rates of lumbar puncture and rates of meningitits as primary diagnosis in 29-to-90-days olds in England from financial years 2010/11 to 2019/20ConclusionOur results suggest that the introduction of the meningococcal B vaccine may be linked to increased rates of lumbar puncture. The increasing rate of lumbar punctures in England, despite static rates of meningitis, suggests we may need to consider alternative approaches to assessing febrile infants, such as the ‘Step-by-Step’ Approach.
The emergence of COVID-19 and public health measures implemented to reduce SARS-CoV-2 infections have both affected acute lower respiratory tract disease (aLRTD) epidemiology and incidence trends. ...The severity of COVID-19 and non-SARS-CoV-2 aLRTD during this period have not been compared in detail.
We conducted a prospective cohort study of adults age ≥18 years admitted to either of two acute care hospitals in Bristol, UK, from August 2020 to November 2021. Patients were included if they presented with signs or symptoms of aLRTD (e.g., cough, pleurisy), or a clinical or radiological aLRTD diagnosis.
12,557 adult aLRTD hospitalisations occurred: 10,087 were associated with infection (pneumonia or non-pneumonic lower respiratory tract infection NP-LRTI), 2161 with no infective cause, with 306 providing a minimal surveillance dataset. Confirmed SARS-CoV-2 infection accounted for 32% (3178/10,087) of respiratory infections. Annual incidences of overall, COVID-19, and non- SARS-CoV-2 pneumonia were 714.1, 264.2, and 449.9, and NP-LRTI were 346.2, 43.8, and 302.4 per 100,000 adults, respectively. Weekly incidence trends in COVID-19 aLRTD showed large surges (median 6.5 IQR 0.7–10.2 admissions per 100,000 adults per week), while other infective aLRTD events were more stable (median 14.3 IQR 12.8–16.4 admissions per 100,000 adults per week) as were non-infective aLRTD events (median 4.4 IQR 3.5–5.5 admissions per 100,000 adults per week).
While COVID-19 disease was a large component of total aLRTD during this pandemic period, non- SARS-CoV-2 infection still caused the majority of respiratory infection hospitalisations. COVID-19 disease showed significant temporal fluctuations in frequency, which were less apparent in non-SARS-CoV-2 infection. Despite public health interventions to reduce respiratory infection, disease incidence remains high.
AvonCAP is an investigator-led project funded under a collaborative agreement by Pfizer.
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