Modelling polio data using the first order non-negative integer-valued autoregressive INAR(1) model.

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts

A Comparison of Chief Complaints, Specific Diagnoses, and Demographics of Pediatric Urgent Care Visits Before and During the COVID-19 Pandemic: A Retrospective Study

There was an increased incidence of pediatric patients who presented with injuries caused by falls not related to sports or other recreational activities, as well as for animal bites, during the early pandemic period of April 2020. Education of parents and caregivers of young children is warranted to raise awareness of the even greater potential for falls and animal bites when children are confined at home for longer than typical periods of time, as occurred with the stay-at-home government orders during the initial period of the COVID-19 pandemic

Revisiting the Applicability of Adult Early Post-Operative Nausea and Vomiting Risk Factors for the Paediatric Patient: A Prospective Study Using Cotinine Levels in Children Undergoing Adenotonsillectomies

Background and Aims: Post-operative vomiting (POV) in children remains a significant clinical problem. This prospective study aims to investigate the applicability of well-established adult early post-operative nausea and vomiting (PONV) risk factors on paediatric POV after adenotonsillectomies under regulated anaesthetic conditions. Methods: After Institutional Review Board approval, 213 children aged 3–10-year-old were enrolled. The participants had pre-operative questionnaires completed, followed protocolised anaesthetic plans and had saliva analysed for cotinine. The primary outcomes were POV as correlated with age, gender, family or personal history of PONV, motion sickness history, opioid use, surgical time, anaesthetic time and environmental tobacco smoke (ETS) exposure, as assessed by cotinine levels and questionnaire reports. Data on analgesics, antiemetics and POV incidence before post-anaesthesia care unit discharge were collected. Statistical analysis was done through multiple logistic regression. Results: A total of 200 patients finalised the study. Early POV occurred in 32%. Family history of PONV (odds ratio [OR] = 5.3, P \u3c 0.01) and motion sickness history (OR = 4.4, P = 0.02) were highly significant risk factors. Age reached borderline statistical significance (OR = 1.4, P = 0.05). None of the other factors reached statistical significance. Conclusion: Early POV occurs frequently in paediatric patients undergoing adenotonsillectomies. In this paediatric-aged group, the incidence of POV was affected by the family history of PONV, and history of motion sickness. Age, female gender, opioid use, surgical and anaesthetic times did not affect the incidence of POV. ETS exposure, as assessed by cotinine levels and questionnaire reports, had no protective effect on early paediatric POV

Exploratory data analysis for almost everyone

This book is intended to introduce the rudiments of the techniques of Exploratory Data Analysis (EDA) for anyone who is interested in data analysis. The book is simple enough to reach not only undergraduate students but also very wide audience

First-order random coefficient autoregressive (RCA(1)) model : joint Whittle estimation and information.

Random coefficient autoregressive model, RCA(p), has been discussed widely as a suitable model for nonlinear time series. The conditional least squares and likelihood parameter estimation of RCA(p) model has also been discussed in [3]. The statistical inference of RCA(1) model has been presented in [4] while the conditional least square estimates for nonstationary processes is studied in [7]. The optimal estimation for nonlinear time series using estimating equations has been investigated in [6]. Recently there has been interest in joint prediction based on spectral density of popular nonlinear time series models such as RCA(p) models. Another way of estimating the parameters of the RCA(1) model is to do Whittle's estimation. In this paper the Whittle estimates of the parameters of an RCA(p) model are studied. It is shown that the Whittle information of the autoregressive parameter in an RCA(p) model is larger than the corresponding information in an autoregressive (AR) model

Complement effectors, C5a and C3a, in cystic fibrosis lung fluid correlate with disease severity.

In cystic fibrosis (CF), lung damage is mediated by a cycle of obstruction, infection, inflammation and tissue destruction. The complement system is a major mediator of inflammation for many diseases with the effectors C5a and C3a often playing important roles. We have previously shown in a small pilot study that CF sputum soluble fraction concentrations of C5a and C3a were associated with clinical measures of CF disease. Here we report a much larger study of 34 CF subjects providing 169 testable sputum samples allowing longitudinal evaluation comparing C5a and C3a with clinical markers. Levels of the strongly pro-inflammatory C5a correlated negatively with FEV1% predicted (P < 0.001), whereas the often anti-inflammatory C3a correlated positively with FEV1% predicted (P = 0.01). C5a concentrations correlated negatively with BMI percentile (P = 0.017), positively with worsening of an acute pulmonary exacerbation score (P = 0.007) and positively with P. aeruginosa growth in sputum (P = 0.002). C5a levels also correlated positively with concentrations of other sputum markers associated with worse CF lung disease including neutrophil elastase (P < 0.001), myeloperoxidase activity (P = 0.006) and DNA concentration (P < 0.001). In contrast to C5a, C3a levels correlated negatively with worse acute pulmonary exacerbation score and correlated negatively with sputum concentrations of neutrophil elastase, myeloperoxidase activity and DNA concentration. In summary, these data suggest that in CF sputum, increased C5a is associated with increased inflammation and poorer clinical measures, whereas increased C3a appears to be associated with less inflammation and improved clinical measures

ADHD prescription patterns and medication adherence in children and adolescents during the COVID-19 pandemic in an urban academic setting

Abstract Background COVID-19 impacted all students, especially those with attention deficit hyperactivity disorder (ADHD), putting them at risk for disruption to their medication regimen and school performance. Our study aimed to identify if ADHD medication regimens were disrupted through analyzing prescription refills and if telehealth management demonstrated a higher rate of adherence. Methods A total of 396 patients from the General Academic Pediatrics (GAP) clinic at Children’s Hospital of The King’s Daughters (CHKD) were included in the study. Patients were between the ages of 8–18 with a history of ADHD for three or more years that was medically managed with four or more prescription refills between January 2019 and May 2022. A retrospective chart review collected age, sex, race, refill schedule, appointment schedule, and number of telehealth appointments. Data analysis compared the variables and defined “pre-pandemic months” as January 2019 through March 2020 and “pandemic months” as April 2020 through June 2022. Results The total percentage of patients who had their ADHD medications during pre-pandemic months ranged from 40 to 66% versus 31–44% during pandemic months. Additionally, the total percentage of patients who had quarterly ADHD management appointments during pre-pandemic months ranged between 59 and 70% versus 33–50% during pandemic months. The number of months with ADHD prescription refills over the last three years was significantly higher among those who had both virtual and in-person visits than those who had just in-person visits, p < 0.001. Regarding race, Black patients had a lower number of medication refills compared to White patients when controlled for appointment type. They also had a lower number of total appointments, but there was not a significant difference in the number of virtual appointments. Conclusions Since the start of the pandemic, ADHD patients have both refilled their prescriptions and returned to clinic less frequently. This data suggests a need to re-evaluate the ADHD symptoms of GAP patients periodically and return them to a more consistent medication regimen. Telehealth appointments are a potential solution to increase adherence. However, racial inequities found in this study need to be addressed

C5a and C3a correlations with sputum concentration of Neutrophil Elastase (NE), myeloperoxidase (MPO) and DNA.

<p>C5a and C3a correlations with sputum concentration of Neutrophil Elastase (NE), myeloperoxidase (MPO) and DNA.</p

Longitudinal C5a level (red) and FEV1% predicted (black) for the six subjects with the most sputum samples.

<p>(A-C) For 3 subjects elevations in C5a concentration (purple arrows) appear to precede declines in FEV1% predicted. (D–F) For three subjects elevations in C5a concentration (blue arrows) appear to be coincident with declines in FEV1% predicted.</p

Correlation of C5a and C3a with FEV1% predicted and BMI percentile.

<p>(A) FEV1% predicted compared with C5a (ng/ml). (B) FEV1% predicted compared with C3a (ng/ml). (C) FEV1% predicted compared with age. (D) C5a concentration correlation with BMI percentile in ≤ 20 year olds. Best fit line is shown for each graph.</p