Fixed dose ketamine for prehospital management of hyperactive delirium with severe agitation.

INTRODUCTION: Patients exhibiting signs of hyperactive delirium with severe agitation (HDSA) may require sedating medications for stabilization and safe transport to the hospital. Determining the patient's weight and calculating the correct weight-based dose may be challenging in an emergency. A fixed dose ketamine protocol is an alternative to the traditional weight-based administration, which may also reduce dosing errors. The objective of this study was to evaluate the frequency and characteristics of adverse events following pre-hospital ketamine administration for HDSA. METHODS: Emergency Medical Services (EMS) records from four agencies were searched for prehospital ketamine administration. Cases were included if a 250 mg dose of ketamine was administered on standing order to an adult patient for clinical signs consistent with HDSA. Protocols allowed for a second 250 mg dose of ketamine if the first dose was not effective. Both the 250 mg initial dose and the total prehospital dose were analyzed for weight based dosing and adverse events. RESULTS: Review of 132 cases revealed 60 cases that met inclusion criteria. Patients' median weight was 80 kg (range: 50-176 kg). No patients were intubated by EMS, one only requiring suction, three required respiratory support via bag valve mask (BVM). Six (10%) patients were intubated in the emergency department (ED) including the three (5%) supported by EMS via BVM, three (5%) others who were sedated further in the ED prior to requiring intubation. All six patients who were intubated were discharged from the hospital with a Cerebral Performance Category (CPC) 1 score. The weight-based dosing equivalent for the 250 mg initial dose (OR: 2.62, CI: 0.67-10.22) and the total prehospital dose, inclusive of the 12 patients that were administered a second dose, (OR: 0.74, CI: 0.27, 2.03), were not associated with the need for intubation. CONCLUSION: The 250 mg fixed dose of ketamine was not >5 mg/kg weight-based dose equivalent for all patients in this study. Although a second 250 mg dose of ketamine was permitted under standing orders, only 12 (20%) of the patients were administered a second dose, none experienced an adverse event. This indicates that the 250 mg initial dose was effective for 80% of the patients. Four patients with prehospital adverse events likely related to the administration of ketamine were found. One required suction, three (5%) requiring BVM respiratory support by EMS were subsequently intubated upon arrival in the ED. All 60 patients were discharged from the hospital alive. Further research is needed to determine an optimal single administration dose for ketamine in patients exhibiting signs of HDSA, if employing a standardized fixed dose medication protocol streamlines administration, and if the fixed dose medication reduces the occurrence of dosage errors.

Interval estimation of relative risks for combined unilateral and bilateral correlated data.

Measurements are generally collected as unilateral or bilateral data in clinical trials, epidemiology, or observational studies. For example, in ophthalmology studies, the primary outcome is often obtained from one eye or both eyes of an individual. In medical studies, the relative risk is usually the parameter of interest and is commonly used. In this article, we develop three confidence intervals for the relative risk for combined unilateral and bilateral correlated data under the equal dependence assumption. The proposed confidence intervals are based on maximum likelihood estimates of parameters derived using the Fisher scoring method. Simulation studies are conducted to evaluate the performance of proposed confidence intervals with respect to the empirical coverage probability, the mean interval width, and the ratio of mesial non-coverage probability to the distal non-coverage probability. We also compare the proposed methods with the confidence interval based on the method of variance estimates recovery and the confidence interval obtained from the modified Poisson regression model with correlated binary data. We recommend the score confidence interval for general applications because it best controls converge probabilities at the 95% level with reasonable mean interval width. We illustrate the methods with a real-world example.

National Variation in EMS Response and Antiepileptic Medication Administration for Children with Seizures in the Prehospital Setting.

BACKGROUND AND OBJECTIVES: Prehospital Advanced Life Support (ALS) is important to improve patient outcomes in children with seizures, yet data is limited regarding national prehospital variation in ALS response for these children. We aimed to determine the variation in ALS response and prehospital administration of antiepileptic medication for children with seizures across the United States. METHODS: We analyzed children <19 years with 9-1-1 dispatch codes for seizure in the 2019 National Emergency Medical Services Information System dataset. We defined ALS response as ALS-paramedic, ALS-Advanced Emergency Medical Technician, or ALS-intermediate responses. We conducted regression analyses to identify associations between ALS response (primary outcome), antiepileptic administration (secondary outcome) and age, gender, location, and US census regions. RESULTS: Of 147,821 pediatric calls for seizures, 88% received ALS responses. Receipt of ALS response was associated with urbanicity, with wilderness (adjusted odds ratio [aOR] 0.44, 0.39-0.49) and rural (aOR 0.80, 0.75-0.84) locations less likely to have ALS responses than urban areas. Of 129,733 emergency medical service (EMS) activations with an ALS responder's impression of seizure, antiepileptic medications were administered in 9%. Medication administration was independently associated with age (aOR 1.008, 95% confidence interval [CI] 1.005-1.010) and gender (aOR 1.22, 95% CI 1.18-1.27), with females receiving medications more than males. Of the 11,698 children who received antiepileptic medications, midazolam was the most commonly used (83%). CONCLUSION: The majority of children in the US receive ALS responses for seizures. Although medications are infrequently administered, the majority who received medications had midazolam given, which is the current standard of care. Further research should determine the proportion of children who are continuing to seize upon EMS arrival and would most benefit from immediate treatment.

Homogeneity test of relative risk ratios for stratified bilateral data under different algorithms.

Medical clinical studies about paired body parts often involve stratified bilateral data. The correlation between responses from paired parts should be taken into account to avoid biased or misleading results. This paper aims to test if the relative risk ratios across strata are equal under the optimal algorithms. Based on different algorithms, we obtain the desired global and constrained maximum likelihood estimations (MLEs). Three asymptotic test statistics (i.e. T L , T S C and T W ) are proposed. Monte Carlo simulations are conducted to evaluate the performance of these algorithms with respect to mean square errors of MLEs and convergence rate. The empirical results show Fisher scoring algorithm is usually better than other methods since it has effective convergence rate for global MLEs, and makes mean-square error lower for constrained MLEs. Three test statistics are compared in terms of type I error rate (TIE) and power. Among these statistics, T S C is recommended according to its robust TIEs and satisfactory power.

Relationship between Physical Activity and Pain in U.S. Adults.

PURPOSE: We sought to assess the relationship between physical activity (PA) and pain within the available sample, with secondary aims to assess prevalence of pain, PA levels, health care seeking behaviors, and impact of pain on daily activities and work. METHODS: We conducted an epidemiological cross-sectional observational study utilizing National Health Interview Survey data from 2020. We examined the self-reported adherence to current PA guidelines and the prevalence of pain. We hypothesized those dealing with pain were less likely to meet PA guidelines. The PA levels, pain prevalence, frequency, and intensity were assessed via the survey and relationships explored via modeling. RESULTS: Of 31,568, 46% were men and 53.99% women with mean age of 52.27 yr (±17.31 yr). There were 12,429 (39.37%) participants that reported pain on some days, 2761 (8.75%) on most days, and 4661 (14.76%) every day. The odds of engaging in PA decreased in a stepwise fashion based on frequency and intensity of pain reporting when compared with no pain. Importantly, PA is a significant correlate affecting pain reporting, with individuals engaging in PA (strength and aerobic) demonstrating two times lower odds of reporting pain when compared with those not meeting the PA guidelines. CONCLUSIONS: There is a significant correlation between meeting PA guidelines and pain. Meeting both criteria of PA guidelines resulted in lower odds of reporting pain. In addition, the odds of participating in PA decreased based on pain frequency reporting. These are important findings for clinicians, highlighting the need for assessing PA not only for those dealing with pain but also as a potential risk factor for minimizing development of chronic pain.

Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy.

BACKGROUND: Previous studies have examined the associations between ambient fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas. OBJECTIVES: To examine the associations of prenatal ambient PM2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area. METHODS: From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM2.5 exposure. RESULTS: Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM2.5 exposure during the 1st trimester was associated with higher odds of GDM (10 µg/m3 increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 µg/m3 increase in PM2.5 during the 2nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM2.5 exposure at 24th-27th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21st-24th weeks for higher 1-h and 2-h blood glucose levels and of 20th-22nd weeks for increased Δ1h-fasting and Δ2h-fasting. CONCLUSIONS: Ambient PM2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.

Emergency Department Patients' COVID-19 Vaccination Status and Self-Reported Barriers.

INTRODUCTION: This study surveyed adult emergency department (ED) patients and the adult companions of pediatric patients to determine whether rates of coronavirus disease 2019 (COVID-19) vaccination were comparable to that of the general population in the region. This study also sought to identify self-reported barriers to vaccination and possible areas for intervention. METHODS: A survey was administered to 607 adult ED patients or the adult companions of pediatric patients from three different regional hospitals to assess their COVID-19 vaccination status, COVID-19 vaccine barriers, and demographic information. RESULTS: Of the 2,267 adult patients/companions considered for enrollment, we approached 730 individuals about participating in the study. Of the individuals approached, 607 (41% male; mean age 47.0+17.4 years) consented to participate. A total of 403 (66.4%) participants had received at least one vaccine dose as compared to 70% of the adult population in the county where the three hospitals were located. Of those, 382 (94.8%) were fully vaccinated and among the individuals who were partially vaccinated the majority (17 of 21) had an appointment for their second dose. Of those approached, 204 (33.6%) were not vaccinated, with 66 (10.9% of the total population) expressing an interest in becoming vaccinated while the remaining 138 did not want to be vaccinated. Of those who wanted to be vaccinated 32% were waiting for more safety data, and of those who did not want to be vaccinated 26% were concerned about side effects and risks and 28% were waiting for more safety data. CONCLUSION: Adult ED patients and adult companions of pediatric ED patients were vaccinated at a slightly lower rate than the general population in our county. A small but significant proportion of those who were unvaccinated expressed the desire to be vaccinated, indicating that the ED may be a suitable location to introduce a COVID-19 vaccination program.

Coenzyme Q10 supplementation for the treatment of statin-associated muscle symptoms.

Aim: To determine the association of coenzyme Q10 (CoQ10) use with the resolution of statin-associated muscle symptoms (SAMS). Patients & methods: Retrospective analysis of a large, multicenter survey study of SAMS (total n = 511; n = 64 CoQ10 users). Univariate and multivariate logistic regression models assessed the association between CoQ10 use and the resolution of SAMS. Results: The frequency of SAMS resolution was similar between CoQ10 users and non-users (25% vs 31%, respectively; unadjusted odds ratio [OR]: 0.75 [95% CI: 0.41-1.38]; p = 0.357). Similarly, CoQ10 use was not significantly associated with the resolution of SAMS in multivariable models adjusted for SAMS risk factors (OR: 0.84 [95% CI: 0.45-1.55]; p = 0.568) or adjusted for significant differences among CoQ10 users and non-users (OR: 0.82 [95% CI: 0.45-1.51]; p = 0.522). Conclusion: CoQ10 was not significantly associated with the resolution of SAMS.

Statins are medications that help lower cholesterol and treat cardiovascular disease, but muscle pain is the most common side effect of statins. Statins decrease the body's levels of coenzyme Q10 (CoQ10), and thus taking CoQ10 supplements (which are widely available over the counter in pharmacies) may help treat the muscle side effects from statins. However, the results of previous studies are not clear whether CoQ10 is effective for treating statin-associated muscle symptoms. Therefore, the purpose of this study was to analyze whether the use of CoQ10 supplements improved statin-associated muscle side effects in a large group of individuals. When the authors compared the survey responses of 64 CoQ10 users versus those of 447 non-CoQ10 users with statin-associated muscle symptoms, CoQ10 supplements did not improve their muscle symptoms.

An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing.

BACKGROUND: Multi-sample comparison is commonly used in cancer genomics studies. By using next-generation sequencing (NGS), a mutation's status in a specific sample can be measured by the number of reads supporting mutant or wildtype alleles. When no mutant reads are detected, it could represent either a true negative mutation status or a false negative due to an insufficient number of reads, so-called "coverage". To minimize the chance of false-negative, we should consider the mutation status as "unknown" instead of "negative" when the coverage is inadequately low. There is no established method for determining the coverage threshold between negative and unknown statuses. A common solution is to apply a universal minimum coverage (UMC). However, this method relies on an arbitrarily chosen threshold, and it does not take into account the mutations' relative abundances, which can vary dramatically by the type of mutations. The result could be misclassification between negative and unknown statuses. METHODS: We propose an adaptive mutation-specific negative (MSN) method to improve the discrimination between negative and unknown mutation statuses. For a specific mutation, a non-positive sample is compared with every known positive sample to test the null hypothesis that they may contain the same frequency of mutant reads. The non-positive sample can only be claimed as "negative" when this null hypothesis is rejected with all known positive samples; otherwise, the status would be "unknown". RESULTS: We first compared the performance of MSN and UMC methods in a simulated dataset containing varying tumor cell fractions. Only the MSN methods appropriately assigned negative statuses for samples with both high- and low-tumor cell fractions. When evaluated on a real dual-platform single-cell sequencing dataset, the MSN method not only provided more accurate assessments of negative statuses but also yielded three times more available data after excluding the "unknown" statuses, compared with the UMC method. CONCLUSIONS: We developed a new adaptive method for distinguishing unknown from negative statuses in multi-sample comparison NGS data. The method can provide more accurate negative statuses than the conventional UMC method and generate a remarkably higher amount of available data by reducing unnecessary "unknown" calls.

Testing the homogeneity of proportions for combined unilateral and bilateral data.

Measurements are generally collected as unilateral or bilateral data in clinical trials or observational studies. For example, in ophthalmologic studies, statistical tests are often based on one or two eyes of an individual. For the bilateral data, recent literatures have shown some test procedures that take into account the intraclass correlation between paired organs of the same person. Ma et al. investigated three test procedures under Rosner's model. In this paper, we extend Ma's work for bilateral data to combined bilateral and unilateral data. The proposed procedures are based on the likelihood estimate algorithm derived from the root of 4th order polynomial equations and the Fisher scoring iterations. Simulation studies are performed to compare the testing procedures under different parameter configurations. The result shows that score test has satisfactory type I error rates and powers. Therefore, we recommend score test for testing the homogeneity of proportions. We illustrate the application of the proposed methods with two real world examples.

Simultaneous confidence interval construction for many-to-one comparisons of proportion differences based on correlated paired data.

In some medical researches such as ophthalmological, orthopaedic and otolaryngologic studies, it is often of interest to compare multiple groups with a control using data collected from paired organs of patients. The major difficulty in performing the data analysis is to adjust the multiplicity between the comparison of multiple groups, and the correlation within the same patient's paired organs. In this article, we construct asymptotic simultaneous confidence intervals (SCIs) for many-to-one comparisons of proportion differences adjusting for multiplicity and the correlation. The coverage probabilities and widths of the proposed CIs are evaluated by Monte Carlo simulation studies. The methods are illustrated by a real data example.

Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data.

In ophthalmologic or otolaryngologic studies, bilateral correlated data often arise when observations involving paired organs (e.g., eyes, ears) are measured from each subject. Based on Donner's model , in this paper, we focus on investigating the relationship between the disease probability and covariates (such as ages, weights, gender, and so on) via the logistic regression for the analysis of bilateral correlated data. We first propose a new minorization-maximization (MM) algorithm and a fast quadratic lower bound (QLB) algorithm to calculate the maximum likelihood estimates of the vector of regression coefficients, and then develop three large-sample tests (i.e., the likelihood ratio test, Wald test, and score test) to test if covariates have a significant impact on the disease probability. Simulation studies are conducted to evaluate the performance of the proposed fast QLB algorithm and three testing methods. A real ophthalmologic data set in Iran is used to illustrate the proposed methods.

Statistical tests under Dallal's model: Asymptotic and exact methods.

This paper proposes asymptotic and exact methods for testing the equality of correlations for multiple bilateral data under Dallal's model. Three asymptotic test statistics are derived for large samples. Since they are not applicable to small data, several conditional and unconditional exact methods are proposed based on these three statistics. Numerical studies are conducted to compare all these methods with regard to type I error rates (TIEs) and powers. The results show that the asymptotic score test is the most robust, and two exact tests have satisfactory TIEs and powers. Some real examples are provided to illustrate the effectiveness of these tests.

Symptom Criteria for COVID-19 Testing of Heath Care Workers.

BACKGROUND: Symptom criteria for COVID-19 testing of heath care workers (HCWs) limitations on testing availability have been challenging during the COVID-19 pandemic. An evidence-based symptom criteria for identifying HCWs for testing, based on the probability of positive COVID-19 test results, would allow for a more appropriate use of testing resources. METHODS: This was an observational study of outpatient COVID-19 testing of HCWs. Prior to testing, HCWs were asked about the presence of 10 symptoms. Their responses were then compared to their subsequent pharyngeal swab COVID-19 polymerase chain reaction test results. These data were used to derive and evaluate a symptom-based testing criteria. RESULTS: A total of 961 HCWs were included in the analysis, of whom 225 (23%) had positive test results. Loss of taste or smell was the symptom with the largest positive likelihood ratio (3.33). Dry cough, regardless of the presence or absence of other symptoms, was the most sensitive (74%) and the least specific (32%) symptom. The existing testing criteria consisting of any combination of one or more of three symptoms (fever, shortness of breath, dry cough) was 93% sensitive and 9% specific (area unce the curve [AUC] = 0.63, 95% confidence interval [CI] = 0.59 to 0.67). The derived testing criteria consisting of any combination of one or more of two symptoms (fever, loss of taste or smell) was 89% sensitive and 48% specific (AUC = 0.75, 95% CI = 0.71 to 0.78). The hybrid testing criteria consisting of any combination of one or more of four symptoms (fever, shortness of breath, dry cough, loss of taste or smell) was 98% sensitive and 8% specific (AUC = 0.77, 95% CI = 0.73 to 0.80). CONCLUSION: An evidence-based approach to COVID-19 testing that at least includes fever and loss of taste or smell should be utilized when determining which HCWs should be tested.

Association of SLCO1B1 c.521T>C (rs4149056) with discontinuation of atorvastatin due to statin-associated muscle symptoms.

The most common adverse drug reaction from statins are statin-associated muscle symptoms (SAMS), characterized by myopathy (weakness), myalgia (muscle pain), and commonly elevation in serum creatine kinase. All statins are substrates of the organic anion transporter 1B1 (OATP1B1; gene: SLCO1B1), albeit to different degrees. A genetic polymorphism in SLCO1B1, c.521T>C (rs4149056), markedly decreases OATP1B1 function. The literature is currently unclear as to whether SLCO1B1 c.521T>C is significantly associated with discontinuation of atorvastatin specifically due to SAMS. Our hypothesis was that individuals carrying the SLCO1B1 decreased function 521C allele are more likely to discontinue atorvastatin due to SAMS. This was a retrospective analysis of survey data from 379 Caucasians genotyped for rs4149056 and treated with atorvastatin for at least 12 months. Crude and multivariable logistic regression, adjusted for established risk factors for SAMS, determined the association of SLCO1B1 c.521T>C with discontinuation of atorvastatin due to SAMS (SLCO1B1 521T-homozygotes vs. 521C-carriers). The sample was 51% male, with a mean age of 57 years (SD = 11). Sixty-one percent of participants reported discontinuing atorvastatin due to SAMS, and 32% overall carried the 521C allele. SLCO1B1 521C-carrier status was not a significant predictor of atorvastatin discontinuation in any model: crude OR = 1.07; 95% CI, 0.68-1.66; P = 0.78 and adjusted OR = 1.07; 95% CI, 0.68-1.69; P = 0.76. The results were similar in a sub-group of participants treated with higher doses of atorvastatin (>20 mg). In summary, SLCO1B1 c.521T>C was not significantly associated with discontinuation of atorvastatin therapy due to SAMS.

Retrospective Analysis of Short-Term Respiratory Outcomes of Three Different Steroids Used in Clinical Practice in Intubated Preterm Infants.

OBJECTIVE: This study aimed to compare short-term respiratory outcomes of three steroids (dexamethasone, hydrocortisone, and methylprednisolone) to facilitate extubation by improving respiratory status in preterm infants. STUDY DESIGN: This is a retrospective, single-center, cohort study of 98 intubated preterm infants ≤346/7 weeks' gestation, admitted to a 64-bed, level III neonatal intensive care unit at the Women & Children's Hospital of Buffalo, Buffalo, NY, between 2006 and 2012, who received a short course of low-dose steroids for lung disease after first week of life. RESULTS: Study infants received dexamethasone (34%), hydrocortisone (44%), or methylprednisolone (22%) based on clinical team preference. By day 7 after initiation of steroids, extubation occurred in 59, 44, and 41%, respectively, in infants on dexamethasone, hydrocortisone, and methylprednisolone (p = 0.3). The mean respiratory severity score (RSS = fraction of inspired oxygen × mean airway pressure), a quantitative measure of respiratory status, decreased by 44% for all infants and by 59% in the dexamethasone group by day 7. CONCLUSION: Steroids improved short-term respiratory outcomes in all infants (RSS and extubation); by day 7, dexamethasone treatment was associated with the greatest decrease in RSS. Additional prospective, randomized trials of short-course low-dose steroids are warranted to substantiate these findings to guide clinical decision making and in evaluating differential steroid effects on long-term neurodevelopmental outcomes.

Interval estimation of proportion ratios for stratified bilateral correlated binary data.

Confidence interval (CI) methods for the ratio of two proportions in the presence of correlated bilateral binary data are constructed for comparative clinical trials with stratified design. Simulations are conducted to evaluate the performance of the presented CIs with respect to mean coverage probability (MCP), mean interval width (MIW), and the ratio of mesial non-coverage probability to the distal non-coverage probability (RMNCP). Based on the empirical results, we suggest the use of the proposed CI method based on the complete score statistics (CS) for general applications. An example from a rheumatology study is used to demonstrate the proposed methodologies.

Efficient statistical inference for a parallel study with missing data by using an exact method.

In a parallel group study comparing a new treatment with a standard of care, missing data often occur for various reasons. When the outcome is binary, the data from such studies can be summarized into a 2 × 3 contingency table, with the missing observations in the last column. When the missingness is neither related to the outcome of interest nor related to other outcomes from the study but it is covariate dependent with the sole covariate being treatment, this type of missing data mechanism is considered as missing at random. In 2016, Tian et al.  proposed three statistics to test the hypothesis that the response rate is equivalent for a parallel group study with missing data. The asymptotic limiting distributions of these test statistics were used for statistical inference. However, asymptotic approaches for testing proportions generally do not have satisfactory performance with regard to type I error rate control for a clinical trial with the sample size from small to medium. For this reason, we consider an exact approach based on maximization to provide valid and efficient statistical inference for a parallel group study with missing data. Exact approaches can guarantee the type I error rate and they are computationally feasible in this setting. We conduct extensive numerical studies to compare the performance of the exact approach based on the three statistics for a one-sided hypothesis testing problem. We conclude that the exact approach based on the likelihood ratio statistic is more powerful than the exact approach based on the other two statistics. Two real clinical trial data sets are used to illustrate the application of the proposed exact approach.

Asymptotic confidence interval construction for proportion ratio based on correlated paired data.

In ophthalmological and otolaryngology studies, measurements obtained from both organs (e.g., eyes or ears) of an individual are often highly correlated. Ignoring the intraclass correlation between paired measurements may yield biased inferences. In this article, four different confidence interval (CI) construction methods (maximum likelihood estimates based Wald-type CI, profile likelihood CI, asymptotic score CI and an existing method adjusted for correlated bilateral data) are applied to this type of correlated bilateral data to construct CI for proportion ratio, taking the intraclass correlation into consideration. The coverage probabilities and widths of the resulting CIs are compared with each other in a Monte Carlo simulation study to evaluate their performances. A real dataset from an ophthalmologic study is used to illustrate our methodology.

Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data.

Bilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type I error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.