Checking the checklist: a content analysis of expert‐ and evidence‐based case‐specific checklist items

Medical Education 2010: 44 : 874–883 Objectives Research on objective structured clinical examinations (OSCEs) is extensive. However, relatively little has been written on the development of case‐specific checklists on history taking and physical examination. Background information on the development of these checklists is a key element of the assessment of their content validity. Usually, expert panels are involved in the development of checklists. The objective of this study is to compare expert‐based items on OSCE checklists with evidence‐based items identified in the literature. Methods Evidence‐based items covering both history taking and physical examination for specific clinical problems and diseases were identified in the literature. Items on nine expert‐based checklists for OSCE examination stations were evaluated by comparing them with items identified in the literature. The data were grouped into three categories: (i) expert‐based items; (ii) evidence‐based items, and (iii) evidence‐based items with a specific measure of their relevance. Results Out of 227 expert‐based items, 58 (26%) were not found in the literature. Of 388 evidence‐based items found in the literature, 219 (56%) were not included in the expert‐based checklists. Of these 219 items, 82 (37%) had a specific measure of importance, such as an odds ratio for a diagnosis, making that diagnosis more or less probable. Conclusions Expert‐based, case‐specific checklist items developed for OSCE stations do not coincide with evidence‐based items identified in the literature. Further research is needed to ascertain what this inconsistency means for test validity.     

A Bayesian approach to strengthen inference for case‐control studies with multiple error‐prone exposure assessments

In case‐control studies, exposure assessments are almost always error‐prone. In the absence of a gold standard, two or more assessment approaches are often used to classify people with respect to exposure. Each imperfect assessment tool may lead to misclassification of exposure assignment; the exposure misclassification may be differential with respect to case status or not; and, the errors in exposure classification under the different approaches may be independent (conditional upon the true exposure status) or not. Although methods have been proposed to study diagnostic accuracy in the absence of a gold standard, these methods are infrequently used in case‐control studies to correct exposure misclassification that is simultaneously differential and dependent. In this paper, we proposed a Bayesian method to estimate the measurement‐error corrected exposure‐disease association, accounting for both differential and dependent misclassification. The performance of the proposed method is investigated using simulations, which show that the proposed approach works well, as well as an application to a case‐control study assessing the association between asbestos exposure and mesothelioma. Copyright © 2013 John Wiley & Sons, Ltd.     

Study design for non‐recurring,time‐to‐event outcomes in the presence of error‐prone diagnostic tests or self‐reports

Sequentially administered, laboratory‐based diagnostic tests or self‐reported questionnaires are often used to determine the occurrence of a silent event. In this paper, we consider issues relevant in design of studies aimed at estimating the association of one or more covariates with a non‐recurring, time‐to‐event outcome that is observed using a repeatedly administered, error‐prone diagnostic procedure. The problem is motivated by the Women's Health Initiative, in which diabetes incidence among the approximately 160,000 women is obtained from annually collected self‐reported data. For settings of imperfect diagnostic tests or self‐reports with known sensitivity and specificity, we evaluate the effects of various factors on resulting power and sample size calculations and compare the relative efficiency of different study designs. The methods illustrated in this paper are readily implemented using our freely available R software package icensmis, which is available at the Comprehensive R Archive Network website. An important special case is that when diagnostic procedures are perfect, they result in interval‐censored, time‐to‐event outcomes. The proposed methods are applicable for the design of studies in which a time‐to‐event outcome is interval censored. Copyright © 2016 John Wiley & Sons, Ltd.     

A run‐based procedure to identify time‐lagged gene clusters in microarray experiments

Motivation: The analysis of gene‐expression data obtained from microarray experiments can be useful to identify regulatory relationship between genes. Genes with a common functional role have similar expression patterns across different microarray experiments. These similar expression patterns are perhaps due to co‐regulation of genes in the same functional group. Most of the existing methods available for the identification of the regulatory relationships are either made for comparing two genes at a time or methods are not computationally efficient in the identification of the regulatory relationships. The procedures adopted by these methods do not use complete information contained in the data set. In this paper, we propose a statistical procedure, which will use the information contained in the data set to cluster genes that show similar patterns. The proposed procedure compares several genes at a time instead of pair‐wise comparisons as done in some of the other procedures. The proposed procedure provides gene clusters based on time‐lagged data sets with more details. The proposed method provides a numerical value that would facilitate in comparing different sets of data obtained from different expressions. It also provides the identification of the gene involved and the time point at which the observation is made so that proper medicine can be developed for the gene‐specific and time‐specific disease. Results: We applied the proposed procedure on the Spellman data set (Mol. Biol. Cell 1998; 9 (12): 3273–3297) and compared our procedure with some of the other existing procedures. We found that our procedure is more computationally efficient than Ji and Tan (Bioinformatics 2005; 21 :509–516), event method and edge detection procedures. The proposed procedure also provides more details about the clusters than Ji and Tan (Bioinformatics 2005; 21 :509–516), event method and edge detection procedures. The proposed procedure is really simple to apply as compared with other available procedures in the literature including Ji and Tan (Bioinformatics 2005; 21 :509–516), event method and edge detection procedures. Copyright © 2008 John Wiley & Sons, Ltd.     

Use of Raman spectroscopy to identify carbon nanotube contamination at an analytical balance workstation

Carbon nanotubes (CNTs) are cylindrical molecules of carbon with diverse commercial applications. CNTs are also lightweight, easily airborne, and have been shown to be released during various phases of production and use. Therefore, as global CNT production increases, so do concerns that CNTs could pose a safety threat to those who are exposed to them. This makes it imperative to fully understand CNT release scenarios to make accurate risk assessments and to implement effective control measures. However, the current suite of direct-reading and off-line instrumentation used to monitor the release of CNTs in workplaces lack high chemical specificity, which complicates risk assessments when the sampling and/or measurements are performed at a single site where multiple CNT types are handled in the presence of naturally occurring background particles, or dust. Herein, we demonstrate the utility of Raman spectroscopy to unequivocally identify whether particulate matter collected from a multi-user analytical balance workstation comprised CNTs, as well as, whether the contamination included CNTs that were synthesized by a Ni/Y-catalyzed electric-arc method or a Co/Mo-catalyzed chemical vapor deposition method. Identifying the exact CNT type generated a more accurate risk assessment by knowing the metallic impurities involved, and it also led to the identification of the users who handled these CNTs, a review of their handling techniques, and an improved protocol for safely weighing CNTs.     

Development of an iron checklist to guide food intake

An iron checklist comprised of 93 foods was developed to evaluate food choices in terms of iron concentration or frequency of use and to incorporate principles of iron nutriture. The instrument was tested with 89 Expanded Food and Nutrition Education Program technicians. The correlation between points scored on the iron checklist and milligrams of iron calculated from the same 24-hour recall was 0.77. Analyzing iron points by food group highlighted the fact that half of the group had not consumed milk foods and half of the group was receiving 6 to 18 mg iron from the meat group. Seventy-five percent of the sample improved their knowledge of iron foods by using the checklist to assess their diets and to identify food sources of iron. In comparison with the use of a computer, use of the iron checklist was shown to be cost-effective for assessing, teaching, and evaluating program outcomes.     

复方利多卡因乳膏在儿童腰椎穿刺中的应用效果

目的：探讨5％复方利多卡因乳膏在小儿腰椎穿刺中的应用效果分析。方法随机选取住院治疗需行腰椎穿刺术的患儿80例,分为对照组和干预组各40例。干预组在以腰椎穿刺点为圆心的局部皮肤上,涂以0．5g／5cm2的5％复方利多卡因乳膏,并用无菌透明敷贴覆盖1小时,去除敷贴和乳膏进行消毒后行常规小儿腰椎穿刺术。对照组患儿用2％利多卡因注射液作局部浸润麻醉后行常规小儿腰椎穿刺术。两组患儿均全部由专人观察记录心率、呼吸、自诉痛觉评价、穿刺成功率、穿刺后不适感情况,并加以分析。结果干预组的自诉痛觉评价疼痛发生率（χ2＝61．596）、穿刺成功率（χ2＝6．135）、穿刺后不适感发生率（χ2＝6．275）均明显高于对照组（均P＜0．05）。对照组患儿穿刺后的心率（t＝27．594）、呼吸（t＝4．567）均明显较穿刺前加快（均P＜0．05）,而干预组患儿穿刺后的心率（t＝0．516）、呼吸（t＝2．716）较穿刺前均无显著性差异（均P＞0．05）。结论5％复方利多卡因乳膏在小儿腰椎穿刺时做表面麻醉的镇痛作用较好,效果显著,可在儿科临床推广使用。     

Bayesian measurement‐error‐driven hidden Markov regression model for calibrating the effect of covariates on multistate outcomes: Application to androgenetic alopecia

Multistate Markov regression models used for quantifying the effect size of state‐specific covariates pertaining to the dynamics of multistate outcomes have gained popularity. However, the measurements of multistate outcome are prone to the errors of classification, particularly when a population‐based survey/research is involved with proxy measurements of outcome due to cost consideration. Such a misclassification may affect the effect size of relevant covariates such as odds ratio used in the field of epidemiology. We proposed a Bayesian measurement‐error‐driven hidden Markov regression model for calibrating these biased estimates with and without a 2‐stage validation design. A simulation algorithm was developed to assess various scenarios of underestimation and overestimation given nondifferential misclassification (independent of covariates) and differential misclassification (dependent on covariates). We applied our proposed method to the community‐based survey of androgenetic alopecia and found that the effect size of the majority of covariate was inflated after calibration regardless of which type of misclassification. Our proposed Bayesian measurement‐error‐driven hidden Markov regression model is practicable and effective in calibrating the effects of covariates on multistate outcome, but the prior distribution on measurement errors accrued from 2‐stage validation design is strongly recommended.     

Use of geocoding in managed care settings to identify quality disparities

Tracking quality-of-care measures is essential for improving care, particularly for vulnerable populations. Although managed care plans routinely track quality measures, few examine whether their performance differs by enrollee race/ethnicity or socioeconomic status (SES), in part because plans do not collect that information. We show that plans can begin examining and targeting potential disparities using indirect measures of enrollee race/ethnicity and SES based on geocoding. Using such measures, we demonstrate disparities within both Medicare+Choice and commercial plans on Health Plan Employer Data and Information Set (HEDIS) measures of diabetes and cardiovascular care, including instances in which race/ethnicity and SES have distinct effects.     

综合护理对小儿白血病腰穿和骨穿患者依从性的影响

目的:研究并分析对小儿白血病患者使用综合护理后对其腰穿和骨穿依从性的影响效果.方法:收集小儿白血病患者共98例,按照完全随机化分组原则将其分为对照组(49例)和观察组(49例),对照组接受常规护理,观察组联合综合护理,将两组依从性、疼痛控制情况、不良反应发生率进行观察和对比.结果:观察组患儿的依从性比对照组更高;观察组的疼痛控制情况显著优于对照组;观察组的不良反应发生率显著低于对照组(P均<0.05).结论:在小儿白血病患者的腰穿和骨穿护理过程中,综合护理能够显著提升患儿的依从性,缓解患儿痛苦并减少不良反应的发生风险,值得推广应用.     

Use of Medicare data to identify incident breast cancer cases

Surveillance, Epidemiology and End Results (SEER) data from the National Cancer Institute (NCI) provide reliable information about cancer incidence. However, because SEER data are geographically limited and have a 2-year time lag, we evaluated whether Medicare data could provide timely information on cancer incidence. Comparing Medicare women hospitalized for breast cancer with women reported to SEER, Medicare data had high specificity (96.6 percent), yet low sensitivity (59.4 percent). We conclude that Medicare hospitalization data can identify incident cases for cancers that usually require inpatient hospitalization. For cancers that often only receive outpatient treatment, such as breast cancer, additional Medicare data, such as physician bills, are needed to understand the entirety of treatment practices.     

Use of isotope ratios to identify sources contributing to pediatric lead poisoning in Peru

In 1998, a school-based blood lead level (BLL) survey of 2,510 children, conducted in Lima and Callao, Peru, revealed elevated BLLs in children from 2 Callao schools (mean BLL = 25.6 microg/dl; n = 314) and in children from Callao overall (mean BLL = 15.2 microg/dl; n = 898), compared with children from Lima (mean BLL = 7.1 microg/dl; n = 1,612). Public health officials at Peru's Direccion General de Salud Ambiental (DIGESA) hypothesized that a possible source of the elevated pediatric BLLs observed in Callao was a large depository near the port where mineral concentrates are stored prior to shipment. The U.S. Centers for Disease Control and Prevention worked with DIGESA to identify source(s) that contributed to the pediatric lead poisonings by comparing isotopic profiles of lead in blood, mineral, gasoline, and air filter samples. The lead isotope ratio (IR) observed in mineral samples from the depository in Callao differed from those in gasoline samples from Lima and Callao. The blood lead IRs of children living near the depository were similar to the IRs of the mineral samples and different from the IRs of the gasoline samples, suggesting that lead from the depository-and not gasoline-was the primary source of lead in these children. Lead IR analysis of regional air filter samples supported these findings.     

Use of a structured diagnostic interview to identify depressive episodes in an epidemiologic study: a posteriori internal validation

BACKGROUND: During these last years, many structured and standardized diagnostic interviews have been developed in order to identify psychiatric disorders in a standardized way. These tools enable a systematic investigation of these disorders according to international classifications. Their main drawback is to be long. To assess the care of depression, we used a shorter and more simple tool: the Mini International Neuropsychiatric Interview (MINI) to identify depressive subjects. METHOD: The study was conducted in the Gazel cohort from the French National Electricity and Gas Company. A stratified sample of 2394 civil servants selected in order to over-represent depressive subjects was asked to answer to the MINI interview through a phone interview. An epidemiological and statistical analysis was performed to test the MINI internal validity: prevalence of depressive disorders using different threshold of diagnosis (number of symptoms required to identify someone as depressive), frequency of different symptoms, variability between investigators and potential biases. RESULTS: Respondents to the phone interview (1108 civil servants) had more often presented depression markers for the last 5 years. Prevalence of depressive episodes changed little when we varied the threshold of diagnosis and did not stress any threshold problem. The variability between investigators was important, but the estimation of prevalence remained stable when we excluded extreme rates of prevalence. The choice of a classification system affected the prevalence estimation. Using the Diagnostic and Statistical Manual of Mental Disorders (DSM IV) from the American Psychiatric Association, the prevalence of depressive episodes was lower and closer to the estimations shown in the literature than using the International Classification of Disease (ICD 10). Moreover, the stratification assigned very unbalanced weights to the stratification strata. By excluding depressive episodes observed in the stratum "control" (no depression "marker" from 1989 to 1994 in the database), the prevalence was very lower, whatever the classification was. Finally, factors which appeared linked to care of depression with the ICD definition remained the same when the DSM diagnosis definition was used, and relative risks were quite similar. CONCLUSION: The MINI appears to be a short and simple tool, suited to the epidemiological studies. This analysis does not highlight any failure in the internal consistency of the MINI. The remaining question is what the MINI really measures, particularly comparing to a psychiatrist's diagnosis.     

Use of multivariate statistics to identify unreliable data obtained using CASA

In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.     

Use of malaria rapid diagnostic test to identify Plasmodium knowlesi infection

Reports of human infection with Plasmodium knowlesi, a monkey malaria, suggest that it and other nonhuman malaria species may be an emerging health problem. We report the use of a rapid test to supplement microscopic analysis in distinguishing the 5 malaria species that infect humans.