ABSTRACT
Race-based and skin pigmentation-related inaccuracies in pulse oximetry have recently been highlighted in several large electronic health record-based retrospective cohort studies across diverse patient populations and healthcare settings. Overestimation of oxygen saturation by pulse oximeters, particularly in hypoxic states, is disparately higher in Black compared to other racial groups. Compared to adult literature, pediatric studies are relatively few and mostly reliant on birth certificates or maternal race-based classification of comparison groups. Neonates, infants, and young children are particularly susceptible to the adverse life-long consequences of hypoxia and hyperoxia. Successful neonatal resuscitation, precise monitoring of preterm and term neonates with predominantly lung pathology, screening for congenital heart defects, and critical decisions on home oxygen, ventilator support and medication therapies, are only a few examples of situations that are highly reliant on the accuracy of pulse oximetry. Undetected hypoxia, especially if systematically different in certain racial groups may delay appropriate therapies and may further perpetuate health care disparities. The role of biological factors that may differ between racial groups, particularly skin pigmentation that may contribute to biased pulse oximeter readings needs further evaluation. Developmental and maturational changes in skin physiology and pigmentation, and its interaction with the operating principles of pulse oximetry need further study. Importantly, clinicians should recognize the limitations of pulse oximetry and use additional objective measures of oxygenation (like co-oximetry measured arterial oxygen saturation) where hypoxia is a concern.
Subject(s)
Oximetry , Skin Pigmentation , Humans , Infant, Newborn , Infant , Healthcare Disparities , Child, Preschool , Hypoxia/diagnosis , Racial Groups , Oxygen Saturation/physiologyABSTRACT
Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 (N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 (N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.
Subject(s)
Gait , Running , Humans , Running/physiology , Gait/physiology , Male , Biomechanical Phenomena/physiology , Female , Adult , Wearable Electronic Devices , Young Adult , Gait Analysis/methodsABSTRACT
BACKGROUND: There is a lack of consensus on a reference range for ionized magnesium (iMg2+) in blood as a measure of the status of circulating iMg2+ for the screening of populations. OBJECTIVES: We estimated the reference range of iMg2+ levels for healthy adult populations and the ranges for populations with cardiovascular disease (CVD), type 2 diabetes, hypertension, and renal disease. We also estimated 95% ranges for circulating magnesium (Mg) in healthy and those with cardiometabolic diseases. METHODS: We searched Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and Embase through 24 July, 2020 to identify articles. We included English, peer-reviewed, randomized controlled trials, prospective and retrospective cohort studies, case-control studies, and cross-sectional studies that measured iMg2+ in blood or circulating Mg at baseline. The protocol was registered on PROSPERO (CRD42020216100). Estimated ranges were calculated by employing a frequentist random-effects model using extracted (or calculated) means and SDs from each included study. We determined the 95% confidence interval of the pooled mean. RESULTS: A total of 95 articles were included with 53 studies having data for healthy participants and 42 studies having data for participants with cardiometabolic diseases. The estimated reference range for iMg2+ for healthy populations was 0.40-0.68 mmol/L, 0.38-0.64 mmol/L for CVD, 0.34-0.66 mmol/L for type 2 diabetes, 0.39-1.04 mmol/L for hypertension, and 0.40-0.76 mmol/L for renal disease. For circulating Mg, the estimated range was 0.72-1.0 mmol/L for healthy adults, 0.56-1.05 mmol/L for CVD, 0.58-1.14 mmol/L for type 2 diabetes, 0.60-1.08 mmol/L for hypertension, and 0.59-1.26 mmol/L for renal disease. CONCLUSIONS: Estimated reference ranges for cardiometabolic disease states for both iMg2+ and circulating Mg were broad and overlapped with the estimated range for healthy populations (0.40-0.68 mmol/L). Further studies should evaluate whether iMg2+ can be used as a biomarker of cardiometabolic disease.
Subject(s)
Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Hypertension , Adult , Humans , Magnesium , Reference Values , Prospective Studies , Cross-Sectional Studies , Retrospective StudiesABSTRACT
To date, nutritional epidemiology has relied heavily on relatively weak methods including simple observational designs and substandard measurements. Despite low internal validity and other sources of bias, claims of causality are made commonly in this literature. Nutritional epidemiology investigations can be improved through greater scientific rigor and adherence to scientific reporting commensurate with research methods used. Some commentators advocate jettisoning nutritional epidemiology entirely, perhaps believing improvements are impossible. Still others support only normative refinements. But neither abolition nor minor tweaks are appropriate. Nutritional epidemiology, in its present state, offers utility, yet also needs marked, reformational renovation. Changing the status quo will require ongoing, unflinching scrutiny of research questions, practices, and reporting-and a willingness to admit that "good enough" is no longer good enough. As such, a workshop entitled "Toward more rigorous and informative nutritional epidemiology: the rational space between dismissal and defense of the status quo" was held from July 15 to August 14, 2020. This virtual symposium focused on: (1) Stronger Designs, (2) Stronger Measurement, (3) Stronger Analyses, and (4) Stronger Execution and Reporting. Participants from several leading academic institutions explored existing, evolving, and new better practices, tools, and techniques to collaboratively advance specific recommendations for strengthening nutritional epidemiology.
Subject(s)
Nutrition Assessment , Research Design , Humans , CausalityABSTRACT
We were interested to read the report by Halenova et al. [...].
Subject(s)
Obesity , Water , Adjuvants, Pharmaceutic , Animals , Deuterium/pharmacology , Diet , Obesity/drug therapy , Obesity/etiology , Rats , Water/pharmacologyABSTRACT
Randomization is an important tool used to establish causal inferences in studies designed to further our understanding of questions related to obesity and nutrition. To take advantage of the inferences afforded by randomization, scientific standards must be upheld during the planning, execution, analysis, and reporting of such studies. We discuss ten errors in randomized experiments from real-world examples from the literature and outline best practices for their avoidance. These ten errors include: representing nonrandom allocation as random, failing to adequately conceal allocation, not accounting for changing allocation ratios, replacing subjects in nonrandom ways, failing to account for non-independence, drawing inferences by comparing statistical significance from within-group comparisons instead of between-groups, pooling data and breaking the randomized design, failing to account for missing data, failing to report sufficient information to understand study methods, and failing to frame the causal question as testing the randomized assignment per se. We hope that these examples will aid researchers, reviewers, journal editors, and other readers to endeavor to a high standard of scientific rigor in randomized experiments within obesity and nutrition research.
Subject(s)
Nutritional Sciences/standards , Obesity/diet therapy , Public Reporting of Healthcare Data , Research Design/standards , Humans , Nutritional Sciences/methods , Nutritional Sciences/trends , Obesity/physiopathology , Practice Guidelines as TopicABSTRACT
Dairy has been described as everything from a superfood to a poison; yet, arguments, assumptions, and data justifying these labels are not always clear. We used an issue-based information system, "dialogue mapping™," to summarize scientific points of a live panel discussion on the putative effects of dairy on cardiovascular diseases (CVD) from a day-long session among experts in nutrition and CVD. Dialogue mapping captures relations among ideas to explicitly, logically, and visually connect issues/questions, ideas, pro/con arguments, and agreements, even if discussed at different times. Experts discussed two propositions: for CVD risk, consumption of full-fat dairy products 1) should be minimized, in part because of their saturated fat content, or 2) need not be minimized, despite their saturated fat content. The panel discussed the dairy-CVD relation through blood lipids, diabetes, obesity, energy balance, blood pressure, dairy bioactives, biobehavioral components, and other putative causal pathways. Associations and effects reported in the literature have varied by fat content of dairy elements considered, study design, intake methods, and biomarker versus disease outcomes. Two conceptual topics emerged from the discussion: 1) individual variability: whether recommendations should be targeted only to those at high CVD risk; 2) quality of evidence: whether data on dairy-CVD relations are strong enough for reliable conclusions-positive, negative, or null. Future procedural improvements for science dialog mapping include using singular rather than competing propositions for discussion.
Subject(s)
Cardiovascular Diseases , Cardiovascular System , Dairy Products , Diet , Dietary Fats , Humans , Obesity , Risk FactorsABSTRACT
Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and system-level approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge.
Subject(s)
Data Collection , Research Design , Scientific Experimental Error , Statistics as Topic/standards , Data Collection/standards , Data Collection/statistics & numerical data , Humans , Quality Control , Reproducibility of Results , Research Design/standards , Research Design/statistics & numerical data , Science/standards , Science/statistics & numerical dataABSTRACT
BACKGROUND/OBJECTIVES: Genetic contributors to obesity are frequently studied in murine models. However, the sample sizes of these studies are often small, and the data may violate assumptions of common statistical tests, such as normality of distributions. We examined whether, in these cases, type I error rates and power are affected by the choice of statistical test. SUBJECTS/METHODS: We conducted "plasmode"-based simulation using empirical data on body mass (weight) from murine genetic models of obesity. For the type I error simulation, the weight distributions were adjusted to ensure no difference in means between control and mutant groups. For the power simulation, the distributions of the mutant groups were shifted to ensure specific effect sizes. Three to twenty mice were resampled from the empirical distributions to create a plasmode. We then computed type I error rates and power for five common tests on the plasmodes: Student's t test, Welch's t test, Wilcoxon rank sum test (aka, Mann-Whitney U test), permutation test, and bootstrap test. RESULTS: We observed type I error inflation for all tests, except the bootstrap test, with small samples (≤5). Type I error inflation decreased as sample size increased (≥8) but remained. The Wilcoxon test should be avoided because of heterogeneity of distributions. For power, a departure from the reference was observed with small samples for all tests. Compared with the other tests, the bootstrap test had less power with small samples. CONCLUSIONS: Overall, the bootstrap test is recommended for small samples to avoid type I error inflation, but this benefit comes at the cost of lower power. When sample size is large enough, Welch's t test is recommended because of high power with minimal type I error inflation.
Subject(s)
Computer Simulation , Data Interpretation, Statistical , Models, Genetic , Obesity/genetics , Animals , Mice , Sample Size , Statistics, NonparametricABSTRACT
Randomized Controlled Trials (RCTs) are the best method to determine causal effects for treatments if they are well done and well reported. Good evidence about proposed treatments for obesity is needed, and Hsieh et al. (Biomed Eng Online 17:149, 2018) are to be commended for putting moxibustion to the test. However, careful evaluation of the paper reveals inconsistencies and apparent reporting errors, which raise doubts about conclusions from the study.
Subject(s)
Body Weight , Data Analysis , Moxibustion , Obesity, Abdominal/therapy , Randomized Controlled Trials as Topic , Research Design , Humans , Treatment OutcomeABSTRACT
We read the recent article in Psychology of Sport and Exercise by Liu et al. ("A randomized controlled trial of coordination exercise on cognitive function in obese adolescents") with great interest. Our interest in the article stemmed from the extraordinary differences in obesity-related outcomes reported in response to a rope-jumping intervention. We requested the raw data from the authors to confirm the results and, after the journal editors reinforced our request, the authors graciously provided us with their data. We share our evaluation of the original data herein, which includes concerns that weight and BMI loss by the intervention appears extraordinary in both magnitude and aspects of the distributions. We request that the authors address our findings by providing explanations of the extraordinary data or correcting any errors that may have occurred in the original report, as appropriate.
Subject(s)
Overweight , Pregnancy Complications , Female , Pregnancy , Humans , Pregnant Women , Food, Processed , Weight Gain , CounselingSubject(s)
Obesity, Abdominal , Sex Characteristics , Humans , Male , Female , Child , Obesity , Lipoproteins , Lipoproteins, LDLABSTRACT
Alkynylboranes show unprecedented reactivity in their [4+2] cycloaddition of sydnones offering access to fully substituted pyrazoles within a few hours at room temperature. This method delivers synthetically valuable pyrazoleboranes with complete control of regioselectivity, and these intermediates can be further elaborated through functionalization of the C-B bond.
ABSTRACT
The regioselective condensation of hydrazines and ynone trifluoroborates provides access to a range of pyrazole 5-trifluoroborates. The stability of the borate unit allows chemoselective halogenation of the heteroaromatic ring, thereby delivering pyrazole scaffolds that allow orthogonal functionalization at C5 and C4. The modular reactivity of these intermediates is exemplified by cross-coupling reactions, enabling regiocontrolled synthesis of fully functionalized pyrazole derivatives.
Subject(s)
Editorial Policies , Peer Review, Research/methods , Peer Review, Research/standards , Periodicals as Topic/standards , Research Design/statistics & numerical data , Retraction of Publication as Topic , Access to Information , Humans , Periodicals as Topic/economics , Reproducibility of ResultsABSTRACT
BACKGROUND: Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information. METHODS: Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations. RESULTS: We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations. CONCLUSIONS: False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.).
Subject(s)
Energy Intake , Exercise/physiology , Obesity , Weight Loss , Breast Feeding , Diet, Reducing , Energy Metabolism , Environment , Female , Goals , Humans , Male , Obesity/physiopathology , Obesity/prevention & control , Obesity/therapyABSTRACT
The direct arylation of the C4 position of both N-alkyl- and N-arylsydnones with aryl/heteroaryl chlorides has been realized. The reaction is quite general and allows access to a wide range of 4-substituted sydnones. Yields of more challenging substrates can be improved through the use of aryl bromides.