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Biochemia Medica 2014The appropriate choice in study design is essential for the successful execution of biomedical and public health research. There are many study designs to choose from... (Review)
Review
The appropriate choice in study design is essential for the successful execution of biomedical and public health research. There are many study designs to choose from within two broad categories of observational and interventional studies. Each design has its own strengths and weaknesses, and the need to understand these limitations is necessary to arrive at correct study conclusions.Observational study designs, also called epidemiologic study designs, are often retrospective and are used to assess potential causation in exposure-outcome relationships and therefore influence preventive methods. Observational study designs include ecological designs, cross sectional, case-control, case-crossover, retrospective and prospective cohorts. An important subset of observational studies is diagnostic study designs, which evaluate the accuracy of diagnostic procedures and tests as compared to other diagnostic measures. These include diagnostic accuracy designs, diagnostic cohort designs, and diagnostic randomized controlled trials.Interventional studies are often prospective and are specifically tailored to evaluate direct impacts of treatment or preventive measures on disease. Each study design has specific outcome measures that rely on the type and quality of data utilized. Additionally, each study design has potential limitations that are more severe and need to be addressed in the design phase of the study. This manuscript is meant to provide an overview of study design types, strengths and weaknesses of common observational and interventional study designs.
Topics: Biomedical Research; Epidemiologic Studies; Humans; Observational Studies as Topic; Randomized Controlled Trials as Topic; Research Design; Treatment Outcome
PubMed: 24969913
DOI: 10.11613/BM.2014.022 -
Journal of the International Society of... 2022Tendinopathy is a painful condition that is prevalent in athletes as well as the general human population, and whose management is challenging. (Review)
Review
BACKGROUND
Tendinopathy is a painful condition that is prevalent in athletes as well as the general human population, and whose management is challenging.
OBJECTIVE
This systematic review aimed to evaluate the impact of nutrition on the prevention and treatment of tendinopathy.
METHODS
Searches were conducted in PubMed, EMBASE, Web of Science, and SPORTDiscus without restriction to year of publication. Studies examining the impact of exposure to nutrient intake in an adult human population on 1) prevalence/incidence of tendinopathy, 2) clinical outcomes of tendinopathy, 3) structural changes in the tendon by imaging modalities. Experimental and observational study designs written in English, Dutch, or German were eligible.
RESULTS
Nineteen studies met the inclusion criteria. The effects of the habitual diet were investigated in one study. Four studies examined the effects of exposure to alcohol. Alcohol consumption can be a potential risk factor associated with Achilles tendinopathy and rotator cuff tears, although findings were inconsistent. The use of dietary supplements was examined in fourteen studies. Among these, collagen-derived peptides were most often part of the supplements evaluated. Combining training and dietary supplements seems to induce better clinical and functional outcomes in tendinopathy.
CONCLUSION
This review demonstrates the paucity of high-quality studies and a wide variety among studies regarding nutrients, tendon location, study population, and reported outcome measures. Individual studies showed promising clinical implications for the use of dietary supplements, particularly those containing collagen-derived peptides. However, giving any definitive dietary recommendations on the prevention and treatment of tendinopathy remains elusive.
Topics: Achilles Tendon; Adult; Diet; Dietary Supplements; Humans; Nutritional Status; Observational Studies as Topic; Tendinopathy
PubMed: 35937777
DOI: 10.1080/15502783.2022.2104130 -
BMJ Quality & Safety Jul 2020Double checking medication administration in hospitals is often standard practice, particularly for high-risk drugs, yet its effectiveness in reducing medication... (Review)
Review
BACKGROUND
Double checking medication administration in hospitals is often standard practice, particularly for high-risk drugs, yet its effectiveness in reducing medication administration errors (MAEs) and improving patient outcomes remains unclear. We conducted a systematic review of studies evaluating evidence of the effectiveness of double checking to reduce MAEs.
METHODS
Five databases (PubMed, Embase, CINAHL, Ovid@Journals, OpenGrey) were searched for studies evaluating the use and effectiveness of double checking on reducing medication administration errors in a hospital setting. Included studies were required to report any of three outcome measures: an effect estimate such as a risk ratio or risk difference representing the association between double checking and MAEs, or between double checking and patient harm; or a rate representing adherence to the hospital's double checking policy.
RESULTS
Thirteen studies were identified, including 10 studies using an observational study design, two randomised controlled trials and one randomised trial in a simulated setting. Studies included both paediatric and adult inpatient populations and varied considerably in quality. Among three good quality studies, only one showed a significant association between double checking and a reduction in MAEs, another showed no association, and the third study reported only adherence rates. No studies investigated changes in medication-related harm associated with double checking. Reported double checking adherence rates ranged from 52% to 97% of administrations. Only three studies reported if and how independent and primed double checking were differentiated.
CONCLUSION
There is insufficient evidence that double versus single checking of medication administration is associated with lower rates of MAEs or reduced harm. Most comparative studies fail to define or investigate the level of adherence to independent double checking, further limiting conclusions regarding effectiveness in error prevention. Higher-quality studies are needed to determine if, and in what context (eg, drug type, setting), double checking produces sufficient benefits in patient safety to warrant the considerable resources required. CRD42018103436.
Topics: Databases, Factual; Humans; Medication Errors; Observational Studies as Topic; Pharmaceutical Preparations; Randomized Controlled Trials as Topic
PubMed: 31391315
DOI: 10.1136/bmjqs-2019-009552 -
Nature Medicine Nov 2021The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics,... (Review)
Review
The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.
Topics: Computational Biology; Dysbiosis; Humans; Microbiota; Observational Studies as Topic; Research Design; Translational Science, Biomedical
PubMed: 34789871
DOI: 10.1038/s41591-021-01552-x -
Journal of Clinical Epidemiology Nov 2016Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles... (Review)
Review
Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research.
Topics: Bias; Comparative Effectiveness Research; Epidemiologic Research Design; Humans; Observational Studies as Topic; Selection Bias; Time Factors
PubMed: 27237061
DOI: 10.1016/j.jclinepi.2016.04.014 -
Advances in Nutrition (Bethesda, Md.) Oct 2021Numerous observational studies have investigated the role of the Dietary Inflammatory Index (DII®) in chronic disease risk. The aims of this umbrella review and... (Review)
Review
Numerous observational studies have investigated the role of the Dietary Inflammatory Index (DII®) in chronic disease risk. The aims of this umbrella review and integrated meta-analyses were to systematically synthesize the observational evidence reporting on the associations between the DII and health outcomes based on meta-analyses, and to assess the quality and strength of the evidence for each associated outcome. This umbrella review with integrated meta-analyses investigated the association between the DII and a range of health outcomes based on meta-analyses of observational data. A credibility assessment was conducted for each outcome using the following criteria: statistical heterogeneity, 95% prediction intervals, evidence for small-study effect and/or excess significance bias, as well as effect sizes and P values using calculated random effects meta-analyses. In total, 15 meta-analyses reporting on 38 chronic disease-related outcomes were included, incorporating a total population of 4,360,111 subjects. Outcomes (n = 38) were examined through various study designs including case-control (n = 8), cross-sectional (n = 5), prospective (n = 5), and combination (n = 20) study designs. Adherence to a pro-inflammatory dietary pattern had a significant positive association with 27 (71%) of the included health outcomes (P value < 0.05). Using the credibility assessment, Class I (Convincing) evidence was identified for myocardial infarction only, Class II (Highly suggestive) evidence was identified for increased risk of all-cause mortality, overall risk of incident cancer, and risk of incident site-specific cancers (colorectal, pancreatic, respiratory, and oral cancers) with increasing (more pro-inflammatory) DII score. Most outcomes (n = 31) presented Class III (Suggestive) or lower evidence (Weak or No association). Pro-inflammatory dietary patterns were nominally associated with an increased risk of many chronic disease outcomes. However, the strength of evidence for most outcomes was limited. Further prospective studies are required to improve the precision of the effect size.
Topics: Diet; Humans; Meta-Analysis as Topic; Neoplasms; Observational Studies as Topic
PubMed: 33873204
DOI: 10.1093/advances/nmab037 -
BMJ (Clinical Research Ed.) Jul 2018Mendelian randomisation uses genetic variation as a natural experiment to investigate the causal relations between potentially modifiable risk factors and health...
Mendelian randomisation uses genetic variation as a natural experiment to investigate the causal relations between potentially modifiable risk factors and health outcomes in observational data. As with all epidemiological approaches, findings from Mendelian randomisation studies depend on specific assumptions. We provide explanations of the information typically reported in Mendelian randomisation studies that can be used to assess the plausibility of these assumptions and guidance on how to interpret findings from Mendelian randomisation studies in the context of other sources of evidence
Topics: Causality; Confounding Factors, Epidemiologic; Effect Modifier, Epidemiologic; Genetic Variation; Genome-Wide Association Study; Humans; Mendelian Randomization Analysis; Observational Studies as Topic; Outcome Assessment, Health Care; Public Health
PubMed: 30002074
DOI: 10.1136/bmj.k601 -
Journal of Traditional Chinese Medicine... Aug 2020To analyze clinical studies on correlations between Traditional Chinese Medicine (TCM) body constitution types and diseases published in the past 10 years, and to... (Review)
Review
OBJECTIVE
To analyze clinical studies on correlations between Traditional Chinese Medicine (TCM) body constitution types and diseases published in the past 10 years, and to provide an evidence base to support the use of such correlations for health maintenance and disease prevention.
METHODS
We searched five databases for the period April 2009 to December 2019: China National Knowledge Infrastructure Database, Wanfang Database, China Science and Technology Journal Database, PubMed and Embase. Three types of observational studies on correlation between constitution types and diseases were included: cross-sectional, case-control and cohort studies. Descriptive statistical methods were employed for data analysis.
RESULTS
A total of 1639 clinical studies were identified: 1452 (88.59%) cross-sectional studies, 115 (7.02%) case-control studies and 72 (4.39%) cohort studies covering 30 regions of China and five other countries (Malaysia, South Korea, Singapore, Thailand and France). The collection of studies comprised 19 disease categories and 333 different diseases. The 10 most commonly studied diseases were hypertension, diabetes, stroke, coronary atherosclerotic heart disease (CAHD), sleep disorders, neoplasm of the breast, dysmenorrhea, fatty liver disease, chronic viral hepatitis B and dyslipidemia. We found high distributions for each biased constitution type in different patient populations as follows: Qi-deficiency constitution in stroke, diabetes, chronic obstructive pulmonary disease, acquired immunodeficiency syndrome and hypertension; Yang-deficiency constitution in female infertility, osteoporosis, irritable bowel syndrome, gonarthrosis and dysmenorrhea; Yin-deficiency constitution in hypertension, diabetes, constipation, female climacteric states and osteoporosis; phlegm- dampness constitution in hypertension, stroke, fatty liver disease, diabetes and metabolic syndrome; damp-heat constitution in acne, chronic gastritis, chronic viral hepatitis B, human papillomavirus infection and hyperuricemia; blood-stasis constitution in CAHD, endometriosis and stroke; Qi-stagnation constitution in hyperplasia and neoplasms of the breast, insomnia, depression and thyroid nodules; and inherited-special constitution in asthma and allergic rhinitis.
CONCLUSION
Eight biased TCM constitutions were closely related to specific diseases, and could be used to guide individualized prevention and treatment. More rigorously designed studies are recommended to further verify the constitution-disease relationship.
Topics: Drug Therapy; Drugs, Chinese Herbal; Humans; Medicine, Chinese Traditional; Observational Studies as Topic; Treatment Outcome
PubMed: 32744037
DOI: 10.19852/j.cnki.jtcm.2020.04.019 -
Statistics in Medicine Dec 2015The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse... (Review)
Review
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in which we found that the use of IPTW has increased rapidly in recent years, but that in the most recent year, a majority of studies did not formally examine whether weighting balanced measured covariates between treatment groups. We then proceed to describe a suite of quantitative and qualitative methods that allow one to assess whether measured baseline covariates are balanced between treatment groups in the weighted sample. The quantitative methods use the weighted standardized difference to compare means, prevalences, higher-order moments, and interactions. The qualitative methods employ graphical methods to compare the distribution of continuous baseline covariates between treated and control subjects in the weighted sample. Finally, we illustrate the application of these methods in an empirical case study. We propose a formal set of balance diagnostics that contribute towards an evolving concept of 'best practice' when using IPTW to estimate causal treatment effects using observational data.
Topics: Humans; Models, Statistical; Monte Carlo Method; Observational Studies as Topic; Outcome Assessment, Health Care; Propensity Score
PubMed: 26238958
DOI: 10.1002/sim.6607 -
BMJ (Clinical Research Ed.) Oct 2021Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often...
Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often hampered by inadequate reporting. Reporting guidelines help authors effectively communicate all critical information about what was done and what was found. STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) assists authors in reporting their MR research clearly and transparently. Adopting STROBE-MR should help readers, reviewers, and journal editors evaluate the quality of published MR studies. This article explains the 20 items of the STROBE-MR checklist, along with their meaning and rationale, using terms defined in a glossary. Examples of transparent reporting are used for each item to illustrate best practices.
Topics: Epidemiologic Research Design; Guidelines as Topic; Humans; Mendelian Randomization Analysis; Observational Studies as Topic
PubMed: 34702754
DOI: 10.1136/bmj.n2233