194 research outputs found
Studies of prevalence: how a basic epidemiology concept has gained recognition in the COVID-19 pandemic.
BACKGROUND
Prevalence measures the occurrence of any health condition, exposure or other factors related to health. The experience of COVID-19, a new disease caused by SARS-CoV-2, has highlighted the importance of prevalence studies, for which issues of reporting and methodology have traditionally been neglected.
OBJECTIVE
This communication highlights key issues about risks of bias in the design and conduct of prevalence studies and in reporting them, using examples about SARS-CoV-2 and COVID-19.
SUMMARY
The two main domains of bias in prevalence studies are those related to the study population (selection bias) and the condition or risk factor being assessed (information bias). Sources of selection bias should be considered both at the time of the invitation to take part in a study and when assessing who participates and provides valid data (respondents and non-respondents). Information bias appears when there are systematic errors affecting the accuracy and reproducibility of the measurement of the condition or risk factor. Types of information bias include misclassification, observer and recall bias. When reporting prevalence studies, clear descriptions of the target population, study population, study setting and context, and clear definitions of the condition or risk factor and its measurement are essential. Without clear reporting, the risks of bias cannot be assessed properly. Bias in the findings of prevalence studies can, however, impact decision-making and the spread of disease. The concepts discussed here can be applied to the assessment of prevalence for many other conditions.
CONCLUSIONS
Efforts to strengthen methodological research and improve assessment of the risk of bias and the quality of reporting of studies of prevalence in all fields of research should continue beyond this pandemic
Molecular Interactions Of Tectonin Proteins In Host and Pathogen Recognition
Ph.DDOCTOR OF PHILOSOPH
Surviving, But Not Thriving: The Politics of Care and the Experience of Motherhood in Academia
How to update a living systematic review and keep it alive during a pandemic: a practical guide.
BACKGROUND
The covid-19 pandemic has highlighted the role of living systematic reviews. The speed of evidence generated during the covid-19 pandemic accentuated the challenges of managing high volumes of research literature.
METHODS
In this article, we summarise the characteristics of ongoing living systematic reviews on covid-19, and we follow a life cycle approach to describe key steps in a living systematic review.
RESULTS
We identified 97 living systematic reviews on covid-19, published up to 7th November 2022, which focused mostly on the effects of pharmacological interventions (n = 46, 47%) or the prevalence of associated conditions or risk factors (n = 30, 31%). The scopes of several reviews overlapped considerably. Most living systematic reviews included both observational and randomised study designs (n = 45, 46%). Only one-third of the reviews has been updated at least once (n = 34, 35%). We address practical aspects of living systematic reviews including how to judge whether to start a living systematic review, methods for study identification and selection, data extraction and evaluation, and give recommendations at each step, drawing from our own experience. We also discuss when it is time to stop and how to publish updates.
CONCLUSIONS
Methods to improve the efficiency of searching, study selection, and data extraction using machine learning technologies are being developed, their performance and applicability, particularly for reviews based on observational study designs should improve, and ways of publishing living systematic reviews and their updates will continue to evolve. Finally, knowing when to end a living systematic review is as important as knowing when to start
Vulvovaginal yeast infections during pregnancy and perinatal outcomes: systematic review and meta-analysis.
BACKGROUND
Vulvovaginal yeast infections in pregnancy are common and can cause extensive inflammation, which could contribute to adverse pregnancy outcomes. Symptomatic yeast infections are likely to cause more inflammation than asymptomatic. The objective of this study was to investigate associations between symptomatic and asymptomatic vulvovaginal yeast infections in pregnancy and perinatal outcomes.
METHODS
We did a systematic review and searched eight databases until 01 July 2022. We included studies reporting on pregnant women with and without laboratory confirmed vulvovaginal yeast infection and preterm birth or eight other perinatal outcomes. We used random effects meta-analysis to calculate summary odds ratios (OR), 95% confidence intervals (CI) and prediction intervals for the association between yeast infection and outcomes. We described findings from studies with multivariable analyses. We assessed the risk of bias using published tools.
RESULTS
We screened 3909 references and included 57 studies. Only 22/57 studies reported information about participant vulvovaginal symptoms. Preterm birth was an outcome in 35/57 studies (49,161 women). In 32/35 studies with available data, the summary OR from univariable analyses was 1.01 (95% CI 0.84-1.21, I2 60%, prediction interval 0.45-2.23). In analyses stratified by symptom status, we found ORs of 1.44 (95% CI 0.92-2.26) in two studies with ≥ 50% symptomatic participants, 0.84 (95% CI 0.45-1.58) in seven studies with < 50% symptomatic participants, and 1.12 (95% CI 0.94-1.35) in four studies with asymptomatic participants. In three studies with multivariable analysis, adjusted ORs were greater than one but CIs were compatible with there being no association. We did not find associations between vulvovaginal yeast infection and any secondary outcome. Most studies were at high risk of bias in at least one domain and only three studies controlled for confounding.
CONCLUSIONS
We did not find strong statistical evidence of an increased risk for preterm birth or eight other adverse perinatal outcomes, in pregnant women with either symptomatic or asymptomatic vulvovaginal yeast infection. The available evidence is insufficient to make recommendations about testing and treatment of vulvovaginal yeast infection in pregnancy. Future studies should assess vulvovaginal symptoms, yeast organism loads, concomitant vaginal or cervical infections, and microbiota using state-of-the-art diagnostics.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO CRD42020197564
Compromised Motor Dexterity Confounds Processing Speed Task Outcomes in Stroke Patients
Most conventional measures of information processing speed require motor responses to facilitate performance. However, although not often addressed clinically, motor impairment, whether due to age or acquired brain injury, would be expected to confound the outcome measure of such tasks. The current study recruited 29 patients (20 stroke and 9 transient ischemic attack) with documented reduction in dexterity of the dominant hand, and 29 controls, to investigate the extent to which 3 commonly used processing speed measures with varying motor demands (a Visuo-Motor Reaction Time task, and the Wechsler Adult Intelligence Scale-IV Symbol Search and Coding subtests) may be measuring motor-related speed more so than cognitive speed. Analyses include correlations between indices of cognitive and motor speed obtained from two other tasks (Inspection Time and Pegboard task, respectively) with the three speed measures, followed by hierarchical regressions to determine the relative contribution of cognitive and motor speed indices toward task performance. Results revealed that speed outcomes on tasks with relatively high motor demands, such as Coding, were largely reflecting motor speed in individuals with reduced dominant hand dexterity. Thus, findings indicate the importance of employing measures with minimal motor requirements, especially when the assessment of speed is aimed at understanding cognitive rather than physical function
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