Speed
40 days to first decision for all manuscripts (Median)
60 days to first decision for reviewed manuscripts only (Median)
Usage
128,292 Downloads (2021)
482 Altmetric mentions (2021)
Page 3 of 3
Chest X-ray has been the standard imaging method for patients suspected of non-traumatic pulmonary disease at the emergency department (ED) for years. Recently, ultra-low-dose chest computed tomography (ULD ch...
Influenza is an acute viral infection of the respiratory tract. A rapid confirmatory diagnosis of influenza is important, since it is highly transmissible and outbreaks of influenza within the hospital setting...
The risk reclassification table assesses clinical performance of a biomarker in terms of movements across relevant risk categories. The Reclassification- Calibration (RC) statistic has been developed for binar...
Competing risks occur when populations may experience outcomes that either preclude or alter the probability of experiencing the main study outcome(s). Many standard survival analysis methods do not account fo...
Over the past few decades, interest in biomarkers to enhance predictive modeling has soared. Methodology for evaluating these has also been an active area of research. There are now several performance measure...
Diagnosing pulmonary embolism in suspected patients is notoriously difficult as signs and symptoms are non-specific. Different diagnostic strategies have been developed, usually combining clinical probability ...
Diagnostic tests’ impact on patient outcomes and health processes is potentially large, and proper evaluations before widespread adoption are warranted. Such evaluations are challenged by the fact that tests c...
An important aim of clinical prediction models is to positively impact clinical decision making and subsequent patient outcomes. The impact on clinical decision making and patient outcome can be quantified in ...
Biomarker studies may involve an ordinal outcome, such as no, mild, or severe disease. There is often interest in predicting one particular level of the outcome due to its clinical significance.
Many measures of prediction accuracy have been developed. However, the most popular ones in typical medical outcome prediction settings require additional investigation of calibration.
Head injury is an extremely common clinical presentation to hospital emergency departments (EDs). Ninety-five percent of patients present with an initial Glasgow Coma Scale (GCS) score of 13–15, indicating a n...
In literature, not much emphasis has been placed on methods for analyzing repeatedly measured independent variables, even less so for the use in prediction modeling specifically. However, repeated measurements...
Prognostic models incorporating survival analysis predict the risk (i.e., probability) of experiencing a future event over a specific time period. In 2002, Royston and Parmar described a type of flexible param...
Clinical prediction rules (CPRs) should be externally validated by independent researchers. Although there are many cardiovascular CPRs, most have not been externally validated. It is not known why some CPRs a...
Presenting results of diagnostic test accuracy research so that it is accessible to users is challenging. Commonly used accuracy measures (e.g. sensitivity and specificity) are poorly understood by health prof...
Unexpected weight loss is a symptom of serious disease in primary care, for example between 1 in 200 and 1 in 30 patients with unexpected weight loss go on to develop cancer. However, it remains unclear how an...
Surrogate outcomes are often utilized when disease outcomes are difficult to directly measure. When a biological threshold effect exists, surrogate outcomes may only represent disease in specific subpopulation...
Clinical predictive models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision-making and individualize care. The Tufts Predictive Analytics and Comparative Effectiv...
A variety of statistics have been proposed as tools to help investigators assess the value of diagnostic tests or prediction models. The Brier score has been recommended on the grounds that it is a proper scor...
Research on prognostic prediction models frequently uses data from routine healthcare. However, potential misclassification of predictors when using such data may strongly affect the studied associations. Ther...
Disease prevalence is rarely explicitly considered in the early stages of the development of novel prognostic tests. Rather, researchers use the area under the receiver operating characteristic (AUROC) as the ...
Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed t...
Ignoring treatments in prognostic model development or validation can affect the accuracy and transportability of models. We aim to quantify the extent to which the effects of treatment have been addressed in ...
Improved dementia identification is a global health priority, and general practitioners (GPs) are often the first point of contact for people with concerns about their cognition. However, GPs often express unc...
Diagnostic clinical prediction rules (CPRs) are worthwhile if they improve patient outcomes or provide benefits such as reduced resource use, without harming patients. We conducted a systematic review to asses...
Stability in baseline risk and estimated predictor effects both geographically and temporally is a desirable property of clinical prediction models. However, this issue has received little attention in the met...
The use of multinomial logistic regression models is advocated for modeling the associations of covariates with three or more mutually exclusive outcome categories. As compared to a binary logistic regression ...
The purpose of the predictors for major cardiovascular outcomes in stable ischaemic heart disease (PREMAC) study is exploratory and hypothesis generating. We want to identify biochemical quantities which—condi...
Prognosis research refers to the investigation of association between a baseline health state, patient characteristic and future outcomes. The findings of several prognostic studies can be summarized in system...
Early-onset pre-eclampsia with raised blood pressure and protein in the urine before 34 weeks’ gestation is one of the leading causes of maternal deaths in the UK. The benefits to the child from prolonging the...
Why do we need a new journal titled Diagnostic and Prognostic Research in the year 2017, in an era where communication has shifted towards instant messaging via avenues such as Twitter, blogs and Facebook and whe...
Regulatory and health technology assessment agencies have commented differently on the question whether results from enrichment studies can be used to justify to bring a test into use. We try to provide a fram...
Numerous prediction models for gestational diabetes mellitus (GDM) have been developed, but their methodological quality is unknown. The objective is to systematically review all studies describing first-trime...
Risk models often perform poorly at external validation in terms of discrimination or calibration. Updating methods are needed to improve performance of multinomial logistic regression models for risk prediction.
Prognosis research studies (e.g. those deriving prognostic models or examining potential predictors of outcome) often collect information on time-varying predictors after their intended moment of use, sometimes u...
Speed
40 days to first decision for all manuscripts (Median)
60 days to first decision for reviewed manuscripts only (Median)
Usage
128,292 Downloads (2021)
482 Altmetric mentions (2021)