Diagnostic Accuracy and User-Friendliness of 5 Point-of-Care D-Dimer Tests for the Exclusion of Deep Vein Thrombosis

Geersing, Geert‐Jan; Toll, D. B.; Janssen, Kristel J.M.; Oudega, Ruud; Blikman, Marloes J.C.; Wijland, René; Vooght, Karen M.K. de; Hoes, Arno W.; Moons, Karel G.M.

doi:10.1373/clinchem.2010.147892

Cited by 39 publications

(32 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Indeed, EMS usually pre-notify us the BP laterality, which sometimes lets the AAD diagnosis in suspected acute stroke patients at our center. Recently available quantitative D-dimer point-of-care tests [33] have a potential to shorten the delay and improve the measurability.…”

Section: Predictors For Aad In Patients Presenting With Aismentioning

confidence: 99%

Frequency and Detection of Stanford Type A Aortic Dissection in Hyperacute Stroke Management

Sakamoto¹,

Koga²,

Ohara³

et al. 2016

Cerebrovasc Dis

View full text Add to dashboard Cite

Background and Purpose: Acute Stanford type A aortic dissection (AAD) is a devastating aortic disease, and prompt diagnosis is sometimes difficult to make. Identification of AAD in suspected acute stroke patients is especially challenging. Nevertheless, the frequencies and predictive factors of AAD in suspected acute stroke patients have not been well investigated. The aim of this study was to elucidate the prevalence of and predictors for AAD in patients with suspected acute stroke. Methods: From January 2012 through January 2013, consecutive patients who visited our emergency department (ED) due to suspected acute (<24 h from onset) stroke were retrospectively enrolled. Clinical parameters including systolic blood pressure (SBP) and laboratory data were collected. Frequency of AAD in suspected acute stroke patients and acute ischemic stroke (AIS) subjects were assessed, and factors associated with AAD among AIS patients were investigated. Results: A total of 1,637 patients were included in this study. Five patients (0.31%, 95% CI 0.04-0.57) were diagnosed as having AAD. The prevalence of AAD in all AIS individuals during the study period was 1.09% (95% CI 0.14-2.05), and AAD accounted for 1.70% (95% CI 0.05-3.36) of AIS patients who appeared at the hospital within 4 h from onset. Most AAD patients presented with disturbed consciousness, and none of the AAD patients complained of chest pain. Neck ultrasonography detected an intimal flap in AAD patients. Two AAD cases died soon after ED arrival. The remaining 3 were promptly diagnosed as having AAD in the ED and underwent emergency surgery; all were discharged with only mild neurological symptoms. Low SBP in the right arm (cut-off value ≤110 mm Hg, sensitivity 100%, specificity 94.4%) and high D-dimer level (cut-off value ≥5.0 μg/ml, sensitivity 100%, specificity 91.7%) had high predictive values for detecting AAD in patients with AIS presenting within 4 h from onset. Conclusions: AAD was seen in 0.31% of suspected acute stroke patients and 1.70% of AIS patients presenting within 4 h from onset. AAD patients who were initially suspected as having acute stroke had severe neurological symptoms, including disturbance of consciousness, did not complain of typical chest pain, and when emergency surgery was performed, favorable neurological and survival outcomes were achieved. Low SBP in the right arm and high D-dimer level could predict AAD.

show abstract

Section: Predictors For Aad In Patients Presenting With Aismentioning

confidence: 99%

Frequency and Detection of Stanford Type A Aortic Dissection in Hyperacute Stroke Management

Sakamoto¹,

Koga²,

Ohara³

et al. 2016

Cerebrovasc Dis

View full text Add to dashboard Cite

show abstract

“…User-friendliness of automated urinalysis was assessed using a standardised user-friendliness questionnaire 10 consisting of five questions concerning the userfriendliness of the analyser, test procedure and the susceptibility of flaws. Subsequently, practice assistants were asked if a POCT urine analyser was deemed useful in their daily practice and if they thought that using such an analyser would improve their productivity and efficiency, and whether the analyser would make urine analysis more precise.…”

Section: User-friendlinessmentioning

confidence: 99%

Prospective, observational study comparing automated and visual point-of-care urinalysis in general practice

Delft¹,

Goedhart²,

Spigt

et al. 2016

BMJ Open

View full text Add to dashboard Cite

ObjectivePoint-of-care testing (POCT) urinalysis might reduce errors in (subjective) reading, registration and communication of test results, and might also improve diagnostic outcome and optimise patient management. Evidence is lacking. In the present study, we have studied the analytical performance of automated urinalysis and visual urinalysis compared with a reference standard in routine general practice.SettingThe study was performed in six general practitioner (GP) group practices in the Netherlands. Automated urinalysis was compared with visual urinalysis in these practices. Reference testing was performed in a primary care laboratory (Saltro, Utrecht, The Netherlands).Primary and secondary outcome measuresAnalytical performance of automated and visual urinalysis compared with the reference laboratory method was the primary outcome measure, analysed by calculating sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) and Cohen's κ coefficient for agreement. Secondary outcome measure was the user-friendliness of the POCT analyser.ResultsAutomated urinalysis by experienced and routinely trained practice assistants in general practice performs as good as visual urinalysis for nitrite, leucocytes and erythrocytes. Agreement for nitrite is high for automated and visual urinalysis. κ's are 0.824 and 0.803 (ranked as very good and good, respectively). Agreement with the central laboratory reference standard for automated and visual urinalysis for leucocytes is rather poor (0.256 for POCT and 0.197 for visual, respectively, ranked as fair and poor). κ's for erythrocytes are higher: 0.517 (automated) and 0.416 (visual), both ranked as moderate. The Urisys 1100 analyser was easy to use and considered to be not prone to flaws.ConclusionsAutomated urinalysis performed as good as traditional visual urinalysis on reading of nitrite, leucocytes and erythrocytes in routine general practice. Implementation of automated urinalysis in general practice is justified as automation is expected to reduce human errors in patient identification and transcribing of results.

show abstract

“…A practical way of deriving the posttest probability of disease from the prevalence (pretest probability of disease) and the diagnostic LR is to apply the Fagan nomogram (29 ). A recent example is the estimation of the probability of DVT on the basis of testing for D-dimer (30 ). Finally, it should be mentioned that the diagnostic LR of a result X equals the slope of the ROC curve at the given point.…”

Section: Likelihood Ratiomentioning

confidence: 99%

Quantifying the Accuracy of a Diagnostic Test or Marker

et al. 2012

View full text Add to dashboard Cite

BACKGROUND:In recent years, increasing focus has been directed to the methodology for evaluating (new) tests or biomarkers. A key step in the evaluation of a diagnostic test is the investigation into its accuracy. CONTENT:We reviewed the literature on how to assess the accuracy of diagnostic tests. Accuracy refers to the amount of agreement between the results of the test under evaluation (index test) and the results of a reference standard or test. The generally recommended approach is to use a prospective cohort design in patients who are suspected of having the disease of interest, in which each individual undergoes the index and same reference standard tests. This approach presents several challenges, including the problems that can arise with the verification of the index test results by the preferred reference standard test, the choice of cutoff value in case of a continuous index test result, and the determination of how to translate accuracy results to recommendations for clinical use. This first in a series of 4 reports presents an overview of the designs of singletest accuracy studies and the concepts of specificity, sensitivity, posterior probabilities (i.e., predictive values) for the presence of target disease, ROC curves, and likelihood ratios, all illustrated with empirical data from a study on the diagnosis of suspected deep venous thrombosis. Limitations of the concept of the diagnostic accuracy for a single test are also highlighted.

show abstract

Diagnostic Accuracy and User-Friendliness of 5 Point-of-Care D-Dimer Tests for the Exclusion of Deep Vein Thrombosis

Cited by 39 publications

References 30 publications

Frequency and Detection of Stanford Type A Aortic Dissection in Hyperacute Stroke Management

Frequency and Detection of Stanford Type A Aortic Dissection in Hyperacute Stroke Management

Prospective, observational study comparing automated and visual point-of-care urinalysis in general practice

Quantifying the Accuracy of a Diagnostic Test or Marker

Contact Info

Product

Resources

About