scholarly journals Inertial sensors-determined match characteristics that serve as predictors of elite, male badminton players’ performance levels

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Yahaya Abdullahi ◽  
Ben Coetzee
Keyword(s):  
Logistic Regression ◽  
High Intensity ◽  
Inertial Sensors ◽  
Characteristic Curve ◽  
Group Classification ◽  
Classification Model ◽  
Stepwise Logistic Regression ◽  
African Countries ◽  
Performance Levels ◽  
Significant Difference

The study's purpose was to establish the inertial sensors-containing device (ISCD)-determined match characteristics that predict elite, male badminton players’ performance levels. Twenty-two (22) male single players (aged: 23.39 ± 3.92 years), who represented 10 African countries, participated in the study. Players were categorized as successful and less-successful players according to the results of five championships during two seasons. ISCD units (Catapult MinimaxV4), Polar Heart Rate Transmitter Belts, and digital video cameras were used to collect match data. ISCD-determined variables were corrected for match duration, and independent t-tests, cluster analysis, and a binary forward stepwise logistic regression were used for statistical analyses. A Receiver Operating Characteristic Curve (ROCC) indicated the validity of the group classification model. High-intensity accelerations per second were identified as the only ISCD-determined variable that showed a significant difference (p = 0.05) between groups. Furthermore, only high-intensity accelerations per second (p = 0.03) and low-intensity efforts per second (p = 0.04) were identified as significant predictors of group classification, with 76.88% of players that could be classified back into their original groups by making use of the ISCD-based logistic regression formula. The ROCC showed a value of 0.87. The identification of the last-mentioned ISCD-determined variables for the attainment of badminton performances emphasizes the importance of using badminton drills and conditioning techniques to improve not only the physical fitness levels of players but also their ability to accelerate at high intensities.

scholarly journals Serum Biomarkers for Prediction of Response to Methotrexate Monotherapy in Early Rheumatoid Arthritis: Results from the SWEFOT Trial

2019 ◽  
Vol 46 (6) ◽  
pp. 555-563 ◽  
Author(s):  
Karen Hambardzumyan ◽  
Rebecca J. Bolce ◽  
Johan K. Wallman ◽  
Ronald F. van Vollenhoven ◽  
Saedis Saevarsdottir
Keyword(s):  
Rheumatoid Arthritis ◽  
Logistic Regression ◽  
Disease Activity ◽  
Early Rheumatoid Arthritis ◽  
Characteristic Curve ◽  
Serum Biomarkers ◽  
Stepwise Logistic Regression ◽  
Stepwise Logistic Regression Analysis ◽  
Baseline Serum ◽  
Baseline Levels

Objective.To investigate baseline levels of 12 serum biomarkers that constitute a multibiomarker disease activity test, as predictors of response to methotrexate (MTX) in patients with early rheumatoid arthritis (eRA).Methods.In 298 patients from the Swedish Pharmacotherapy (SWEFOT) clinical trial, baseline serum levels of 12 proteins were analyzed for association with disease activity based on the 28-joint count Disease Activity Score (DAS28) after 3 months of MTX monotherapy using uni-/multivariate logistic regression. Primary outcome was low disease activity (LDA; DAS28 ≤ 3.2).Results.Of 298 patients, 104 achieved LDA after 3 months on MTX. Four of the 12 biomarkers [C-reactive protein (CRP), leptin, tumor necrosis factor receptor I (TNF-RI), and vascular cell adhesion molecule 1 (VCAM-1)] significantly predicted LDA based on stepwise logistic regression analysis. Dichotomization of patients using receiver-operating characteristic curve analysis-based cutoffs for these biomarkers showed significantly higher proportions with LDA among patients with lower versus higher levels of CRP or leptin (40% vs 23%, p = 0.004, and 40% vs 25%, p = 0.011, respectively), as well as among those with higher versus lower levels of TNF-RI or VCAM-1 (43% vs 27%, p = 0.004, and 41% vs 25%, p = 0.004, respectively). Combined score based on these biomarkers, adjusted for known predictors of LDA (smoking, sex, and age), associated with decreased chance of LDA (adjusted OR 0.45, 95% CI 0.32–0.62).Conclusion.Low baseline levels of CRP and leptin, and high baseline levels of TNF-RI and VCAM-1 were associated with LDA after 3 months of MTX therapy in patients with eRA. Combination of these 4 biomarkers increased accuracy of prediction. [Trial registration number: NCT00764725]

scholarly journals Daptomycin Improves Outcomes Regardless of Vancomycin MIC in a Propensity-Matched Analysis of Methicillin-Resistant Staphylococcus aureus Bloodstream Infections

2016 ◽  
Vol 60 (10) ◽  
pp. 5841-5848 ◽  
Author(s):  
Kimberly C. Claeys ◽  
Evan J. Zasowski ◽  
Anthony M. Casapao ◽  
Abdalhamid M. Lagnf ◽  
Jerod L. Nagel ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Logistic Regression ◽  
Bloodstream Infections ◽  
Attributable Mortality ◽  
Stepwise Logistic Regression ◽  
Clinical Failure ◽  
Methicillin Resistant ◽  
Content Type ◽  
Vancomycin Mics ◽  
Significant Difference

ABSTRACTVancomycin remains the mainstay treatment for methicillin-resistantStaphylococcus aureus(MRSA) bloodstream infections (BSIs) despite increased treatment failures. Daptomycin has been shown to improve clinical outcomes in patients with BSIs caused by MRSA isolates with vancomycin MICs of >1 mg/liter, but these studies relied on automated testing systems. We evaluated the outcomes of BSIs caused by MRSA isolates for which vancomycin MICs were determined by standard broth microdilution (BMD). A retrospective, matched cohort of patients with MRSA BSIs treated with vancomycin or daptomycin from January 2010 to March 2015 was completed. Patients were matched using propensity-adjusted logistic regression, which included age, Pitt bacteremia score, primary BSI source, and hospital of care. The primary endpoint was clinical failure, which was a composite endpoint of the following metrics: 30-day mortality, bacteremia with a duration of ≥7 days, or a change in anti-MRSA therapy due to persistent or worsening signs or symptoms. Secondary endpoints included MRSA-attributable mortality and the number of days of MRSA bacteremia. Independent predictors of failure were determined through conditional backwards-stepwise logistic regression with vancomycin BMD MIC forced into the model. A total of 262 patients were matched. Clinical failure was significantly higher in the vancomycin cohort than in the daptomycin cohort (45.0% versus 29.0%;P= 0.007). All-cause 30-day mortality was significantly higher in the vancomycin cohort (15.3% versus 6.1%;P= 0.024). These outcomes remained significant when stratified by vancomycin BMD MIC. There was no significant difference in the length of MRSA bacteremia. Variables independently associated with treatment failure included vancomycin therapy (adjusted odds ratio [aOR] = 2.16, 95% confidence interval [CI] = 1.24 to 3.76), intensive care unit admission (aOR = 2.46, 95% CI = 1.34 to 4.54), and infective endocarditis as the primary source (aOR = 2.33, 95% CI = 1.16 to 4.68). Treatment of MRSA BSIs with daptomycin was associated with reduced clinical failure and 30-day mortality; these findings were independent of vancomycin BMD MIC.

Improved Removal Rates for Retrievable Inferior Vena Cava Filters with the Use of a ‘Filter Registry’

2012 ◽  
Vol 78 (1) ◽  
pp. 94-97 ◽  
Author(s):  
Michael Kalina ◽  
Marilyn Bartley ◽  
Mark Cipolle ◽  
Glen Tinkoff ◽  
Scott Stevenson ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Inferior Vena Cava ◽  
Inferior Vena ◽  
Vena Cava ◽  
Control Group ◽  
Stepwise Logistic Regression ◽  
Removal Rates ◽  
Inferior Vena Cava Filters ◽  
Vena Cava Filters ◽  
Significant Difference

The American Association for the Surgery of Trauma challenged the trauma community to improve a 22 per cent average removal rate for retrievable inferior vena cava filters (r-IVCFs). Since 2006, we maintained a “filter registry” documenting all IVCFs placed in trauma patients. Our goal was to improve removal rates for r-IVCF. Patients receiving an IVCF before implementation of filter registry, 2003–2005, comprised the control group. Patients receiving an IVCF after implementation of filter registry, 2006–2009, comprised the study group. Data obtained included age, gender, Injury Severity Score (ISS), length of stay (LOS), mortality, filter inserted, placement indication, removal rates, and reasons why removal did not occur. Fisher exact test and chi square were used for nominal variables. Stepwise logistic regression analysis was used to define predictors of removing and not removing an IVCF. Three hundred seven patients received an IVCF, 142 preregistry and 165 post-registry. No significant difference existed between groups in age, gender, ISS, placement indication, or mortality. A significant difference existed between groups in LOS and presence of deep vein thrombosis (DVT) and pulmonary embolism. A total of 98.2 per cent of postregistry patients received a Günther Tulip filter and all retrievals were performed by Interventional Radiology. Retrieval rates improved, 15.5 to 31.5 per cent post registry ( P < 0.001). No differences existed in lost to follow-up (LTF) between groups. Univariate analysis identified age, IVC clot, DVT, and LTF as predictors for not removing a filter. Stepwise logistic regression revealed the filter registry independently predicts the removal of an r-IVCF. A filter registry is effective in improving rates of removal for r-IVCFs.

Volar Cortical Integrity in Non-Operatively Treated Adult Distal Radius Fractures

2020 ◽  
Vol 25 (02) ◽  
pp. 192-198
Author(s):  
John Erickson ◽  
Wylie Lopez ◽  
Owolabi Shonuga ◽  
Anthony Azzolini ◽  
David Tyler ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Distal Radius ◽  
Distal Radius Fractures ◽  
Published Data ◽  
Stepwise Logistic Regression ◽  
Radius Fractures ◽  
Data Set ◽  
Initial Reduction ◽  
Significant Difference ◽  
Forward Stepwise

Background: We sought to independently validate published data that volar cortical integrity (VCI) is an independent predictor of maintenance of closed reduction in a series of non-surgically treated distal radius fractures, while simultaneously investigating previously reported predictors of instability. Our null hypothesis was that volar cortical integrity would not affect maintenance of reduction. Methods: Four hundred thirty-three adult distal radius fractures were screened from our Orthopedic database with 112 meeting inclusion criteria. Two groups were determined on the basis of maintenance of reduction (MOR) or loss of reduction (LOR) at 5–6 weeks post-reduction. Bivariate analysis was applied to previously published instability factors along with VCI. A forward stepwise logistic regression was then used to identify instability factors that, as a group, are most predictive of outcome. Results: Results of 112 patients were collected. Reduction was maintained in 62 patients (55.35%) at 5–6 weeks Biivariate analysis showed a statistically significant difference in volar cortical integrity between the 2 groups (80.6% MOR vs 59.2% LOR). Forward stepwise logistic regression analysis of subgroups revealed that post-reduction radial height and VCI were together statistically significant in the model. The presence of VCI, post-reduction radial height greater than or equal to ulnar neutral at the time of initial reduction resulted in a 67.8% successful MOR. Conclusions: We were able to confirm the importance of volar cortical integrity as a predictor of successful maintenance of reduction in non-surgically managed distal radius fractures. When combined with post-reduction radial height greater than or equal to ulnar neutral at the time of initial reduction, it showed a 67.8% MOR with non-operative management in our data-set.

scholarly journals Regional Variation and Factors Associated With Fetal Macrosomia in Ethiopia

2021 ◽  
Author(s):  
Gurmessa Nugussu ◽  
Akalu Banbeta ◽  
Jaleta Abdisa
Keyword(s):  
Logistic Regression ◽  
Regional Variation ◽  
Information Criteria ◽  
Fetal Macrosomia ◽  
Multilevel Logistic Regression ◽  
African Countries ◽  
Chi Square ◽  
Factors Associated ◽  
Significant Difference ◽  
Chi Square Test

Abstract Background: Globally, there is an increase in the prevalence and incidence of fetal macrosomia. In Sub-Sahara African countries including Ethiopia, all infants were not weighed at birth, and there is a limit to knowledge regarding fetal macrosomia in Ethiopia. The main objective of this study is to assess the regional variation and determinants of fetal macrosomia using the multilevel logistic regression model.Methods: The study was based on the recent Ethiopian Demographic and Health Survey of 2016. A total of 2110 weighted infants at birth were extracted. Multilevel logistic regression analysis is performed to identify the factors associated with fetal macrosomia after various candidate models for their efficiency have been compared based on Akaike’s Information Criteria. Chi-square test of association and the inter-class correlation (ICC) are used to test and compute the variation of fetal macrosomia among the regions, respectively.Results: The overall prevalence of fetal macrosomia among the weighted infants at birth is 219 (10.4%). Based on the estimated chi-square test, there is a significant difference in fetal macrosomia across the regions of Ethiopia. The ICC reveals that 14% of the variation in fetal macrosomia can be explained by grouping the infants into the regions. Random intercept with fixed slope model fits the study data well as compared to the other competitors. Based on this model, the age of the mother, residence, educational level of mother, body mass index of mother, gestational age, wealth index, multiple pregnancies, and the infant sex are the significant factors associated with fetal macrosomia in all regions of Ethiopia.Conclusion: Concerned bodies, including the ministry of health and its hierarchical body, need to give special support and attention to women aged between 35 and 49, post-term pregnant women, and overweight or obese women to minimize the prevalence of fetal macrosomia.

Source of funding, conflict of interest (COI), and the interpretation of cancer clinical trials

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6530-6530 ◽  
Author(s):  
R. P. Riechelmann ◽  
V. Dounaevskaia ◽  
N. Taback ◽  
A. O′Carroll ◽  
M. K. Krzyzanowska
Keyword(s):  
Clinical Trials ◽  
Logistic Regression ◽  
Phase Ii ◽  
Randomized Clinical Trials ◽  
Stepwise Logistic Regression ◽  
Cancer Clinical Trials ◽  
Clinical Cancer Research ◽  
Clinical Cancer ◽  
Significant Difference ◽  
Financial Relationships

6530 Background: Concern exists that industry sponsorship and financial relationships between investigators and drug companies may bias clinical cancer research. Our objective was to determine whether funding or authors' COI are associated with interpreting cancer clinical trials in more positive light. Methods: We reviewed phase II and randomized clinical trials (RCT) of anticancer and supportive care drugs published in 5 clinical cancer journals in a one-year period. We collected information on study design, source of funding, COI disclosure and results of primary endpoints (EP). Each concluding statement in the articles′s abstracts were independently rated by two reviewers (blinded to other study information) with respect to level of enthusiasm for the experimental agent using a 5-point scale ( Table 1 ). Summary statistics and logistic regression were used to describe the results. Results: 213 articles met inclusion criteria: 124 phase II and 89 RCT. Approximately 40% were funded by industry, at least one COI was declared in 35% of articles. Among 130/213 (61%) articles with clearly positive conclusions, the proportion of articles with highly positive conclusions was 61% in articles that declared COI vs. 40% in articles with no COI (p=0.017, CMH, adjusted for study result). In a stepwise logistic regression with journal, funding, study type, study result, and COI only COI remained significant (OR=2.4, 95%CI 1.2–5.0, P=0.017). While all articles with a negative conclusion had a negative primary EP, 21 articles with clearly positive conclusions had a negative primary EP. The most common reasons for such finding were: positive secondary EP (6 studies), experimental agent had better toxicity profile (5), non-statistically significant difference in favour of experimental agent (4). Conclusion: COI is associated with highly positive conclusions that use superlatives to promote the experimental arm No significant financial relationships to disclose. [Table: see text]

Normal Tissue Complication Probability (NTCP) model for erectile dysfunction (ED) following external beam radiotherapy (RT) for prostate cancer.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 135-135
Author(s):  
Julia Murray ◽  
Clare Griffin ◽  
Emma Hall ◽  
Jamie Dean ◽  
Isabel Syndikus ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Data ◽  
Goodness Of Fit ◽  
Risk Group ◽  
Characteristic Curve ◽  
External Validation ◽  
Model Performance ◽  
Goodness Of Fit Test ◽  
Dosimetric Data ◽  
Significant Difference

135 Background: ED remains a common toxicity of prostate RT despite technological advances. Penile bulb (PB) dose has been proposed as a predictor of ED post RT. The main objective of this study was to develop NTCP models for ED. Methods: 162 men treated within the CHHiP IGRT substudy (CRUK/06/16) had baseline clinical data, PB dosimetric data & evaluation of ED using EPIC-26 at least 3 years post RT. Planning CT and reference dose distributions were imported into analysis software (VODCA, MSS GmbH) and PB retrospectively contoured by one clinician. The defined endpoint (severe ED) was a standardised average value of 0-33 for EPIC-26 sexual domain. Predictive models of ED were generated using PB dose in EQD2 (α/β ratio = 3Gy) & clinical data (age, diabetes, hypertension, NCCN risk group, baseline PSA, hormone therapy, IGRT, margin size, PB volume). Multivariate logistic regression method using resampling methods was applied to select model order and parameters. Models were fitted using logistic regression of the form Probability = eA(x)/1+eA(x), where A(x) = constant + sum of (variables * associated regression coefficients). Model performance was evaluated through area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow (HL) goodness-of-fit test. Results: 101/162 (62%) men had severe ED with statistically significant difference in PB max and mean dose between those patients with or without severe ED (max: 61.8Gy vs 43Gy & mean: 27.4Gy vs 14Gy respectively; p = 0.001). In the univariate analyses, age, diabetes, risk group, PB mean and max doses were significantly associated with EPIC calculated severe ED. The optimal NTCP model (AUC 0.78; CI 0.71-0.86: p for HL = 0.75) for EPIC calculated severe ED included age, PB mean dose and diabetes where A(x) = -10.13+(0.14*age)+(0.03*PB mean dose)+(2.88 if diabetic). A comparable model using clinician completed outcomes will be reported. Conclusions: This study provides the first known clinical prediction model for ED including PB dose, with good model performance. The determined predictors for the NTCP model of severe ED in this cohort were PB mean dose, age & diabetes. External validation of this model is desirable. Clinical trial information: 97182923.

scholarly journals Isolated subdural hematomas in mild traumatic brain injury. Part 2: a preliminary clinical decision support tool for neurosurgical intervention

2019 ◽  
Vol 130 (5) ◽  
pp. 1626-1633 ◽  
Author(s):  
Alessandro Orlando ◽  
A. Stewart Levy ◽  
Benjamin A. Rubin ◽  
Allen Tanner ◽  
Matthew M. Carrick ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Treatment Guidelines ◽  
Characteristic Curve ◽  
Stepwise Logistic Regression ◽  
Acute Hemorrhage ◽  
Subdural Hematomas ◽  
Neurosurgical Intervention

OBJECTIVEA paucity of studies have examined neurosurgical interventions in the mild traumatic brain injury (mTBI) population with intracranial hemorrhage (ICH). Furthermore, it is not understood how the dimensions of an ICH relate to the risk of a neurosurgical intervention. These limitations contribute to a lack of treatment guidelines. Isolated subdural hematomas (iSDHs) are the most prevalent ICH in mTBI, carry the highest neurosurgical intervention rate, and account for an overwhelming majority of all neurosurgical interventions. Decision criteria in this population could benefit from understanding the risk of requiring neurosurgical intervention. The aim of this study was to quantify the risk of neurosurgical intervention based on the dimensions of an iSDH in the setting of mTBI.METHODSThis was a 3.5-year, retrospective observational cohort study at a Level I trauma center. All adult (≥ 18 years) trauma patients with mTBI and iSDH were included in the study. Maximum length and thickness (in mm) of acute SDHs, the presence of acute-on-chronic (AOC) SDH, mass effect, and other hemorrhage-related variables were double–data entered; discrepant results were adjudicated after a maximum of 4 reviews. Patients with coagulopathy, skull fractures, no acute hemorrhage, a non-SDH ICH, or who did not undergo imaging on admission were excluded. Tentorial SDHs were not measured. The primary outcome was neurosurgical intervention (craniotomy, burr holes, intracranial pressure monitor placement, shunt, ventriculostomy, or SDH evacuation). Multivariate stepwise logistic regression was used to identify significant covariates, to assess interactions, and to create the scoring system.RESULTSThere were a total of 176 patients included in our study: 28 patients did and 148 did not receive a neurosurgical intervention. There were no significant differences between neurosurgical intervention groups in 11 demographic and 22 comorbid variables. Patients with neurosurgical intervention had significantly longer and thicker SDHs than nonsurgical controls. Logistic regression identified thickness and AOC hemorrhage as being the most important variables in predicting neurosurgical intervention; SDH length was not. Risk of neurosurgical intervention was calculated based on the SDH thickness and presence of an AOC hemorrhage from a multivariable logistic regression model (area under the receiver operating characteristic curve 0.94, 95% CI 0.90–0.97; p < 0.001). With a decision point of 2.35% risk, we predicted neurosurgical intervention with 100% sensitivity, 100% negative predictive value, and 53% specificity.CONCLUSIONSThis is the first study to quantify the risk of neurosurgical intervention based on hemorrhage characteristics in patients with mTBI and iSDH. Once validated in a second population, these data can be used to inform the necessity of interhospital transfers and neurosurgical consultations.

Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

1980 ◽  
Vol 19 (01) ◽  
pp. 42-49 ◽  
Author(s):  
B. W. Brown ◽  
C. Engelhard ◽  
J. Haipern ◽  
J. F. Fries ◽  
L. S. Coles
Keyword(s):  
Logistic Regression ◽  
Predictor Variable ◽  
Clinical Problem ◽  
Relevant Information ◽  
Stepwise Logistic Regression ◽  
Multiple Logistic Regression ◽  
Binary Outcome ◽  
Medical Problems ◽  
Valuable Predictor ◽  
Data Banks

In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

The Role of a Decision Rule in Symptomatic Pulmonary Embolism Patients with a Non-high Probability Ventilation-perfusion Scan

1997 ◽  
Vol 78 (02) ◽  
pp. 794-798 ◽  
Author(s):  
Bowine C Michel ◽  
Philomeen M M Kuijer ◽  
Joseph McDonnell ◽  
Edwin J R van Beek ◽  
Frans F H Rutten ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Decision Rule ◽  
Predictive Value ◽  
Patient Population ◽  
High Probability ◽  
Characteristic Curve ◽  
Stepwise Logistic Regression ◽  
Pulmonary Angiogram ◽  
Symptomatic Pulmonary Embolism ◽  
Perfusion Scan

Summary Background: In order to improve the use of information contained in the medical history and physical examination in patients with suspected pulmonary embolism and a non-high probability ventilation-perfusion scan, we assessed whether a simple, quantitative decision rule could be derived for the diagnosis or exclusion of pulmonary embolism. Methods: In 140 consecutive symptomatic patients with a non- high probability ventilation-perfusion scan and an interpretable pulmonary angiogram, various clinical and lung scan items were collected prospectively and analyzed by multivariate stepwise logistic regression analysis to identify the most informative combination of items. Results: The prevalence of proven pulmonary embolism in the patient population was 27.1%. A decision rule containing the presence of wheezing, previous deep venous thrombosis, recently developed or worsened cough, body temperature above 37° C and multiple defects on the perfusion scan was constructed. For the rule the area under the Receiver Operating Characteristic curve was larger than that of the prior probability of pulmonary embolism as assessed by the physician at presentation (0.76 versus 0.59; p = 0.0097). At the cut-off point with the maximal positive predictive value 2% of the patients scored positive, at the cut-off point with the maximal negative predictive value pulmonary embolism could be excluded in 16% of the patients. Conclusions: We derived a simple decision rule containing 5 easily interpretable variables for the patient population specified. The optimal use of the rule appears to be in the exclusion of pulmonary embolism. Prospective validation of this rule is indicated to confirm its clinical utility.

Sign in / Sign up

Export Citation Format

Share Document