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D‐dimer Interval Likelihood Ratios for Pulmonary Embolism
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| Zeitschriftentitel: | Academic Emergency Medicine |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Academic Emergency Medicine, 24, 2017, 7, S. 832-837 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
|
| Schlagwörter: |
| author_facet |
Kohn, Michael A. Klok, Frederikus A. van Es, Nick Kohn, Michael A. Klok, Frederikus A. van Es, Nick |
|---|---|
| author |
Kohn, Michael A. Klok, Frederikus A. van Es, Nick |
| spellingShingle |
Kohn, Michael A. Klok, Frederikus A. van Es, Nick Academic Emergency Medicine D‐dimer Interval Likelihood Ratios for Pulmonary Embolism Emergency Medicine General Medicine |
| author_sort |
kohn, michael a. |
| spelling |
Kohn, Michael A. Klok, Frederikus A. van Es, Nick 1069-6563 1553-2712 Wiley Emergency Medicine General Medicine http://dx.doi.org/10.1111/acem.13191 <jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>The objective was to estimate D‐dimer interval likelihood ratios (<jats:styled-content style="fixed-case">iLR</jats:styled-content>s) for diagnosing pulmonary embolism (<jats:styled-content style="fixed-case">PE</jats:styled-content>).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The authors used pooled patient‐level data from five <jats:styled-content style="fixed-case">PE</jats:styled-content> diagnostic management studies to estimate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s for the eight D‐dimer intervals with boundaries 250, 500, 750, 1,000, 1,500, 2,500, and 5,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>. Logistic regression was used to fit the data so that an interval increase corresponds to increasing the likelihood ratio by a constant factor.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The <jats:styled-content style="fixed-case">iLR</jats:styled-content> for the D‐dimer interval 1,000–1,499 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> was essentially 1.0 (0.98 with 95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] = 0.82–1.18). In the logistic regression model, the constant between‐interval factor was 2.0 (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> = 1.9–2.1). Using these <jats:styled-content style="fixed-case">iLR</jats:styled-content> estimates, if the pre–D‐dimer probability of <jats:styled-content style="fixed-case">PE</jats:styled-content> is 15%, only a D‐dimer less than 500 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> will result in a posttest probability below 3%; if the pretest probability is 5%, the threshold for a “negative” D‐dimer is 1,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>A decision strategy based on these approximate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s agrees with several published strategies.</jats:p></jats:sec> D‐dimer Interval Likelihood Ratios for Pulmonary Embolism Academic Emergency Medicine |
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10.1111/acem.13191 |
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Medizin |
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Wiley, 2017 |
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Wiley, 2017 |
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Wiley |
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Academic Emergency Medicine |
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49 |
| title |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_unstemmed |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_full |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_fullStr |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_full_unstemmed |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_short |
D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_sort |
d‐dimer interval likelihood ratios for pulmonary embolism |
| topic |
Emergency Medicine General Medicine |
| url |
http://dx.doi.org/10.1111/acem.13191 |
| publishDate |
2017 |
| physical |
832-837 |
| description |
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>The objective was to estimate D‐dimer interval likelihood ratios (<jats:styled-content style="fixed-case">iLR</jats:styled-content>s) for diagnosing pulmonary embolism (<jats:styled-content style="fixed-case">PE</jats:styled-content>).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The authors used pooled patient‐level data from five <jats:styled-content style="fixed-case">PE</jats:styled-content> diagnostic management studies to estimate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s for the eight D‐dimer intervals with boundaries 250, 500, 750, 1,000, 1,500, 2,500, and 5,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>. Logistic regression was used to fit the data so that an interval increase corresponds to increasing the likelihood ratio by a constant factor.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The <jats:styled-content style="fixed-case">iLR</jats:styled-content> for the D‐dimer interval 1,000–1,499 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> was essentially 1.0 (0.98 with 95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] = 0.82–1.18). In the logistic regression model, the constant between‐interval factor was 2.0 (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> = 1.9–2.1). Using these <jats:styled-content style="fixed-case">iLR</jats:styled-content> estimates, if the pre–D‐dimer probability of <jats:styled-content style="fixed-case">PE</jats:styled-content> is 15%, only a D‐dimer less than 500 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> will result in a posttest probability below 3%; if the pretest probability is 5%, the threshold for a “negative” D‐dimer is 1,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>A decision strategy based on these approximate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s agrees with several published strategies.</jats:p></jats:sec> |
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| author | Kohn, Michael A., Klok, Frederikus A., van Es, Nick |
| author_facet | Kohn, Michael A., Klok, Frederikus A., van Es, Nick, Kohn, Michael A., Klok, Frederikus A., van Es, Nick |
| author_sort | kohn, michael a. |
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| description | <jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>The objective was to estimate D‐dimer interval likelihood ratios (<jats:styled-content style="fixed-case">iLR</jats:styled-content>s) for diagnosing pulmonary embolism (<jats:styled-content style="fixed-case">PE</jats:styled-content>).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The authors used pooled patient‐level data from five <jats:styled-content style="fixed-case">PE</jats:styled-content> diagnostic management studies to estimate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s for the eight D‐dimer intervals with boundaries 250, 500, 750, 1,000, 1,500, 2,500, and 5,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>. Logistic regression was used to fit the data so that an interval increase corresponds to increasing the likelihood ratio by a constant factor.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The <jats:styled-content style="fixed-case">iLR</jats:styled-content> for the D‐dimer interval 1,000–1,499 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> was essentially 1.0 (0.98 with 95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] = 0.82–1.18). In the logistic regression model, the constant between‐interval factor was 2.0 (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> = 1.9–2.1). Using these <jats:styled-content style="fixed-case">iLR</jats:styled-content> estimates, if the pre–D‐dimer probability of <jats:styled-content style="fixed-case">PE</jats:styled-content> is 15%, only a D‐dimer less than 500 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> will result in a posttest probability below 3%; if the pretest probability is 5%, the threshold for a “negative” D‐dimer is 1,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>A decision strategy based on these approximate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s agrees with several published strategies.</jats:p></jats:sec> |
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| imprint | Wiley, 2017 |
| imprint_str_mv | Wiley, 2017 |
| institution | DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229 |
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| series | Academic Emergency Medicine |
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| spelling | Kohn, Michael A. Klok, Frederikus A. van Es, Nick 1069-6563 1553-2712 Wiley Emergency Medicine General Medicine http://dx.doi.org/10.1111/acem.13191 <jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>The objective was to estimate D‐dimer interval likelihood ratios (<jats:styled-content style="fixed-case">iLR</jats:styled-content>s) for diagnosing pulmonary embolism (<jats:styled-content style="fixed-case">PE</jats:styled-content>).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The authors used pooled patient‐level data from five <jats:styled-content style="fixed-case">PE</jats:styled-content> diagnostic management studies to estimate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s for the eight D‐dimer intervals with boundaries 250, 500, 750, 1,000, 1,500, 2,500, and 5,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>. Logistic regression was used to fit the data so that an interval increase corresponds to increasing the likelihood ratio by a constant factor.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The <jats:styled-content style="fixed-case">iLR</jats:styled-content> for the D‐dimer interval 1,000–1,499 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> was essentially 1.0 (0.98 with 95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] = 0.82–1.18). In the logistic regression model, the constant between‐interval factor was 2.0 (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> = 1.9–2.1). Using these <jats:styled-content style="fixed-case">iLR</jats:styled-content> estimates, if the pre–D‐dimer probability of <jats:styled-content style="fixed-case">PE</jats:styled-content> is 15%, only a D‐dimer less than 500 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content> will result in a posttest probability below 3%; if the pretest probability is 5%, the threshold for a “negative” D‐dimer is 1,000 ng/<jats:styled-content style="fixed-case">mL</jats:styled-content>.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>A decision strategy based on these approximate <jats:styled-content style="fixed-case">iLR</jats:styled-content>s agrees with several published strategies.</jats:p></jats:sec> D‐dimer Interval Likelihood Ratios for Pulmonary Embolism Academic Emergency Medicine |
| spellingShingle | Kohn, Michael A., Klok, Frederikus A., van Es, Nick, Academic Emergency Medicine, D‐dimer Interval Likelihood Ratios for Pulmonary Embolism, Emergency Medicine, General Medicine |
| title | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_full | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_fullStr | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_full_unstemmed | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_short | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| title_sort | d‐dimer interval likelihood ratios for pulmonary embolism |
| title_unstemmed | D‐dimer Interval Likelihood Ratios for Pulmonary Embolism |
| topic | Emergency Medicine, General Medicine |
| url | http://dx.doi.org/10.1111/acem.13191 |