Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.
We aimed to develop and validate a risk score to aid in the early identification of laboratory-confirmed dengue patients at high risk of severe dengue (SD) (i.e. severe plasma leakage with shock or respiratory distress, or severe bleeding or organ impairment). We retrospectively analyzed data of 118...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4854400?pdf=render |
| _version_ | 1830475359036899328 |
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| author | Ing-Kit Lee Jien-Wei Liu Yen-Hsu Chen Yi-Chun Chen Ching-Yen Tsai Shi-Yu Huang Chun-Yu Lin Chung-Hao Huang |
| author_facet | Ing-Kit Lee Jien-Wei Liu Yen-Hsu Chen Yi-Chun Chen Ching-Yen Tsai Shi-Yu Huang Chun-Yu Lin Chung-Hao Huang |
| author_sort | Ing-Kit Lee |
| collection | DOAJ |
| description | We aimed to develop and validate a risk score to aid in the early identification of laboratory-confirmed dengue patients at high risk of severe dengue (SD) (i.e. severe plasma leakage with shock or respiratory distress, or severe bleeding or organ impairment). We retrospectively analyzed data of 1184 non-SD patients at hospital presentation and 69 SD patients before SD onset. We fit a logistic regression model using 85% of the population and converted the model coefficients to a numeric risk score. Subsequently, we validated the score using the remaining 15% of patients. Using the derivation cohort, two scoring algorithms for predicting SD were developed: models 1 (dengue illness ≤4 days) and 2 (dengue illness >4 days). In model 1, we identified four variables: age ≥65 years, minor gastrointestinal bleeding, leukocytosis, and platelet count ≥100×10(9) cells/L. Model 1 (ranging from -2 to +6 points) showed good discrimination between SD and non-SD, with an area under the receiver operating characteristic curve (AUC) of 0.848 (95% confidence interval [CI], 0.771-0.924). The optimal cutoff value for model 1 was 1 point, with a sensitivity and specificity for predicting SD of 70.3% and 90.6%, respectively. In model 2 (ranging from 0 to +3 points), significant predictors were age ≥65 years and leukocytosis. Model 2 showed an AUC of 0.859 (95% CI, 0.756-0.963), with an optimal cutoff value of 1 point (sensitivity, 80.3%; specificity, 85.8%). The median interval from hospital presentation to SD was 1 day. This finding underscores the importance of close monitoring, timely resuscitation of shock including intravenous fluid adjustment and early correction of dengue-related complications to prevent the progressive dengue severity. In the validation data, AUCs of 0.904 (95% CI, 0.825-0.983) and 0.917 (95% CI, 0.833-1.0) in models 1 and 2, respectively, were achieved. The observed SD rates (in both cohorts) were <3% for patients with a score <1 point, but >50% for those with a score of ≥2 points, irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management. |
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| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-21T15:33:59Z |
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| spelling | doaj.art-1cefae136d694d5182b10abb72d3afa32022-12-21T18:58:40ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01115e015477210.1371/journal.pone.0154772Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.Ing-Kit LeeJien-Wei LiuYen-Hsu ChenYi-Chun ChenChing-Yen TsaiShi-Yu HuangChun-Yu LinChung-Hao HuangWe aimed to develop and validate a risk score to aid in the early identification of laboratory-confirmed dengue patients at high risk of severe dengue (SD) (i.e. severe plasma leakage with shock or respiratory distress, or severe bleeding or organ impairment). We retrospectively analyzed data of 1184 non-SD patients at hospital presentation and 69 SD patients before SD onset. We fit a logistic regression model using 85% of the population and converted the model coefficients to a numeric risk score. Subsequently, we validated the score using the remaining 15% of patients. Using the derivation cohort, two scoring algorithms for predicting SD were developed: models 1 (dengue illness ≤4 days) and 2 (dengue illness >4 days). In model 1, we identified four variables: age ≥65 years, minor gastrointestinal bleeding, leukocytosis, and platelet count ≥100×10(9) cells/L. Model 1 (ranging from -2 to +6 points) showed good discrimination between SD and non-SD, with an area under the receiver operating characteristic curve (AUC) of 0.848 (95% confidence interval [CI], 0.771-0.924). The optimal cutoff value for model 1 was 1 point, with a sensitivity and specificity for predicting SD of 70.3% and 90.6%, respectively. In model 2 (ranging from 0 to +3 points), significant predictors were age ≥65 years and leukocytosis. Model 2 showed an AUC of 0.859 (95% CI, 0.756-0.963), with an optimal cutoff value of 1 point (sensitivity, 80.3%; specificity, 85.8%). The median interval from hospital presentation to SD was 1 day. This finding underscores the importance of close monitoring, timely resuscitation of shock including intravenous fluid adjustment and early correction of dengue-related complications to prevent the progressive dengue severity. In the validation data, AUCs of 0.904 (95% CI, 0.825-0.983) and 0.917 (95% CI, 0.833-1.0) in models 1 and 2, respectively, were achieved. The observed SD rates (in both cohorts) were <3% for patients with a score <1 point, but >50% for those with a score of ≥2 points, irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.http://europepmc.org/articles/PMC4854400?pdf=render |
| spellingShingle | Ing-Kit Lee Jien-Wei Liu Yen-Hsu Chen Yi-Chun Chen Ching-Yen Tsai Shi-Yu Huang Chun-Yu Lin Chung-Hao Huang Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. PLoS ONE |
| title | Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. |
| title_full | Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. |
| title_fullStr | Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. |
| title_full_unstemmed | Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. |
| title_short | Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients. |
| title_sort | development of a simple clinical risk score for early prediction of severe dengue in adult patients |
| url | http://europepmc.org/articles/PMC4854400?pdf=render |
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