Platelet Distribution Width at First Day of Hospital Admission in Patients with Hemorrhagic Fever with Renal Syndrome Caused by Hantaan Virus May Predict Disease Severity and Critical Patients’ Survival

Fan, Xiude; Liu, Zitong; Fu, Shiqi; Sang, Jiao; Deng, Huan; Li, Fang; Li, Na; Han, Qunying; Liu, Zhengwen

doi:10.1155/2018/9701619

Cited by 14 publications

(12 citation statements)

References 32 publications

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“…A prognostic role for thrombocytopenia in the HFRS has been suggested. In patients with HFRS caused by Hantaan orthohantavirus infection, the platelet distribution width at admission was reported as a mortality risk factor [24], while an independent association between nadir platelet count and development of severe acute kidney injury has also been described in these patients [25]. Interestingly, thrombocytopenia has been associated with capillary leakage and severity of inflammation in Puumala orthohantavirus infection [26].…”

Section: Discussionmentioning

confidence: 99%

Platelet Count in Patients with Mild Disease at Admission is Associated with Progression to Severe Hantavirus Cardiopulmonary Syndrome

López

Graf

Calvo

et al. 2019

Viruses

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Background: Hantavirus cardiopulmonary syndrome (HCPS) has a mortality up to 35–40% and its treatment is mainly supportive. A variable to predict progression from mild to severe disease is unavailable. This study was performed in patients with documented infection by Andes orthohantavirus, and the aim was to find a simple variable to predict progression to moderate/severe HCPS in patients with mild disease at admission. Methods: We performed a retrospective analysis of 175 patients between 2001 and 2018. Patients were categorized into mild, moderate, and severe disease according to organ failure and advanced support need at hospital admission (e.g., mechanical ventilation, vasopressors). Progression to moderate/severe disease was defined accordingly. Clinical and laboratory variables associated with progression were explored. Results: Forty patients with mild disease were identified; 14 of them progressed to moderate/severe disease. Only platelet count was different between those who progressed versus those that did not (37 (34–58) vs. 83 (64–177) K/mm3, p < 0.001). A ROC curve analysis showed an AUC = 0.889 (0.78–1.0) p < 0.001, with a platelet count greater than 115K /mm3 ruling out progression to moderate/severe disease. Conclusions: In patients with mild disease at presentation, platelet count could help to define priority of evacuation to tertiary care centers.

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Section: Discussionmentioning

confidence: 99%

Platelet Count in Patients with Mild Disease at Admission is Associated with Progression to Severe Hantavirus Cardiopulmonary Syndrome

López

Graf

Calvo

et al. 2019

Viruses

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“…This mechanism leads to the aggravation of the patient's condition [18] . Other studies have shown that WBC, PLT, platelet distribution width (PDW) and PCT can be used as valuable parameters for the severity of HFRS patients, especially the change of PDW on the rst day of hospitalization is related to the survival rate of severe HFRS patients and can be used as potential predictors [19] . In this study, the increase of WBC in patients with severe HFRS was signi cantly higher than that in mild patients, whereas a study showed that compared with leukocytosis, thrombocytopenia may better predict the prognosis of severe acute kidney injury (AKI) in patients with acute HTNV infection [20] .…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram for predicting severity in patients with hemorrhagic fever with renal syndrome: A retrospective study

Yang

Feng

et al. 2021

Open Medicine

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Background Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused by hantavirus infection. Patients with severe HFRS may develop multiple organ failure or even death, which makes HFRS a serious public health problem. Methods In this retrospective study, we included a total of 155 consecutive patients who were diagnosed with HFRS, of whom 109 patients served as a training cohort and 46 patients as an independent verification cohort. In the training set, the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables of the risk model. Multivariate logistic regression analysis was used to construct a nomogram containing the characteristic variables selected in the LASSO regression model. Results The area under the receiver operating characteristic curve (AUC) of the nomogram indicated that the model had good discrimination. The calibration curve exhibited that the nomogram was in good agreement between the prediction and the actual observation. Decision curve analysis and clinical impact curve suggested that the predictive nomogram had clinical utility. Conclusion In this study, we established a simple and feasible model to predict severity in patients with HFRS, with which HFRS would be better identified and patients can be treated early.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Nomogram for Predicting Severity in Patients With Hemorrhagic Fever With Renal Syndrome: a Retrospective Study

Yang

Feng

et al. 2021

Preprint

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Background: Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused by hantavirus infection. China is one of the most endemic countries of HFRS in the world. Patients with severe HFRS may develop multiple organ failure or even death, which makes HFRS a serious public health problem in China. Therefore, we constructed and verified a reliable nomogram to predict the severity in patients with HFRS and provide guidance for medical practice.Methods: In this retrospective study, we included a total of 155 consecutive patients with HFRS who were diagnosed from January 1, 2015 to December 31, 2019, of which 109 patients served as a training cohort and 46 patients as an independent verification cohort. 54 laboratory and clinical indicators were applied to assess the severity of HFRS patients. In the training set, the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables of the risk model. Multivariate logistic regression analysis was used to construct a nomogram containing the characteristic variables selected in the LASSO regression model. The nomogram's performance was evaluated by the discrimination, calibration, and clinical applicability in the training set and validation set.Results: The prediction nomogram included six predictors such as neutrophils, hemoglobin (Hb), platelets, creatinine, calcium (Ca) and dyspnea, which were screened by LASSO regression. The area under the receiver operating characteristic curve (AUC) of the nomogram in the training and validation cohorts was 0.969 (95%CI:0.935-1.000) and 0.934(95%CI: 0.847-1.000), respectively, indicating that the model has good discrimination. The calibration curve exhibited that the nomogram was in good agreement between the prediction and the actual observation. Decision curve analysis and clinical impact curve indicated that the predictive nomogram had clinical utility.Conclusion: In this study, we established a simple and feasible model to predict severity in patients with HFRS, with which HFRS will be better identified and patients can be treated early.

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Platelet Distribution Width at First Day of Hospital Admission in Patients with Hemorrhagic Fever with Renal Syndrome Caused by Hantaan Virus May Predict Disease Severity and Critical Patients’ Survival

Cited by 14 publications

References 32 publications

Platelet Count in Patients with Mild Disease at Admission is Associated with Progression to Severe Hantavirus Cardiopulmonary Syndrome

Platelet Count in Patients with Mild Disease at Admission is Associated with Progression to Severe Hantavirus Cardiopulmonary Syndrome

Development and validation of a nomogram for predicting severity in patients with hemorrhagic fever with renal syndrome: A retrospective study

Development and Validation of a Nomogram for Predicting Severity in Patients With Hemorrhagic Fever With Renal Syndrome: a Retrospective Study

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