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Simple clinical and laboratory predictors to improve empirical treatment strategies in areas of high scrub typhus and dengue endemicity, central Vietnam

PLoS neglected tropical diseases, 2022-05, Vol.16 (5), p.e0010281-e0010281 [Peer Reviewed Journal]

COPYRIGHT 2022 Public Library of Science ;2022 Tran et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Tran et al 2022 Tran et al ;ISSN: 1935-2735 ;ISSN: 1935-2727 ;EISSN: 1935-2735 ;DOI: 10.1371/journal.pntd.0010281 ;PMID: 35507541

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Title:
Simple clinical and laboratory predictors to improve empirical treatment strategies in areas of high scrub typhus and dengue endemicity, central Vietnam
Author: Tran, Hanh Thi Duc ; Schindler, Christian ; Pham, Thuy Thi Thanh ; Vien, Mai Quang ; Do, Hung Manh ; Ngo, Quyet Thi ; Nguyen, Trieu Bao ; Hoang, Hang Thi Hai ; Vu, Lan Thi Hoang ; Schelling, Esther ; Paris, Daniel H
Gawarammana, Indika
Subjects: Adult ; Aetiology ; Algorithms ; Antigens ; Antiinfectives and antibacterials ; Bacterial diseases ; Bacterial infections ; Biology and Life Sciences ; Care and treatment ; Cell number ; Datasets ; Decision making ; Dengue ; Dengue - complications ; Dengue - diagnosis ; Dengue - epidemiology ; Dengue fever ; Diagnosis ; Diagnosis, Differential ; Diagnostic tests ; Endemism ; Engineering and Technology ; Enrollments ; Ethics ; Etiology ; Fatalities ; Fever ; Fever - epidemiology ; Health aspects ; Health services ; Hospitals ; Human diseases ; Humans ; Illnesses ; Laboratories ; Leukocytes (neutrophilic) ; Lymphadenopathy ; Lymphocytes ; Malaria ; Measurement ; Medical records ; Medicine and Health Sciences ; Methods ; Mortality ; NS1 protein ; Nucleotide sequence ; Orientia tsutsugamushi ; PCR ; People and Places ; Population ; Primary care ; Probability theory ; Regression analysis ; Regression models ; Regressions ; Research and Analysis Methods ; Retrospective Studies ; Risk factors ; Scrub typhus ; Scrub Typhus - diagnosis ; Scrub Typhus - epidemiology ; Sensitivity ; Specificity ; Statistical analysis ; Tropical diseases ; Typhus ; Vector-borne diseases ; Vietnam - epidemiology ; Viral diseases ; Viremia
Is Part Of: PLoS neglected tropical diseases, 2022-05, Vol.16 (5), p.e0010281-e0010281
Description: Dengue fever is highly endemic in Vietnam, but scrub typhus-although recognized as an endemic disease-remains underappreciated. These diseases together are likely to account for more than half of the acute undifferentiated fever burden in Vietnam. Scrub typhus (ST) is a bacterial disease requiring antimicrobial treatment, while dengue fever (DF) is of viral etiology and does not. The access to adequate diagnostics and the current understanding of empirical treatment strategies for both illnesses remain limited. In this study we aimed to contribute to the clinical decision process in the management of these two important etiologies of febrile illness in Vietnam. Using retrospective data from 221 PCR-confirmed scrub typhus cases and 387 NS1 protein positive dengue fever patients admitted to five hospitals in Khanh Hoa province (central Vietnam), we defined predictive characteristics for both diseases that support simple clinical decision making with potential to inform decision algorithms in future. We developed models to discriminate scrub typhus from dengue fever using multivariable logistic regression (M-LR) and classification and regression trees (CART). Regression trees were developed for the entire data set initially and pruned, based on cross-validation. Regression models were developed in a training data set involving 60% of the total sample and validated in the complementary subsample. Probability cut points for the distinction between scrub typhus and dengue fever were chosen to maximise the sum of sensitivity and specificity. Using M-LR, following seven predictors were identified, that reliably differentiate ST from DF; eschar, regional lymphadenopathy, an occupation in nature, increased days of fever on admission, increased neutrophil count, decreased ratio of neutrophils/lymphocytes, and age over 40. Sensitivity and specificity of predictions based on these seven factors reached 93.7% and 99.5%, respectively. When excluding the "eschar" variable, the values dropped to 76.3% and 92.3%, respectively. The CART model generated one further variable; increased days of fever on admission, when eschar was included, the sensitivity and specificity was 95% and 96.9%, respectively. The model without eschar involved the following six variables; regional lymphadenopathy, increased days of fever on admission, increased neutrophil count, increased lymphocyte count, platelet count ≥ 47 G/L and age over 28 years as predictors of ST and provided a sensitivity of 77.4% and a specificity of 90.7%. The generated algorithms contribute to differentiating scrub typhus from dengue fever using basic clinical and laboratory parameters, supporting clinical decision making in areas where dengue and scrub typhus are co-endemic in Vietnam.
Publisher: United States: Public Library of Science
Language: English
Identifier: ISSN: 1935-2735
ISSN: 1935-2727
EISSN: 1935-2735
DOI: 10.1371/journal.pntd.0010281
PMID: 35507541
Source: PubMed Central database
Geneva Foundation Free Medical Journals at publisher websites
PLoS
MEDLINE
ProQuest Central
DOAJ Directory of Open Access Journals

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Simple clinical and laboratory predictors to improve empirical treatment strategies in areas of high scrub typhus and dengue endemicity, central Vietnam

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