Abstract

BackgroundEarly recognition and treatment of circulatory volume loss is essential in the clinical management of dengue viral infection. We hypothesized that a novel computational algorithm, originally developed for noninvasive monitoring of blood loss in combat casualties, could: (1) indicate the central volume status of children with dengue during the early stages of “shock”; and (2) track fluid resuscitation status.MethodsContinuous noninvasive photoplethysmographic waveforms were collected over a 5-month period from three children of Thai ethnicity with clinical suspicion of dengue. Waveform data were processed by the algorithm to calculate each child’s Compensatory Reserve Index, where 1 represents supine normovolemia and 0 represents the circulatory volume at which hemodynamic decompensation occurs. Values between 1 and 0 indicate the proportion of reserve remaining before hemodynamic decompensation.ResultsThis case report describes a 7-year-old Thai boy, another 7-year-old Thai boy, and a 9-year-old Thai boy who exhibited signs and symptoms of dengue shock syndrome; all the children had secondary dengue virus infections, documented by serology and reverse transcriptase polymerase chain reaction. The three boys experienced substantial plasma leakage demonstrated by pleural effusion index >25, ascites, and >20 % hemoconcentration. They received fluid administered intravenously; one received a blood transfusion. All three boys showed a significantly low initial Compensatory Reserve Index (≥0.20), indicating a clinical diagnosis of “near shock”. Following 5 days with fluid resuscitation treatment, their Compensatory Reserve Index increased towards “normovolemia” (that is, Compensatory Reserve Index >0.75).ConclusionsThe results from these cases demonstrate a new variation in the diagnostic capability to manage patients with dengue shock syndrome. The findings shed new light on a method that can avoid possible adverse effects of shock by noninvasive measurement of a patient’s compensatory reserve rather than standard vital signs or invasive diagnostic methods.

Highlights

  • Recognition and treatment of circulatory volume loss is essential in the clinical management of dengue viral infection

  • Through high-speed computing processes that combine machine learning with feature extraction, we have developed an algorithm capable of integrating all of the physiological compensatory mechanisms and the changes in their status and features in response to compromised circulating blood volume, which gives the Compensatory Reserve Index (CRI) its unique individual specific predictive capability to assess one’s capacity to compensate

  • The present study provides preliminary evidence of the value of the CRI algorithm in the management of clinical conditions of central hypovolemia such as those associated with dengue

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Summary

Introduction

Recognition and treatment of circulatory volume loss is essential in the clinical management of dengue viral infection. We hypothesized that a novel computational algorithm, originally developed for noninvasive monitoring of blood loss in combat casualties, could: (1) indicate the central volume status of children with dengue during the early stages of “shock”; and (2) track fluid resuscitation status. The clinical manifestations of DENV infection range from an asymptomatic infection to a debilitating but self-limited illness termed dengue fever (DF), to more severe forms of the Moulton et al Journal of Medical Case Reports (2016) 10:233 progress to develop DSS, evidenced by signs of circulatory failure, including tachycardia, a narrow pulse pressure, hypotension and, in its late stages, lethargy and other mental status changes. Fatality rates among patients with DSS are typically around 2.5 %, or approximately 22,000 deaths per year [4, 5].

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