Mathematical model of volume kinetics and renal function after burn injury and resuscitation

Arabidarrehdor, Ghazal; Tivay, Ali; Bighamian, Ramin; Meador, C. Lawrence; Kramer, George C.; Hahn, Jin-Oh; Salinas, José

doi:10.1016/j.burns.2020.07.003

Cited by 8 publications

(11 citation statements)

References 67 publications

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“…The final version of this paper has been accepted for publication in the IEEE journal of Transactions on Biomedical Engineering and is available for early access at https://ieeexplore.ieee.org/document/9478222 DOI: 10.1109/TBME.2021.3094515 oncotic pressure constant. The lymphatic water flow is expressed by a phenomenological model in the form of a sigmoidal curve [31]:…”

Section: Volume Kineticsmentioning

confidence: 99%

“…We continued to develop a mathematical model capable of predicting volume kinetic and kidney function responses to burn injury and resuscitation developed in our prior work [31]. The mathematical model consists of (i) volume kinetics to replicate water volume and protein concentration dynamics in the intravascular and the tissue compartments ("Volume Kinetics" in Fig.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…( 35)). The kidney function was represented by a lumped-parameter model developed in our prior work [31], which includes a hybrid combination of first-principles and phenomenological elements that describe UO control governed by the kidneys, including the glomerular filtration rate (GFR; 𝐽 𝐺𝐹𝑅 in Fig. 1 and Eq.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…pore ratio) in the intact (𝑀 𝛼 𝐼𝑇 in Table AI) and burnt (𝑀 𝛼 𝐵𝑇 in Table AI) tissue capillary bed, the maximum drop in the burnt tissue hydrostatic pressure (𝑀 𝑃 𝐵𝑇 in Table AI), and the maximum increase in the capillary hydrostatic pressure (𝑀 𝑃 𝐶 in Table AI) to list a few. To make the mathematical model (which was initially developed based on the dataset collected from animals in our prior work [31]) more compatible with human burn patients, we refined the values of a number of parameters that are inherently different between animals and humans according to the literature (see Table AI…”

Section: Mathematical Model Enhancementmentioning

confidence: 99%

“…(2) (i.e., it is a subset of 𝜃), and 𝜃 ̆𝑖 is 𝜃 ̆ estimated for the subject 𝑖. Then, we examined the faithfulness of the mathematical model in terms of (i) normalized mean absolute error (NMAE) [31], (ii) correlation coefficient, and (iii) UO range agreement, all between measured versus model-replicated UO on an individual patient basis, and (iv) Bland-Altman statistics between all measured versus model-replicated UO. We computed the UO…”

Section: Mathematical Model Optimization Training and Validationmentioning

confidence: 99%

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Mathematical Modeling, In-Human Evaluation and Analysis of Volume Kinetics and Kidney Function After Burn Injury and Resuscitation

Arabidarrehdor

Tivay

Meador

et al. 2022

IEEE Trans. Biomed. Eng.

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Existing burn resuscitation protocols exhibit a large variability in treatment efficacy. Hence, they must be further optimized based on comprehensive knowledge of burn pathophysiology. A physics-based mathematical model that can replicate physiological responses in diverse burn patients can serve as an attractive basis to perform non-clinical testing of burn resuscitation protocols and to expand knowledge on burn pathophysiology. We intend to develop, optimize, validate, and analyze a mathematical model to replicate physiological responses in burn patients. Methods: Using clinical datasets collected from 233 burn patients receiving burn resuscitation, we developed and validated a mathematical model applicable to computer-aided in-human burn resuscitation trial and knowledge expansion. Using the validated mathematical model, we examined possible physiological mechanisms responsible for the cohort-dependent differences in burn pathophysiology between younger versus older patients, female versus male patients, and patients with versus without inhalational injury. Results: We demonstrated that the mathematical model could replicate physiological responses in burn patients associated with wide demographic characteristics and injury severity, and that an increased inflammatory response to injury may be a key contributing factor in increasing the mortality risk of older patients and patients with inhalation injury via an increase in the fluid retention. Conclusion: We developed and validated a physiologically plausible mathematical model of volume kinetic and kidney function after burn injury and resuscitation suited to in-human application. Significance: The mathematical model may provide an attractive platform to conduct non-clinical testing of burn resuscitation protocols and test new hypotheses on burn pathophysiology.

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Section: Volume Kineticsmentioning

confidence: 99%

Section: Mathematical Modelmentioning

confidence: 99%

Section: Mathematical Modelmentioning

confidence: 99%

Section: Mathematical Model Enhancementmentioning

confidence: 99%

Section: Mathematical Model Optimization Training and Validationmentioning

confidence: 99%

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Mathematical Modeling, In-Human Evaluation and Analysis of Volume Kinetics and Kidney Function After Burn Injury and Resuscitation

Arabidarrehdor

Tivay

Meador

et al. 2022

IEEE Trans. Biomed. Eng.

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Acute kidney injury in patients with burns

Legrand,

Clark,

Neyra

et al. 2023

Nat Rev Nephrol

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Pioneering predictions of AKI and AKIN severity in burn patients: a comprehensive CBC approach

Park,

Kym,

Kim

et al. 2024

Sci Rep

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This study aims to evaluate the utility of complete blood count (CBC) markers, in conjunction with the acute kidney injury network (AKIN) criteria, for the early detection, severity assessment, and prediction of mortality outcomes of acute kidney injury (AKI) in burn patients. The research seeks to fill existing gaps in knowledge and validate the cost-effectiveness of using CBC as a routine diagnostic tool for better management of AKI. The study was conducted at Hangang Sacred Heart Hospital. We performed a large-scale retrospective analysis of 2758 adult patients admitted to the burn intensive care unit over a 12-year period. Among these patients, AKI occurred in 1554 patients (56.3%). Based on the AKIN stage classification, 794 patients (28.8%) were categorized as AKIN 1, 494 patients (17.9%) as AKIN 2, and 266 patients (9.6%) as AKIN 3. We defined several ratio markers, including the Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and various mean platelet volume (MPV) ratios. Our statistical analyses, conducted using the R programming language, revealed significant correlations between these markers and AKI severity. The AUC values for neutrophil count and WBC count were 0.790 and 0.793, respectively, followed by immature granulocyte count with an AUC of 0.727. For red blood cell (RBC)-related parameters, the AUC values for hematocrit (Hct), hemoglobin (Hb), and RBC count were 0.725, 0.713, and 0.713, respectively. Among the platelet-related parameters, only platelet distribution width (PDW) had an AUC of 0.677. Among the ratio markers, the NLR had the highest AUC at 0.772, followed by MPVNR and SII with AUC values of 0.700 and 0.680, respectively. The findings underscore the potential of CBC as an economical, routine test for AKI, thereby paving the way for enhanced patient outcomes. Our study suggests the utility of routine CBC tests, specifically WBC count and PLR, for predicting AKI and platelet, MPV, and NLR for mortality assessment in burn patients. These findings underscore the potential of easily accessible CBC tests in enhancing AKI management. However, further multicenter studies are needed for validation.

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Mathematical model of volume kinetics and renal function after burn injury and resuscitation

Cited by 8 publications

References 67 publications

Mathematical Modeling, In-Human Evaluation and Analysis of Volume Kinetics and Kidney Function After Burn Injury and Resuscitation

Mathematical Modeling, In-Human Evaluation and Analysis of Volume Kinetics and Kidney Function After Burn Injury and Resuscitation

Acute kidney injury in patients with burns

Pioneering predictions of AKI and AKIN severity in burn patients: a comprehensive CBC approach

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