ArticleJournal of clinical monitoring and computing2011
A comprehensive, computer-model-based approach for diagnosis and treatment of complex acid-base disorders in critically-ill patients.
Article in Journal of clinical monitoring and computing, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A head to head evaluation of 8 biochemical scanning tools for unmeasured ions.Journal of clinical monitoring and computing · 2017Trial
- Anthropometric Measurements for Predicting Low Appendicular Lean Mass Index for the Diagnosis of Sarcopenia: A Machine Learning Model.Journal of functional morphology and kinesiology · 2025Article
- Quantifying pH-induced changes in plasma strong ion difference during experimental acidosis: clinical implications for base excess interpretation.Journal of applied physiology (Bethesda, Md. : 1985) · 2024Article
- Reducing complexity in acid-base diagnosis - how far should we go?Journal of clinical monitoring and computing · 2020Article
- Modern and traditional approaches combined into an effective gray-box mathematical model of full-blood acid-base.Theoretical biology & medical modelling · 2018Article
- Journal of Clinical Monitoring and Computing 2015 end of year summary: respiration.Journal of clinical monitoring and computing · 2016Review
- Comprehensive diagnosis of whole-body acid-base and fluid-electrolyte disorders using a mathematical model and whole-body base excess.Journal of clinical monitoring and computing · 2015Article
- Partitioning standard base excess: a new approach.Journal of clinical monitoring and computing · 2011Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a computer-model-based approach to quantitatively diagnose the causes of metabolic acid-base disorders in critically-ill patients. We use an interstitial-plasma-erythrocyte (IPE) model that is sufficiently detailed to accurately calculate steady-state changes from normal in fluid volumes and electrolyte concentrations in a given patient due to a number of causes of acid-base disorders. Normal fluid volumes for each patient are determined from their sex, height and weight using regression equations derived from measured data in humans. The model inputs (electrolyte masses and volumes) are altered to simulate the laboratory chemistry of each critically-ill patient. In this process, the model calculates changes in body-fluid volumes, osmolality and yields the individual values of IPE base excess (BE(IPE)) attributed to changes due to: (1) fluid dilution/contraction, (2) gain or loss of Cl(-), (3) hyper- or hypoalbuminemia, (4) presence of unmeasured ions, (5) gain of lactate, (6) gain or loss of phosphate, (7) gain or loss of calcium and magnesium, (8) gain or loss of potassium and (9) gain or loss of sodium. We use critically-ill patient data to show how our new approach is more informative and much simpler to interpret as compared to the approaches of Siggaard-Andersen or Stewart. We demonstrate how the model can be used at the bedside to diagnose acid-base disorders and suggest appropriate treatment. Hence, this new approach gives clinicians a new tool for diagnosing disorders and specifying fluid-therapy options for critically-ill patients.
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Registered trials
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