Evidence map›Paper›PMID 42525887›Full record

ArticleJournal of investigative medicine high impact case reports

Integrating Physiology Into Hyponatremia Algorithms: Moving Beyond Volume Status.

Jodie Mogensen, Livia Frost, Bryan Tucker, L Parker Gregg, Maulin K Shah

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In one paragraph

Article in Journal of investigative medicine high impact case reports. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jodie MogensenDepartment of Internal Medicine, Baylor College of Medicine, Houston, TX, USA.
Livia FrostSchool of Medicine, Baylor College of Medicine, Houston, TX, USA.
Bryan TuckerDepartment of Medicine, Selzman Institute for Kidney Health, Baylor College of Medicine, Houston, TX, USA.
L Parker GreggDepartment of Medicine, Selzman Institute for Kidney Health, Baylor College of Medicine, Houston, TX, USA.
Maulin K ShahDepartment of Medicine, Selzman Institute for Kidney Health, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-7195-6443

Funding

CSRD VA IK2 CX002368
6 · The paper itself

Abstract

Hyponatremia is a prevalent electrolyte disorder with a broad differential diagnosis, which can pose a challenge for determining the underlying etiology. Academic resources teach two diagnostic frameworks designed to guide a physician to the underlying etiology. One approach uses volume status and serum osmolality as earlier branch points, with later consideration of urine osmolality and urine sodium for diagnosis within certain pathways in the branching logic. The other uses serum osmolality, urine osmolality, and spot urine sodium to guide the entire diagnostic reasoning process. These two approaches can ultimately guide clinicians to different diagnoses for the same patient. In this case series, we present an adapted physiology-based (European) algorithm and describe three patients who illustrate key shortcomings of the volume status-based approach to identifying the etiology of hyponatremia. The first case emphasizes that understanding the relationship between osmolality and tonicity adds important nuance to the interpretation of measured serum osmolality. The second case demonstrates how the inherent limitations of the physical examination for volume status contribute to imprecision and inter-individual variation in volume status assessment and underscores the importance of interpreting laboratory values with nuance rather than relying rigidly on strict cutoff values as branch points in clinical reasoning. The third case illustrates that more complex presentations may not fit neatly within any single algorithm and require more nuanced clinical judgment. Together, these cases demonstrate how a diagnostic approach to hyponatremia rooted in physiology provides learners with greater insight into the underlying pathophysiology and may improve diagnostic accuracy.

Indexed as

AlgorithmsHyponatremiaDiagnosis, DifferentialFemaleHumansMaleOsmolar ConcentrationSodiumSodiumdiagnostic errordiagnostic reasoninghyponatremiatonicityvolume status

Identifiers

PMID42525887
PMCPMC13424767

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