Mathematical analysis of the stability of heart-rate dynamics in postinfarction patients

Mezentseva, L. V.; Перцов, С. С.; Kopilov, F. Yu.; Lastovetsky, A. G.

doi:10.1134/s0006350917030113

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…While historically collected and recorded in a manual fashion, the advent of bedside monitors now provides for the automated collection of vital sign data, in particular that of heart rate, where measures of stability/variability have repeatedly been to be valuable metrics in assessing patient outcomes. [11][12][13] Continuous monitoring devices and telemetry systems now link directly to a patient's electronic medical record and can autopopulate this document. Yet, despite the continuous stream of data made available through these monitors; a patient's chart often reflects only a subset of this information with a series of heart rate snapshots recorded throughout a hospitalization.…”

Section: Implications For Clinical Practicementioning

confidence: 99%

Section: Implications For Clinical Practicementioning

confidence: 99%

See 1 more Smart Citation

Discrete Heart Rate Values or Continuous Streams? Representation, Variability, and Meaningful Use of Vital Sign Data

Feldman¹,

Rohan²,

Chawla³

2021

CIN: Computers, Informatics, Nursing

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Documentation and review of patient heart rate are a fundamental process across a myriad of clinical settings. While historically recorded manually, bedside monitors now provide for the automated collection of such data. Despite the availability of continuous streaming data, patients' charts continue to reflect only a subset of this information as snapshots recorded throughout a hospitalization. Over the past decade, prominent works have explored the implications of such practices and established fundamental differences in the alignment of discrete charted vitals and steaming data captured by monitoring systems. Limited work has examined the temporal properties of these differences, how they manifest, and their relation to clinical applications. The work presented in this article addresses this disparity, providing evidence that differences between charting techniques extend to measures of variability. Our results demonstrate how variability manifests with respect to temporal elements of charting timing and how it can facilitate personalized care by contextualizing deviations in magnitude. This work also highlights the utility of variability metrics with relation to clinical measures including associations to severity scores and a case study utilizing complex variability metrics derived from the complete set of monitor data.

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Section: Implications For Clinical Practicementioning

confidence: 99%

Section: Implications For Clinical Practicementioning

confidence: 99%