Correlation Between Haemoglobin Level and Electrocardiographic (ECG) Findings in Anaemia: A Cross-Sectional Study

Gv, Shashikala; Pk, Shashidhar; Herur, Anita; Chinagudi, Surekharani; Patil, Sangamesh A.; Ankad, Roopa; Badami, Sukanya

doi:10.7860/jcdr/2014/8966.4202

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…As shown by Shakuntala et al [ 21 ] we also observed that in the group which had acute blood loss, there was a strong correlation between change in hemoglobin and ST segment with a Pearson coefficient of 0.608 ( P -value = 0.012). ST segment depression reflects myocardial ischemia and as the myocardium has a higher extraction ratio of oxygen than the other tissues, changes in the ST segment are also reflective of hemoglobin content and may be a sensitive indicator of acute hypovolemic anemia.…”

Section: Discussionsupporting

confidence: 80%

Changes in central venous oxygen saturation, lactates, and ST segment changes in a V lead ECG with changes in hemoglobin in neurosurgical patients undergoing craniotomy and tumor excision: A prospective observational study

Pappachan

Williams

Sebastian

et al. 2019

J Anaesthesiol Clin Pharmacol

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Section: Discussionsupporting

confidence: 80%

Changes in central venous oxygen saturation, lactates, and ST segment changes in a V lead ECG with changes in hemoglobin in neurosurgical patients undergoing craniotomy and tumor excision: A prospective observational study

Pappachan

Williams

Sebastian

et al. 2019

J Anaesthesiol Clin Pharmacol

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“…Thus, this decrease in amplitude of QRS and T waves has been reported during anemia. 43 The observed changes in ECG could be linked to hypoxia-induced changes in ATPdependent channels. During cardiac ischemia, ATP levels drop and then K ATP channels are opened to reduce ADP and to prevent excessive depolarization, 44 shortening the action potential duration, maintaining excitability, and protecting the metabolism of myocytes from the injuries caused by ischemia.…”

Section: Discussionmentioning

confidence: 99%

Electrocardiographic Changes During Exercise in Acute Hypoxia and Susceptibility to Severe High-Altitude Illnesses

et al. 2015

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Background-The goals of this study were to compare ECG at moderate exercise in normoxia and hypoxia at the same heart rate, to provide evidence of independent predictors of hypoxia-induced ECG changes, and to evaluate ECG risk factors of severe high-altitude illness. Methods and Results-A total of 456 subjects performed a 20-minute hypoxia exercise test with continuous recording of ECG and physiological measurements before a sojourn above 4000 m. Hypoxia did not induce any conduction disorder, arrhythmias, or change in QRS axis. The amplitude of the P wave in V 1 was lower in hypoxia than in normoxia. The amplitudes of the R, S, and T waves and the Sokolow index decreased in hypoxia. Under hypoxia, the amplitude of the ST segment decreased in II and V 6 and increased in V 1 , the ST slope rose in V 5 and V 6 , and the J point was lower in II, V 5 , and V 6 . Multivariate regression of hypoxic/normoxic ratios of electrophysiological parameters and clinical characteristics showed a correlation between the decrease in Sokolow index and T-wave amplitude in V 5 with desaturation at exercise. Trained status and low body mass index were associated with a smaller decrease in T-wave amplitude in V 5 and V 6 .Comparison of ECG between subjects suffering or not suffering from severe high-altitude illness failed to show any difference. Conclusions-During

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“…[6][7][8] In several previous studies, anaemia was shown to change the morphology of the electrocardiogram (ECG), and researchers suggested that mismatching oxygen demand and supply in the myocardium affects the ECG. [9][10][11][12] However, it is not easy to detect such subtle ECG changes, so the current state of the ECG is not useful for detecting anaemia. Screening for anaemia with an ECG would be straightforward, and patients who were suspected to be anaemic could be referred for confirmatory laboratory tests.…”

Section: Introductionmentioning

confidence: 99%

A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study

Kwon

Cho²,

Jeon

et al. 2020

The Lancet Digital Health

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Background Anaemia is an important health-care burden globally, and screening for anaemia is crucial to prevent multi-organ injury, irreversible complications, and life-threatening adverse events. We aimed to establish whether a deep learning algorithm (DLA) that enables non-invasive anaemia screening from electrocardiograms (ECGs) might improve the detection of anaemia.Methods We did a retrospective, multicentre, diagnostic study in which a DLA was developed using ECGs and then internally and externally validated. We used data from two hospitals, Sejong General Hospital (hospital A) and Mediplex Sejong Hospital (hospital B), in South Korea. Data from hospital A was for DLA development and internal validation, and data from hospital B was for external validation. We included individuals who had at least one ECG with a haemoglobin measurement within 1 h of the index ECG and excluded individuals with missing demographic, electrocardiographic, or haemoglobin information. Three types of DLA were developed with 12-lead, 6-lead (limb lead), and single-lead (lead I) ECGs to detect haemoglobin concentrations of 10 g/dL or less. The DLA was built by a convolutional neural network and used 500-Hz raw ECG, age, and sex as input data.

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Correlation Between Haemoglobin Level and Electrocardiographic (ECG) Findings in Anaemia: A Cross-Sectional Study

Cited by 11 publications

References 18 publications

Changes in central venous oxygen saturation, lactates, and ST segment changes in a V lead ECG with changes in hemoglobin in neurosurgical patients undergoing craniotomy and tumor excision: A prospective observational study

Changes in central venous oxygen saturation, lactates, and ST segment changes in a V lead ECG with changes in hemoglobin in neurosurgical patients undergoing craniotomy and tumor excision: A prospective observational study

Electrocardiographic Changes During Exercise in Acute Hypoxia and Susceptibility to Severe High-Altitude Illnesses

A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study

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