Temperature‐Dependent Modulation of the QRS Axis Following Water Intake in Healthy Adults: A Cross‐Sectional Study

ABSTRACT

Background and Aims

Anecdotal concerns persist regarding the safety of cold and warm water ingestion and their impact on cardiac rhythms. This study aimed to investigate the acute effects of water temperature on QRS amplitude, duration, and axis in healthy individuals using electrocardiography (ECG).

Methods

A cross‐sectional study was conducted between January 2019 and October 2020 with 25 healthy volunteers (aged 18–35). Participanats ingested 250 mL of cold (0°C–8°C), room‐temperature (~27°C), and warm water (55°C–60°C) at 10‐min intervals. Simultaneous digital ECGs were recorded, with leads III, aVR, aVL, and aVF derived using Einthoven's laws. Data was analyzed using one‐way repeated measures ANOVA and Dunnett's post‐hoc analysis ($\alpha =0.05$).

Results

Statistics are reported as Mean ± SD (n = 25). Warm water ingestion significantly decreased mean QRS amplitude in lead II (0.91 ± 0.09 to 0.86 ± 0.09 mV; p = 0.009), lead III (0.62 ± 0.09 to 0.52 ± 0.09 mV; p < 0.001), and lead aVF (0.73 ± 0.24 to 0.65 ± 0.24 mV; p < 0.001). Amplitude decreased by up to 16.3% (Lead III, warm water) and increased by 3.4% (Lead I, warm water). Cold water ingestion significantly decreased mean QRS duration from 92.1 ± 10.0 to 86.6 ± 10.0 ms (p < 0.001). Warm water intake shifted the mean QRS axis from 62.3 ± 4.86° to 59.4 ± 4.86° (p = 0.01), a 5° anticlockwise shift.

Conclusion

Water temperature acutely modulates ventricular depolarization, causing transient decreases in QRS amplitude, duration, and axis. These findings suggest internal thermal perturbations influence cardiac electrical orientation, likely due to the anatomical proximity of the gastrointestinal tract to the myocardium.

1. Introduction

The effect of drinking water temperature on cardiac rhythm remains a subject of significant scientific inquiry, with studies revealing that temperature variations can have deleterious impacts, particularly in patients with acute myocardial infarction [1, 2, 3, 4]. These effects include bradycardia [1, 2], vasoconstriction of peripheral vascular tissues [2], and arrhythmias [4]. Cardiac rhythm is governed by the heart's electrical conduction system, which controls the cardiac cycle. This system comprises a specialized pathway that transmits action potentials from the sinoatrial node to the Purkinje fibers, prompting ventricular contraction [5, 6]. When the signal reaches the Purkinje‐myocardial junctions, it triggers ventricular myocardium depolarization, producing the QRS complex observed on an electrocardiogram (ECG), characterized by its amplitude and duration [5]. Body temperature is a known independent determinant of heart rate; for instance, each 1°C rise above average core temperature can increase the heart rate by approximately 10 beats per minute [4]. Furthermore, external thermal stimuli, such as warming or cooling the forehead, can significantly modulate heart rate via peripheral thermoreceptors [1, 2].

In Sub‐Saharan Africa, specifically Ghana, ambient temperatures fluctuate significantly between the dry and rainy seasons [7]. Inhabitants adapt to these environmental stressors by modifying clothing and the temperature of consumed food and beverages to maintain thermal homeostasis [8]. While high ambient temperatures primarily influence surface temperature and trigger autonomic nervous system (ANS) responses via peripheral thermoreception [9], the ingestion of liquids introduces a direct internal thermal perturbation. Cold water ingestion, for example, is preferred in hot environments as it stimulates thermal receptors in the esophagus and osmoreceptors in the gut [10]. Unlike environmental heat gain, which must navigate the skin‐to‐core thermal gradient, liquid ingestion acts as an acute conductive load due to the anatomical proximity of the esophagus and stomach to the myocardium [11].

The ANS, through its sympathetic and parasympathetic divisions, modulates the depolarization of the sinoatrial node, thereby influencing heart rate [10, 12, 13]. ECG provides a comprehensive method to study these interactions. Despite the known association between autonomic modulation and heart rate, factors like the mean electrical axis, a measure characterizing the magnitude and predominant direction of current flow through the heart [5] have been infrequently studied in the context of internal thermal stimuli. Although extensive research has explored general cardiac electrophysiology, the specific impact of localized temperature stimuli from water ingestion on ventricular activation remains unexamined. Therefore, this study aims to investigate the effect of drinking water temperature on QRS amplitude, duration, and the mean electrical axis. We hypothesize that these internal thermal perturbations significantly affect ventricular depolarization parameters.

2. Methods

2.1. Subjects and Ethical Approval

A cross‐sectional study was conducted with twenty‐five consenting healthy volunteers aged between 18 and 35 years. While this age group historically presents a lower prevalence of cardiovascular disease, recent evidence suggests an increasing trend of subclinical cardiovascular risks in young populations [14]. Consequently, participants were recruited from the Koforidua Technical University community and subjected to rigorous objective screening. Exclusion criteria included a self‐reported history of cardiovascular disease, as well as clinical measurements of hypertension or obesity. Blood pressure (BP) was measured using an Omron digital monitor (Omron Healthcare, USA). In accordance with clinical standards for identifying normotensive controls, individuals with BP readings exceeding 140/90 mmHg were excluded. Additionally, obese subjects were excluded because elevated body mass index (BMI) correlates negatively with heart rate and may indicate a thicker esophageal lining, potentially reducing the sensitivity of thermal receptors during ingestion [10]. Baseline cardiovascular metrics are presented as systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP), segregated by gender (Table 1). MAP represents the average arterial pressure during a single cardiac cycle, serving as an indicator of the perfusion pressure to vital organs [15]. The relationship between MAP, SBP, and DBP was calculated using the following standard equation:

$$\mathit{MAP}\approx \mathit{DBP}+\frac{1}{3}(\mathit{SBP}-\mathit{DBP})$$ (1)

Table 1.

Characteristics of research participants (Mean ± SD).

Variables	Male (n = 15)	Female (n = 10)
Age, years	25 ± 3	21 ± 3
SBP, mmHg	121 ± 10	115 ± 11
DBP, mmHg	80 ± 9	74 ± 6
MAP, mmHg	94 ± 9	88 ± 7

The mean age was 25 years for male participants and 21 years for female participants. Participants within this range typically exhibit a mean electrical axis between 0 and +90 degrees, indicating normal ventricular depolarization and absence of underlying pathology [5]. All participants met the inclusion criteria, with BP values falling within the normal physiological range. The study protocol was reviewed and approved by the Ethics Committee for Basic and Applied Sciences (ECBAS) of the University of Ghana (Reference: ECBAS 013/19‐20). All experimental procedures were conducted between January 2019 and October 2020.

2.2. ECG Acquisition and Experimental Protocol

Frontal plane 12‐lead electrocardiograms (ECG) were digitally recorded using the BIOPAC MP36 data acquisition system (BIOPAC Systems Inc., USA) at a sampling rate of 2000 Hz. The system was configured with three analog channels and four calculation channels, utilizing a preset frequency bandpass filter of 0.5–35 Hz to minimize signal artifacts (Table 2). Two analog channels were dedicated to the acquisition of leads I and II, while the third was allocated for chest lead recordings. Calculation channels were employed to derive limb leads III, aVR, aVL, and aVF based on the mathematical derivations of Einthoven's laws [5, 6]. Chest leads were recorded simultaneously with the limb leads over a total duration of 60 s per trial. Participants were positioned in a supine posture with the head elevated at a 30‐degree angle to standardize the anatomical orientation of the heart relative to the stomach. Electrodes were affixed to specific anatomical sites on the limbs and precordium to ensure a standard 12‐lead configuration [5]. Following baseline (control) recordings, participants consumed 250 mL of water at three distinct temperatures in randomized order: cold (0°C–8°C), room temperature (~27°C), and warm (55°C–60°C). Post‐ingestion ECG recordings were obtained after each session. A 10‐min rest interval was maintained between drinking sessions to allow the internal temperature of the esophagus and stomach to return to physiological homeostasis. This interval was selected based on established models of thermoregulatory recovery, which suggest that localized internal thermal perturbations dissipate significantly within this time frame [16].

Table 2.

Software channels setup for 12‐LEAD ECG [Reproduced from Ref. Pflanzer, McMullen [5].

Channel	Label	Preset	Function
Analog CH1 (A1)	Lead I	ECG (0.5–35 Hz)
Analog CH2 (A2)	Lead II	ECG (0.5–35 Hz)
Analog CH3	Precordial (chest)	ECG (0.5–35 Hz)
Calculation C1 (40)	Lead III (calc)	Expression	A2 − A1
Calculation C2 (41)	aVR (calc)	Expression	‐(A1 + A2)/2
Calculation C3 (42)	aVL (calc)	Expression	(A1 − C1)/2
Calculation C4 (43)	aVF (calc)	Expression	(A2 + C1)/2

2.3. Signal Processing and Morphological Analysis

The electrocardiogram (ECG) waveforms were visualized using the BIOPAC Student Lab software (BIOPAC Systems Inc., USA), optimized for high‐resolution analysis of the QRS complex across all recorded leads (I, II, V, III, aVR, aVL, and aVF; Figure 1A). To ensure temporal and jurisdictional accuracy in measuring ventricular depolarization, the automated QRS boundary detection algorithm within the BIOPAC system was employed. This feature identified the exact onset (Q‐wave initiation) and termination (J‐point) of the QRS complex within each cardiac cycle (Figure 1B). The QRS amplitude was quantified as the peak‐to‐peak voltage (mV) from the maximum positive deflection to the maximum negative deflection within the identified complex. To minimize the impact of respiratory sinus arrhythmia and baseline wander, multiple measurements were performed over a 60‐second window, and the results were averaged to derive the mean QRS amplitude. Similarly, the QRS duration (milliseconds) was defined as the temporal width of the complex from the initial deflection from the isoelectric baseline to its return. Multiple cycles were sampled and averaged to compute the mean QRS duration for each lead. These metrics provided the necessary data for subsequent calculation of the mean electrical axis in the frontal plane [5].

Figure 1.

Automated QRS boundary detection and morphological analysis. (A) Representative 60‐second digital ECG recording of the frontal limb leads (I, II, III) and augmented leads (aVR, aVL, aVF) acquired at 2000 Hz. (B) Magnified view of a single cardiac cycle in lead I. The vertical dashed lines indicate the automated detection of the QRS onset (Q‐wave initiation) and termination (J‐point) used to calculate mean QRS duration and peak‐to‐peak amplitude.

2.4. Mean Electrical Axis Calculation

The mean QRS axis in the frontal plane was determined using the bipolar method, which offers superior precision over the traditional isoelectric lead approach. While the isoelectric method identifies the equiphasic complex where the electrical current travels orthogonally to a lead axis, it is often limited by a $\pm 15°$ margin of error when leads are not perfectly isoelectric [5, 17]. To enhance measurement accuracy, the algebraic sum of the Q, R, and S‐wave amplitudes from leads I and III were calculated for each participant [18]. These resultant amplitudes were plotted as vectors on a vectorcardiogram in the frontal plane. A resultant vector was then derived between the two leads; the direction of this vector represents the mean QRS axis, while its magnitude indicates the mean electrical potential [6]. This vectorcardiographic approach ensures that the 5‐degree anticlockwise shifts observed in this study were captured with high sensitivity, surpassing the resolution of standard lead‐axis estimations.

2.5. Statistical Analysis

Statistical analyses were conducted using GraphPad Prism version 10.6.1 (GraphPad Software Inc., USA). The distribution of electrocardiogram (ECG) measurements was assessed for normality using the D'Agostino‐Pearson test; the normality assumption was considered met at $P>0.05$. Descriptive statistics for all normally distributed continuous variables are presented as Mean ± Standard Deviation (SD). To evaluate the effect of drinking water temperature on QRS amplitude, QRS duration, and the mean electrical axis, a one‐way repeated measures analysis of variance (ANOVA) was performed. For all significant ANOVA results, Dunnett's post hoc analysis was subsequently carried out to identify specific differences between temperature conditions and the baseline control. In these analyses, the studentized range $\left(q\right)$ was calculated to determine the standardized difference between means relative to the sample standard deviation. In accordance with the SAMPL guidelines, all primary outcomes are reported with 95% Confidence Intervals (CIs) to indicate the precision of the estimates [19]. All statistical tests were two‐sided with a priori significance level set at $\alpha =.05$. $P$‐values are reported following standard clinical conventions [20].

3. Results

3.1. Mean QRS Amplitude

The mean QRS amplitudes in millivolts (mV) are presented as Mean ± SD for all experimental conditions (Table 3). A one‐way repeated measures ANOVA revealed a statistically significant main effect of water temperature on the mean QRS amplitude in lead II [F(3, 72) = 3.41, p = 0.02]. Statistically significant main effects were also detected in lead III [F(3, 72) = 11.28, p < 0.001] and lead aVF [F(3, 72) = 11.03, p < 0.001] (Figure 2A).

Table 3.

Anova results on the mean QRS amplitudes (Mean ± SD) millivolts.

Lead	Control (K)	Cold water (C)	Water at room temperature (R)	Warm water (W)	$\mathit{F}$ ‐ratio	$\mathit{P}$ ‐value
I	0.501 ± 0.06	0.510 ± 0.06	0.499 ± 0.06	0.518 ± 0.06	1.13	0.34
II	0.910 ± 0.09	0.883 ± 0.09	0.896 ± 0.09	0.855 ± 0.09	3.41	0.02
III	0.620 ± 0.09	0.536 ± 0.09	0.560 ± 0.09	0.519 ± 0.09	11.28	< 0.001
aVR	0.663 ± 0.13	0.638 ± 0.13	0.668 ± 0.13	0.658 ± 0.13	0.51	0.68
aVL	0.358 ± 0.17	0.323 ± 0.17	0.328 ± 0.17	0.328 ± 0.17	2.37	0.08
aVF	0.729 ± 0.24	0.680 ± 0.24	0.698 ± 0.24	0.650 ± 0.24	11.03	< 0.001
V1	1.142 ± 0.25	1.081 ± 0.25	1.109 ± 0.25	1.148 ± 0.25	0.81	0.49
V2	1.973 ± 0.46	1.788 ± 0.46	1.795 ± 0.46	1.945 ± 0.46	2.23	0.09
V3	2.135 ± 0.50	1.972 ± 0.50	1.948 ± 0.50	2.110 ± 0.50	1.79	0.16
V4	2.092 ± 0.56	1.998 ± 0.56	1.923 ± 0.56	2.118 ± 0.56	1.26	0.29
V5	1.664 ± 0.47	1.589 ± 0.47	1.532 ± 0.47	1.694 ± 0.47	1.25	0.30
V6	1.279 ± 0.30	1.235 ± 0.30	1.205 ± 0.30	1.306 ± 0.30	1.12	0.35

Note: Bold values were meant to highlight the groups that showed significant main effects as well as during the posthoc tests.

Figure 2.

Effect of drinking water temperature on ventricular depolarization parameters. Comparison of (A) Mean QRS amplitude in leads II, III, and aVF, (B) Mean QRS duration in lead I, and (C) Mean electrical axis in the frontal plane (n = 25). Conditions include baseline control (K), cold water (C: 0°C–8°C), room temperature water (R: ~27°C), and warm water (W: 55°C–60°C). All digital ECG signals were acquired at a sampling frequency of 2000 Hz. QRS amplitudes were measured peak‐to‐peak, and the frontal axis was derived via the bipolar method using leads I and III. Data is presented as Mean ± SD. Statistical significance was determined using one‐way repeated measures ANOVA followed by Dunnett's post‐hoc analysis.

Further post‐hoc analysis (Dunnett's test) indicated specific differences relative to the control (Table 4). In lead II, the mean QRS amplitude decreased significantly during the warm water experiment (0.91 ± 0.09 to 0.86 ± 0.09 mV; 95% CI [0.012, 0.098]; p = 0.009). In lead III, significant reductions were observed across cold (p < 0.001), room temperature (p = 0.005), and warm water (p < 0.001) conditions. Similarly, lead aVF showed significant decreases during the cold water (p = 0.003) and warm water (p < 0.001) experiments. A relative change analysis indicated that QRS amplitude decreased by as much as 16.3% (Lead III, warm water) and increased by up to 3.4% (Lead I, warm water) across all leads (Table 5).

Table 4.

Dunnett post hoc analysis on the variables that detected significant main effect in the group comparisons using one‐way repeated measures Anova.

Variable	Group	Mean difference	95% CI	$\mathit{q}$ ‐value	$\mathit{P}$ ‐value
II Amplitude (mV)	Control vs. Cold Water Control vs. Water at Room Temperature Control vs. Warm Water	0.027 0.014 0.055	[−0.016, 0.071] [−0.029, 0.057] [0.012, 0.098]	1.514 0.766 3.061	0.31 0.79 0.009
III amplitude (mV)	Control vs. Cold Water Control vs. Water at Room Temperature Control vs. Warm Water	0.084 0.060 0.101	[0.039, 0.129] [0.016, 0.105] [0.057, 0.146]	4.507 3.246 5.438	< 0.001 0.005 < 0.001
aVF amplitude (mV)	Control vs. Cold Water Control vs. Water at Room Temperature Control vs. Warm Water	0.049 0.031 0.080	[0.015, 0.083] [−0.003, 0.065] [0.046, 0.114]	3.439 2.187 5.614	0.003 0.08 < 0.001
QRS duration (ms)	Control vs. Cold Water Control vs. Water at Room Temperature Control vs. Warm Water	5.512 −0.280 0.096	[2.672, 8.352] [−3.120, 2.560] [−2.744, 2.936]	4.658 0.237 0.081	< 0.001 > 0.99 > 0.99
QRS axis (deg)	Control vs. Cold Water Control vs. Water at Room Temperature Control vs. Warm Water	2.028 1.368 2.876	[−0.312, 4.368] [−0.972, 3.708] [0.536, 5.216]	2.080 1.403 2.950	0.10 0.37 0.01

Note: Bold values were meant to highlight the groups that showed significant main effects as well as during the posthoc tests.

Table 5.

Percentage change in mean QRS amplitude relative to baseline.

Lead	Cold water v control	Water at room temperature v control	Warm water v control
I	+0.009/0.501 (+ 1.8%)	−0.002/0.501 (−0.4%)	+0.017/0.501 (+ 3.4%)
II	−0.027/0.910 (−3.0%)	−0.014/0.910 (−1.5%)	−0.055/0.910 (−6.0%)
III	−0.084/0.620 (−13.5%)	−0.060/0.620 (−9.7%)	−0.101/0.620 (−16.3%)
aVR	−0.025/0.663 (−3.8%)	+0.005/0.663 (+ 0.8%)	−0.005/0.663 (−0.8%)
aVL	−0.035/0.358 (−9.8%)	−0.030/0.358 (−8.4%)	−0.030/0.358 (−8.4%)
aVF	−0.049/0.729 (−6.7%)	−0.031/0.729 (−4.3%)	−0.079/0.729 (−10.8%)
V1	−0.061/1.142 (−5.3%)	−0.033/1.142 (−2.9%)	+0.006/1.142 (+ 0.5%)
V2	−0.185/1.973 (−9.4%)	−0.178/1.973 (−9.0%)	−0.028/1.973 (−1.4%)
V3	−0.163/2.135 (−7.6%)	−0.187/2.135 (−8.8%)	−0.025/2.135 (−1.2%)
V4	−0.094/2.092 (−4.5%)	−0.169/2.092 (−8.1%)	+0.026/2.092 (+ 1.2%)
V5	−0.075/1.664 (−4.5%)	−0.132/1.664 (−7.9%)	+0.030/1.664 (+ 1.8%)
V6	−0.044/1.279 (−3.4%)	−0.074/1.279 (−5.8%)	+0.027/1.279 (+ 2.1%)

3.2. Mean QRS Duration

Mean QRS durations (Mean ± SD) for control, cold, room temperature, and warm water experiments were 92.1 ± 10.0 ms, 86.6 ± 10.0 ms, 92.4 ± 10.0 ms, and 92.0 ± 10.0 ms, respectively. The one‐way repeated measures ANOVA detected a significant main effect in lead I [F(3, 72) = 11.13, p < 0.001] (Figure 2B). Post‐hoc analysis identified a significant reduction between the control and cold water ingestion (92.1 ± 10.0 to 86.6 ± 10.0 ms; 95% CI [2.67, 8.35]; p < 0.001) (Table 4). This represents a 5.97% decrease in mean QRS duration, whereas no significant changes were observed for room temperature or warm water.

3.3. QRS Axis

The mean QRS axis (Mean ± SD) for control, cold, room temperature, and warm water experiments were 62.3 ± 4.86°, 60.2 ± 4.86°, 60.9 ± 4.86°, and 59.4 ± 4.86°, respectively. A one‐way repeated measures ANOVA detected a significant main effect of ingestion temperature on the frontal QRS axis [F(3, 72) = 3.10, p = 0.03] (Figure 2C).

Post‐hoc analysis revealed a significant anticlockwise shift between the control and the warm water experiment (62.3 ± 4.86° to 59.4 ± 4.86°; 95% CI [0.54, 5.22]; p = 0.01) (Table 4). This represents a 5° anticlockwise shift on the frontal vectorcardiogram. The axis decreased (shifted anticlockwise) by 3.26% after cold water, 2.20% after room temperature water, and 4.61% after warm water ingestion.

4. Discussion

The QRS amplitude across cold, room‐temperature, and warm water experiments differed significantly from baseline. The reduction in mean QRS amplitude was most prominent in leads II, III, and aVF, with the most substantial effect observed following warm water ingestion. These leads provide specific graphical information regarding the heart's inferior electrical activities, where the QRS complex is typically upright in lead II and may vary in III and aVF based on the electrical axis [21]. The marked decrease in amplitude following warm water ingestion aligns with documented literature regarding thermal influences on ventricular myocardium depolarization [6, 22].

QRS amplitude is influenced by several biophysical factors, including the speed of endocardial activation and both intracellular and extracellular conductivities [13]. As established by volume conductor theory, changes in the conductivity of internal media such as the presence of water at varying temperatures in the anatomically adjacent stomach can alter the projection of cardiac electrical sources to the body surface [11]. Warm water ingestion appears to delay endocardial activation and the conduction of action potentials through ventricular myocytes. Conversely, the decrease observed during cold water ingestion likely validates findings suggesting that such stimuli trigger cardiovagal activations, primarily via the esophageal‐cardiac reflex [10].

The mean QRS duration also exhibited significant changes, particularly a decrease following cold water ingestion. This aligns with reports that stimulating the oral cavity and esophagus with cold stimuli triggers autonomic responses [2, 10]. A reduced QRS duration suggests increased intracellular conductivity, potentially driven by heightened sympathetic activity [12]. While increased sympathetic tone typically enhances the force of contraction (R‐peak), the concurrent decrease in QRS amplitude suggests a complex interplay between sympathetic and parasympathetic influences. Furthermore, the reduced QRS width may reflect peripheral vasoconstriction responses to cold stimuli, which inherently modulate heart rate [5].

The QRS axis significantly shifted after ingestion, most notably following warm water. Warm water intake resulted in an approximately 5‐degree anticlockwise shift toward the $0°$ axis. This shift is mathematically consistent with the observed decrease in electrical potentials in leads I and III. Beyond physiological shifts, axis deviations are often associated with conduction obstructions, such as bundle branch blocks [23]. The transient shift observed here likely reflects a combination of localized thermal effects on conduction velocity and a minor anatomical displacement of the heart's apex due to gastric distension.

From a clinical perspective, these observations are hypothesis‐generating. Prolonged ventricular depolarization (QRS duration $\ge 120$ ms) indicates electrical dyssynchrony and represents an established prognostic risk factor in heart failure [24]. While the transient shortening of QRS duration following cold water ingestion is an intriguing physiological observation, whether acute internal thermal stimuli could exert any meaningful or sustained effect on prolonged ventricular activation in clinical populations remains speculative and requires dedicated investigation.

5. Limitations and Future Directions

While this study establishes a baseline for temperature‐dependent QRS modulation, several limitations warrant consideration. First, while the sample size of 25 participants was sufficient to detect statistically significant main effects, the cohort was restricted to healthy young adults to minimize confounding variables [14]. Consequently, these findings may not be directly generalizable to older populations or those with pre‐existing conduction abnormalities. Second, although the 10‐min rest interval between sessions was based on established thermoregulatory recovery models [16], future research could utilize continuous esophageal temperature monitoring to verify the precise return to homeostasis.

Additionally, while the bipolar method (leads I and III) is a validated standard for axis calculation [18], future studies might employ a full 12‐lead triad formula to further enhance the resolution of the frontal axis shift. We recommend that future investigations explore these thermal effects in patients with clinical electrical dyssynchrony or heart failure. Determining whether controlled internal thermal perturbations can reliably and safely shorten a prolonged QRS duration could lead to the development of non‐invasive, home‐based therapeutic adjuncts for cardiac resynchronization.

6. Conclusion

In this work, we demonstrated the significant impact of ingested water temperature on the QRS amplitude, duration, and axis of the human heart. One‐way repeated measures ANOVA revealed that the consumption of cold, room‐temperature, and warm water acutely modulates ventricular depolarization, most notably through a reduction in mean QRS amplitude in the inferior leads (II, III, and aVF). Specifically, the ingestion of cold water was found to trigger esophageal and cardiovagal activations, resulting in a statistically significant decrease in mean QRS duration.

Furthermore, the consumption of warm water led to a reduction in the mean electrical potentials of leads I and III. When plotted via the bipolar method, these changes manifested as a transient 5‐degree anticlockwise shift in the mean electrical axis. These findings suggest that internal thermal perturbations facilitated by the anatomical proximity of the gastrointestinal tract to the myocardium can acutely alter cardiac electrical orientation and conduction velocity. Given these results, further research is warranted to explore how localized thermal modulation might be utilized as a non‐invasive tool in managing clinical conditions characterized by electrical dyssynchrony.

Author Contributions

Larry Atakora‐Amaniampong: investigation, formal analysis, data curation, methodology, software, validation, writing – original draft, writing – review and editing, conceptualization, visualization. Elsie Effah Kaufmann: conceptualization, methodology, writing – review and editing, supervision, formal analysis. Anderson Mon: conceptualization, methodology, writing – review and editing, supervision, formal analysis.

Funding

The authors further declare that no supporting source or financial relationship had any involvement in the study design; collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication.

Ethics Statement

The study protocol was reviewed and approved by the Ethics Committee for Basic and Applied Sciences (ECBAS) of the University of Ghana (Reference: ECBAS 013/19‐20). All procedures followed the ethical standards of the Helsinki Declaration of 1975, as revised in 2000. Data collection was conducted between January 2019 and October 2020. Informed consent was obtained from all individual participants included in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Author Responsibility and Data Access

All authors have read and approved the final version of the manuscript. Larry Atakora‐Amaniampong had full access to all the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.

Generative AI and AI‐Assisted Technologies in the Writing Process

The authors used Gemini 2.5 to check for grammar and style.

1. Transparency Statement

Larry Atakora‐Amaniampong affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

Data Availability Statement

The dataset supporting the findings of this study is available via the Mendeley Data repository at: https://data.mendeley.com/datasets/3pj4nnhng5/1. Custom code was not utilized for this study.