European Journal of Cardiovascular Medicine

Anemia is a widespread hematological condition defined by a diminished oxygen-carrying capacity of the blood, primarily due to a reduced number of red blood cells (RBCs) or a lower-than-normal concentration of hemoglobin. Rather than being a definitive diagnosis, anemia often serves as a clinical indicator of an underlying pathological process. Globally, anemia continues to represent a major public health concern, particularly in developing nations where nutritional deficiencies, chronic infections, and parasitic infestations are common.^1-3

India bears a disproportionate share of this burden. According to the National Family Health Survey (NFHS-4, 2016), anemia affected 58.6% of children aged 6–59 months, 53.2% of non-pregnant women, and 50.4% of pregnant women. The World Health Organization (WHO) reported in 2019 that 53% of Indian women of reproductive age were anemic, placing the country among the top five globally in anemia prevalence.^4,5

Beyond its systemic manifestations, anemia significantly impacts the cardiovascular system. Chronic hypoxia resulting from anemia triggers compensatory mechanisms such as increased heart rate and cardiac output, which can progress to left ventricular hypertrophy and, in severe cases, high-output heart failure. Anemia is reported in approximately 30% of stable heart failure (HF) patients and up to 50% of hospitalized HF patients, underlining its clinical relevance in cardiovascular pathophysiology.^6,7

Electrocardiography (ECG), a non-invasive and cost-effective diagnostic modality, has shown promise in detecting cardiac abnormalities secondary to anemia. Commonly reported ECG changes in anemic patients include ST segment depression, T wave flattening or inversion, prolonged QT intervals, and reduced QRS amplitude. These alterations often reflect myocardial hypoxia or altered cardiac function. In recent years, advances in artificial intelligence (AI) have enabled the development of deep learning algorithms capable of detecting anemia through ECG analysis, potentially transforming ECG into a novel screening tool.^8-12

Given the high prevalence of anemia and its cardiovascular implications, the present study aims to analyze electrocardiographic changes in patients with anemia and to correlate these findings with the severity and grading of anemia. This study seeks to highlight the diagnostic value of ECG in identifying early cardiac involvement in anemic individuals and underscores its potential as a non-invasive, adjunctive tool for risk stratification and monitoring of therapy response.

Study Design and Setting

This study was a hospital-based prospective observational study conducted at Patna Medical College and Hospital, Patna, in collaboration with the Departments of Physiology, Medicine, and Obstetrics & Gynecology. The study was carried out over a period of 20 months, from February 2020 to September 2021.

Sample Size and Selection Criteria

A total of 100 patients presenting to the outpatient departments with clinical features of anemia were enrolled in the study based on specific inclusion and exclusion criteria.

• Inclusion Criteria:
• Patients with hemoglobin levels ≤7.0 g/dL
• RBC count ≤3 million/cu.mm
• Packed cell volume (PCV) ≤22%
• Patients with no known cardiac disease unrelated to anemia
• Exclusion Criteria:
• Patients with pre-existing heart disease unrelated to anemia
• Patients with systemic illnesses or electrolyte disturbances affecting ECG interpretation

Patients were classified into three groups based on RBC count:

• Severe anemia: RBC ≤1.5 million/cu.mm
• Moderate anemia: RBC between 1.51–2.5 million/cu.mm
• Mild anemia: RBC between 2.51–3.0 million/cu.mm

Data Collection and Clinical Evaluation

Each patient underwent a detailed clinical history and physical examination, which included:

• General symptoms: weakness, fatigue, palpitations, breathlessness, orthopnea, and gastrointestinal disturbances
• Past history: worm infestation, gastrointestinal bleeding, excessive menstrual bleeding
• Personal history: occupation, diet, addictions (tobacco, alcohol, etc.)

General physical examination was done with attention to:

• Vital signs (pulse, blood pressure)
• Signs of pallor, cyanosis, edema, clubbing, lymphadenopathy, koilonychia
• Systemic examination of cardiovascular, respiratory, gastrointestinal, and central nervous systems

Laboratory Investigations

Blood, stool, and urine investigations were performed for all patients:

• Hematological Parameters:
• Hemoglobin (Sahli’s method)
• RBC count, PCV, WBC count (using Semi-Automated Analyzer: Caretium NB201)
• Reticulocyte count
• Differential WBC count using Leishman-stained peripheral smear
• Calculated Indices:
• Mean Corpuscular Volume (MCV)
• Mean Corpuscular Hemoglobin (MCH)
• Mean Corpuscular Hemoglobin Concentration (MCHC)
• Color Index
• Stool Examination: Microscopy using saline and iodine suspension and levitation method for ova detection
• Urine Analysis: Routine physical, chemical, and microscopic examination

Radiological Assessment

All patients underwent chest X-ray (PA view). Cardiothoracic ratio (CTR) was calculated as per standard guidelines and considered abnormal if >50%.

Electrocardiographic Evaluation

Electrocardiograms were recorded using a 12-lead direct-writing machine (HEIDELCO 1200) for all patients:

• 3 standard bipolar limb leads (I, II, III)
• 3 augmented unipolar limb leads (aVR, aVL, aVF)
• 6 precordial (chest) leads (V1–V6)

ECG Parameters Analyzed:

1. Heart Rate: Bradycardia (<60 bpm), normal (60–99 bpm), tachycardia (≥100 bpm)
2. Voltage Criteria: R wave amplitude ≤5 mm in limb leads or ≤7 mm in chest leads
3. ST Segment Changes: Depression or sagging, especially in leads II, III, aVF, V5, V6
4. T Wave Abnormalities: Flattening, inversion, or isoelectric patterns
5. Presence of:
• Bundle branch blocks
• Ventricular or atrial hypertrophy
• Prolonged PR or QT intervals

ECG tracings were repeated after correction of anemia (Hb >7.0 g/dL) to evaluate reversibility of changes.

Statistical Analysis

Descriptive statistics were used to summarize demographic and clinical variables. Frequencies, percentages, and averages were calculated to represent the prevalence of ECG changes across various grades of anemia. Correlations between hemoglobin levels, RBC count, heart rate, and ECG abnormalities were analyzed.

The study conducted at Patna Medical College Hospital, Patna from February 2020 to September 2021 analyzed electrocardiographic (ECG) changes in 100 anemic patients, correlating these with anemia severity, hemoglobin levels, and other factors.

This table presents the demographic profile and anemia severity classification of the study population. The study included 100 patients aged between 15 and 60 years, with a slight male predominance (54 males vs. 46 females). Based on red blood cell (RBC) counts, the majority of cases (74%) fell into the moderate anemia category (RBC 1.51–2.5 million/cu.mm), followed by 14% classified as severe (≤1.5 million/cu.mm), and 10% as mild (2.51–3.0 million/cu.mm). Hemoglobin levels ranged from 2.0 to 7.0 g/100 ml, reflecting a population with predominantly moderate to severe anemia.

Table 1: Demographic and Anemia Severity Distribution

This table details the distribution of heart rate abnormalities among the patients. Sinus tachycardia was the most common finding, present in 45 patients (45%) with an average heart rate of 109.6 bpm, particularly in those with lower hemoglobin levels. Fifteen patients (15%) had sinus bradycardia with an average rate of 58.6 bpm, often associated with borderline or moderately low hemoglobin. The remaining 40 patients (40%) exhibited normal heart rates ranging between 62 to 93 bpm. These findings suggest a compensatory cardiovascular response to anemia, with tachycardia predominating in cases of more severe anemia.

Table 2: Heart Rate  This table consolidates heart rate distribution (Table IV) and axis deviation observations.

The axis deviation findings show that 98% of the study subjects had a horizontal heart position with left axis deviation, consistent with a normotensive heart in most anemic individuals. Only two patients exhibited right axis deviation, which was associated with a vertical heart position. This observation suggests that axis deviation was not a frequent or dominant feature in this anemic cohort and likely reflects individual anatomical variation rather than a direct effect of anemia.

Table 3: Axis Deviation

Out of the 100 patients, 83 exhibited ECG abnormalities, with a nearly even distribution between males (39) and females (44). The most frequent ECG abnormality was low amplitude QRS complexes, recorded in 60 patients, with 5 of these cases showing abnormally low amplitudes (≤2 mm). ST segment depression was present in 45 patients, with sagging noted in 20 of those cases. T wave abnormalities included flattening in 15 patients and inversion in 11, predominantly in leads III, aVF, V5, and V6. Notably, 5 patients showed no inversion in V1, which is typically expected. This table highlights a high prevalence of electrocardiographic changes in anemic patients, with a range of subtle to significant abnormalities that are potentially reversible.

Table 4: ECG Abnormalities by Type and Gender

This table clearly demonstrates a positive correlation between anemia severity and the frequency of ECG abnormalities. Among the 14 severely anemic patients, the majority exhibited significant changes—12 had low QRS amplitude, 12 had ST depression, 8 had sagging ST segments, and 10 showed T wave changes. In the moderate anemia group (74 patients), abnormalities were still prevalent but less frequent, and in the mild anemia group (10 patients), such changes were minimal. These trends suggest that the severity of anemia has a direct and quantifiable effect on cardiac electrical activity.

Table 5: ECG Abnormalities by Anemia Severity

While most ECG changes resolved following anemia correction (particularly when hemoglobin rose above 7 g/100 ml), three patients exhibited persistent abnormalities. Two had partial right bundle branch block, and one had left ventricular hypertrophy accompanied by posterior hemi-block, ST segment sagging, and T wave inversion. These persistent changes were not reversible post-treatment, indicating possible underlying structural heart disease or chronic damage due to prolonged anemia. Conversely, 80 patients demonstrated complete resolution of low QRS amplitude, ST segment depression, and T wave changes upon correction of their hemoglobin levels, reinforcing the reversible nature of anemia-induced ECG alterations in the majority of cases.

Table 6: Persistent ECG Changes and Reversibility

This table summarizes critical observational insights. There was no consistent correlation between hemoglobin level and cardiac enlargement, or between hemoglobin and ECG changes—some patients with hemoglobin <3 g/dL had normal ECGs, while others with >5 g/dL exhibited abnormalities. Heart rate tended to be higher in those with hemoglobin <3 g/dL, whereas bradycardia was found in the 4–7 g/dL range. ECG abnormalities were more common in females, especially in those with a cardiothoracic ratio (CTR) >60%. Age and anemia etiology did not significantly influence ECG changes. Although anemia duration varied from 3 months to 1 year, no clear relationship was found between duration and ECG abnormality. Maximum abnormalities were recorded in patients with CTR >55%, especially >60%, indicating a strong correlation between heart size and ECG alterations.

Table 7: Correlations and Additional Observations

This study evaluated the electrocardiographic (ECG) manifestations in patients with varying degrees of anemia and attempted to correlate these findings with hemoglobin levels, red blood cell (RBC) counts, and cardiothoracic parameters. The analysis revealed a significant prevalence of ECG abnormalities in anemic patients, with distinct trends observed in relation to the severity of anemia, supporting previous findings in both classical and contemporary studies.

The demographic profile demonstrated a nearly balanced gender distribution, with a slightly higher number of male patients. Most patients belonged to the 15–60 years age group. The majority of cases (74%) had moderate anemia, followed by severe (14%) and mild (10%) cases. This reflects the real-world prevalence of moderate anemia in outpatient settings. Hemoglobin levels ranged from 2.0 to 7.0 g/dL, placing the entire sample within the clinically significant anemia threshold. These figures align with national data from NFHS and WHO reports, which highlight the widespread prevalence of moderate-to-severe anemia in the Indian population, especially among females.4,5

A predominant finding was sinus tachycardia, present in 45% of cases, with an average heart rate of 109.6 bpm. This can be interpreted as a physiological compensatory mechanism to maintain adequate tissue oxygenation in the face of diminished hemoglobin levels. Sinus bradycardia, though less common (15%), was observed in cases where hemoglobin ranged between 4 and 7 g/dL, suggesting that chronic adaptation or coexisting autonomic dysfunction may play a role. Interestingly, most patients demonstrated left axis deviation, consistent with a horizontal heart position. Only two cases had right axis deviation, which may be attributed to anatomical or postural variation rather than anemia per se.

ECG abnormalities were observed in 83% of patients. The most common findings included low amplitude QRS complexes (60%), ST segment depression (45%), and T wave changes (15% flattening, 11% inversion). These abnormalities reflect underlying myocardial stress, possible subendocardial ischemia, or altered conduction pathways, which are known to occur in chronic hypoxic states. Flattened or inverted T waves, especially in leads III, aVF, V5, and V6, are suggestive of repolarization disturbances due to tissue hypoxia. These findings are supported by earlier studies, who reported similar ECG patterns in anemic patients, linking them to myocardial anoxia and high-output states.^8,10,11

A strong association between the severity of anemia and frequency of ECG abnormalities was evident. Among severely anemic patients, 85% had low QRS amplitude, 85% had ST depression, and 71% showed T wave changes. The moderate anemia group still showed considerable abnormalities, though at a reduced frequency. The mild group, as expected, showed minimal ECG changes. These observations underscore the progressive nature of anemia-induced myocardial strain and support the hypothesis that as anemia worsens, myocardial oxygen demand-supply mismatch intensifies, leading to measurable electrical changes.

Notably, the majority of ECG abnormalities—especially low voltage QRS, ST depression, and T wave flattening—were reversible upon correction of anemia, typically once hemoglobin exceeded 7 g/dL. This supports the view that these changes are largely functional rather than structural. However, a small subset (3%) of patients demonstrated persistent abnormalities, including partial right bundle branch block and left ventricular hypertrophy with posterior hemi-block. These may indicate long-standing cardiac remodeling or coexisting cardiomyopathy that has developed due to chronic hypoxia, reinforcing the need for timely intervention in anemic patients to prevent irreversible cardiac changes.

Contrary to intuitive assumptions, there was no consistent linear relationship between hemoglobin levels and ECG abnormalities. Some patients with extremely low hemoglobin (<3 g/dL) had normal ECGs, while others with higher levels (>5 g/dL) showed significant changes. This highlights the role of individual variation, chronicity of anemia, and compensatory mechanisms. Heart rate correlated more predictably, with higher rates noted in more severe anemia. Gender differences were also apparent, with females showing more abnormalities, especially in those with a cardiothoracic ratio (CTR) >60%, possibly due to delayed presentation and nutritional deficits. Duration of anemia did not show a strong correlation with ECG findings, although those with longer-standing anemia were more likely to have tachycardia.

Another important observation was the association between cardiac enlargement (CTR >55%) and the presence of multiple ECG abnormalities. This supports prior findings that chronic anemia may lead to dilated cardiac chambers and high-output failure, especially if left untreated.^9-12

Clinical Relevance and Future Scope

The findings of this study carry important clinical implications. ECG, being a simple and widely available diagnostic tool, can offer valuable insights into the cardiovascular status of anemic patients. Its ability to reflect early myocardial stress, even before clinical heart failure manifests, makes it a potentially powerful screening tool in both rural and urban healthcare settings. Moreover, the observed reversibility of ECG abnormalities post-treatment reaffirms the importance of early anemia detection and correction.

The growing intersection of AI with ECG analysis, as mentioned in recent literature, offers an exciting avenue for developing automated, non-invasive screening systems to detect anemia based on ECG patterns. This could revolutionize screening protocols, especially in resource-limited areas.

This study reaffirms the significant impact of anemia on cardiac electrophysiology and highlights the value of electrocardiography (ECG) as a sensitive, non-invasive tool in detecting early cardiovascular changes in anemic patients. A high prevalence of ECG abnormalities—particularly low QRS amplitude, ST segment depression, and T wave changes—was observed, with a strong correlation to the severity of anemia. Importantly, most of these alterations were reversible upon correction of hemoglobin levels, indicating functional rather than structural myocardial involvement in the majority of cases. The findings underscore the need for early identification and management of anemia to prevent long-term cardiac complications. Moreover, the study supports the integration of ECG into routine anemia assessment, particularly in resource-limited settings where more advanced diagnostics may not be readily accessible. With the advent of artificial intelligence in healthcare, future research may focus on leveraging ECG-based algorithms to screen and monitor anemia more efficiently. In conclusion, timely ECG evaluation in anemic patients can serve not only as a diagnostic aid but also as a predictive marker for cardiac stress, guiding both immediate intervention and long-term care strategies.

1. World Health Organization. Anaemia [Internet]. Geneva: WHO; [cited 2025 Apr 18]. Available from: https://www.who.int/health-topics/anaemia#tab=tab_1
2. Anaemia [Internet]. [cited 2025 Apr 18]. Available from: https://www.physio-pedia.com/Anaemia
3. Understanding Anemia: Basics [Internet]. [cited 2025 Apr 18]. Available from: https://www.webmd.com/a-to-z-guides/understanding-anemia-basics
4. Rai RK, Kumar SS, Sen Gupta S, Parasannanavar DJ, Anish TSN, Barik A, et al. Shooting shadows: India's struggle to reduce the burden of anaemia. Br J Nutr. 2023;129(3):416–27.
5. Chakrabarty M, Singh A, Singh S, Chowdhury S. Is the burden of anaemia among Indian adolescent women increasing? Evidence from Indian Demographic and Health Surveys (2015-21). PLOS Glob Public Health. 2023;3(9):e0002117.
6. Metivier F, Marchais SJ, Guerin AP, Pannier B, London GM. Pathophysiology of anaemia: focus on the heart and blood vessels. Nephrol Dial Transplant. 2000;15 Suppl 3:14–8.
7. Mozos I. Mechanisms linking red blood cell disorders and cardiovascular diseases. Biomed Res Int. 2015;2015:682054.
8. Biradar SM, Teja VR, Shannawaz M, Holyachi R. Electrocardiographic abnormalities in severe anaemia and its reversibility after correction of anaemia in North Karnataka, India. Int J Adv Med. 2020;7:1566–9.
9. Stanojević M, Stankov S. Elektrokardiografske promene kod bolesnika s hronicnom anemijom [Electrocardiographic changes in patients with chronic anemia]. Srp Arh Celok Lek. 1998;126(11–12):461–6.
10. Ceasovschih A, Șorodoc V, Covantsev S, et al. Electrocardiogram features in non-cardiac diseases: From mechanisms to practical aspects. J Multidiscip Healthc. 2024;17:1695–1719.
11. Patidar V, Sharma A, Malvi M, Adhikari A, Tripathi AP. Study of cardiac changes in patients with iron deficiency anaemia and its correlation. J Res Med Dent Sci. 2022;10(2):788–93.
12. GV S, PK S, Herur S, Chinagudi A, Patil S, Ankad RB, Badami SV. Correlation between haemoglobin level and electrocardiographic (ECG) findings in anaemia: A cross-sectional study. J Clin Diagn Res. 2014;8(4):BC04–6.