European Journal of Cardiovascular Medicine

Dengue is a rapidly expanding arthropod-borne viral disease that poses a significant global public health threat, placing over 2.5 billion people at risk worldwide [1]. It is transmitted primarily by Aedes aegypti and Aedes albopictus mosquitoes and is endemic in more than 100 countries, particularly in tropical and subtropical regions [2]. Clinical manifestations range from mild febrile illness to severe complications, including dengue haemorrhagic fever and dengue shock syndrome, both of which can be life-threatening without timely intervention [3]. The World Health Organization emphasises that early and accurate diagnosis is essential to reduce morbidity and mortality through prompt clinical management and targeted public health measures [4].

Enzyme-linked immunosorbent assay (ELISA) is among the most widely used diagnostic tools for dengue virus detection because of its high sensitivity, specificity, and cost-effectiveness [1,4,5]. Nevertheless, the accuracy of ELISA results can be compromised by factors such as reagent degradation, operator variability, environmental influences, and improper equipment calibration [2,3]. To ensure reliability, internal quality control (IQC) is essential for continuously monitoring assay performance, detecting analytical errors, and maintaining diagnostic accuracy [5].

Levey–Jennings (LJ) charts, together with Westgard rules, are established methodologies for interpreting IQC data. These tools facilitate the identification of both random and systematic errors, enabling laboratories to promptly detect deviations and prevent the reporting of false-positive or false-negative results [4,5]. Incorporating these quality assurance measures is therefore critical for sustaining high standards in dengue diagnostic services.

This study was undertaken to prepare and implement IQC samples for Dengue IgM capture ELISA, monitor assay precision and accuracy over multiple runs, and evaluate performance using LJ charting and Westgard criteria to strengthen diagnostic quality assurance.

Study Design and Setting
This was a laboratory-based observational study conducted in the Department of Microbiology, Guntur Medical College, over a two-month period (October–December 2023). The study aimed to evaluate the internal quality control (IQC) performance of Dengue IgM capture ELISA.

Study Population and Sample Selection
The target population comprised patient serum samples received for dengue virus testing. Only samples of high quality were included. Exclusion criteria were leakage, contamination, improper storage, or insufficient volume.

Sample Size
A total of 30 ELISA runs incorporating IQC samples were evaluated.

Preparation of Internal Quality Control Samples
Positive serum samples were pooled and serially diluted with sterile normal saline. Dilutions yielding an E-Ratio between 1.5 and 2.0 were selected. The pooled control sample was adjusted to this dilution and aliquoted. Inter-aliquot variation was assessed, and only those with a coefficient of variation (CV) <10% were accepted. Aliquots were stored at −40 °C for long-term preservation, with one aliquot thawed weekly and stored at 2–8 °C for routine use.

ELISA Procedure
IQC samples were included randomly in each Dengue IgM capture ELISA run, alongside patient samples, positive controls, and negative controls. Optical density (OD) values were measured, and E-Ratios calculated as:

E-Ratio=OD of IQC sample/cut-off OD

Data Analysis and Quality Control Monitoring
Mean, standard deviation (SD), and CV were calculated using Microsoft Excel. Performance was monitored using Levey–Jennings (LJ) charts, and Westgard rules were applied to detect both systematic and random errors.

Ethical Considerations
Approval for the study was obtained from the Institutional Ethics Committee, Government Medical College and General Hospital, Guntur (Approval No: GMC/IEC/12/2023). No patient identifiers were recorded at any stage of the study, and all data were handled with strict confidentiality in accordance with institutional and ethical guidelines.

A total of 30 ELISA runs incorporating internal quality control (IQC) samples were evaluated for E-Ratio consistency (Table 1).

Table 1. E-Ratio Values for Internal Quality Control (IQC) Samples Across 30 ELISA Runs

The E-Ratio values ranged from 1.62 to 1.85, with all observations lying within the acceptable control limits. No outliers beyond the predefined Westgard criteria were detected, and the sequential runs demonstrated stable assay performance without significant fluctuations.

Statistical analysis of the IQC runs (Table 2) revealed a mean E-Ratio of 1.75 with a standard deviation of 0.07, corresponding to a coefficient of variation (CV) of 4%, indicating minimal inter-aliquot variation and high reproducibility.

Table 2. Statistical Parameters for Dengue IgM Capture ELISA IQC Samples (n = 30)

The calculated control limits were Mean ± 1SD (1.68–1.81), Mean ± 2SD (1.62–1.88), and Mean ± 3SD (1.55–1.94), all of which encompassed the observed data points.

Levey–Jennings chart interpretation was guided by the Westgard rules (Table 3). Throughout the study period, no violations of warning or rejection rules (W, R1, R2, R3, Shift, or Trend) were observed, confirming consistent assay precision and accuracy. The plotted chart further supported the absence of systematic or random errors, reinforcing the reliability of the ELISA performance across the study duration.

Table 3. Levey-Jennings Chart Interpretation and Westgard Rules Applied

Figure 1. Levey-Jennings Chart for Dengue IgM Capture ELISA IQC(n=30)

Internal quality control (IQC) is a cornerstone of laboratory diagnostic reliability, particularly in assays such as Dengue IgM capture ELISA, where timely and accurate detection directly influences patient care and public health interventions [6,7]. In this study, the performance of in-house prepared IQC samples was assessed across 30 ELISA runs using E-Ratio evaluation, Levey–Jennings (LJ) charting, and Westgard rules.

The E-Ratio values (Table 1) consistently fell within calculated control limits (Table 2), ranging from 1.62 to 1.85, with a mean of 1.75 and standard deviation of 0.07. The coefficient of variation (CV) was 4%, well below the acceptable threshold of 10% for ELISA quality control, indicating high reproducibility [8]. No Westgard rule violations were detected, supporting the assay’s precision and stability over the study period.

The LJ chart provided visual confirmation of stability, showing no trends, shifts, or outliers—findings consistent with previous reports advocating the combined use of LJ charts and Westgard rules to identify systematic and random errors early in the testing process [9]. The use of in-house IQC samples proved cost-effective and adaptable, aligning with recommendations for sustainable quality assurance in resource-limited settings [7,8].

A limitation of this study is its relatively short duration and single-centre scope, which may not capture inter-laboratory variability. Broader implementation across multiple centres and longer monitoring periods would provide more robust data on reproducibility [10–12]. Nevertheless, the findings reinforce that integrating IQC into routine dengue diagnostics can minimise diagnostic errors, prevent false-positive and false-negative results, and improve surveillance accuracy [6,11,12].

The present study demonstrated that incorporating internal quality control (IQC) into each Dengue IgM capture ELISA run ensures consistent assay performance and enhances diagnostic reliability. Across 30 runs, E-Ratio values remained within established control limits, with a low coefficient of variation (4%) and no violations of Westgard rules, confirming high precision and stability. The Levey–Jennings chart analysis further supported the absence of systematic or random errors. In-house prepared IQC samples proved cost-effective, reproducible, and suitable for routine monitoring. Regular application of such quality control measures is essential to minimise diagnostic errors, enable timely and accurate patient management, and strengthen dengue surveillance and public health response systems.

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