The study utilized experimental research design that aimed at investigating and developing a rapid POC diagnostic test specifically to detect cardiac biomarkers relevant to early diagnosis of myocardial injury and cardiovascular stress. The approach was designed to assess the usefulness of the test in identifying specific biomarkers, such as cTnI, BNP, and CRP, which are relevant to heart diseases. This was performed in a way that gradually introduced changes to assay performance while testing the sample population that was chosen to cover the possible range of cardiac health status.

The study was done on sera and plasma from a cross section of apparently healthy patients and of those admitted with suspected acute myocardial infarction and heart failure. Because determining the subjects' age difference correlates with the levels of the cardiac biomarkers, the patients' inclusion criteria had to consider those who were 30–80 years of age. The samples were collected from different hospitals (Shifa International Hospital Islamabad, Rahman Medical Complex Peshawar) and clinical laboratories in Pakistan after receiving administrative approval from institutional review boards the participant medical centers. All participants gave their informed consent in compliance with the samples’ ethical standards provided by the Declaration of Helsinki for medical research on human beings.

For the purposes of this study, three protein biomarkers, namely cTnI, BNP, and CRP, were deemed relevant to the diagnosis of acute and chronic cardiovascular diseases like atherosclerosis. Rationally and theoretically, cTnI is a highly specific biomarker of myocardial damage, because any elevation in its levels suggests myocardial infarction (5). Plasma BNP, in addition to traditional, ventricular stress–based measures of heart failure, was also used as an index for even probable ancillary cardiac function and future heart failure (11). CRP was included because of its recognized correlation with the risk and progression of cardiovascular disease (15). It was first anticipated that integrating CRP with additional indicators in a quick test method may facilitate a comprehensive evaluation of cardiovascular health.

It was the synthesis of LFIA technology and colorimetric detection as shown in the Figure 1 that led to the development of the rapid test. Optical signals emerged because anti-cTnI, anti-BNP, and anti-CRP were labeled to various regions of the nitrocellulose membrane on the LFIA strip. Secondary antibodies in the form of gold nanoparticles were collected in tubes placed on the sample pad of the test strip called SF or P. The biomarker-antibody complexes migrated through the strip by capillary action, and upon reaching the fields of capture antibodies, generated toned bands for the visual determination of the results. Lastly, by adjusting an appropriate quantity of conjugates and other test parameters and/or reagent, for example flow rate, the degree of conjugation of the antibody was optimized to an optimal state, enabling rapid detection within 15 min.

The calibration and analytical interference of the rapid test were assessed by running samples with a standard concentration of each biomarker according to the guidelines for assay validation as mentioned by Apple et al. (7). Dilutions of biomarker standards were made in a 1:10 serial fashion to establish the range of detection for the three biomarkers, cTnI, BNP, and CRP. Thus, various types of non-target proteins and other molecules were tested in the described test system and the rate of false positives recorded in repeated trials was calculated statistically. Here, selectivity of the test was operationalized as the ability of the test to identify the target biomarkers, while having minimal detectable affinity with other plasma proteins.

To clinically validate the rapid test, the strip was compared with laboratory standards that include ELISA commonly used in cTnI and BNP testing together with CRP. Rapid test and comparator assays were used on the sera of 150 individuals with confirmed or suspected CVD conditions to match the invented test against the standard requirements of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The level of consistency between the rapid test and other conventional tests was determined using a Cohen's kappa statistic. The accuracy of the diagnostic tests was again verified by calculating the receiver operating characteristic (ROC) curve in a real-life situation.

A statistical analysis of sensitivity and specificity results obtained from isolated bacterial assays, together with comparative evaluations against standard diagnostic procedures, was undertaken by employing the Statistical Package for the Social Sciences (SPSS). Descriptive statistics were employed to encapsulate the essential distribution properties of biomarkers in all the study groups. The diagnostic efficacy of the fast test was evaluated by ROC analysis, with the area under the curve (AUC) determined for each biomarker. AUC values of 0.80 or higher were deemed indicative of dependable diagnostic accuracy. The ideal cutoff value for clinical application was established by assessing the test's overall sensitivity, specificity, PPV, and NPV. In all statistical studies, a p-value of less than 0.05 was deemed statistically significant at a 95% confidence interval.

Realizing the possibility of systematic bias, the study included several measures to minimize variability and improve assay quality. High-quality antiserum and antigens remained active in the test kits within standardized conditions that were maintained to avoid deterioration of reagents. All samples of an assay batch contained control samples with known biomarker concentrations to determine batch to batch variation. Furthermore, repeat tests were prepared to ensure the accuracy of results in a different ambient environment to consider factors such as temperature and humidity that could affect LFIA performance.

The baseline characteristics of the study population included demographic variables and common risk factors such as hypertension, diabetes, and smoking history. The study sample consisted of 200 participants, subdivided into four groups based on cardiovascular health status: asymptomatic, suspected CVD, confirmed MI, and heart failure Table 1 provides the details.

As shown in the Table 1 the patients are fairly evenly distributed across different health categories, with the average age of 58.6 (±13.4) years. The male population comprised 60% of the study, because CVDs have for long been known to affect the male gender more. Among suspected and confirmed CVD patients, hypertension and diabetes were the most common and are related to traditional risk factors of cardiovascular incidents. Interestingly, smoking history was documented in 32.5% of participants; a higher proportion was identified among the confirmed MI and heart failure groups, hence the influence of the lifestyle factor on cardiovascular health.

Both Supplementary Table S2 and the corresponding Figure 2 provide information regarding the mean concentrations (± standard deviation) of three cardiac biomarkers, cTnI), BNP, and CRP. These biomarkers were detected in four patient categories that were classified according to their cardiovascular health status. These categories were asymptomatic, suspected of having CVD, confirmed to have MI, and diagnosed with heart failure. As demonstrated, the concentration of cTnI increases dramatically from 0.03 ng/mL in individuals who are asymptomatic to 5.6 ng/mL in those with verified myocardial infarction, which is indicative of its excellent specificity for myocardial damage. BNP, which is a measure of ventricular strain, gradually increases from 30 pg/mL in persons who are asymptomatic to 800 pg/mL in patients who are suffering from cardiac failure. This is consistent with the role that BNP plays in the pathophysiology regarding heart failure. In addition, CRP, which is a measure of inflammation, increases gradually from 1.5 to 15.8 mg/L. Higher levels of CRP are observed in both myocardial infarction and heart failure, which indicates that systemic inflammation is in progress. These conclusions are visually reinforced by the grouped bar chart, which provides a visual representation of both the central tendency and the variation by utilizing color-coded bars and error margins. The table and the graph, when used together, provide an illustration of the diagnostic and prognostic significance of these biomarkers. They demonstrate the ability of the biomarkers to differentiate between different degrees of illness severity and to provide assistance for making clinical choices.

Figure 3 provides a comparative examination of four important diagnostic accuracy metrics: sensitivity, specificity, PPV, and NPV for the three cardiac biomarkers: cTnI, BNP, and CRP. Each of these biomarkers was examined at their corresponding clinical thresholds. A measurement of cardiac troponin I (cTnI) at a concentration of ≥0.10 ng/mL displays the highest sensitivity (95.2%) and NPV (96.5%). This highlights its remarkable capacity to accurately identify patients who have experienced cardiovascular events and to successfully rule out disease in circumstances when the test results are negative. In addition, BNP, which has a threshold of ≥100 pg/mL, demonstrates remarkable performance, particularly in terms of sensitivity (91.8%) and NPV (91.2%), which further strengthens its significance in the diagnostic process of heart failure. With a sensitivity of approximately 89.0% and a specificity of approximately 87.2%, CRP, when evaluated at a concentration of at least 5 mg/L, possesses values that are slightly lower but still clinically relevant. With cTnI demonstrating the most consistent and superior performance across all parameters, the high NPVs of all biomarkers indicate that they have the potential to be useful for initial triage and avoidance of cardiovascular events Supplementary Table S3.

The Figure 5 below illustrates a comparative comparison of mean concentrations (± standard deviation) of the three main cardiovascular biomarkers—cTnI, BNP, and CRP—assessed using both fast test kits and traditional laboratory tests. The error bar plot illustrates the consistency and dependability of the quick testing approach in estimating results derived from conventional assays.

Notwithstanding their biological and unit disparities (cTnI in ng/mL, BNP in pg/mL, and CRP in mg/L), the data derived from both approaches exhibit a strong correlation among all biomarkers, with only negligible variations within standard deviations. The Pearson correlation coefficient (r = 0.999) indicates a nearly flawless linear relationship, demonstrating exceptional concordance between the two assessment modalities. The associated p-value (p < 0.001) substantiates the statistical importance of this link. This alignment reinforces the analytical validity of the quick test method, indicating that it may function as a time-efficient and cost-effective substitute for standard assays, especially at point-of-care or emergency contexts when diagnostic speed is essential. Further details are provided in Supplementary Table S4.

The Figure 6 presents a comparison of the coefficient of variation (CV%) for repeatability and reproducibility among the three biomarkers, as determined by the performance features of a rapid diagnostic test. The repeatability coefficient of variation (CV) indicates intra-assay variability under identical conditions, whereas the reproducibility CV denotes interassay variability across different days, operators, or tools. A lower coefficient of variation signifies greater precision.

Repeatability coefficients of variation (CVs) range from 4.5% for cTnI to 5.8% for CRP, whereas reproducibility CVs range from 5.2% for cTnI to 6.7% for CRP. The data indicate a constant low variability, as all coefficients of variation are significantly below 10%, an acceptable threshold for clinical biomarker assays. The limit of detection (LOD) for each biomarker is specified as follows: 0.03 ng/mL for cTnI, 10 pg/mL for BNP, and 1 mg/L for CRP. These values demonstrate high assay sensitivity and significant clinical utility, particularly in early detection contexts; details are provided in Supplementary Table S5.

The cost-effectiveness of the rapid test compared with conventional methods is summarized in Supplementary Table S6. This table highlights the mean turnaround time and associated costs per test. The rapid test offers substantial advantages in both cost and turnaround time. While the average laboratory assay requires 60–90 min per test, the rapid test achieves results in 15 min at a fraction of the cost, enhancing accessibility and feasibility for point-of-care settings. These cost and time reductions position the rapid test as an efficient alternative, particularly useful in resource-limited environments. Figure 7 provides a comparative comparison of four diagnostic procedures frequently employed in cardiovascular evaluation: rapid test, ELISA for cTnI, BNP assay, and high-sensitivity CRP. Two essential criteria are analyzed: turnaround time (minutes) and cost per test (USD).

The rapid test exhibits the quickest efficiency, with a turnaround time of 15 min and a minimal cost of $5 per test, underscoring its appropriateness for point-of-care and emergency environments. Conversely, the ELISA for cTnI necessitates a somewhat extended processing duration of 90 min and entails the highest expense ($20/test), rendering it more appropriate for centralized laboratory operations. The BNP assay and high-sensitivity CRP are positioned intermediately, with turnaround times of 75 and 60 min and costs of $18 and $15, respectively.

The bar graph distinctly illustrates the trade-offs between velocity and expense in medical decision-making. Standard tests exhibit good sensitivity and specificity; however, the rapid test presents a quicker, cost-effective alternative, potentially enhancing early triage and resource distribution in acute care settings.

The high sensitivity and specificity of the rapid test, especially for cTnI, underscore its clinical value in accurately diagnosing myocardial infarction (MI) early. Biomarker cTnI demonstrated an overall sensitivity of 95.2% at a cutoff value of 0.10 ng/mL, along with a specificity of 92.4% and an AUC of 0.94. These results are in line with prior findings, where high-sensitivity troponin assays have reported high diagnostic concordance for MI detection (4, 5, 7). Thygesen. (6) and Neumann et al. (4) reported cTnI sensitivities of 94.6% and specificities of 91.8% using high-sensitivity assays. The close agreement between these results and those of the current study justifies that the rapid test is effective without compounding the need for infrastructure enhancement in the laboratory.

BNP, a biomarker of cardiac stress, demonstrated 91.8% sensitivity and 88.6% specificity for the diagnosis of heart failure, with an AUC of 0.90. High levels of BNP are indicative of heart failure and left ventricular dysfunction (37), and previous research has supported the usefulness of BNP assays for early detection and risk assessment in patients with suspected heart failure (11, 12). For instance, Cullen et al. (8) reported that BNP > 100 pg/mL achieved a high sensitivity of 90% and a specificity of 86% in diagnosing heart failure, findings that are greatly consistent with those of our study. The ability of the rapid test to provide real-time assessment of elevated BNP levels represents a major advantage, particularly in facilities where access to laboratory-based BNP assays is a challenge, enabling earlier intervention.

CRP, a common inflammatory marker, demonstrated a sensitivity of 89.0% and a specificity of 87.2% at a cutoff value of 5 mg/L, with an AUC of 0.89. This level of diagnostic accuracy is significant, as increased CRP levels are associated with poor prognosis and the presence of systemic inflammation, both of which indicate a potential risk of cardiovascular events. Wang et al., Cook et al., and Ridker et al. (14, 15, 38) employed human sensitivity CRP assays and reported raised CRP levels with 88% sensitivity, closely aligning with the performance of the CRP test reported here. Together, these results underscore the importance of the rapid test in the POC diagnostics, as it allows simultaneous detection of multiple biomarkers relevant to different CV disorders and supports faster decision-making by clinicians.

The results we obtained for all biomarkers showed a high level of correlation between the SARS-CoV-2 rapid test and biochemical laboratory assays, demonstrating consistency, with Pearson correlation coefficients exceeding 0.85. For cTnI, the correlation coefficient was 0.92 (p < 0.001); similar results were found in other studies assessing high-sensitivity troponin assays (3, 5, 17). Likewise, BNP and CRP showed strong correlation coefficients of 0.89 and 0.87, respectively, indicating that the rapid test provides diagnostic terminologies equivalent to those of laboratory-based assays.

The comparison of time-to-result and testing cost further underscores the value of the rapid test. The currently available assays for cTnI and BNP require 90 min to complete at a relatively high cost, whereas the rapid test provides results within 15 min at a substantially lower cost. These results align with the views of Crapnell et al. (10) and Maisel et al. (11), who emphasize the need for fast, low-cost diagnostic approaches for better patient classification and more efficient use of medical resources. Rapid results, however, are crucial in emergency and primary care settings, where timely diagnosis results and prompt treatment decisions are imperative due to the quick progression of the disease.

Table 2 outlines a comparative analysis of various cardiovascular biomarkers. The biomarkers selected for this study—cardiac troponin I (cTnI), brain natriuretic peptide (BNP), and C-reactive protein (CRP)—were chosen due to their robust clinical validation and extensive use in cardiovascular diagnostics. cTnI is considered the gold-standard biomarker for diagnosing myocardial infarction due to its superior specificity and sensitivity compared to older markers such as CK-MB and myoglobin, both of which have been largely supplanted in contemporary practice (40, 43, 45). BNP functions as a key biomarker for diagnosing and monitoring heart failure, providing prompt information regarding ventricular stress. While its diagnostic efficacy is comparable to that of NT-pro-BNP, BNP is more frequently utilized in rapid testing platforms (41, 44). C-reactive protein (CRP), despite its lower specificity, is a clinically relevant and affordable inflammatory indicator of cardiovascular risk. Its use is warranted due to its availability and compatibility with point-of-care platforms (42). While Hs-CRP (7) and Galectin-3 (47) offer enhanced prognostic value and improved risk stratification, their integration into standard clinical workflows is still limited or under development. This study emphasized biomarkers that optimize diagnostic accuracy, cost-effectiveness, and feasibility for rapid testing applications. A comparative table would further elucidate the strategic rationale behind biomarker selection and demonstrate how these three markers provide complementary insights into myocardial injury, hemodynamic stress, and systemic inflammation.

The study instituted numerous essential quality assurance procedures to mitigate potential systematic biases and guarantee robust test performance in point-of-care (POC) settings. Acknowledging that POC tests are susceptible to variability arising from reagent instability, environmental conditions, and user handling, uniform protocols were implemented across all LFIA procedures. High-quality antibodies and antigen conjugates, which markedly affect assay specificity and sensitivity, were stored under controlled humidity and temperature conditions to sustain bioactivity and avert degradation—an issue commonly noted in field-based diagnostic platforms (48, 49). To mitigate inter-batch variability, each assay run incorporated internal positive and negative controls with predetermined biomarker levels, facilitating real-time validation of test accuracy and consistency of signal generation (50).

Furthermore, repeated testing was performed under diverse ambient settings to replicate real-world environments, acknowledging that factors such as humidity, temperature fluctuations, and variations in sample viscosity can profoundly affect LFIA membrane flow dynamics and analyte–antibody binding kinetics (51, 52). These environmental stress tests confirmed that the assay sustained adequate analytical efficacy across various operational conditions, which is an essential requirement for implementation in resource-constrained or emergency settings. The proactive design components conform to the World Health Organization's ASSURED standards (Affordable, Sensitive, Specific, User-friendly, Rapid, Equipment-free, and Deliverable), highlighting the importance of environmental resilience and operational repeatability for diagnostic tools intended for decentralized environments (53). By implementing these mitigation measures, the study sought to improve test reliability, reduce errors arising from human and environmental factors, and facilitate the practical integration of the assay into clinical settings.

The study acknowledges numerous shortcomings that may limit its generalizability. Although 200 volunteers were recruited, this sample size may not adequately represent broader communities. The study also lacked a multivariable or longitudinal design, which prevented it from evaluating long-term health outcomes or comparing the cost-effectiveness of the test against routine diagnostic pathways. No longitudinal follow-up was conducted to assess the impact of the test on patient prognosis or treatment. To address these gaps, larger multicenter studies, incorporating cross-sectional and longitudinal designs, are needed to expand the present findings.

Inflammatory conditions such as sepsis, autoimmune diseases, and certain malignancies can provide false-positive CRP test results that are unrelated to cardiovascular diseases (17, 42). Despite this, the assay used in this study demostrated 87.2% specificity, indicating reliability. However, multiplex testing technologies that can distinguish cardiac-specific inflammation from general systemic responses could further improve clinical diagnostic accuracy.

Although LFIA-based approaches possess fundamentally poorer sensitivity and specificity than laboratory-based platforms such as ELISA or chemiluminescent assays (54), the current study showed comparatively strong diagnostic performance across all evaluated biomarkers. CRP, BNP, and cTnI exhibited specificities ranging from 87.2% to 92.4% and sensitivities ranging from 89.0% to 95.2%, with AUC values of at least 0.89, signifying clinically acceptable precision.

Nonetheless, the potential for false positives and false negatives persists, especially with CRP, which may be elevated in non-cardiac inflammatory conditions like sepsis, autoimmune diseases, and certain malignancies (55). The lack of specificity may result in false-positive interpretations when CRP is utilized independently, particularly in individuals with elevated BMI or chronic systemic inflammation (56). Conversely, false negatives may occur due to diminished analyte concentrations in the earliest stages of myocardial infarction or variability in the assay caused by temperature, humidity, or human manipulation—issues that are prevalent in field-deployed LFIA environments (50, 57).

To address these concerns, our investigation utilized internal quality controls, repeated testing across diverse ambient conditions, and batch-to-batch validation using established biomarker standards, in accordance with WHO recommendations and best practices for point-of-care diagnostic design (58). However, multiplex testing methodologies and their integration with clinical symptomatology may further diminish diagnostic ambiguity in future LFIA-based applications.

Based on the results of this study, it can be concluded that the rapid test for cardiac biomarkers could have significant practical value, especially in healthcare centers with limited laboratory facilities. Due to its high sensitivity and specificity for cTnI, BNP, and CRP, the test can effectively diagnose patients at risk of potential cardiovascular events and promote early treatment. Point-of-care diagnostic methods that are very simple and easy to use have the potential to improve health outcomes by reducing the duration required for individuals in at-risk categories to receive their results and initiate appropriate treatment (19, 20).

For future studies, there is a need to improve the sensitivity and specificity of rapid diagnostic tests and consider including other biomarkers to improve diagnosis. Future improvements in biosensing technologies, including nanomaterials and electrochemical detection methods, could enhance the rapid test by detecting biomarker levels associated with latent or prodromal forms of the disease (18, 20, 23). Further, combining biomarker analysis with artificial intelligence-based algorithms could make the interpretation of results more accurate and provide additional support in decision-making (8, 20).