False Positivity in Anti-HIV Tests: Causes and Determination of a Reliable Cut-Off Value

False Positivity in Anti-HIV Tests: Causes and Determination of a Reliable Cut-Off Value | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article False Positivity in Anti-HIV Tests: Causes and Determination of a Reliable Cut-Off Value Mediha Uğur, Ahmet Melih Şahin, Esin Avcı This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6602813/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Currently, fourth-generation assays detecting HIV-1/2 antibodies and p24 antigen are widely used as screening tools for human immunodeficiency virus (HIV). However, false-positive (FP) results remain a significant issue additional confirmatory testing. This study aimed to identify factors associated with false positivity and to determine an optimal cut-off index (COI) value with high sensitivity and specificity by evaluating the relationship between COI values in screening tests and confirmed HIV infection. Methods Between January 2024 and January 2025, a total of 36,046 patients were screened for anti-HIV. The serum samples were tested for anti-HIV using a chemiluminescence immunoassay (Cobas E601, Roche Diagnostics, Germany) with the Elecsys® HIV combi PT kit (Roche Diagnostics, Germany). Reactive samples were referred to a reference laboratory for confirmation testing. The optimal COI value for predicting true HIV infection was determined using receiver operating characteristic (ROC) curve analysis. FP and non-reactive patients were evaluated for various parameters to identify factors contributing to false positivity. Results A total of 36,046 patients were screened for anti-HIV and 122 patients (0.33%) were found to be reactive by ELISA testing. 24 were confirmed as positive and 98 as negative, yielding a false positive (FP) rate of 80.32%. False positivity was found to be positively and moderately associated with having a concurrent infection or receiving a vaccination within the past six months (p<0.05). The median and interquartile range (IQR) of COI values in (FP) cases were 1.75 and 1.66, respectively, while in true-positive (TP) cases, the median and IQR were 458.9 and 384.93, respectively. This difference was statistically significant (p<0.05). The optimal COI value to differentiate TP from FP cases was determined to be 72.085. Conclusion Identifying potential factors that contribute to false positivity in individuals with reactive screening results, along with consideration of COI values before confirmatory testing, may facilitate more accurate clinical decision-making and improve patient counseling during the interim period before definitive results are available. HIV infection cut-off value false positivity Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Since the first case of acquired immunodeficiency syndrome (AIDS) was identified in the United States in 1981, HIV has spread globally at an alarming rate [ 1 ]. By the end of 2023, it is estimated that 39.9 million [36.1–44.6] people were living with HIV worldwide, including 1.4 million children aged 0–14 years and 38.6 million adults aged 15 years and older. In the same year, approximately 630,000 people died from HIV-related causes globally [ 2 ]. In Turkey, the first HIV case was reported in 1985, and it was classified as a notifiable disease in the same year [ 3 ]. The World Health Organization (WHO) and the European Centre for Disease Prevention and Control (ECDC) recommend the promotion and regulation of early detection of HIV carriers. The Joint United Nations Programme on HIV/AIDS (UNAIDS) and WHO aim for zero new HIV infections, zero discrimination and zero AIDS-related deaths by 2030. While the UNAIDS report published in 2023 suggests that AIDS could be eliminated by 2030 based on current progress, the ECDC has stated that Europe and Central Asia are unlikely to meet thesetargets [ 4 , 5 ]. Early and rapid identification of HIV infection is crucial to prevent further transmission [ 6 ]. A two-step algorithm is employed in in the diagnosis of HIV infection: a screening test followed by confirmation of reactive samples. HIV antigen-antibody immunoassays are the preferred screening tests for HIV. These immunoassays detect the HIV-1 p24 (capsid) antigen as well as antibodies (IgM and IgG) against HIV-1 and HIV-2. The CDC and the Association of Public Health Laboratories (APHL) HIV testing algorithm recommends an HIV-1/2 antigen-antibody immunoassay followed by confirmation of reactive results using the HIV-1/2 antibody differential rapid confirmatory test. Negative or indeterminate results from the HIV-1/2 antibody differential rapid confirmatory test should be further evaluated using HIV nucleic acid tests [ 7 , 8 ]. Today, fourth-generation HIV screening tests, which detect both HIV-1/2 antibodies and the p24 antigen, are widely used [ 9 ]. These tests have significantly reduced the “window period” to approximately 11–14 days post-exposure, allowing fort the early detection of acute HIV infections [ 10 ]. Although these tests demonstrate high sensitivity and specificity, FP results remain a major concern. FP results can be caused by factors such as autoimmune diseases, malignancies, other infections, pregnancy, or technical issues related to the test kit, reagents, or analytical devices [ 11 – 18 ]. In particular, it is essential for both patient well-being and public health that individuals with repeatedly reactive screening results receive appropriate counseling until confirmatory test results are available [ 19 ]. FP test results outcomes may lead to significant anxiety and emotional distress during the waiting period. Therefore, understanding the mechanisms and contributing factors of FP results is critical for accurate clinical interpretation [ 11 ]. Furthermore, high FP rates in screening tests increase the demand for confirmatory testing, which is more expensive and time-consuming, resulting in substantial financial burdens for healthcare systems [ 20 ]. Elecsys® HIV combi PT (Roche Diagnostics GmbH, Penzberg, Germany) is a fourth-generation test used for HIV screening. Test results are expressed as a COI, which is automatically calculated by comparing the chemiluminescent signal intensity of the sample to a calibration-defined cut-off value [ 6 ]. Many studies have reported that COI values from screening tests are strongly correlated with the probability of confirmed HIV infection. Therefore, determining a predictive COI threshold for true HIV positivity holds significant clinical value [ 20 – 22 ]. In this study, we aimed to investigate the factors causing FP results in anti-HIV screening tests and to identify a reliable COI value in relation to confirmatory test outcomes. Methods Between January 2024 and January 2025, a total of 220 individuals were included in this study: 24 patients with repeated reactive anti-HIV-1/2 test results confirmed as positive (TP), 98 patients with repeated reactive anti-HIV-1/2 test results confirmed as negative (FP), and 98 individuals with non-reactive anti-HIV-1/2 test results, who were included as the control group. Samples were processed using a modular preanalytical system (Modular Evo, Roche Diagnostics, Germany). The separated serum samples were tested for anti-HIV using a chemiluminescence immunoassay (Cobas E601, Roche Diagnostics, Germany) with the Elecsys® HIV combi PT kit (Roche Diagnostics, Germany). This fourth-generation enzyme-linked immunosorbent assay (ELISA) test, referred to as a “combo” test, can detect HIV-1 and HIV-2 antibodies as well as the HIV-1 p24 antigen. Test results were interpreted according to the COI values: <0.90 as negative, ≥ 0.90 to < 1.00 as borderline, and ≥ 1.00 as reactive. If a sample was borderline or reactive, it was retested twice—once from the same tube. A result was considered non-reactive if two of the three tests were negative, and reactive if two of the three tests were positive. Reactive samples were referred to a reference laboratory for confirmation testing. Confirmation involved testing anti-HIV-1/2 antibodies and p24 antigen using the enzyme linked fluorescent assay (ELFA) method. Samples confirmed as reactive were further evaluated using antibody-detecting rapid HIV confirmatory tests (HIV-1/2 Antibody Discriminating Rapid Confirmatory Tests). Samples that tested positive in these assays were classified as TP. Samples that yielded non-reactive or indeterminate results in the ELFA test were subsequently tested for HIV-1 ribonucleic acid (RNA) by polymerase chain reaction (PCR). If PCR results were negative, the case was considered confirmation-negative and classified as a FP. COI values of FP and TP cases were recorded, with the lower of the two COI values from initial reactive tests included in the analysis. Confirmation results were communicated to patients. Among the 98 FP patients, follow-up was conducted via questionnaire, after obtaining informed consent, to identify potential contributing factors. Additionally, 98 patients from the control group (non-reactive) were randomly selected, and the same questionnaire was administered. Epidemiologic and clinical data for all participants were retrieved from the Hospital Information System (HIS). Data were analyzed using Statistical Package for the Social Sciences (SPSS), version 22.0 (IBM Corp., Armonk, NY, USA). The Phi coefficient and p-value were used to identify variables associated with FP status. The optimal COI value for predicting true HIV infection was determined using receiver operating characteristic (ROC) curve analysis. Results Between January 2024 and January 2025, a total of 36,046 patients were screened for anti-HIV. Among these, 122 patients (0.33%) were found to be reactive by ELISA testing. Of the 122 samples sent for confirmatory testing, 24 were confirmed as positive and 98 as negative, yielding a FP rate of 80.32%. The diagnostic algorithm for HIV infection is shown in Fig. 1 . Since the COI values of TP and FP cases were not normally distributed (p < 0.05), results were summarized using medians and IQR values. A boxplot comparing COI values of TP and FP cases is presented in Fig. 2 . The median COI value in the FP group was 1.75 (IQR: 1.66), whereas the TP group exhibited a significantly higher median COI of 458.9 (IQR: 384.93). The difference in median COI values between TP and FP groups was statistically significant (p < 0.05), as determined by the Mann-Whitney U test. ROC curve analysis identified a COI threshold of 72.085 as optimal for discriminating between TP and FP cases. At this cut-off point, both sensitivity and specificity were 100%. The area under the receiver operating characteristic curve (AUC) was calculated as 1.0, indicating excellent diagnostic performance (p < 0.000). This confirms that a COI threshold of 72.085 is a highly reliable value for differentiating between HIV-infected and non-infected individuals (Fig. 3 ). Sensitivity and specificity values for various COI cut-offs are summarized in Table 1 .The median age of TP patients was 38.5 years (IQR: 23.75), while the median age of FP patients was 49.5 years (IQR: 39). No statistically significant difference was observed in age distribution between the two groups (p > 0.05). However, 96% of TP patients were male, compared to 53% of FP patients. A significant association was found between gender and test outcome (p < 0.05), with males being 1.412 times more likely to be confirmed positive than females. When analyzed by clinical department, 48% of FP cases had been admitted to Internal Medicine, 33% to Surgery, and 19% to Infectious Diseases. In contrast, 54% of TP cases were admitted to Infectious Diseases, 33% to Internal Medicine, and 13% to Surgery. A statistically significant difference was observed in confirmatory outcomes based on department (p < 0.05), with the highest proportion of TP cases detected among patients admitted to Infectious Diseases (Fig. 4 ). Table 1 Sensitivity and specificity according to COI values Cut-off values Sensitivity Specificity > 1.035 100 0.102 > 20.225 100 0.989 > 72.085* 100 100 > 270.3 0.792 100 > 960 0.208 100 To explore potential causes of false positivity, various categorical variables were assessed among FP cases, and their associations with FP status are summarized in Table 2 . Accordingly, being reactive was positively and moderately associated with the presence of concurrent infection and vaccination in the past 6 months (p < 0.05). Risk analysis indicated that the likelihood of reactivity was approximately 64% lower in individuals without recent infections, and about 50% lower in those who had not received any vaccinations in the last six months, compared to their respective counterparts. Table 2 Association of false positivity with various variables Variables n Non-reactive (n,%) Reactive (FP) (n,%) Phi coefficient p-value Gender Female 92 46 (50) 46 (50) 0 1 Male 104 52 (50) 52 (50) Autoimmune disease Negative 161 83 (51.6) 78 (48.4) 0.067 0.351 Positive 35 15 (42.9) 20 (57.1) Neurological disease Negative 186 96 (51.6) 90 (48.4) 0.139 0.051 Positive 10 2 (20) 8 (80) Cardiovascular Disease Negative 113 57 (50.4) 56 (49.6) 0.010 0.885 Positive 83 41 (49.4) 42 (50.6 COPD Negative 174 89 (51.1) 85 (48.9) 0.065 0.365 Positive 22 9 (40.9) 13 (59.1) Renal failure Negative 182 88 (48.4) 94 (51.6) -0.119 0.096 Positive 14 10 (71.4) 4 (28.6) Hemodialysis Negative 189 92 (48.7) 97 (51.3) -0.137 0.054 Positive 7 6 (85.7) 1 (14.3) Blood transfusion Negative 195 98 (50.3) 97 (49.7) 0.072 0.316 Positive 1 0 (0) 1 (100) Organ transplantation Negative 196 98 (50) 98 (50) - - Positive - - - Malignancy Negative 190 97 (51.1) 93 (48.9) 0.118 0.097 Positive 6 1 (16.7) 5 (83.3) Hepatitis Negative 188 96 (51.1) 92 (48.9) 0.103 0.149 Positive 8 2 (25) 6 (75) Tuberculosis Negative 195 98 (50.3) 97 (49.7) 0.072 0.316 Positive 1 0 (0) 1 (100) Malaria Negative 196 98 (50) 98 (50) - - Positive - - - Concurrent infection Negative 161 88 (54.7) 73 (45.3) 0.200 0.005* Positive 35 10 (28.6) 25 (71.4) Vaccination in the past 6 months Negative 188 98 (52.1) 90 (47.9) 0.206 0.004* Positive 8 0 (0) 8 (100) * p-value < 0.05, COPD : Chronic obstructive pulmonary disease Discussion HIV infection remains a major global health concern, with early diagnosis, timely treatment, and effective self-management being key strategies for reducing transmission [ 20 ]. Diagnosis of HIV infection typically involves initial screening followed by confirmatory testing. However, FP results in HIV screening tests present a notable challenge in clinical practice, often leading to psychological distress, unnecessary testing, and delayed diagnosis [ 6 , 9 ]. This study aimed to investigate the factors contributing to FP results and to determine a reliable COI value to enhance diagnostic accuracy. In studies conducted in our country, anti-HIV seropositivity rates were reported to range from 0.03–0.08% [ 23 – 25 ]. It was also determined that the rate of recurrent reactivity has increased over the years, with an average reactivity rate of 0.7% reported in 2020 (26). Additionally, FP rates haveconsistently exceeded 70% in several local studies. [ 25 , 27 ]. In the present study, the seropositivity rate was 0.33%, and the FP rate was calculated as 80.32%, aligning with earlier findings. Tang et al. reported that FP results were more common in elderly and female patients and were associated with conditions such as cancer, infections, and neurological disorders. [ 14 ]. In our study, no statistically significant difference was observed in age between FP and TP groups. However, a significant association with gender was identified, with males being 1.412 times more likely to have a TP result- consistent with previous literature indicating higher HIV prevalence among males [ 25 , 28 ]. Recent studies have demonstrated a strong correlation between HIV screening test values and confirmatory test results. As COI increases, the likelihood of FP results decreases, making COI a valuable early indicator in distinguishing true infection before confirmatory results are available [ 19 , 29 ]. In a study conducted in our country, the highest micro-ELISA value observed in FP cases was 13.3 signal-to-cutoff (S/CO), while the lowest value recorded in TP cases was 5.29 S/CO [ 28 ]. Another study reported that the highest ELISA value in FP cases was 24.09 S/CO, whereas the lowest value in TP cases was 16.78 S/CO (27). Similarly, another study demonstrated that COI values in FP samples ranged from 1.0 to 15.0, while COI values in TP samples were consistently above 100.0. Notably, in cases where the COI exceeded 200, both sensitivity and specificity were reported to reach 100% [ 20 ]. Tang et al. similarly noted a decline in FP rates with increasing COI values, identifying a COI of 52.74 as optimal (AUC:0.998, p < 0.001) [ 14 ]. Another study reported optimal cut-offs of 8.96 for males and 26.97 for females, while yet another using a fourth-generation ELISA test determined an optimal COI of 32.7 via ROC analysis [ 29 , 30 ]. In our study, the median COI for FP cases was 1.75 (IQR: 1.66), and 458.9 (IQR: 384.93) for TP cases, with a statistically significant difference between the groups. The highest COI in FP cases was 21.27, and the lowest in TP cases was 122.29. A COI threshold of 72.085 was identified as the optimal discriminator between FP and TP results, achieving 100% sensitivity and specificity. Notably, although the current kit uses a COI of 1.0 as the threshold for reactivity, our findings suggest that this low value may contribute to the high FP rate observed. False positivity was moderately and positively associated with concurrent infections and recent vaccinations (within the past six months). FP results have been previously reported in various inflammatory conditions and are often attributed to cross-reactivity. For example, Epstein–Barr virus (EBV) infection has been identified as a cause of FP results in fourth-generation HIV tests [ 31 , 32 ]. In our study, 25.5% of FP patients had an upper respiratory tract infection at the time of testing, which may have triggered heightened immune responses, contributing to false reactivity. Several studies have also reported increased FP rates following COVID-19 infection [ 16 , 33 ]. Additionally, vaccination has been recognized as a contributing factor. In our study, FP results were significantly more frequent among individuals who had received a vaccine within the past six months—specifically tetanus, hepatitis B, and influenza vaccines. Previous reports have associated influenza vaccination with FP HIV results, with one study reporting an average duration of false reactivity lasting 4.2 months [ 34 – 37 ]. Sequence homology between HIV-1 envelope proteins and influenza hemagglutinin has been suggested as a potential mechanism for cross-reactivity, though this remains unconfirmed [ 35 ]. A case of FP HIV results following administration of the Tdap vaccine has also been reported. Clinicians should consider recent vaccination or immune stimulation when interpreting reactive HIV screening results and may opt to repeat testing sooner in cases of uncertainty [ 38 ]. Patients should also be informed that HIV screening conducted shortly after vaccination may result in FP results. Unless clinically necessary, delaying screening until several weeks after vaccination may help avoid unnecessary anxiety and confirmatory testing. In summary, anti-HIV screening results- known to be influenced by various biological factors- were significantly associated with concurrent infections and recent vaccination in this study. A COI threshold of 72.085 was identified as a highly accurate discriminator between FP and TP results. However, as this study was conducted in a single center, regional variations must be considered. Multicenter studies are needed to validate these findings and to establish standardized COI thresholds. In the meantime, patients with COI values exceeding the proposed threshold may benefit from expedited initiation of antiretroviral therapy. Clinicians should also be encouraged to evaluate potential contributing factors such as recent vaccination or infection when interpreting reactive HIV screening results. Conclusions Our findings highligt the importance of considering COI thresholds, recent vaccinations, and concurrent infections when interpreting HIV screening results. Increasing the current COI may significantly reduce FP rates and improve diagnostic accuracy. Moreover, access to the COI value prior to confirmatory testing can support clinical decision-making and improve patient counseling. Abbreviations HIV Human Immunodeficiency Virus FP False-Positive COI Cut-Off Index ROC Receiver Operating Characteristic ELISA Enzyme-Linked ImmunoSorbent Assay IQR Interquartile Range TP True-Positive AIDS Acquired Immunodeficiency Syndrome WHO World Health Organization ECDC European Centre for Disease Prevention and Control UNAIDS Joint United Nations Programme on HIV/AIDS APHL Association of Public Health Laboratories ELFA Enzyme Linked Fluorescent Assay RNA R ibonucleic Acid PCR Polymerase Chain Reaction HIS Hospital Information System SPSS Statistical Package for the Social Sciences S/CO Signal-to-cutoff AUC Area under the Receiver Operating Characteristic curve Declarations Ethics approval and consent to participate The study was approved by the Research Ethics Committee of Giresun Training and Research Hospital (25.12.2023/08) and conducted in accordance with the Declaration of Helsinki. Informed consent to participate was taken from all participants and parents/legal guardians of minors participants. Clinical trial number Clinical trial number not applicable. Consent for publication The corresponding author has read the journal policies and submit this manuscript in accordance with those policies. Availability of data and material The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Giresun Training and Research Hospital and Turkısh Public Healt, Ministry of Health of Turkey. Competing interests The authors declare no competing interests. Funding There is no financial support for this study. Authors' contributions M.U: conception, design of the work, analysis, interpretation of data, drafted the work or substantively revised it, approved the submitted version, wrote the main manuscript text, All authors reviewed the manuscript A.M.Ş: conception, design of the work, analysis, interpretation of data, drafted the work or substantively revised it, approved the submitted version , All authors reviewed the manuscript E.A: analysis, interpretation of data, approved the submitted version, wrote the main manuscript text, All authors reviewed the manuscript, prepared all figures and tables Acknowledgements Not applicable References Wang L, Zhou KH, Zhao HP, et al. The characteristics of screening and confirmatory test results for HIV in Xi'an, China. PLoS One. 2017;12(7):e0180071. Global HIV, Hepatitis and STIs Programmes [ https://www.who.int/teams/global-hiv-hepatitis-and-stis] Gökengin D. HIV Infection in Turkey: How Close Are We to the Target?. Klimik Journal. 2018;31(1):4-10. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6602813","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":467068051,"identity":"9c05e84a-faca-4f2f-a381-58e273d83489","order_by":0,"name":"Mediha Uğur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYHACg8NQBhvDxwYQzdh4gGgtjDMbGCSAWhoIamGGaWHmBWthYMCrRbe9eePhgho7OfPZh589tt1hU6fbfhhoS41NNC4tZmeOFRyecSzZWOZcmrlx7pk0CbMziUAtx9JyG3BpuZFjcJiH7UDiDB4GM+nctsMSZgeAWhgbDuPWcv8NUMu/A/UzeNi/SVuCtJx/SEDLDR6Dw7xtBxIkeHjMpBlBWm4QsuVMWsFh3r5kwxk8PGWSvW1pkttuAG1JwOeX44c3f+b5ZicvwcO+TeJnmw2/2fn0hw8+1Njg1IIDJJCmfBSMglEwCkYBGgAAztdgpdGmybAAAAAASUVORK5CYII=","orcid":"","institution":"1.\tDepartment of Medical Microbiology, Giresun University Faculty of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Mediha","middleName":"","lastName":"Uğur","suffix":""},{"id":467068052,"identity":"4288f71c-f6d7-4400-a13e-dcd0571fafd1","order_by":1,"name":"Ahmet \tMelih Şahin","email":"","orcid":"","institution":"2.\tDepartment of Clinical Microbiology anda Infectious Diseases, Giresun University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ahmet","middleName":"\tMelih","lastName":"Şahin","suffix":""},{"id":467068053,"identity":"3a623033-1874-4fb3-9680-1a0d5fcdac23","order_by":2,"name":"Esin Avcı","email":"","orcid":"","institution":"3.\tDepartment of Statistics, Giresun University Faculty of Science and Letters","correspondingAuthor":false,"prefix":"","firstName":"Esin","middleName":"","lastName":"Avcı","suffix":""}],"badges":[],"createdAt":"2025-05-06 12:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6602813/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6602813/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84338121,"identity":"190688ba-1b58-4b1a-a623-afbac3969efa","added_by":"auto","created_at":"2025-06-10 18:06:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":39126,"visible":true,"origin":"","legend":"\u003cp\u003eThe diagnostic algorithm for HIV infection\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6602813/v1/3c077df26eab861b96d88293.png"},{"id":84338118,"identity":"77d5274a-49cc-4613-801e-fe1818809ed4","added_by":"auto","created_at":"2025-06-10 18:06:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9325,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot of COI values of TP and FP HIV cases\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6602813/v1/06d04f57e404aaec149b6d3f.png"},{"id":84338123,"identity":"b4b1e86f-d478-40ce-9685-4db155df8033","added_by":"auto","created_at":"2025-06-10 18:06:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40326,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of TP and FP HIV cases\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6602813/v1/99e1257efcac3376599e710d.png"},{"id":84338129,"identity":"edcb7e85-7047-4ef7-803f-5f31aea4bf8e","added_by":"auto","created_at":"2025-06-10 18:06:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":18150,"visible":true,"origin":"","legend":"\u003cp\u003eTP and FP HIV cases by hospital department\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6602813/v1/f2abacb4c366d7299b38cc7c.png"},{"id":84341526,"identity":"e8c78aba-0b99-4e10-8618-cc5a400e6825","added_by":"auto","created_at":"2025-06-10 18:38:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":889885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6602813/v1/c1dc0c59-9187-4f69-9039-435c811534ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"False Positivity in Anti-HIV Tests: Causes and Determination of a Reliable Cut-Off Value","fulltext":[{"header":"Background","content":"\u003cp\u003eSince the first case of acquired immunodeficiency syndrome (AIDS) was identified in the United States in 1981, HIV has spread globally at an alarming rate [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. By the end of 2023, it is estimated that 39.9\u0026nbsp;million [36.1\u0026ndash;44.6] people were living with HIV worldwide, including 1.4\u0026nbsp;million children aged 0\u0026ndash;14 years and 38.6\u0026nbsp;million adults aged 15 years and older. In the same year, approximately 630,000 people died from HIV-related causes globally [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Turkey, the first HIV case was reported in 1985, and it was classified as a notifiable disease in the same year [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The World Health Organization (WHO) and the European Centre for Disease Prevention and Control (ECDC) recommend the promotion and regulation of early detection of HIV carriers. The Joint United Nations Programme on HIV/AIDS (UNAIDS) and WHO aim for zero new HIV infections, zero discrimination and zero AIDS-related deaths by 2030. While the UNAIDS report published in 2023 suggests that AIDS could be eliminated by 2030 based on current progress, the ECDC has stated that Europe and Central Asia are unlikely to meet thesetargets [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly and rapid identification of HIV infection is crucial to prevent further transmission [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A two-step algorithm is employed in in the diagnosis of HIV infection: a screening test followed by confirmation of reactive samples. HIV antigen-antibody immunoassays are the preferred screening tests for HIV. These immunoassays detect the HIV-1 p24 (capsid) antigen as well as antibodies (IgM and IgG) against HIV-1 and HIV-2. The CDC and the Association of Public Health Laboratories (APHL) HIV testing algorithm recommends an HIV-1/2 antigen-antibody immunoassay followed by confirmation of reactive results using the HIV-1/2 antibody differential rapid confirmatory test. Negative or indeterminate results from the HIV-1/2 antibody differential rapid confirmatory test should be further evaluated using HIV nucleic acid tests [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Today, fourth-generation HIV screening tests, which detect both HIV-1/2 antibodies and the p24 antigen, are widely used [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These tests have significantly reduced the \u0026ldquo;window period\u0026rdquo; to approximately 11\u0026ndash;14 days post-exposure, allowing fort the early detection of acute HIV infections [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Although these tests demonstrate high sensitivity and specificity, FP results remain a major concern. FP results can be caused by factors such as autoimmune diseases, malignancies, other infections, pregnancy, or technical issues related to the test kit, reagents, or analytical devices [\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In particular, it is essential for both patient well-being and public health that individuals with repeatedly reactive screening results receive appropriate counseling until confirmatory test results are available [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. FP test results outcomes may lead to significant anxiety and emotional distress during the waiting period. Therefore, understanding the mechanisms and contributing factors of FP results is critical for accurate clinical interpretation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, high FP rates in screening tests increase the demand for confirmatory testing, which is more expensive and time-consuming, resulting in substantial financial burdens for healthcare systems [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eElecsys\u0026reg; HIV combi PT (Roche Diagnostics GmbH, Penzberg, Germany) is a fourth-generation test used for HIV screening. Test results are expressed as a COI, which is automatically calculated by comparing the chemiluminescent signal intensity of the sample to a calibration-defined cut-off value [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Many studies have reported that COI values from screening tests are strongly correlated with the probability of confirmed HIV infection. Therefore, determining a predictive COI threshold for true HIV positivity holds significant clinical value [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we aimed to investigate the factors causing FP results in anti-HIV screening tests and to identify a reliable COI value in relation to confirmatory test outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eBetween January 2024 and January 2025, a total of 220 individuals were included in this study: 24 patients with repeated reactive anti-HIV-1/2 test results confirmed as positive (TP), 98 patients with repeated reactive anti-HIV-1/2 test results confirmed as negative (FP), and 98 individuals with non-reactive anti-HIV-1/2 test results, who were included as the control group. Samples were processed using a modular preanalytical system (Modular Evo, Roche Diagnostics, Germany). The separated serum samples were tested for anti-HIV using a chemiluminescence immunoassay (Cobas E601, Roche Diagnostics, Germany) with the Elecsys\u0026reg; HIV combi PT kit (Roche Diagnostics, Germany). This fourth-generation enzyme-linked immunosorbent assay (ELISA) test, referred to as a \u0026ldquo;combo\u0026rdquo; test, can detect HIV-1 and HIV-2 antibodies as well as the HIV-1 p24 antigen. Test results were interpreted according to the COI values: \u0026lt;0.90 as negative, \u0026ge;\u0026thinsp;0.90 to \u0026lt;\u0026thinsp;1.00 as borderline, and \u0026ge;\u0026thinsp;1.00 as reactive. If a sample was borderline or reactive, it was retested twice\u0026mdash;once from the same tube. A result was considered non-reactive if two of the three tests were negative, and reactive if two of the three tests were positive. Reactive samples were referred to a reference laboratory for confirmation testing. Confirmation involved testing anti-HIV-1/2 antibodies and p24 antigen using the enzyme linked fluorescent assay (ELFA) method. Samples confirmed as reactive were further evaluated using antibody-detecting rapid HIV confirmatory tests (HIV-1/2 Antibody Discriminating Rapid Confirmatory Tests). Samples that tested positive in these assays were classified as TP. Samples that yielded non-reactive or indeterminate results in the ELFA test were subsequently tested for HIV-1 ribonucleic acid (RNA) by polymerase chain reaction (PCR). If PCR results were negative, the case was considered confirmation-negative and classified as a FP. COI values of FP and TP cases were recorded, with the lower of the two COI values from initial reactive tests included in the analysis. Confirmation results were communicated to patients. Among the 98 FP patients, follow-up was conducted via questionnaire, after obtaining informed consent, to identify potential contributing factors. Additionally, 98 patients from the control group (non-reactive) were randomly selected, and the same questionnaire was administered. Epidemiologic and clinical data for all participants were retrieved from the Hospital Information System (HIS).\u003c/p\u003e \u003cp\u003eData were analyzed using Statistical Package for the Social Sciences (SPSS), version 22.0 (IBM Corp., Armonk, NY, USA). The Phi coefficient and p-value were used to identify variables associated with FP status. The optimal COI value for predicting true HIV infection was determined using receiver operating characteristic (ROC) curve analysis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBetween January 2024 and January 2025, a total of 36,046 patients were screened for anti-HIV. Among these, 122 patients (0.33%) were found to be reactive by ELISA testing. Of the 122 samples sent for confirmatory testing, 24 were confirmed as positive and 98 as negative, yielding a FP rate of 80.32%. The diagnostic algorithm for HIV infection is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Since the COI values of TP and FP cases were not normally distributed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), results were summarized using medians and IQR values. A boxplot comparing COI values of TP and FP cases is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The median COI value in the FP group was 1.75 (IQR: 1.66), whereas the TP group exhibited a significantly higher median COI of 458.9 (IQR: 384.93). The difference in median COI values between TP and FP groups was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as determined by the Mann-Whitney U test. ROC curve analysis identified a COI threshold of 72.085 as optimal for discriminating between TP and FP cases. At this cut-off point, both sensitivity and specificity were 100%. The area under the receiver operating characteristic curve (AUC) was calculated as 1.0, indicating excellent diagnostic performance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.000). This confirms that a COI threshold of 72.085 is a highly reliable value for differentiating between HIV-infected and non-infected individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Sensitivity and specificity values for various COI cut-offs are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.The median age of TP patients was 38.5 years (IQR: 23.75), while the median age of FP patients was 49.5 years (IQR: 39). No statistically significant difference was observed in age distribution between the two groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, 96% of TP patients were male, compared to 53% of FP patients. A significant association was found between gender and test outcome (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with males being 1.412 times more likely to be confirmed positive than females. When analyzed by clinical department, 48% of FP cases had been admitted to Internal Medicine, 33% to Surgery, and 19% to Infectious Diseases. In contrast, 54% of TP cases were admitted to Infectious Diseases, 33% to Internal Medicine, and 13% to Surgery. A statistically significant difference was observed in confirmatory outcomes based on department (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with the highest proportion of TP cases detected among patients admitted to Infectious Diseases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity and specificity according to COI values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCut-off values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;72.085*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;270.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo explore potential causes of false positivity, various categorical variables were assessed among FP cases, and their associations with FP status are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Accordingly, being reactive was positively and moderately associated with the presence of concurrent infection and vaccination in the past 6 months (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Risk analysis indicated that the likelihood of reactivity was approximately 64% lower in individuals without recent infections, and about 50% lower in those who had not received any vaccinations in the last six months, compared to their respective counterparts.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of false positivity with various variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-reactive (n,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReactive (FP)\u003c/p\u003e \u003cp\u003e(n,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePhi coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAutoimmune disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeurological disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiovascular Disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOPD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRenal failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHemodialysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood transfusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrgan transplantation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMalignancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHepatitis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 (48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTuberculosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMalaria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent infection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e161\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e88 (54.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e73 (45.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.200\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10 (28.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e25 (71.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination in the past 6 months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e188\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e98 (52.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e90 (47.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.206\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0 (0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8 (100)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003cb\u003eCOPD\u003c/b\u003e: Chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHIV infection remains a major global health concern, with early diagnosis, timely treatment, and effective self-management being key strategies for reducing transmission [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Diagnosis of HIV infection typically involves initial screening followed by confirmatory testing. However, FP results in HIV screening tests present a notable challenge in clinical practice, often leading to psychological distress, unnecessary testing, and delayed diagnosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This study aimed to investigate the factors contributing to FP results and to determine a reliable COI value to enhance diagnostic accuracy.\u003c/p\u003e \u003cp\u003eIn studies conducted in our country, anti-HIV seropositivity rates were reported to range from 0.03\u0026ndash;0.08% [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. It was also determined that the rate of recurrent reactivity has increased over the years, with an average reactivity rate of 0.7% reported in 2020 (26). Additionally, FP rates haveconsistently exceeded 70% in several local studies. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In the present study, the seropositivity rate was 0.33%, and the FP rate was calculated as 80.32%, aligning with earlier findings.\u003c/p\u003e \u003cp\u003eTang et al. reported that FP results were more common in elderly and female patients and were associated with conditions such as cancer, infections, and neurological disorders. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In our study, no statistically significant difference was observed in age between FP and TP groups. However, a significant association with gender was identified, with males being 1.412 times more likely to have a TP result- consistent with previous literature indicating higher HIV prevalence among males [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated a strong correlation between HIV screening test values and confirmatory test results. As COI increases, the likelihood of FP results decreases, making COI a valuable early indicator in distinguishing true infection before confirmatory results are available [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In a study conducted in our country, the highest micro-ELISA value observed in FP cases was 13.3 signal-to-cutoff (S/CO), while the lowest value recorded in TP cases was 5.29 S/CO [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Another study reported that the highest ELISA value in FP cases was 24.09 S/CO, whereas the lowest value in TP cases was 16.78 S/CO (27). Similarly, another study demonstrated that COI values in FP samples ranged from 1.0 to 15.0, while COI values in TP samples were consistently above 100.0. Notably, in cases where the COI exceeded 200, both sensitivity and specificity were reported to reach 100% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Tang et al. similarly noted a decline in FP rates with increasing COI values, identifying a COI of 52.74 as optimal (AUC:0.998, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Another study reported optimal cut-offs of 8.96 for males and 26.97 for females, while yet another using a fourth-generation ELISA test determined an optimal COI of 32.7 via ROC analysis [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our study, the median COI for FP cases was 1.75 (IQR: 1.66), and 458.9 (IQR: 384.93) for TP cases, with a statistically significant difference between the groups. The highest COI in FP cases was 21.27, and the lowest in TP cases was 122.29. A COI threshold of 72.085 was identified as the optimal discriminator between FP and TP results, achieving 100% sensitivity and specificity. Notably, although the current kit uses a COI of 1.0 as the threshold for reactivity, our findings suggest that this low value may contribute to the high FP rate observed.\u003c/p\u003e \u003cp\u003eFalse positivity was moderately and positively associated with concurrent infections and recent vaccinations (within the past six months). FP results have been previously reported in various inflammatory conditions and are often attributed to cross-reactivity. For example, Epstein\u0026ndash;Barr virus (EBV) infection has been identified as a cause of FP results in fourth-generation HIV tests [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In our study, 25.5% of FP patients had an upper respiratory tract infection at the time of testing, which may have triggered heightened immune responses, contributing to false reactivity. Several studies have also reported increased FP rates following COVID-19 infection [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, vaccination has been recognized as a contributing factor. In our study, FP results were significantly more frequent among individuals who had received a vaccine within the past six months\u0026mdash;specifically tetanus, hepatitis B, and influenza vaccines. Previous reports have associated influenza vaccination with FP HIV results, with one study reporting an average duration of false reactivity lasting 4.2 months [\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Sequence homology between HIV-1 envelope proteins and influenza hemagglutinin has been suggested as a potential mechanism for cross-reactivity, though this remains unconfirmed [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A case of FP HIV results following administration of the Tdap vaccine has also been reported. Clinicians should consider recent vaccination or immune stimulation when interpreting reactive HIV screening results and may opt to repeat testing sooner in cases of uncertainty [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Patients should also be informed that HIV screening conducted shortly after vaccination may result in FP results. Unless clinically necessary, delaying screening until several weeks after vaccination may help avoid unnecessary anxiety and confirmatory testing.\u003c/p\u003e \u003cp\u003eIn summary, anti-HIV screening results- known to be influenced by various biological factors- were significantly associated with concurrent infections and recent vaccination in this study. A COI threshold of 72.085 was identified as a highly accurate discriminator between FP and TP results. However, as this study was conducted in a single center, regional variations must be considered. Multicenter studies are needed to validate these findings and to establish standardized COI thresholds. In the meantime, patients with COI values exceeding the proposed threshold may benefit from expedited initiation of antiretroviral therapy. Clinicians should also be encouraged to evaluate potential contributing factors such as recent vaccination or infection when interpreting reactive HIV screening results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur findings highligt the importance of considering COI thresholds, recent vaccinations, and concurrent infections when interpreting HIV screening results. Increasing the current COI may significantly reduce FP rates and improve diagnostic accuracy. Moreover, access to the COI value prior to confirmatory testing can support clinical decision-making and improve patient counseling.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHIV Human Immunodeficiency Virus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFP False-Positive\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCOI Cut-Off Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROC Receiver Operating Characteristic\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eELISA \u003cem\u003eEnzyme-Linked ImmunoSorbent Assay\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIQR Interquartile Range\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTP True-Positive\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAIDS Acquired Immunodeficiency Syndrome\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO World Health Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eECDC European Centre for Disease Prevention and Control\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUNAIDS Joint United Nations Programme on HIV/AIDS\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAPHL Association of Public Health Laboratories\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eELFA Enzyme Linked Fluorescent Assay\u003c/p\u003e\n\u003cp\u003eRNA R\u003cem\u003eibonucleic Acid\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePCR Polymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003eHIS Hospital Information System\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSPSS Statistical Package for the Social Sciences\u003c/p\u003e\n\u003cp\u003eS/CO Signal-to-cutoff\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAUC Area under the Receiver Operating Characteristic curve\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Research Ethics Committee of\u0026nbsp;Giresun Training and Research Hospital (25.12.2023/08) and conducted in accordance with the Declaration of Helsinki. Informed consent to participate was taken from all participants and parents/legal guardians of minors participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author has read the journal policies and submit this manuscript in accordance with those policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Giresun Training and Research Hospital and Turkısh Public Healt, Ministry of Health of Turkey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no financial support for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.U: conception, design of the work, analysis, interpretation of data, drafted the work or substantively revised it, approved the submitted version, wrote the main manuscript text, All authors reviewed the manuscript\u003c/p\u003e\n\u003cp\u003eA.M.Ş: conception, design of the work, analysis, interpretation of data, drafted the work or substantively revised it, approved the submitted version , All authors reviewed the manuscript\u003c/p\u003e\n\u003cp\u003eE.A: analysis, interpretation of data, approved the submitted version, wrote the main manuscript text, All authors reviewed the manuscript, prepared all figures and tables\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang L, Zhou\u003csup\u003e \u003c/sup\u003eKH, Zhao HP, et al. 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Turk Mikrobiyol Cemiy J. 2023;53(2):124-32.\u003c/li\u003e\n\u003cli\u003eAvcık\u0026uuml;\u0026ccedil;\u0026uuml;k H,D\u0026uuml;lger D,Aydın F,Sarı \u0026Uuml;S. HBsAg, Anti-HBs, Anti-HCV and Anti-HIV seroprevalence among patients admitted to our hospital; five-year retrospective data. Turk Bull. Hyg. Exp. Bio. 2022;79(3): 397\u0026ndash;408.\u003c/li\u003e\n\u003cli\u003eVarışlı AN, Demir T, Tekin S. Confirmatory Test Results in Patients With a Reactive Anti-HIV Test Result: Four-Year Data. Klimik J. 2020;33(1):24-8.\u003c/li\u003e\n\u003cli\u003eKLİMUD. Proceeding of the 3rd HIV/AIDS Workshop. 2021. \u003c/li\u003e\n\u003cli\u003eTurkoğlu E, Oner SZ. Evaluation of Fourth-Generation ELISA Assay Cut-Off Values in The Context of Confirmation Test Results. Abant Med J. 2021;10(1):1-6.\u003c/li\u003e\n\u003cli\u003eToptan H, Aslan FG, Karake\u0026ccedil;e E, et al. Evaluation of Patients with Anti-HIV \u0026frac12; Reactivity with Confirmation Test Results. J Biotechnol and Strategic Health Res. 2019;3(1):27-32.\u003c/li\u003e\n\u003cli\u003eChacon L, Mateos ML, Holguin A. Relevance of cutoff on a 4th generation ELISA performance in the false positive rate during HIV diagnostic in a low HIV prevalence setting. J Clin Virol. 2017:92:11-3.\u003c/li\u003e\n\u003cli\u003eZhang X, Zhou X, He X, Liu X, Wang Z. The Optimal Cutoff Value to Predict HIV Infection Using the Architect HIV Ag/Ab Combo. Clin Lab. 2022;68(4).\u003c/li\u003e\n\u003cli\u003eGudipati S, Shalla A, Peterson E, Cook B, Markowitz N. Increase in False-Positive Fourth-Generation Human Immunodeficiency Virus Tests in Patients With Coronavirus Disease 2019. Clin Infect Dis. 2023;77(4):615-9.\u003c/li\u003e\n\u003cli\u003ePeter Liu P, Jackson P, Shaw N, Heysell S. Spectrum of false positivity for the fourth generation human immunodeficiency virus diagnostic tests. AIDS Res Ther. 2016:13:1.\u003c/li\u003e\n\u003cli\u003eHakobyan N, Yadav R, Abaza K, Friedman A. False-Positive Human Immunodeficiency Virus Results in COVID-19 Patients. Cureus. 2023;15(1):e34096. \u003c/li\u003e\n\u003cli\u003eEguchi S, Takatsuki M, Soyama A, Torashima Y, Tsuji A, Kuroki T. False for the Human Immunodeficiency Virus Antibody After Influenza Vaccination in a Living Donor for Liver Transplantation. Liver Transpl. 2013;19(6):666.\u003c/li\u003e\n\u003cli\u003eErickson CP, McNiff T, Klausner JD. Influenza vaccination and falsepositive HIV results. N Engl J Med. 2006;354(13):1422-3.\u003c/li\u003e\n\u003cli\u003eKenzie WR, Davis JP, Peterson DE, Hibbard AJ, Becker G, Zarvan BS. Multiple False-positive Serologic Tests for HIV, HTLV-1, and Hepatitis C Following Influenza vaccination, 1991. JAMA. 1992;268(8):1015-7.\u003c/li\u003e\n\u003cli\u003eArnold NL, Slade BL, Jones MM, Popovsky MA. Donor follow-up of influenza vaccine-related multiple viral enzyme immunoassay reactivity. Vox Sang. 1994;67(2):191-4.\u003c/li\u003e\n\u003cli\u003eYu KOA, Glassman SR, Link HM. False-Positive Human Immunodeficiency Virus-1 Test Results With Rapid Seroreversion After Third-Trimester Tdap Booster Vaccination. Obstet Gynecol. 2024;144(6):e125-e128.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HIV infection, cut-off value, false positivity","lastPublishedDoi":"10.21203/rs.3.rs-6602813/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6602813/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrently, fourth-generation assays detecting HIV-1/2 antibodies and p24 antigen are widely used as screening tools for human immunodeficiency virus (HIV). However, false-positive (FP) results remain a significant issue additional confirmatory testing. This study aimed to identify factors associated with false positivity and to determine an optimal cut-off index (COI) value with high sensitivity and specificity by evaluating the relationship between COI values in screening tests and confirmed HIV infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween January 2024 and January 2025, a total of 36,046 patients were screened for anti-HIV. The serum samples were tested for anti-HIV using a chemiluminescence immunoassay (Cobas E601, Roche Diagnostics, Germany) with the Elecsys® HIV combi PT kit (Roche Diagnostics, Germany). Reactive samples were referred to a reference laboratory for confirmation testing. The optimal COI value for predicting true HIV infection was determined using receiver operating characteristic (ROC) curve analysis. FP and non-reactive patients were evaluated for various parameters to identify factors contributing to false positivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 36,046 patients were screened for anti-HIV and 122 patients (0.33%) were found to be reactive by ELISA testing. 24 were confirmed as positive and 98 as negative, yielding a false positive (FP) rate of 80.32%. False positivity was found to be positively and moderately associated with having a concurrent infection or receiving a vaccination within the past six months (p\u0026lt;0.05). The median and interquartile range (IQR) of COI values in (FP) cases were 1.75 and 1.66, respectively, while in true-positive (TP) cases, the median and IQR were 458.9 and 384.93, respectively. This difference was statistically significant (p\u0026lt;0.05). The optimal COI value to differentiate TP from FP cases was determined to be 72.085.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIdentifying potential factors that contribute to false positivity in individuals with reactive screening results, along with consideration of COI values before confirmatory testing, may facilitate more accurate clinical decision-making and improve patient counseling during the interim period before definitive results are available.\u003c/p\u003e","manuscriptTitle":"False Positivity in Anti-HIV Tests: Causes and Determination of a Reliable Cut-Off Value","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-10 18:05:56","doi":"10.21203/rs.3.rs-6602813/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab4b28cd-ed4c-4c8e-9567-deef3432701e","owner":[],"postedDate":"June 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-10T18:13:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-10 18:05:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6602813","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6602813","identity":"rs-6602813","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}