Serum Albumin Level Compared to CD4+ Count as a Marker of Immunosuppression in HIV/AIDS Patients: An Observational Cross- Sectional Study from South India

Serum Albumin Level Compared to CD4+ Count as a Marker of Immunosuppression in HIV/AIDS Patients: An Observational Cross- Sectional Study from South India | 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 Serum Albumin Level Compared to CD4+ Count as a Marker of Immunosuppression in HIV/AIDS Patients: An Observational Cross- Sectional Study from South India Viraj Govindani, H. Manjunath Hande This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7264509/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 Monitoring of immunosuppression in HIV patients is essential, especially in resource-limited settings. CD4 + T-cell count, though standard, is costly and technically demanding. Serum albumin, an inexpensive and routinely measured parameter, may reflect immunosuppressive status. This study evaluates the correlation between serum albumin and CD4 + count and its relationship with markers of inflammation and opportunistic infections in HIV/AIDS patients. Methods This observational cross-sectional study was conducted at Kasturba Hospital, Manipal, between June 2023 and April 2025. A total of 107 adult patients diagnosed with HIV were enrolled. Comprehensive demographic, clinical, and laboratory data were collected. Pearson correlation analysis was performed to examine the association between CD4 + T-cell counts and serum albumin levels, absolute lymphocyte count (ALC), albumin-to-globulin (A:G) ratio, and neutrophil-to-lymphocyte ratio (NLR). Additionally, Independent sample t-tests were applied to compare serum albumin levels between patients with and without opportunistic infections. Subsequently, Logistic regression analysis was used for analysis. Results CD4 count showed a positive correlation with serum albumin (r = 0.296, p = 0.002), A:G ratio (r = 0.437, p < 0.001), and ALC (r = 0.634, p < 0.001), and a negative correlation with NLR (r = − 0.354, p < 0.001). Albumin levels were significantly lower in patients with opportunistic infections (3.48 ± 0.64 g/dL) compared to those without (4.01 ± 0.68 g/dL; p < 0.001). Logistic regression indicated that each 1 g/dL rise in serum albumin reduced the odds of opportunistic infections by 70% (OR = 0.30; 95% CI: 0.17–0.56; p < 0.001). Conclusions Serum albumin demonstrates a strong positive association with CD4 + counts and an inverse relationship with systemic inflammation and opportunistic infections. Its ease of measurement, cost-effectiveness, and wide availability position it as a valuable surrogate marker for assessing immunosuppression in HIV/AIDS patients, especially in settings with limited access to advanced diagnostics. Trial Registration Registered prospectively with the Clinical Trials Registry - India (CTRI) on 03 July 2023 (CTRI/2023/07/054614). HIV CD4 Count Serum Albumin Immunosuppression Opportunistic Infections Biomarkers Figures Figure 1 Figure 2 Figure 3 BACKGROUND Human Immunodeficiency Virus (HIV) continues to be one of the most significant public health challenges globally, particularly in low- and middle-income countries such as India. Despite advances in antiretroviral therapy (ART) that have dramatically improved life expectancy and quality of life for people living with HIV (PLHIV), the disease remains incurable. Its hallmark feature is the progressive destruction of CD4 + T lymphocytes, which play a central role in coordinating immune responses. This depletion leads to a state of immunodeficiency, rendering patients susceptible to opportunistic infections and AIDS-defining illnesses [ 1 , 2 ] . Monitoring CD4 + T-cell counts remains the cornerstone of immunological assessment in HIV infection. CD4 count is essential not only for disease staging but also for guiding the initiation of prophylaxis for opportunistic infections, evaluating the response to ART, and assessing long-term prognosis. However, the requirement of flow cytometry for CD4 enumeration makes the test expensive and technically demanding. In resource-constrained settings, particularly in rural areas of India and sub-Saharan Africa, regular CD4 monitoring is often not feasible due to cost, limited access to laboratory infrastructure, and shortage of trained personnel [ 3 , 4 ] . As a result, there is a growing interest in identifying alternative biomarkers that are simple, affordable, and reliable for evaluating the immunological status of HIV-infected individuals. One such candidate is serum albumin. Albumin is the most abundant plasma protein synthesized by the liver and plays a crucial role in maintaining colloid osmotic pressure, transporting hormones and drugs, and modulating inflammation. Its levels are influenced by nutritional status, hepatic function, systemic inflammation, and catabolic states—all of which are commonly altered in HIV-infected individuals [ 5 ] . In the context of HIV infection, hypoalbuminemia has been associated with advanced disease, higher HIV viral loads, increased incidence of opportunistic infections, and overall poorer clinical outcomes. Studies have demonstrated that low serum albumin levels are predictive of AIDS progression and mortality, independent of CD4 counts and viral loads [ 6 , 7 ] . Furthermore, albumin estimation is cost-effective and widely available in most clinical laboratories, making it particularly valuable in resource-limited healthcare settings where access to CD4 or viral load testing is not routinely available [ 8 ] . Several studies have explored the role of albumin as a surrogate marker of immunosuppression in HIV, showing that it correlates with CD4 count, systemic inflammation, and risk of secondary infections [3,6]. Inflammation in HIV patients leads to decreased albumin synthesis and increased vascular leakage, further lowering serum levels. Albumin also functions as a negative acute phase reactant and antioxidant, and its reduction may reflect chronic immune activation—a known feature of untreated or poorly controlled HIV [ 9 ] . Given these associations, serum albumin holds promise as a simple yet powerful biomarker for assessing disease severity and predicting clinical outcomes in HIV/AIDS. The present study was undertaken to explore this potential by comparing serum albumin levels with CD4 + counts in HIV-positive patients, while also analyzing its correlation with other immunological markers such as the albumin-to-globulin (A:G) ratio and neutrophil-to-lymphocyte ratio (NLR), and its association with opportunistic infections. METHODOLOGY AIM- To determine the role of serum Albumin level compared to CD4 count as a marker of Immunosuppression in HIV/AIDS patients. OBJECTIVES- 1) To evaluate serum albumin level and correlate between serum albumin levels, CD4 + cell count and other markers of immunosuppression like Albumin/Globulin ratio, Neutrophil/lymphocyte ratio 2) To find a correlation between serum albumin levels and opportunistic infections in HIV positive patients. STUDY DESIGN AND SETTING- An observational, cross-sectional study was conducted on 107 HIV positive patients attending the outpatient and inpatient departments of general medicine and Infectious diseaes from June 2023 to April 2025 at Kasturba Medical College, Manipal. Patients were recruited in accordance with the stated inclusion and exclusion criteria after obtaining informed written consent, ensuring strict confidentiality throughout the process. A thorough and structured case proforma was used to record the details. Subsequently, all patients underwent a thorough history-taking, comprehensive clinical examination, and relevant laboratory investigations, including complete blood count, CD4 count, renal and liver function tests, all of which were systematically documented. CD4 + T cell counts were determined using flow cytometry. Renal and liver function tests were carried out using standard biochemical methods, and complete blood counts were performed using automated haematology analysers under aseptic conditions. Eligibility criteria: Inclusion criteria – 1. All HIV infected patients aged 18 years and above. Exclusion criteria – Pregnant females Patients below 18 years of age Patients with pre-existing hepatobiliary disease Patients with pre-existing renal disease / chronic kidney disease Patients with pre-existing gastrointestinal disease -malabsorption syndrome, IBD Patients exhibiting clinical signs of congestive heart failure Patients with any h/o burns in past 21 days 8. Patients not giving consent STATISTICAL ANALYSIS- The statistical analysis was carried out using SPSS (Statistical Package for Social Sciences) IBM version 25.Statistical analysis among data was done to assess corelation between various parameters using Pearson’s correlation test to establish significant/non-significant association. A ‘p’ value of 0.05 or lower was regarded as statistically significant.The demographic data like age, gender, educational status, area distribution and CDC grading was subjected to frequency distribution Categorical variables were expressed as proportions and percentages.Results were described with the help of various frequency tables, graphs, pie charts, and histograms. RESULTS Demographics and Clinical Profile Out of the 107 HIV-positive patients included in the study, the majority were male (71%), while females constituted 29%. The age distribution showed that 28% were between 40–49 years, 24.3% were between 50–59, 16.8% were aged 30–39, and only 1.9% were aged 70 or above. In terms of BMI, 45.7% had normal BMI, 20.5% were overweight, 14.2% were obese, and 19.6% were underweight. Educational status revealed that 32.7% had completed secondary schooling, while 20.6% were illiterate. The most common CDC staging observed was Grade 3 (56.1%), indicating advanced disease. Opportunistic Infections Out of 107 participants, 62 (57.9%) had at least one opportunistic infection. Tuberculosis (both pulmonary and extrapulmonary) was the most common (21.5%), followed by candidiasis (15%), cytomegalovirus infection (7.5%), syphilis (5.6%), and cryptococcosis, toxoplasmosis, and HSV meningitis (each 1.9%). Patients with opportunistic infections had significantly lower mean serum albumin (3.48 ± 0.64 g/dL) than those without (4.01 ± 0.68 g/dL), with a p-value < 0.001. Laboratory Parameters and Correlation Analysis The descriptive statistics, including the mean, median, and mode values for serum albumin, ANC, ALC, A: G ratio, CD4 + count, and NLR, are summarised in Table 1 Serum Albumin and CD4 + Count The mean serum albumin level among the participants was 3.8 ± 0.71 g/dL, while the mean CD4 + count was 242.3 ± 240.4 cells/mm³. A statistically significant positive correlation was observed between serum albumin and CD4 + count (r = 0.296, p = 0.002) as shown in Table 2 . The relationship is further illustrated by the scatter plot in Graph 1, which depicts a positive linear trend. This indicates that higher serum albumin levels are associated with better immune status, reinforcing the role of albumin as a potential surrogate marker of immunosuppression in HIV-positive individuals. Albumin-to-Globulin (A:G) Ratio and CD4 + Count The A:G ratio also showed a strong positive correlation with CD4 + count (r = 0.437, p < 0.001). This reflects the systemic impact of HIV on protein metabolism, where reductions in albumin or elevations in globulin levels (e.g., due to hypergammaglobulinemia) are associated with immune deterioration. Serum Albumin and Neutrophil-to-Lymphocyte Ratio (NLR) An inverse correlation was found between serum albumin and NLR (r = − 0.354, p < 0.001), as shown in Table 3 . This negative linear correlation is visually represented in Graph 2, suggesting that patients with higher levels of systemic inflammation tend to have lower serum albumin. This relationship may be explained by inflammation-induced hepatic suppression of albumin synthesis and increased vascular permeability. CD4 + Count and Absolute Lymphocyte Count (ALC) A strong positive correlation was observed between CD4 + count and ALC (r = 0.634, p < 0.001). This is expected, as CD4 + cells are a subset of lymphocytes. ALC may therefore serve as a cost-effective adjunct for assessing immune status in low-resource settings. CD4 + Count and Absolute Neutrophil Count (ANC) No statistically significant correlation was seen between CD4 + count and ANC (r = − 0.037, p = 0.705), indicating that neutrophil levels are not a reliable indicator of immune suppression in the context of HIV infection. As shown in Table 4 , CD4 + count was positively correlated with serum albumin and ALC, and negatively correlated with NLR and ANC. Serum Albumin and Opportunistic Infections Participants with opportunistic infections (OIs) had significantly lower serum albumin levels (3.48 ± 0.64 g/dL) compared to those without OIs (4.01 ± 0.68 g/dL), with a highly significant p-value (< 0.001). Paired t-test analysis revealed significant differences in serum albumin levels between patients with and without opportunistic infections, as shown in Table 5 . This suggests that hypoalbuminemia is strongly associated with increased susceptibility to OIs, highlighting its potential as a prognostic marker. Logistic Regression Analysis A binary logistic regression analysis demonstrated that for every 1 g/dL increase in serum albumin, the odds of having an opportunistic infection decreased by approximately 70% (Odds Ratio = 0.30; 95% CI: 0.17–0.56; p < 0.001) as indicated in Table 6 . This relationship is visually represented in the logistic regression curve Graph 3. This reinforces the utility of serum albumin as an independent predictor of clinical outcomes in HIV-positive patients. Table 1 Mean mode and median of Albumin, ANC, ALC, A:G ratio, CD4 and NLR Albumin ANC ALC A:G RATIO CD4 NLR N Valid 107 107 107 107 107 107 Mean 3.7974 5.0738 1.5196 1.1131 242.2991 5.6546 Median 3.8000 4.1400 1.3600 1.0000 149.0000 2.9000 Mode 4.00 4.14 .72 .80 96.00 a 1.50 a. Multiple modes exist. The smallest value is shown Table 2 Correlation of CD4 with Albumin ALBUMIN CD4 ALBUMIN Pearson Correlation 1 .296 ** Sig. (2-tailed) .002 N 107 107 CD4 Pearson Correlation .296 ** 1 Sig. (2-tailed) .002 N 107 107 Graph 1 Scatter plot showing positive linear relationship between albumin and CD4 Table 3 Correlation of CD4 RATIO with NLR CD4 NLR CD4 Pearson Correlation 1 − .354 ** Sig. (2-tailed) .000 N 107 107 NLR Pearson Correlation − .354 ** 1 Sig. (2-tailed) .000 N 107 107 Graph 2: Scatter plot showing negative linear relationship between NLR and CD4 Table 4 Pearson’s Correlations amongst various parameters ANC ALC A:G RATIO CD4 ANC Pearson Correlation 1 − .170 .109 − .037 Sig. (2-tailed) .080 .263 .705 N 107 107 107 107 ALC Pearson Correlation − .170 1 .269 ** .634 ** Sig. (2-tailed) .080 .005 .000 N 107 107 107 107 A:G RATIO Pearson Correlation .109 .269 ** 1 .437 ** Sig. (2-tailed) .263 .005 .000 N 107 107 107 107 CD4 Pearson Correlation − .037 .634 ** .437 ** 1 Sig. (2-tailed) .705 .000 .000 N 107 107 107 107 Table 5 Paired t test for presence or absence of Opportunistic Infections Opportunistic infection N Mean Albumin (g/dL) Std. Deviation t value p value Present 43 3.48 0.64 -4.03 0.0001 Absent 64 4.01 0.68 Table 6 Logistic Regression of Opportunistic Infectionsand albumin Parameter Coefficient (β) p-value Odds Ratio (OR) 95% CI for OR Intercept 3.67 — — — Albumin −1.19 < 0.001 0.30 [0.17–0.56] Graph 3: Logistic Regression of Opportunistic Infections and albumin DISCUSSION This study evaluated the role of serum albumin as a surrogate marker of immunosuppression in HIV-positive individuals by analyzing its relationship with CD4 + count, systemic inflammatory markers, and opportunistic infections. Our findings demonstrate that serum albumin is positively associated with CD4 + T-cell counts and inversely related to markers of inflammation such as NLR, as well as the incidence of opportunistic infections. These results reinforce the potential of serum albumin as a low-cost, reliable, and accessible biomarker for assessing immune status, particularly in resource-limited settings [ 10 ] . In our study population, the majority were male and middle-aged, a trend also observed in studies by Mehta et al. [ 11 ] and Shah et al. [ 12 ] , where HIV predominantly affected adult males in the fourth and fifth decades of life. These demographic similarities enhance the external validity of our findings and reflect typical patterns seen in national registries. We found a statistically significant positive correlation between serum albumin and CD4 + count, which is consistent with results reported by Olawumi and Olatunji [ 13 ] , who showed that lower serum albumin levels were strongly associated with advanced HIV disease stages. Similarly, Sudfeld et al. [ 14 ] concluded that hypoalbuminemia at ART initiation predicted poor CD4 + recovery and increased mortality. Mehta et al. [ 11 ] further demonstrated that albumin levels, when combined with CD4 + and viral load, served as independent predictors of clinical progression. Our study also found that patients with opportunistic infections had significantly lower serum albumin levels compared to those without. This association aligns with multiple studies which have highlighted hypoalbuminemia as a marker of increased risk for opportunistic diseases, particularly tuberculosis and fungal infections [ 15 ] . Logistic regression analysis in our study revealed that each 1 g/dL increase in serum albumin was associated with a 70% reduction in the odds of developing an opportunistic infection, reinforcing its prognostic significance. The albumin-to-globulin (A:G) ratio, another nutritional and immunological parameter, also showed a strong positive correlation with CD4 + count in our cohort. This supports the observations made by Ball et al. [ 16 ] , who suggested that chronic immune activation in HIV leads to polyclonal hyperglobulinemia, thereby reducing the A:G ratio. A low A:G ratio, thus, may indirectly indicate progressive immunosuppression. An inverse relationship between serum albumin and the neutrophil-to-lymphocyte ratio (NLR) was also observed, echoing findings from recent studies by Madzime et al. [ 17 ] and Raffetti et al. [ 18 ] , which identified elevated NLR as a predictor of immune decline, virological failure, and mortality in HIV-infected patients. Elevated NLR may reflect ongoing systemic inflammation, a major driver of immune exhaustion and disease progression in untreated or poorly controlled HIV infection. We also observed a strong positive correlation between absolute lymphocyte count (ALC) and CD4 + count, further validating previous studies which suggested that ALC may serve as a practical alternative to CD4 testing where the latter is unavailable [ 19 ] . In contrast, absolute neutrophil count (ANC) showed no significant relationship with CD4 + levels, indicating limited utility as an immune marker in this context. While CD4 + count remains the gold standard for assessing immune function in HIV patients, our findings suggest that serum albumin, in conjunction with simple markers like NLR and ALC, may serve as effective adjuncts or alternatives for risk stratification in low-resource environments. Albumin testing is already widely incorporated in routine clinical chemistry panels, making its integration into HIV care both feasible and cost-effective. That said, our study is not without limitations. Being cross-sectional, it does not allow causal inferences or longitudinal assessment of disease progression. Variables such as ART adherence, liver function, nutritional intake, and comorbid conditions—which may influence serum albumin—were not uniformly controlled. Despite this, the consistency of correlations with CD4 + count, inflammatory indices, and opportunistic infections provides strong support for albumin’s clinical relevance. In summary, this study builds upon previous literature by demonstrating that serum albumin is not only a reflection of nutritional status but also a reliable surrogate marker of immune suppression and predictor of opportunistic infections in HIV/AIDS patients. These results advocate for the broader use of serum albumin in HIV disease monitoring, especially in healthcare settings where advanced immunological testing may not be routinely available. CONCLUSION This study highlights a strong association between low serum albumin levels and immune suppression in HIV/AIDS patients, particularly those with opportunistic infections. A consistent positive correlation with CD4 + count and an inverse relationship with NLR emphasize the role of albumin as a dual indicator of both nutritional and immunological status.Routine albumin monitoring can provide critical insights in resource-limited settings where CD4 or viral load testing is unavailable. The findings advocate for incorporating serum albumin into standard HIV assessment protocols to enable early risk stratification, infection surveillance, and timely intervention. Abbreviations Full Form HIV Human Immunodeficiency Virus AIDS Acquired Immunodeficiency Syndrome PLHIV People Living with HIV ART Antiretroviral Therapy CD4 Cluster of Differentiation 4 NLR Neutrophil-to-Lymphocyte Ratio A:G ratio Albumin-to-Globulin Ratio ALC Absolute Lymphocyte Count ANC Absolute Neutrophil Count OI Opportunistic Infection WHO World Health Organization SPSS Statistical Package for the Social Sciences SD Standard Deviation CI Confidence Interval OR Odds Ratio Declarations Ethical Committee Approval- This study was approved by the Institutional Ethics Committee 2 of Kasturba Medical College and Kasturba Hospital, which is registered under the Central Drugs Standard Control Organisation (CDSCO) and the Department of Health Research (DHR), ICMR. The committee operates in compliance with the ICMR 2017 guidelines for biomedical and health research involving human participants, the Medical Device Rules 2017, the New Drugs and Clinical Trials (NDCT) Rules 2019, and the Declaration of Helsinki (1964) and its later amendments. IEC Number- IEC2: 237/2023 Consent- Written informed consent was taken from all study subjects. Competing interest- The authors declare that they have no competing interests Funding- Not applicable Author Contribution V.G. (Viraj Govindani) conceived and designed the study, collected data, performed data analysis, and drafted the manuscript. M.H. (Manjunath Hande) supervised the study, contributed to data interpretation, and critically revised the manuscript. Both authors reviewed and approved the final version of the manuscript. Acknowledgements- Not applicable Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request, but are not publicly available in order to maintain the privacy and confidentiality of the patients involved. References Fauci AS, Pantaleo G, Stanley S, Weissman D. Immunopathogenic mechanisms of HIV infection. Ann Intern Med. 1996;124(7):654–63. National AIDS Control Organization, India HIVE. Technical Brief. Ministry of Health and Family Welfare, Government of India; 2023. Sudfeld CR, Isanaka S, Aboud S, et al. Serum albumin concentration and HIV-related outcomes. J Infect Dis. 2013;207:1370–8. WHO. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2016. Rothschild MA, Oratz M, Schreiber SS. Serum albumin. Hepatology. 1988;8(2):385–401. Olawumi HO, Olatunji PO. The value of serum albumin in pretreatment assessment and monitoring of therapy in HIV/AIDS patients. HIV Med. 2006;7(6):351–5. Mehta SH, Astemborski J, Sterling TR, et al. Serum albumin as a prognostic indicator for HIV disease progression. AIDS Res Hum Retroviruses. 2006;22(1):14–21. Ball SG. The chemical pathology of AIDS. Ann Clin Biochem. 1994;31:401–9. Kearney A. Serum albumin as a predictor of immune function in HIV/AIDS patients. Clin Infect Dis. 2018;66(12):1945–6. Gupta T, Prakash J. Albumin as a surrogate biomarker of HIV-associated immune suppression. Int J Med Sci. 2022;19(3):151–7. Mehta SH, Astemborski J, Sterling TR, et al. Serum albumin as a prognostic indicator for HIV disease progression. AIDS Res Hum Retroviruses. 2006;22(1):14–21. Shah S, Smith CJ, Lampe F, et al. Haemoglobin and albumin as markers of HIV disease progression in the HAART era. HIV Med. 2007;8(1):38–45. Olawumi HO, Olatunji PO. The value of serum albumin in pretreatment assessment and monitoring of therapy in HIV/AIDS patients. HIV Med. 2006;7(6):351–5. Sudfeld CR, Isanaka S, Aboud S, et al. Serum albumin concentration and HIV-related outcomes. J Infect Dis. 2013;207:1370–8. Ezugwu UM, Igbokwe GE, Okoye OJ, et al. Hypoalbuminemia and opportunistic infections in HIV patients: a retrospective review. Afr Health Sci. 2020;20(2):888–94. Ball SG. The chemical pathology of AIDS. Ann Clin Biochem. 1994;31:401–9. Madzime M, Rossouw TM, Theron AJ, et al. Interactions of HIV and ART with neutrophils and inflammation markers. Front Immunol. 2021;12:634386. Raffetti E, Donato F, Pezzoli C, et al. Systemic inflammation-based biomarkers and survival in HIV-positive subjects with solid cancer. J Acquir Immune Defic Syndr. 2015;69(5):585–92. Kalyani R, Dutta A, Venkatesh S. Absolute lymphocyte count as a predictor of CD4 count in HIV patients. J Clin Diagn Res. 2014;8(9):FC11–13. 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Manjunath Hande","email":"","orcid":"","institution":"Kasturba Medical College, Manipal Academy of Higher Education Manipal","correspondingAuthor":false,"prefix":"","firstName":"H.","middleName":"Manjunath","lastName":"Hande","suffix":""}],"badges":[],"createdAt":"2025-07-31 17:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7264509/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7264509/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91073962,"identity":"bbb02b05-37b6-413c-927d-11fa79bfb222","added_by":"auto","created_at":"2025-09-11 11:01:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23726,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eGraph 1 Scatter plot showing positive linear relationship between albumin and CD4\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7264509/v1/2879952a4b464de221fa423b.png"},{"id":91076311,"identity":"005c80ce-ac68-4da3-b46b-c73a36b56a82","added_by":"auto","created_at":"2025-09-11 11:09:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eGraph 2: Scatter plot showing negative linear relationship between NLR and CD4\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7264509/v1/5d5a66caa0211870fe973b56.png"},{"id":91073970,"identity":"9d60d934-1f86-487d-b914-49ff87d7afb9","added_by":"auto","created_at":"2025-09-11 11:01:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":123649,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eGraph 3: Logistic Regression of Opportunistic Infections and albumin\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7264509/v1/3da0cf1cc79e8809227df923.png"},{"id":106394341,"identity":"40e233fe-aba8-4892-886c-7a0922c739ab","added_by":"auto","created_at":"2026-04-08 07:43:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1177041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7264509/v1/c95ee11b-97fc-4386-9668-e26c3dc0f5e4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Serum Albumin Level Compared to CD4+ Count as a Marker of Immunosuppression in HIV/AIDS Patients: An Observational Cross- Sectional Study from South India","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eHuman Immunodeficiency Virus (HIV) continues to be one of the most significant public health challenges globally, particularly in low- and middle-income countries such as India. Despite advances in antiretroviral therapy (ART) that have dramatically improved life expectancy and quality of life for people living with HIV (PLHIV), the disease remains incurable. Its hallmark feature is the progressive destruction of CD4\u0026thinsp;+\u0026thinsp;T lymphocytes, which play a central role in coordinating immune responses. This depletion leads to a state of immunodeficiency, rendering patients susceptible to opportunistic infections and AIDS-defining illnesses \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMonitoring CD4\u0026thinsp;+\u0026thinsp;T-cell counts remains the cornerstone of immunological assessment in HIV infection. CD4 count is essential not only for disease staging but also for guiding the initiation of prophylaxis for opportunistic infections, evaluating the response to ART, and assessing long-term prognosis. However, the requirement of flow cytometry for CD4 enumeration makes the test expensive and technically demanding. In resource-constrained settings, particularly in rural areas of India and sub-Saharan Africa, regular CD4 monitoring is often not feasible due to cost, limited access to laboratory infrastructure, and shortage of trained personnel \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAs a result, there is a growing interest in identifying alternative biomarkers that are simple, affordable, and reliable for evaluating the immunological status of HIV-infected individuals. One such candidate is serum albumin. Albumin is the most abundant plasma protein synthesized by the liver and plays a crucial role in maintaining colloid osmotic pressure, transporting hormones and drugs, and modulating inflammation. Its levels are influenced by nutritional status, hepatic function, systemic inflammation, and catabolic states\u0026mdash;all of which are commonly altered in HIV-infected individuals \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the context of HIV infection, hypoalbuminemia has been associated with advanced disease, higher HIV viral loads, increased incidence of opportunistic infections, and overall poorer clinical outcomes. Studies have demonstrated that low serum albumin levels are predictive of AIDS progression and mortality, independent of CD4 counts and viral loads \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Furthermore, albumin estimation is cost-effective and widely available in most clinical laboratories, making it particularly valuable in resource-limited healthcare settings where access to CD4 or viral load testing is not routinely available \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSeveral studies have explored the role of albumin as a surrogate marker of immunosuppression in HIV, showing that it correlates with CD4 count, systemic inflammation, and risk of secondary infections [3,6]. Inflammation in HIV patients leads to decreased albumin synthesis and increased vascular leakage, further lowering serum levels. Albumin also functions as a negative acute phase reactant and antioxidant, and its reduction may reflect chronic immune activation\u0026mdash;a known feature of untreated or poorly controlled HIV \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGiven these associations, serum albumin holds promise as a simple yet powerful biomarker for assessing disease severity and predicting clinical outcomes in HIV/AIDS. The present study was undertaken to explore this potential by comparing serum albumin levels with CD4\u0026thinsp;+\u0026thinsp;counts in HIV-positive patients, while also analyzing its correlation with other immunological markers such as the albumin-to-globulin (A:G) ratio and neutrophil-to-lymphocyte ratio (NLR), and its association with opportunistic infections.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e\u003cb\u003eAIM-\u003c/b\u003e To determine the role of serum Albumin level compared to CD4 count as a marker of Immunosuppression in HIV/AIDS patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOBJECTIVES-\u003c/b\u003e 1) To evaluate serum albumin level and correlate between serum albumin levels, CD4\u0026thinsp;+\u0026thinsp;cell count and other markers of immunosuppression like Albumin/Globulin ratio, Neutrophil/lymphocyte ratio\u003c/p\u003e\u003cp\u003e2) To find a correlation between serum albumin levels and opportunistic infections in HIV positive patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSTUDY DESIGN AND SETTING-\u003c/b\u003e An observational, cross-sectional study was conducted on 107 HIV positive patients attending the outpatient and inpatient departments of general medicine and Infectious diseaes from June 2023 to April 2025 at Kasturba Medical College, Manipal. Patients were recruited in accordance with the stated inclusion and exclusion criteria after obtaining informed written consent, ensuring strict confidentiality throughout the process. A thorough and structured case proforma was used to record the details.\u003c/p\u003e\u003cp\u003eSubsequently, all patients underwent a thorough history-taking, comprehensive clinical examination, and relevant laboratory investigations, including complete blood count, CD4 count, renal and liver function tests, all of which were systematically documented. CD4\u0026thinsp;+\u0026thinsp;T cell counts were determined using flow cytometry. Renal and liver function tests were carried out using standard biochemical methods, and complete blood counts were performed using automated haematology analysers under aseptic conditions.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEligibility criteria:\u003c/h2\u003e\u003cp\u003e\u003cb\u003eInclusion criteria \u0026ndash;\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e1. All HIV infected patients aged 18 years and above.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion criteria \u0026ndash;\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePregnant females\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients below 18 years of age\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients with pre-existing hepatobiliary disease\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients with pre-existing renal disease / chronic kidney disease\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients with pre-existing gastrointestinal disease -malabsorption syndrome, IBD\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients exhibiting clinical signs of congestive heart failure\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients with any h/o burns in past 21 days\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e8. Patients not giving consent\u003c/p\u003e\u003cp\u003e\u003cb\u003eSTATISTICAL ANALYSIS-\u003c/b\u003e The statistical analysis was carried out using SPSS (Statistical Package for Social Sciences) IBM version 25.Statistical analysis among data was done to assess corelation between various parameters using Pearson\u0026rsquo;s correlation test to establish significant/non-significant association. A \u0026lsquo;p\u0026rsquo; value of 0.05 or lower was regarded as statistically significant.The demographic data like age, gender, educational status, area distribution and CDC grading was subjected to frequency distribution Categorical variables were expressed as proportions and percentages.Results were described with the help of various frequency tables, graphs, pie charts, and histograms.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eDemographics and Clinical Profile\u003c/h2\u003e\u003cp\u003eOut of the 107 HIV-positive patients included in the study, the majority were male (71%), while females constituted 29%. The age distribution showed that 28% were between 40\u0026ndash;49 years, 24.3% were between 50\u0026ndash;59, 16.8% were aged 30\u0026ndash;39, and only 1.9% were aged 70 or above. In terms of BMI, 45.7% had normal BMI, 20.5% were overweight, 14.2% were obese, and 19.6% were underweight. Educational status revealed that 32.7% had completed secondary schooling, while 20.6% were illiterate. The most common CDC staging observed was Grade 3 (56.1%), indicating advanced disease.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eOpportunistic Infections\u003c/h3\u003e\n\u003cp\u003eOut of 107 participants, 62 (57.9%) had at least one opportunistic infection. Tuberculosis (both pulmonary and extrapulmonary) was the most common (21.5%), followed by candidiasis (15%), cytomegalovirus infection (7.5%), syphilis (5.6%), and cryptococcosis, toxoplasmosis, and HSV meningitis (each 1.9%). Patients with opportunistic infections had significantly lower mean serum albumin (3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 g/dL) than those without (4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 g/dL), with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\n\u003ch3\u003eLaboratory Parameters and Correlation Analysis\u003c/h3\u003e\n\u003cp\u003eThe descriptive statistics, including the mean, median, and mode values for serum albumin, ANC, ALC, A: G ratio, CD4\u0026thinsp;+\u0026thinsp;count, and NLR, are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSerum Albumin and CD4\u0026thinsp;+\u0026thinsp;Count\u003c/h2\u003e\u003cp\u003eThe mean serum albumin level among the participants was 3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71 g/dL, while the mean CD4\u0026thinsp;+\u0026thinsp;count was 242.3\u0026thinsp;\u0026plusmn;\u0026thinsp;240.4 cells/mm\u0026sup3;. A statistically significant positive correlation was observed between serum albumin and CD4\u0026thinsp;+\u0026thinsp;count (r\u0026thinsp;=\u0026thinsp;0.296, p\u0026thinsp;=\u0026thinsp;0.002) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The relationship is further illustrated by the scatter plot in Graph 1, which depicts a positive linear trend. This indicates that higher serum albumin levels are associated with better immune status, reinforcing the role of albumin as a potential surrogate marker of immunosuppression in HIV-positive individuals.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAlbumin-to-Globulin (A:G) Ratio and CD4 + Count\u003c/h3\u003e\n\u003cp\u003eThe A:G ratio also showed a strong positive correlation with CD4\u0026thinsp;+\u0026thinsp;count (r\u0026thinsp;=\u0026thinsp;0.437, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This reflects the systemic impact of HIV on protein metabolism, where reductions in albumin or elevations in globulin levels (e.g., due to hypergammaglobulinemia) are associated with immune deterioration.\u003c/p\u003e\n\u003ch3\u003eSerum Albumin and Neutrophil-to-Lymphocyte Ratio (NLR)\u003c/h3\u003e\n\u003cp\u003eAn inverse correlation was found between serum albumin and NLR (r = \u0026minus;\u0026thinsp;0.354, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. This negative linear correlation is visually represented in Graph 2, suggesting that patients with higher levels of systemic inflammation tend to have lower serum albumin. This relationship may be explained by inflammation-induced hepatic suppression of albumin synthesis and increased vascular permeability.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCD4\u0026thinsp;+\u0026thinsp;Count and Absolute Lymphocyte Count (ALC)\u003c/h2\u003e\u003cp\u003eA strong positive correlation was observed between CD4\u0026thinsp;+\u0026thinsp;count and ALC (r\u0026thinsp;=\u0026thinsp;0.634, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This is expected, as CD4\u0026thinsp;+\u0026thinsp;cells are a subset of lymphocytes. ALC may therefore serve as a cost-effective adjunct for assessing immune status in low-resource settings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eCD4\u0026thinsp;+\u0026thinsp;Count and Absolute Neutrophil Count (ANC)\u003c/h2\u003e\u003cp\u003eNo statistically significant correlation was seen between CD4\u0026thinsp;+\u0026thinsp;count and ANC (r = \u0026minus;\u0026thinsp;0.037, p\u0026thinsp;=\u0026thinsp;0.705), indicating that neutrophil levels are not a reliable indicator of immune suppression in the context of HIV infection.\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, CD4\u0026thinsp;+\u0026thinsp;count was positively correlated with serum albumin and ALC, and negatively correlated with NLR and ANC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSerum Albumin and Opportunistic Infections\u003c/h2\u003e\u003cp\u003eParticipants with opportunistic infections (OIs) had significantly lower serum albumin levels (3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 g/dL) compared to those without OIs (4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 g/dL), with a highly significant p-value (\u0026lt;\u0026thinsp;0.001). Paired t-test analysis revealed significant differences in serum albumin levels between patients with and without opportunistic infections, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. This suggests that hypoalbuminemia is strongly associated with increased susceptibility to OIs, highlighting its potential as a prognostic marker.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLogistic Regression Analysis\u003c/h2\u003e\u003cp\u003eA binary logistic regression analysis demonstrated that for every 1 g/dL increase in serum albumin, the odds of having an opportunistic infection decreased by approximately 70% (Odds Ratio\u0026thinsp;=\u0026thinsp;0.30; 95% CI: 0.17\u0026ndash;0.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. This relationship is visually represented in the logistic regression curve Graph 3. This reinforces the utility of serum albumin as an independent predictor of clinical outcomes in HIV-positive patients.\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\u003eMean mode and median of Albumin, ANC, ALC, A:G ratio, CD4 and NLR\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAlbumin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eANC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eALC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eA:G RATIO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eCD4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eValid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.7974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.0738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.1131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e242.2991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.6546\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.8000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.1400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.3600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e149.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.9000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eMode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e96.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e\u003cp\u003ea. Multiple modes exist. The smallest value is shown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\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\u003eCorrelation of CD4 with Albumin\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eALBUMIN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCD4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eALBUMIN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.296\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eCD4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.296\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\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\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eGraph 1 Scatter plot showing positive linear relationship between albumin and CD4\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation of CD4 RATIO with NLR\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCD4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eCD4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.354\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eNLR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.354\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\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\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eGraph 2: Scatter plot showing negative linear relationship between NLR and CD4\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePearson\u0026rsquo;s Correlations amongst various parameters\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eANC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eA:G RATIO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCD4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eANC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eALC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.269\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.634\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eA:G RATIO\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.269\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.437\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.005\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\u003cp\u003e\u003cb\u003e.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eCD4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.634\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.437\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\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=\"c2\"\u003e\u003cp\u003eSig. (2-tailed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107\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\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePaired t test for presence or absence of Opportunistic Infections\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\u003eOpportunistic infection\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\u003eMean Albumin (g/dL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStd. Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et value\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\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e-4.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.68\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\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLogistic Regression of Opportunistic Infectionsand albumin\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoefficient (β)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOdds Ratio (OR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI for OR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e3.67\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlbumin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e\u0026minus;1.19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.30\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e[0.17\u0026ndash;0.56]\u003c/b\u003e\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\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eGraph 3: Logistic Regression of Opportunistic Infections and albumin\u003c/h2\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study evaluated the role of serum albumin as a surrogate marker of immunosuppression in HIV-positive individuals by analyzing its relationship with CD4\u0026thinsp;+\u0026thinsp;count, systemic inflammatory markers, and opportunistic infections. Our findings demonstrate that serum albumin is positively associated with CD4\u0026thinsp;+\u0026thinsp;T-cell counts and inversely related to markers of inflammation such as NLR, as well as the incidence of opportunistic infections. These results reinforce the potential of serum albumin as a low-cost, reliable, and accessible biomarker for assessing immune status, particularly in resource-limited settings\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn our study population, the majority were male and middle-aged, a trend also observed in studies by Mehta et al.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e and Shah et al.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, where HIV predominantly affected adult males in the fourth and fifth decades of life. These demographic similarities enhance the external validity of our findings and reflect typical patterns seen in national registries.\u003c/p\u003e\u003cp\u003eWe found a statistically significant positive correlation between serum albumin and CD4\u0026thinsp;+\u0026thinsp;count, which is consistent with results reported by Olawumi and Olatunji\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, who showed that lower serum albumin levels were strongly associated with advanced HIV disease stages. Similarly, Sudfeld et al.\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e concluded that hypoalbuminemia at ART initiation predicted poor CD4\u0026thinsp;+\u0026thinsp;recovery and increased mortality. Mehta et al.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003efurther demonstrated that albumin levels, when combined with CD4\u0026thinsp;+\u0026thinsp;and viral load, served as independent predictors of clinical progression.\u003c/p\u003e\u003cp\u003eOur study also found that patients with opportunistic infections had significantly lower serum albumin levels compared to those without. This association aligns with multiple studies which have highlighted hypoalbuminemia as a marker of increased risk for opportunistic diseases, particularly tuberculosis and fungal infections\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Logistic regression analysis in our study revealed that each 1 g/dL increase in serum albumin was associated with a 70% reduction in the odds of developing an opportunistic infection, reinforcing its prognostic significance.\u003c/p\u003e\u003cp\u003eThe albumin-to-globulin (A:G) ratio, another nutritional and immunological parameter, also showed a strong positive correlation with CD4\u0026thinsp;+\u0026thinsp;count in our cohort. This supports the observations made by Ball et al.\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, who suggested that chronic immune activation in HIV leads to polyclonal hyperglobulinemia, thereby reducing the A:G ratio. A low A:G ratio, thus, may indirectly indicate progressive immunosuppression.\u003c/p\u003e\u003cp\u003eAn inverse relationship between serum albumin and the neutrophil-to-lymphocyte ratio (NLR) was also observed, echoing findings from recent studies by Madzime et al.\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e and Raffetti et al.\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, which identified elevated NLR as a predictor of immune decline, virological failure, and mortality in HIV-infected patients. Elevated NLR may reflect ongoing systemic inflammation, a major driver of immune exhaustion and disease progression in untreated or poorly controlled HIV infection.\u003c/p\u003e\u003cp\u003eWe also observed a strong positive correlation between absolute lymphocyte count (ALC) and CD4\u0026thinsp;+\u0026thinsp;count, further validating previous studies which suggested that ALC may serve as a practical alternative to CD4 testing where the latter is unavailable\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In contrast, absolute neutrophil count (ANC) showed no significant relationship with CD4\u0026thinsp;+\u0026thinsp;levels, indicating limited utility as an immune marker in this context.\u003c/p\u003e\u003cp\u003eWhile CD4\u0026thinsp;+\u0026thinsp;count remains the gold standard for assessing immune function in HIV patients, our findings suggest that serum albumin, in conjunction with simple markers like NLR and ALC, may serve as effective adjuncts or alternatives for risk stratification in low-resource environments. Albumin testing is already widely incorporated in routine clinical chemistry panels, making its integration into HIV care both feasible and cost-effective.\u003c/p\u003e\u003cp\u003eThat said, our study is not without limitations. Being cross-sectional, it does not allow causal inferences or longitudinal assessment of disease progression. Variables such as ART adherence, liver function, nutritional intake, and comorbid conditions\u0026mdash;which may influence serum albumin\u0026mdash;were not uniformly controlled. Despite this, the consistency of correlations with CD4\u0026thinsp;+\u0026thinsp;count, inflammatory indices, and opportunistic infections provides strong support for albumin\u0026rsquo;s clinical relevance.\u003c/p\u003e\u003cp\u003eIn summary, this study builds upon previous literature by demonstrating that serum albumin is not only a reflection of nutritional status but also a reliable surrogate marker of immune suppression and predictor of opportunistic infections in HIV/AIDS patients. These results advocate for the broader use of serum albumin in HIV disease monitoring, especially in healthcare settings where advanced immunological testing may not be routinely available.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study highlights a strong association between low serum albumin levels and immune suppression in HIV/AIDS patients, particularly those with opportunistic infections. A consistent positive correlation with CD4\u0026thinsp;+\u0026thinsp;count and an inverse relationship with NLR emphasize the role of albumin as a dual indicator of both nutritional and immunological status.Routine albumin monitoring can provide critical insights in resource-limited settings where CD4 or viral load testing is unavailable. The findings advocate for incorporating serum albumin into standard HIV assessment protocols to enable early risk stratification, infection surveillance, and timely intervention.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFull Form\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHIV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHuman Immunodeficiency Virus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAIDS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcquired Immunodeficiency Syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLHIV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePeople Living with HIV\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eART\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAntiretroviral Therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCD4\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCluster of Differentiation 4\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeutrophil-to-Lymphocyte Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eA:G ratio\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlbumin-to-Globulin Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eALC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAbsolute Lymphocyte Count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eANC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAbsolute Neutrophil Count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOpportunistic Infection\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorld Health Organization\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eEthical Committee Approval-\u003c/b\u003e This study was approved by the Institutional Ethics Committee 2 of Kasturba Medical College and Kasturba Hospital, which is registered under the Central Drugs Standard Control Organisation (CDSCO) and the Department of Health Research (DHR), ICMR. The committee operates in compliance with the ICMR 2017 guidelines for biomedical and health research involving human participants, the Medical Device Rules 2017, the New Drugs and Clinical Trials (NDCT) Rules 2019, and the Declaration of Helsinki (1964) and its later amendments. IEC Number- IEC2: 237/2023\u003c/p\u003e\u003cp\u003e\u003cb\u003eConsent-\u003c/b\u003e Written informed consent was taken from all study subjects.\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interest-\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding-\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eV.G. (Viraj Govindani) conceived and designed the study, collected data, performed data analysis, and drafted the manuscript. M.H. (Manjunath Hande) supervised the study, contributed to data interpretation, and critically revised the manuscript. Both authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements-\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request, but are not publicly available in order to maintain the privacy and confidentiality of the patients involved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFauci AS, Pantaleo G, Stanley S, Weissman D. Immunopathogenic mechanisms of HIV infection. Ann Intern Med. 1996;124(7):654\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eNational AIDS Control Organization, India HIVE. Technical Brief. Ministry of Health and Family Welfare, Government of India; 2023.\u003c/li\u003e\n\u003cli\u003eSudfeld CR, Isanaka S, Aboud S, et al. Serum albumin concentration and HIV-related outcomes. J Infect Dis. 2013;207:1370\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eWHO. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2016.\u003c/li\u003e\n\u003cli\u003eRothschild MA, Oratz M, Schreiber SS. Serum albumin. Hepatology. 1988;8(2):385\u0026ndash;401.\u003c/li\u003e\n\u003cli\u003eOlawumi HO, Olatunji PO. The value of serum albumin in pretreatment assessment and monitoring of therapy in HIV/AIDS patients. HIV Med. 2006;7(6):351\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eMehta SH, Astemborski J, Sterling TR, et al. Serum albumin as a prognostic indicator for HIV disease progression. AIDS Res Hum Retroviruses. 2006;22(1):14\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eBall SG. The chemical pathology of AIDS. Ann Clin Biochem. 1994;31:401\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eKearney A. Serum albumin as a predictor of immune function in HIV/AIDS patients. Clin Infect Dis. 2018;66(12):1945\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eGupta T, Prakash J. Albumin as a surrogate biomarker of HIV-associated immune suppression. Int J Med Sci. 2022;19(3):151\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eMehta SH, Astemborski J, Sterling TR, et al. Serum albumin as a prognostic indicator for HIV disease progression. AIDS Res Hum Retroviruses. 2006;22(1):14\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eShah S, Smith CJ, Lampe F, et al. Haemoglobin and albumin as markers of HIV disease progression in the HAART era. HIV Med. 2007;8(1):38\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eOlawumi HO, Olatunji PO. The value of serum albumin in pretreatment assessment and monitoring of therapy in HIV/AIDS patients. HIV Med. 2006;7(6):351\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eSudfeld CR, Isanaka S, Aboud S, et al. Serum albumin concentration and HIV-related outcomes. J Infect Dis. 2013;207:1370\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eEzugwu UM, Igbokwe GE, Okoye OJ, et al. Hypoalbuminemia and opportunistic infections in HIV patients: a retrospective review. Afr Health Sci. 2020;20(2):888\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eBall SG. The chemical pathology of AIDS. Ann Clin Biochem. 1994;31:401\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eMadzime M, Rossouw TM, Theron AJ, et al. Interactions of HIV and ART with neutrophils and inflammation markers. Front Immunol. 2021;12:634386.\u003c/li\u003e\n\u003cli\u003eRaffetti E, Donato F, Pezzoli C, et al. Systemic inflammation-based biomarkers and survival in HIV-positive subjects with solid cancer. J Acquir Immune Defic Syndr. 2015;69(5):585\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eKalyani R, Dutta A, Venkatesh S. Absolute lymphocyte count as a predictor of CD4 count in HIV patients. J Clin Diagn Res. 2014;8(9):FC11\u0026ndash;13.\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, CD4 Count, Serum Albumin, Immunosuppression, Opportunistic Infections, Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7264509/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7264509/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\u003eMonitoring of immunosuppression in HIV patients is essential, especially in resource-limited settings. CD4 + T-cell count, though standard, is costly and technically demanding. Serum albumin, an inexpensive and routinely measured parameter, may reflect immunosuppressive status. This study evaluates the correlation between serum albumin and CD4 + count and its relationship with markers of inflammation and opportunistic infections in HIV/AIDS patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis observational cross-sectional study was conducted at Kasturba Hospital, Manipal, between June 2023 and April 2025. A total of 107 adult patients diagnosed with HIV were enrolled. Comprehensive demographic, clinical, and laboratory data were collected. Pearson correlation analysis was performed to examine the association between CD4 + T-cell counts and serum albumin levels, absolute lymphocyte count (ALC), albumin-to-globulin (A:G) ratio, and neutrophil-to-lymphocyte ratio (NLR). Additionally, Independent sample t-tests were applied to compare serum albumin levels between patients with and without opportunistic infections. Subsequently, Logistic regression analysis was used for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCD4 count showed a positive correlation with serum albumin (r = 0.296, p = 0.002), A:G ratio (r = 0.437, p \u0026lt; 0.001), and ALC (r = 0.634, p \u0026lt; 0.001), and a negative correlation with NLR (r = − 0.354, p \u0026lt; 0.001). Albumin levels were significantly lower in patients with opportunistic infections (3.48 ± 0.64 g/dL) compared to those without (4.01 ± 0.68 g/dL; p \u0026lt; 0.001). Logistic regression indicated that each 1 g/dL rise in serum albumin reduced the odds of opportunistic infections by 70% (OR = 0.30; 95% CI: 0.17–0.56; p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum albumin demonstrates a strong positive association with CD4 + counts and an inverse relationship with systemic inflammation and opportunistic infections. Its ease of measurement, cost-effectiveness, and wide availability position it as a valuable surrogate marker for assessing immunosuppression in HIV/AIDS patients, especially in settings with limited access to advanced diagnostics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegistered prospectively with the Clinical Trials Registry - India (CTRI) on 03 July 2023 (CTRI/2023/07/054614).\u003c/p\u003e","manuscriptTitle":"Serum Albumin Level Compared to CD4+ Count as a Marker of Immunosuppression in HIV/AIDS Patients: An Observational Cross- Sectional Study from South India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 11:01:30","doi":"10.21203/rs.3.rs-7264509/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":"fecdc556-b3e3-44e1-879f-82b5d3fc712b","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T07:42:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 11:01:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7264509","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7264509","identity":"rs-7264509","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}