Does CRP to Albumin Ratio potentially predict success or failure of DAIR and chronicity of infection?

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Stephen Graham, Calvin Chandler, Kayla Hietpas, Madeline Rieker, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8099428/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Introduction: Periprosthetic joint infection (PJI) is a serious complication of joint replacement, with limited consensus on optimal treatment, especially in early infections. Debridement, antibiotics, and implant retention (DAIR) is often used, but determining the true duration of symptoms—and thus infection chronicity—can be challenging. CRP levels rise in both early and chronic infections, while albumin levels decline more gradually due to increased vascular permeability in chronic cases. The CRP-to-albumin ratio may serve as a useful marker of infection chronicity, potentially aiding in treatment decisions between DAIR and more aggressive options used for chronic infections. Methods: A retrospective longitudinal study was conducted on 35 consecutive patients, reviewing hospital admission CRP and albumin levels, along with patient-reported symptom onset. The study assessed the correlation between these variables and 1-year clinical outcomes following the DAIR procedure. In addition, CRP-to-albumin ratios were analyzed in a separate group of patients with chronic infections undergoing resection arthroplasty to identify potential similarities between these treatment groups. Results: Twenty-seven patients were classified as acute infection (0–28 days of symptoms), and 8 patients were classified as having chronic infection (≥29 days). An additional 39 patients with symptoms >3 months who underwent resection arthroplasty were included for comparison. Median CRP/albumin ratios were 5.8 (CRP 20.8 mg/L, albumin 3.4 g/dL) in the acute group, 0.8 (CRP 2.4 mg/L, albumin 3.8 g/dL) in the chronic group, and 5.6 (CRP 23.3 mg/L, albumin 3.8 g/dL) in the resection group. Conclusions: The use of CRP-to-albumin ratio to predict acute versus chronic infection of total joint arthroplasty does not appear to provide any substantial insights for the surgeon providing care. Additional studies are needed to help provide direction in patient management of these difficult complications. INTRODUCTION: Periprosthetic joint infection (PJI) remains one of the most serious and challenging complications following total joint arthroplasty (TJA) [ 1 – 2 ]. These infections carry significant morbidity for patients and often require complex, prolonged treatments with uncertain outcomes. Among the most debated aspects of PJI management is the optimal approach to early infections, typically defined as those occurring within the first few weeks of symptom onset. While debridement, antibiotics, and implant retention (DAIR) is widely advocated for early PJIs, determining whether an infection is truly acute or has progressed to a chronic phase is often difficult due to the ambiguous nature of symptom duration. The distinction between acute and chronic PJI relies on patient-reported symptom duration, and patients often struggle to accurately pinpoint when their symptoms began, especially if the onset is insidious or they attribute early signs to normal postoperative recovery [ 3 – 4 ]. The stakes of misclassifying infection chronicity are substantial because the distinction between acute and chronic infection influences the likelihood of DAIR success. DAIR procedures have markedly different success rates depending on infection timing, with acute infections showing success rates of 55–90% compared to chronic infections where success drops significantly [ 4 ]. Chronic infections are generally associated with poorer outcomes and may necessitate more aggressive and morbid interventions such as one- or two-stage revision arthroplasty. Laboratory markers such as C-reactive protein (CRP) and serum albumin may offer valuable insights into the inflammatory and nutritional status of patients with PJI [ 5 – 7 ]. CRP, a well-established acute-phase reactant, is frequently elevated in both early and chronic infections. In contrast, albumin, a marker of nutritional status and chronic inflammation, responds more slowly to acute changes and may not accurately reflect the temporal evolution of infection [ 6 ]. Albumin levels tend to decline more slowly, as chronic infections increase vascular permeability and cause albumin to leak into surrounding soft tissues [ 8 – 9 ]. The CRP-to-albumin ratio (CAR) has emerged as a potential surrogate marker for infection chronicity and may offer a more nuanced assessment of disease severity [ 7 , 10 – 11 ]. By combining these two markers, CAR theoretically accounts for both the acute inflammatory response (via CRP) and the chronic systemic effects of infection (via albumin depletion), potentially providing superior discriminatory power compared to either marker alone [ 8 , 9 ]. Although originally explored as a prognostic indicator in various medical conditions, including sepsis, acute kidney injury, and critical illness, recent studies have begun to investigate its role in diagnosing and staging PJI [ 12 – 14 ]. While some research has shown that CAR may not reliably predict outcomes following two-stage revisions [ 15 ], other evidence suggests it could help identify patients more likely to benefit from DAIR by estimating the chronicity of the infection. [ 11 ] Given the critical importance of appropriate treatment selection for PJI, there is a growing need for practical tools that support early and accurate clinical decision-making. By providing a potential biomarker for infection staging, CAR may help orthopedic surgeons tailor interventions more precisely and improve patient outcomes. This study explores the utility of CAR in evaluating infection chronicity in acute PJI cases and assesses its potential role in guiding the decision to pursue DAIR versus more definitive surgical options. METHODS Study Design A retrospective longitudinal study was conducted at the OrthoCarolina Hip & Knee Center to evaluate the correlation between CAR and the chronicity of PJI, as well as its potential utility in predicting the outcome of DAIR procedures. The study analyzed data from 74 patients who underwent DAIR for presumed acute PJI between 2015 and 2022. A comparison cohort of patients undergoing resection arthroplasty for chronic infections was also evaluated for CAR patterns. Patient Selection and Eligibility Criteria Patients eligible for inclusion in the acute PJI group were adults aged 18 years or older who had undergone a DAIR procedure for acute infection following total joint arthroplasty. Eligible patients were also required to have preoperative CRP and albumin levels obtained within one week prior to surgery, as well as a minimum of one year of postoperative clinical follow-up. Patients were excluded if they had a prior history of PJI in the same or another joint, were immunocompromised (including those with inflammatory arthritis), had cognitive impairments such as dementia that limited their ability to accurately report symptom onset, or had atypical or fungal infections. Additionally, patients with incomplete or missing laboratory data were excluded from the analysis. A separate comparison cohort was included, consisting of adults (≥18 years) who underwent two-stage revision arthroplasty for chronic PJI, defined by symptom duration longer than three months. While this group did not follow the same eligibility criteria as the acute PJI group, inclusion still required CRP and albumin levels, and atypical or fungal infections were excluded. Declarations This study received ethics approval by a local institutional review board: Wake Forest University IRB, in accordance with the Declaration of Helsinki. Human Ethics and Consent to Participate declarations: not applicable. This study includes retrospectively collected data (from hospital and clinic medical records) for those eligible patients who have been compliant with their routine follow-up of 2 years. Therefore, a waiver of consent and a full waiver of authorization was used for this group. No external funding was received for this study. Data Collection and Management Patient demographic and clinical data were extracted from electronic medical records and entered into REDCap ( http://project-redcap.org/ ), a secure web-based platform for data management. Variables included: medical record number, name, date of birth, sex, surgical laterality, height, weight, BMI (calculated), procedure type, date of surgery, surgeon, CRP and albumin levels, patient-reported symptom duration, return to operating room, and culture results [16-17]. Follow-up assessments occurred at standard postoperative intervals, including clinical examination and radiographic evaluation. At each visit, signs of infection recurrence or failure were documented. CAR was calculated for each patient and correlated with symptom duration and 1-year clinical outcomes. Statistical Analysis Descriptive statistics including measures of central tendency, variability, frequencies and proportions were calculated. Normality testing was performed and it was determined that all continuous variables violated the assumptions of normality. Medians and interquartile ranges were used to describe the continuous variable. Categorical variables were summarized using frequencies and percentages. Group comparisons were performed using: Wilcoxon rank-sum test for non-normally distributed variables Chi-square or Fisher’s exact test for categorical variables All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC), with significance set at p < 0.05. RESULTS A total of 74 patients were included in the study, categorized into three groups based on symptom duration and treatment type: acute infection (n = 27), chronic infection (n = 8), and chronic infection treated with resection arthroplasty (n = 39) (Table 1). Table 1: Patient Demographics Group Variable 0-28 Days N = 27 29+ Days N = 8 Control Group N = 39 Overall N = 74 Age at Surgery, Median (IQR) 68 (57, 72) 68 (62, 73.5) 69.8 (63.5, 73) 68.9 (61.7, 72.9) BMI, Median (IQR) 29.6 (27.4, 34.8) 30 (26.6, 36.8) 32.8 (27.5, 37.4) 31 (27.4, 35.5) Sex Male 16 (59.3%) 4 (50.0%) 22 (56.4%) 42 (56.8%) Female 11 (40.7%) 4 (50.0%) 17 (43.6%) 32 (43.2%) Ethnicity Missing 0 (0%) 0 (0%) 39 (100.0%) 39 (52.7%) Not Hispanic or Latino 27 (100.0%) 7 (87.5%) 0 (0%) 34 (45.9%) Hispanic or Latino 0 (0%) 1 (12.5%) 0 (0%) 1 (1.4%) Race Missing 0 (0%) 0 (0%) 39 (100.0%) 39 (52.7%) White 24 (88.9%) 8 (100.0%) 0 (0%) 32 (43.2%) Black, African American 3 (11.1%) 0 (0%) 0 (0%) 3 (4.1%) CRP and Albumin Levels by Group In the acute infection group (0–28 days of symptoms), the median CRP level at admission was 20.8 mg/L, with a median albumin level of 3.4 g/dL, resulting in a median CAR of 5.8 . In the chronic infection group (≥29 days), the median CRP level was markedly lower at 2.4 mg/L, while the median albumin level was slightly higher at 3.8 g/dL. The corresponding median CAR was 0.8 , significantly lower than that of the acute group. In the resection arthroplasty group—comprised of patients with symptom durations exceeding 3 months—the median CRP was 23.3 mg/L and median albumin was 3.8 g/dL, producing a median CAR of 5.6 . These values were similar to those observed in the acute infection group. These results are shown in Table 2. Table 2: Outcome Variables Group Variable Acute Group (0-28 Days) N = 30 Chronic Group (29+ Days) N = 9 Resection Group N = 39 Overall N = 78 ESR, Median (IQR) 58 (35, 86) 62 (45.5, 85) 43 (27, 70) 50 (28, 73) CRP, Median (IQR) 20.8 (4.8, 30) 2.4 (1, 7.1) 23.3 (10, 45) 20.3 (6, 35) Albumin, Median (IQR) 3.4 (2.9, 4.1) 3.8 (2.9, 4) 3.8 (3.3, 4.3) 3.6 (3.1, 4.1) CRP/Albumin Ratio, Median (IQR) 5.8 (1.6, 8.3) 0.8 (0.2, 2.4) 5.6 (2.9, 11.7) 5.6 (2, 11.3) Return to OR Missing 5 (16.7%) 0 (0%) 39 (100.0%) 44 (56.4%) No 14 (46.7%) 5 (55.6%) 0 (0%) 19 (24.4%) Yes 11 (36.7%) 4 (44.4%) 0 (0%) 15 (19.2%) DISCUSSION AND CONCLUSION This study aimed to evaluate the potential utility of CAR as a surrogate marker for infection chronicity in patients undergoing surgical treatment for PJI. Although we hypothesized that this ratio could help differentiate between acute and chronic infections and potentially predict the success of DAIR procedures, our findings suggest that the CAR has limited clinical value in guiding surgical decision-making. While numerical differences in CAR were observed across groups, with elevated values in both acute PJI and resection arthroplasty cases and lower values in chronic infections, these patterns lacked the consistency and discriminatory power necessary to reliably correlate with infection chronicity. Interestingly, patients undergoing resection arthroplasty for long-standing infections often had ratios comparable to those with acute infections. This finding challenges the assumption that higher CAR are uniquely indicative of early-stage or acute infection, even keeping in mind that the resection arthroplasty group did not have the same eligibility criteria as the other groups. Biological mechanisms may contribute to this unexpected pattern; chronic biofilm infections can undergo periods of reactivation where dormant bacteria are released from the biofilm matrix, triggering acute inflammatory responses. The ability of biofilm communities to alternate between dormant and active phases means that CAR may be measuring inflammatory activity from episodic biofilm dispersal rather than true infection chronicity, potentially limiting its utility as a staging tool [25]. The variability in CAR observed across groups likely reflects multiple confounding factors, including individual differences in inflammatory response, nutritional status, and the timing of laboratory data collection. The lack of standardized timing for laboratory collection relative to symptom onset or surgical intervention could significantly impact CAR interpretation, as CRP and albumin levels can fluctuate rapidly in response to treatment [5,15]. These limitations underscore the challenge of relying on a single biomarker to distinguish between acute and chronic PJI. Additional study limitations include the small sample sizes, which limits statistical power and generalizability, and the retrospective design potentially introducing biases in data quality and patient selection for different treatment modalities. Given the inherent complexity of diagnosing and managing PJI, particularly when symptom onset is unclear or patient-reported data is incomplete, there remains an unmet need for more reliable diagnostic markers or composite clinical tools. Previous studies have demonstrated potential in alternative biomarkers, including lymphocyte-based indices and other inflammatory parameters [18–24]. Although biomarkers such as CRP, ESR, and newer ratios like CAR and CLR show promise in diagnosing PJI, their reliability is limited by factors such as underlying health conditions, recent surgeries, and nutritional status [18-21]. These markers also lack the ability to clearly define the duration of infection, making them insufficient on their own for guiding treatment decisions [19, 21, 22]. Combining biomarkers with clinical findings, microbiological data, and imaging is likely a more effective strategy for accurate diagnosis and management [18, 19, 23]. Future research should explore integrative approaches that combine laboratory values, microbiological data, imaging findings, and advanced analytics, such as machine learning, to more accurately characterize infection chronicity and predict treatment outcomes. Given the limitations of CAR demonstrated in this study, prospective validation studies are needed to evaluate multi-parameter approaches that account for the complex pathophysiology of biofilm-mediated infections. Additionally, conducting cost-effectiveness analyses of biomarker-guided treatment strategies is important to assess whether these approaches provide sufficient clinical benefit relative to their costs. Such evaluations would inform healthcare providers on the practical value of incorporating these diagnostic tools into routine clinical care. In conclusion, while the CAR may offer some insight into systemic inflammation, our data suggest it is not a reliable standalone indicator of infection chronicity or a differentiator in treatment algorithms in PJI. Further prospective, large-scale studies are warranted to identify more effective markers or multifactorial models that can better inform clinical decision-making in this complex and high-risk patient population. Abbreviations Periprosthetic joint infection (PJI) Debridement, antibiotics, and implant retention (DAIR) C-reactive protein (CRP) CRP-to-albumin ratio (CAR) Total joint arthroplasty (TJA) Erythrocyte sedimentation rate (ESR) Body mass index (BMI) Operating room (OR) Institutional review board (IRB) Interquartile range (IQR) Statistical Analysis System software (SAS). Declarations Ethics approval and consent to participate This study received ethics approval by a local institutional review board: Wake Forest University IRB, in accordance with the Declaration of Helsinki. Human Ethics and Consent to Participate declarations: not applicable. This study includes retrospectively collected data (from hospital and clinic medical records) for those eligible patients who have been compliant with their routine follow-up of 2 years. Therefore, a waiver of consent and a full waiver of authorization was used for this group. No external funding was received for this study. Consent for publication This manuscript contains no identifiable personal data, images, or information requiring individual patient consent. All data were collected retrospectively under an institutional review board–approved protocol with a waiver of consent. As such, broad consent for publication is not applicable, and the authors affirm that all ethical and regulatory requirements for the publication of de-identified clinical data have been met. Availability of data and materials The datasets generated and analyzed during the current study are not publicly available due to patient privacy and institutional restrictions but are available from the corresponding author on reasonable request. All data used in this study were de-identified in accordance with institutional review board requirements. Competing Interests Not applicable Funding Not applicable Authors' contributions Graham: Data curation, Methodology, Project administration, Writing – original draft, Writing – review & editing, Chandler: Conceptualization, Methodology, Hietpas: Data curation, Formal analysis, Methodology, Writing – review & editing, Rieker: Writing – original draft Writing – review & editing, Moorer: Data curation, Resources, Lauck: Writing – original draft Writing – review & editing, Curtin: Conceptualization, Investigation, Supervision, Writing – review & editing Acknowledgements Not applicable References Kurtz SM, Lau E, Watson H, Schmier JK, Parvizi J. Economic burden of periprosthetic joint infection in the United States. J Arthroplasty. 2012;27(8 Suppl):61–5.e1. 10.1016/j.arth.2012.02.022 . PMID: 22554729. Mahmud T, Lyons MC, Naudie DD, Macdonald SJ, McCalden RW. Assessing the gold standard: a review of 253 two-stage revisions for infected TKA. 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16:44:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":510422,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8099428/v1/662c768c-7f09-4409-ab45-02d88b9ebe74.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Does CRP to Albumin Ratio potentially predict success or failure of DAIR and chronicity of infection?","fulltext":[{"header":"INTRODUCTION:","content":"\u003cp\u003ePeriprosthetic joint infection (PJI) remains one of the most serious and challenging complications following total joint arthroplasty (TJA) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These infections carry significant morbidity for patients and often require complex, prolonged treatments with uncertain outcomes. Among the most debated aspects of PJI management is the optimal approach to early infections, typically defined as those occurring within the first few weeks of symptom onset. While debridement, antibiotics, and implant retention (DAIR) is widely advocated for early PJIs, determining whether an infection is truly acute or has progressed to a chronic phase is often difficult due to the ambiguous nature of symptom duration. The distinction between acute and chronic PJI relies on patient-reported symptom duration, and patients often struggle to accurately pinpoint when their symptoms began, especially if the onset is insidious or they attribute early signs to normal postoperative recovery [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe stakes of misclassifying infection chronicity are substantial because the distinction between acute and chronic infection influences the likelihood of DAIR success. DAIR procedures have markedly different success rates depending on infection timing, with acute infections showing success rates of 55\u0026ndash;90% compared to chronic infections where success drops significantly [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Chronic infections are generally associated with poorer outcomes and may necessitate more aggressive and morbid interventions such as one- or two-stage revision arthroplasty. Laboratory markers such as C-reactive protein (CRP) and serum albumin may offer valuable insights into the inflammatory and nutritional status of patients with PJI [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. CRP, a well-established acute-phase reactant, is frequently elevated in both early and chronic infections. In contrast, albumin, a marker of nutritional status and chronic inflammation, responds more slowly to acute changes and may not accurately reflect the temporal evolution of infection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Albumin levels tend to decline more slowly, as chronic infections increase vascular permeability and cause albumin to leak into surrounding soft tissues [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe CRP-to-albumin ratio (CAR) has emerged as a potential surrogate marker for infection chronicity and may offer a more nuanced assessment of disease severity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. By combining these two markers, CAR theoretically accounts for both the acute inflammatory response (via CRP) and the chronic systemic effects of infection (via albumin depletion), potentially providing superior discriminatory power compared to either marker alone [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although originally explored as a prognostic indicator in various medical conditions, including sepsis, acute kidney injury, and critical illness, recent studies have begun to investigate its role in diagnosing and staging PJI [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While some research has shown that CAR may not reliably predict outcomes following two-stage revisions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], other evidence suggests it could help identify patients more likely to benefit from DAIR by estimating the chronicity of the infection. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eGiven the critical importance of appropriate treatment selection for PJI, there is a growing need for practical tools that support early and accurate clinical decision-making. By providing a potential biomarker for infection staging, CAR may help orthopedic surgeons tailor interventions more precisely and improve patient outcomes. This study explores the utility of CAR in evaluating infection chronicity in acute PJI cases and assesses its potential role in guiding the decision to pursue DAIR versus more definitive surgical options.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective longitudinal study was conducted at the OrthoCarolina Hip \u0026amp; Knee Center to evaluate the correlation between CAR and the chronicity of PJI, as well as its potential utility in predicting the outcome of DAIR procedures. The study analyzed data from 74 patients who underwent DAIR for presumed acute PJI between 2015 and 2022. A comparison cohort of patients undergoing resection arthroplasty for chronic infections was also evaluated for CAR patterns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Selection and Eligibility Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients eligible for inclusion in the acute PJI group were adults aged 18 years or older who had undergone a DAIR procedure for acute infection following total joint arthroplasty. Eligible patients were also required to have preoperative CRP and albumin levels obtained within one week prior to surgery, as well as a minimum of one year of postoperative clinical follow-up. Patients were excluded if they had a prior history of PJI in the same or another joint, were immunocompromised (including those with inflammatory arthritis), had cognitive impairments such as dementia that limited their ability to accurately report symptom onset, or had atypical or fungal infections. Additionally, patients with incomplete or missing laboratory data were excluded from the analysis.\u003c/p\u003e\n\u003cp\u003eA separate comparison cohort was included, consisting of adults (≥18 years) who underwent two-stage revision arthroplasty for chronic PJI, defined by symptom duration longer than three months. While this group did not follow the same eligibility criteria as the acute PJI group, inclusion still required CRP and albumin levels, and atypical or fungal infections were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received ethics approval by a local institutional review board: Wake Forest University IRB, in accordance with the Declaration of Helsinki. Human Ethics and Consent to Participate declarations: not applicable. This study includes retrospectively collected data (from hospital and clinic medical records) for those eligible patients who have been compliant with their routine follow-up of 2 years. Therefore, a waiver of consent and a full waiver of authorization was used for this group. No external funding was received for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient demographic and clinical data were extracted from electronic medical records and entered into REDCap (\u003ca href=\"http://project-redcap.org/\" target=\"_new\"\u003ehttp://project-redcap.org/\u003c/a\u003e), a secure web-based platform for data management. Variables included: medical record number, name, date of birth, sex, surgical laterality, height, weight, BMI (calculated), procedure type, date of surgery, surgeon, CRP and albumin levels, patient-reported symptom duration, return to operating room, and culture results [16-17].\u003c/p\u003e\n\u003cp\u003eFollow-up assessments occurred at standard postoperative intervals, including clinical examination and radiographic evaluation. At each visit, signs of infection recurrence or failure were documented. CAR was calculated for each patient and correlated with symptom duration and 1-year clinical outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics including measures of central tendency, variability, frequencies and proportions were calculated. Normality testing was performed and it was determined that all continuous variables violated the assumptions of normality. Medians and interquartile ranges were used to describe the continuous variable. \u0026nbsp;Categorical variables were summarized using frequencies and percentages. Group comparisons were performed using:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eWilcoxon rank-sum test for non-normally distributed variables\u003c/li\u003e\n \u003cli\u003eChi-square or Fisher’s exact test for categorical variables\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u0026nbsp;All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC), with significance set at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 74 patients were included in the study, categorized into three groups based on symptom duration and treatment type: acute infection (n = 27), chronic infection (n = 8), and chronic infection treated with resection arthroplasty (n = 39) (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1: Patient Demographics\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"667\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0-28 Days\u003cbr\u003e\u0026nbsp;N = 27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29+ Days\u003cbr\u003e\u0026nbsp;N = 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eControl Group\u003cbr\u003e\u0026nbsp;N = 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOverall\u003cbr\u003e\u0026nbsp;N = 74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge at Surgery, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68 (57, 72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68 (62, 73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.8 (63.5, 73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.9 (61.7, 72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.6 (27.4, 34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (26.6, 36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.8 (27.5, 37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31 (27.4, 35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (59.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42 (56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (43.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Not Hispanic or Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Hispanic or Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Black, African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRP and Albumin Levels by Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the \u003cstrong\u003eacute infection\u003c/strong\u003e group (0\u0026ndash;28 days of symptoms), the median CRP level at admission was 20.8 mg/L, with a median albumin level of 3.4 g/dL, resulting in a median CAR of \u003cstrong\u003e5.8\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn the \u003cstrong\u003echronic infection\u003c/strong\u003e group (\u0026ge;29 days), the median CRP level was markedly lower at 2.4 mg/L, while the median albumin level was slightly higher at 3.8 g/dL. The corresponding median CAR was \u003cstrong\u003e0.8\u003c/strong\u003e, significantly lower than that of the acute group.\u003c/p\u003e\n\u003cp\u003eIn the \u003cstrong\u003eresection arthroplasty\u003c/strong\u003e group\u0026mdash;comprised of patients with symptom durations exceeding 3 months\u0026mdash;the median CRP was 23.3 mg/L and median albumin was 3.8 g/dL, producing a median CAR of \u003cstrong\u003e5.6\u003c/strong\u003e. These values were similar to those observed in the acute infection group.\u003c/p\u003e\n\u003cp\u003eThese results are shown in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Outcome Variables\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"625\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAcute Group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(0-28 Days)\u003cbr\u003e\u0026nbsp;N = 30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eChronic Group (29+ Days)\u003cbr\u003e\u0026nbsp;N = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eResection Group\u003cbr\u003e\u0026nbsp;N = 39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003cbr\u003e\u0026nbsp;N = 78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eESR, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e58 (35, 86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62 (45.5, 85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43 (27, 70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50 (28, 73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCRP, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.8 (4.8, 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.4 (1, 7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.3 (10, 45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.3 (6, 35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAlbumin, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.4 (2.9, 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.8 (2.9, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.8 (3.3, 4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.6 (3.1, 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCRP/Albumin Ratio, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.8 (1.6, 8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8 (0.2, 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.6 (2.9, 11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.6 (2, 11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eReturn to OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"DISCUSSION AND CONCLUSION","content":"\u003cp\u003eThis study aimed to evaluate the potential utility of CAR as a surrogate marker for infection chronicity in patients undergoing surgical treatment for PJI. Although we hypothesized that this ratio could help differentiate between acute and chronic infections and potentially predict the success of DAIR procedures, our findings suggest that the CAR has limited clinical value in guiding surgical decision-making.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile numerical differences in CAR were observed across groups, with elevated values in both acute PJI and resection arthroplasty cases and lower values in chronic infections, these patterns lacked the consistency and discriminatory power necessary to reliably correlate with infection chronicity. Interestingly, patients undergoing resection arthroplasty for long-standing infections often had ratios comparable to those with acute infections. This finding challenges the assumption that higher CAR are uniquely indicative of early-stage or acute infection, even keeping in mind that the resection arthroplasty group did not have the same eligibility criteria as the other groups. Biological mechanisms may contribute to this unexpected pattern; chronic biofilm infections can undergo periods of reactivation where dormant bacteria are released from the biofilm matrix, triggering acute inflammatory responses. The ability of biofilm communities to alternate between dormant and active phases means that CAR may be measuring inflammatory activity from episodic biofilm dispersal rather than true infection chronicity, potentially limiting its utility as a staging tool [25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe variability in CAR observed across groups likely reflects multiple confounding factors, including individual differences in inflammatory response, nutritional status, and the timing of laboratory data collection. The lack of standardized timing for laboratory collection relative to symptom onset or surgical intervention could significantly impact CAR interpretation, as CRP and albumin levels can fluctuate rapidly in response to treatment [5,15]. These limitations underscore the challenge of relying on a single biomarker to distinguish between acute and chronic PJI. Additional study limitations include the small sample sizes, which limits statistical power and generalizability, and the retrospective design potentially introducing biases in data quality and patient selection for different treatment modalities.\u003c/p\u003e\n\u003cp\u003eGiven the inherent complexity of diagnosing and managing PJI, particularly when symptom onset is unclear or patient-reported data is incomplete, there remains an unmet need for more reliable diagnostic markers or composite clinical tools. Previous studies have demonstrated potential in alternative biomarkers, including lymphocyte-based indices and other inflammatory parameters [18–24]. Although biomarkers such as CRP, ESR, and newer ratios like CAR and CLR show promise in diagnosing PJI, their reliability is limited by factors such as underlying health conditions, recent surgeries, and nutritional status [18-21]. These markers also lack the ability to clearly define the duration of infection, making them insufficient on their own for guiding treatment decisions [19, 21, 22]. Combining biomarkers with clinical findings, microbiological data, and imaging is likely a more effective strategy for accurate diagnosis and management [18, 19, 23]. Future research should explore integrative approaches that combine laboratory values, microbiological data, imaging findings, and advanced analytics, such as machine learning, to more accurately characterize infection chronicity and predict treatment outcomes. Given the limitations of CAR demonstrated in this study, prospective validation studies are needed to evaluate multi-parameter approaches that account for the complex pathophysiology of biofilm-mediated infections. \u0026nbsp;Additionally, conducting cost-effectiveness analyses of biomarker-guided treatment strategies is important to assess whether these approaches provide sufficient clinical benefit relative to their costs. Such evaluations would inform healthcare providers on the practical value of incorporating these diagnostic tools into routine clinical care.\u003c/p\u003e\n\u003cp\u003eIn conclusion, while the CAR may offer some insight into systemic inflammation, our data suggest it is not a reliable standalone indicator of infection chronicity or a differentiator in treatment algorithms in PJI. Further prospective, large-scale studies are warranted to identify more effective markers or multifactorial models that can better inform clinical decision-making in this complex and high-risk patient population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003ePeriprosthetic joint infection (PJI)\u003c/li\u003e\n \u003cli\u003eDebridement, antibiotics, and implant retention (DAIR)\u003c/li\u003e\n \u003cli\u003eC-reactive protein (CRP)\u003c/li\u003e\n \u003cli\u003eCRP-to-albumin ratio (CAR)\u003c/li\u003e\n \u003cli\u003eTotal joint arthroplasty (TJA)\u003c/li\u003e\n \u003cli\u003eErythrocyte sedimentation rate (ESR)\u003c/li\u003e\n \u003cli\u003eBody mass index (BMI)\u003c/li\u003e\n \u003cli\u003eOperating room (OR)\u003c/li\u003e\n \u003cli\u003eInstitutional review board (IRB)\u003c/li\u003e\n \u003cli\u003eInterquartile range (IQR)\u003c/li\u003e\n \u003cli\u003eStatistical Analysis System software (SAS).\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n \u003cli\u003eEthics approval and consent to participate\u003cul\u003e\n \u003cli\u003eThis study received ethics approval by a local institutional review board: Wake Forest University IRB, in accordance with the Declaration of Helsinki. Human Ethics and Consent to Participate declarations: not applicable. This study includes retrospectively collected data (from hospital and clinic medical records) for those eligible patients who have been compliant with their routine follow-up of 2 years. Therefore, a waiver of consent and a full waiver of authorization was used for this group. No external funding was received for this study.\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eConsent for publication\u003cul\u003e\n \u003cli\u003eThis manuscript contains no identifiable personal data, images, or information requiring individual patient consent. All data were collected retrospectively under an institutional review board\u0026ndash;approved protocol with a waiver of consent. As such, broad consent for publication is not applicable, and the authors affirm that all ethical and regulatory requirements for the publication of de-identified clinical data have been met.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eAvailability of data and materials\u003cul\u003e\n \u003cli\u003eThe datasets generated and analyzed during the current study are not publicly available due to patient privacy and institutional restrictions but are available from the corresponding author on reasonable request. All data used in this study were de-identified in accordance with institutional review board requirements.\u003cbr\u003e\u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eCompeting Interests\u003cul\u003e\n \u003cli\u003eNot applicable\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eFunding\u003cul\u003e\n \u003cli\u003eNot applicable\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eAuthors\u0026apos; contributions\u003cul\u003e\n \u003cli\u003eGraham: Data curation, Methodology, Project administration, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Chandler: Conceptualization, Methodology, Hietpas: Data curation, Formal analysis, Methodology, Writing \u0026ndash; review \u0026amp; editing, Rieker: Writing \u0026ndash; original draft\u0026nbsp;\u003cbr\u003e\u0026nbsp;Writing \u0026ndash; review \u0026amp; editing, Moorer: Data curation, Resources, Lauck: Writing \u0026ndash; original draft\u0026nbsp;\u003cbr\u003e\u0026nbsp;Writing \u0026ndash; review \u0026amp; editing, Curtin: Conceptualization, Investigation, Supervision, Writing \u0026ndash; review \u0026amp; editing\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eAcknowledgements\u003cul\u003e\n \u003cli\u003eNot applicable\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKurtz SM, Lau E, Watson H, Schmier JK, Parvizi J. 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PMID: 37557968.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCosterton JW, Stewart PS, Greenberg EP. Bacterial biofilms: a common cause of persistent infections. Science. 1999;284(5418):1318-22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.284.5418.1318\u003c/span\u003e\u003cspan address=\"10.1126/science.284.5418.1318\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 10334980.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8099428/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8099428/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Introduction: \nPeriprosthetic joint infection (PJI) is a serious complication of joint replacement, with limited consensus on optimal treatment, especially in early infections. Debridement, antibiotics, and implant retention (DAIR) is often used, but determining the true duration of symptoms—and thus infection chronicity—can be challenging. CRP levels rise in both early and chronic infections, while albumin levels decline more gradually due to increased vascular permeability in chronic cases. The CRP-to-albumin ratio may serve as a useful marker of infection chronicity, potentially aiding in treatment decisions between DAIR and more aggressive options used for chronic infections. \nMethods: \nA retrospective longitudinal study was conducted on 35 consecutive patients, reviewing hospital admission CRP and albumin levels, along with patient-reported symptom onset. The study assessed the correlation between these variables and 1-year clinical outcomes following the DAIR procedure. In addition, CRP-to-albumin ratios were analyzed in a separate group of patients with chronic infections undergoing resection arthroplasty to identify potential similarities between these treatment groups. \nResults: \nTwenty-seven patients were classified as acute infection (0–28 days of symptoms), and 8 patients were classified as having chronic infection (≥29 days). An additional 39 patients with symptoms \u003e3 months who underwent resection arthroplasty were included for comparison. Median CRP/albumin ratios were 5.8 (CRP 20.8 mg/L, albumin 3.4 g/dL) in the acute group, 0.8 (CRP 2.4 mg/L, albumin 3.8 g/dL) in the chronic group, and 5.6 (CRP 23.3 mg/L, albumin 3.8 g/dL) in the resection group. \nConclusions: \nThe use of CRP-to-albumin ratio to predict acute versus chronic infection of total joint arthroplasty does not appear to provide any substantial insights for the surgeon providing care. Additional studies are needed to help provide direction in patient management of these difficult complications. ","manuscriptTitle":"Does CRP to Albumin Ratio potentially predict success or failure of DAIR and chronicity of infection?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-25 10:37:10","doi":"10.21203/rs.3.rs-8099428/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-06T05:08:07+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"77609216777409995745291421392159831072","date":"2026-04-01T18:59:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T16:48:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183634012052888335897144906616510770389","date":"2026-02-28T15:59:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218940351100550083467063017829834449125","date":"2026-02-28T03:26:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-27T05:38:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109315819154792210260973763078440303688","date":"2026-02-27T03:00:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12151455265783891355673565506200495504","date":"2025-12-25T09:46:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-23T09:04:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-19T09:06:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-24T05:12:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-21T16:12:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2025-11-21T16:09:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4cfd5ae0-1017-4dea-9e37-866062a7bab3","owner":[],"postedDate":"December 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T09:25:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-25 10:37:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8099428","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8099428","identity":"rs-8099428","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}