Abstract
Purpose
-
Periprosthetic joint infection (PJI) is a serious complication after joint arthroplasty, resulting in high morbidity and mortality. The neutrophil-to-lymphocyte ratio (NLR) and albumin-to-globulin ratio (AGR) are novel diagnostic markers for PJI; however, their diagnostic value remains inconsistent.
Methods
-
This meta-analysis was conducted using the PubMed, Embase, and MEDLINE databases to determine the diagnostic accuracy of NLR and AGR for PJI in the knee or hip. Data extraction and quality assessment were independently completed by two reviewers. The pooled sensitivity and specificity, diagnostic odds ratio (DOR), summary receiver operating characteristic curve (sROC), and area under the sROC curve (AUC) were assessed using the univariate meta-analysis framework.
Results
-
Nineteen eligible studies were included in the quantitative analysis. The pooled sensitivity and specificity of NLR for the diagnosis of PJI were 0.73 (95% CI: 0.68–0.77) and 0.72 (95% CI: 0.66–0.77), respectively. Its pooled DOR was 6.89 (95% CI: 5.03–9.43), and AUC was 0.79 (95% CI: 0.75–0.82). The pooled sensitivity and specificity of AGR for the diagnosis of PJI were 0.80 (95% CI: 0.70–0.88) and 0.83 (95% CI: 0.79–0.87), respectively. Its DOR was 17.69 (95% CI: 10.76–29.07), and AUC was 0.88 (95% CI: 0.85–0.91).
Conclusion
-
NLR and AGR can be individually used as reliable serum biomarkers for the detection of PJI. Future research is warranted to determine the diagnostic value of these markers in combination with C-reactive protein levels and erythrocyte sedimentation rates to improve diagnostic accuracy for PJI in clinical practice.
Background
Arthroplasty is a common surgery for older patients with end-stage joint disease (1). Although the surgical techniques have considerably progressed recently, some undesirable complications may occasionally occur (2). Periprosthetic joint infection (PJI) is one of the most serious complications after knee or hip arthroplasty, resulting in high morbidity and mortality (3). The incidence of PJI is approximately 0.5–2% following total knee or hip replacement (4). The clinical presentation of PJI can be variable, with some patients exhibiting atypical symptoms or presenting with low-grade infections that are challenging to detect using conventional methods. This variability complicates the diagnostic process, leading to delays in treatment initiation or misdiagnosis (5). The creation of a diagnostic tool capable of effectively identifying PJI would significantly aid in overcoming the diagnostic challenges linked with this condition.
Many organizations, such as the MusculoSkeletal Infection Society (MSIS) (6), the American Academy of Orthopaedic Surgeons (7), and the European Bone and Joint Infection Society (EBJIS) (8), have proposed several criteria for the accurate diagnosis of PJI based on peripheral blood examination, imaging, and microbiological assessment (3). However, the current criteria are complicated, and their accuracy varies under different conditions. New potential diagnostic tools with reliable sensitivity and specificity for PJI may be warranted to facilitate early diagnosis and strengthen the accuracy of the current diagnostic criteria.
In recent years, serum biomarkers have played a crucial role in the diagnosis of PJI (6). Neutrophil-to-lymphocyte ratio (NLR) and albumin-to-globulin ratio (AGR) have been proposed to be novel diagnostic biomarkers for PJI (9, 10). They have higher sensitivity and specificity than other serum biomarkers. NLR is the ratio of the absolute neutrophil count to absolute lymphocyte count. It has been reported to be a highly accurate indicator of the systemic inflammatory burden (11). Gölge et al. first reported that NLR can be used as a biomarker for PJI by comparing preoperative and 6-month postoperative NLR values of patients (9). In recent years, increasing numbers of studies have proposed the diagnostic value of NLR, particularly for early PJI (12, 13, 14, 15, 16, 17).
In addition to NLR, AGR was first used as a prognostic index for patients with cancer (18); however, it can also serve as a biomarker for chronic infections (19). The serum contains two major proteins: albumin and globulin. Albumin, which accounts for 50% of the serum protein content, is usually used to reflect nutritional and inflammatory status (20, 21). Globulin, which accounts for approximately 48% of the serum protein content, is formed by the immune system and is associated with inflammation and infection (19). The normal AGR is approximately 1–2. A low AGR could indicate chronic infections (19).
Both NLR and AGR are easily accessible serum biomarkers in routine blood examinations and have the potential to assist in the diagnosis of early or low-grade PJI in combination with the current diagnostic criteria. However, the clinical value of NLR and AGR for diagnosing PJI remains unclear and is under investigation (17). Considering the heterogeneity of existing research and differences in data on the diagnostic accuracy of NLR and AGR for PJI, this systematic review and meta-analysis was conducted to assess published data and offer strong evidence regarding the diagnostic value of NLR and AGR for PJI.
Methods
Search strategy
The research procedures and statistical methods used in this study are consistent with the methodology specified in the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy (22). The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria (23). PubMed, Embase, MEDLINE, and Cochrane Library databases were searched for data published from their inception dates till February 2024. The search strategy included the following comprehensive set of keywords: (‘neutrophil to lymphocyte ratio,’ ‘neutrophil lymphocyte ratio,’ ‘neutrophil-to-lymphocyte ratio,’ ‘NL ratio,’ or ‘NLR’) or (‘albumin to globulin ratio,’ ‘albumin globulin ratio,’ ‘AG ratio,’ or ‘AGR’) and (‘periprosthetic infection’ or ‘periprosthetic joint infection’). No language restrictions were imposed, and reference lists of the included studies were screened. This study is registered with the International Prospective Register of Systematic Reviews.
Study selection
Studies in which i) participants underwent total hip arthroplasty (THA) or total knee arthroplasty (TKA), ii) complete preoperative NLR or AGR data were available, and iii) the diagnosis of PJI was confirmed according to the MSIS guideline (6), the International Consensus Meeting (ICM) definition (24), and the EBJIS (8) of PJI were included. The diagnosis of chronic PJI was defined by the MSIS guideline (6).
Studies in which i) neutrophil or lymphocyte counts were separately obtained instead of calculating the NLR, because the NLR could not be calculated based on the average neutrophil or lymphocyte counts in the ex-post analysis, ii) participants did not undergo revision arthroplasty, iii) preoperative NLR or AGR data were not available, and iv) participants had inflammatory diseases, such as rheumatoid arthritis, were excluded.
Data extraction and management
Two reviewers independently evaluated the retrieved studies. The data extracted from the individual studies included the first author’s last name, study inclusion period, year of publication, study location (country), participants’ demographic information, study design, site of arthroplasty, number of infected/total joints, preoperative NLR or AGR and cutoff values, diagnostic criteria, and the number of false/true positive and false/true negative cases.
The methodological quality of each study was also assessed and scored according to the Quality Assessment of Diagnostic Accuracy Studies, version 2 (QUADAS-2) (25). The QUADAS-2 tool has four sections: patient selection, index test, reference standard, and flow and timing. Review Manager 5.3 (Nordic Cochrane Centre, Copenhagen, Denmark) was used to process and present the assessment results.
Statistical analysis
A meta-analysis was performed to assess the collected data using Stata 15.1 software. The pooled sensitivity and specificity of the extracted data were calculated using the univariate meta-analysis framework. The diagnostic odds ratio (DOR) was calculated based on the pooled sensitivity and specificity. A univariate random-effects model was used. Moreover, the accuracy of the tests was assessed based on pooled summary receiver operating characteristic (sROC) curves and the area under the sROC curve (AUC). Heterogeneity among the included studies was assessed using the I 2 statistic test. A value of 0% indicated no heterogeneity, whereas a value greater than 50% indicated a high degree of heterogeneity. The subgroup analysis of chronic PJI was conducted for the heterogeneity. Deek’s funnel plot was used to visually assess possible publication bias. P < 0.05 indicated a statistically significant difference.
Results
Search results and study selection
PubMed, MEDLINE, and Embase databases were initially searched. After the removal of duplicate studies, 75 records were included for title and abstract screening. After the screening of the titles and abstracts, 39 articles met the preselection criteria. After the evaluation of the full texts, 19 articles were finally included in the quantitative analysis. Figure 1 depicts the selection process of the included studies.
PRISMA flowchart of the selection process.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Study characteristics
Nineteen studies involving a total of 4991 patients (1795 patients with PJIs) were included in this systematic review to determine the diagnostic accuracy of NLR and AGR. The site of PJI was reported in all studies, which involved patients with hip or knee PJIs. The average age of the patients was 60.7–70.5 years, and the proportion of male patients was 44.6–54.7%. The main characteristics of the included studies are summarized in Table 1.
Characteristics of included studies.
| Study | Study period | Study location | Study population | Condition | Mean age (years) | Study type | Arthro-plasty site | PJI type | Diagnostic criteria | Study parameter | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | M | F | ||||||||||
| Wu et al. (12) | 2001.01–2019.12 | China | 164 | 60 | 114 | TKA or THA | 67.03 | RCS | 49/125 | AC, CH | ICM 2018 | NLR, AGR |
| Ye et al. (15) | 2011.01–2020.07 | China | 158 | 56 | 102 | TKA or THA | 63.76 | RCS | 46/112 | CH | ICM 2018 | NLR, AGR |
| Ye et al. (10) | 2011.12–2018.11 | China | 127 | 56 | 71 | TKA or THA | 62.47 | RCS | 56/71 | CH | ICM 2018 | AGR |
| Maimaiti et al. (14) | 2017.01–2018.12 | China | 246 | 100 | 148 | TKA or THA | 62.01 | RCS | 99/147 | CH | ICM 2013 | NLR |
| Xu et al. (39) | 2008.01–2020.09 | China | 63 | 32 | 31 | TKA or THA | 63.36 | RCS | 12/51 | AC, CH | ICM 2013 | NLR |
| Jiao et al. (17) | 2017.01–2020.12 | China | 115 | 56 | 59 | TKA or THA | 68.46 | RCS | NR | CH | ICM 2018 | NLR, AGR |
| Wang et al. (16) | 2017.01–2019.12 | China | 221 | 133 | 88 | TKA or THA | 64.85 | RCS | 80/141 | AC, CH | ICM 2013 | NLR, AGR |
| Choe et al. (40) | 2013.01–2021.12 | Japan | 96 | 30 | 66 | THA | 70.53 | RCS | 0/96 | CH | ICM 2018 | NLR, AGR |
| Klemt et al. (13) | 2010–2016 | USA | 464 | 229 | 245 | THA | 65.2 | RCS | 0/464 | CH | ICM 2018 | NLR |
| Zhang et al. (41) | 2010.01–2020.01 | China | 241 | 98 | 143 | TKA or THA | 63.76 | RCS | 54/187 | AC, CH | ICM 2013 | AGR |
| Shang et al. (42) | 2013.08–2020.12 | China | 206 | 101 | 105 | TKA or THA | 69.19 | RCS | 117/110 | AC, CH | ICM 2018 | AGR |
| Tirumala et al. (43) | NA | USA | 538 | 268 | 270 | TKA | 66 | RCS | 538/0 | CH | ICM 2018 | NLR |
| Shi et al. (44) | 2013.06–2022.07 | China | 303 | 130 | 114 | TKA or THA | 65.13 | RCS | 117/157 | AC, CH | ICM 2018 | NLR |
| Balato et al. (45) | 2018.12–2020.06 | Italy | 261 | 94 | 167 | TKA | 68 | RCS | 261/0 | AC, CH | ICM 2013 | NLR |
| Balta et al. (46) | 2006.07–2020.12 | Turkey | 264 | 65 | 199 | TKA or THA | 65.88 | RCS | 144/120 | AC, CH | EBJIS 2021 | NLR |
| Li et al. (47) | 2016.01–2019.04 | China | 446 | 155 | 188 | TKA or THA | 60.76 | RCS | 206/309 | CH | ICM 2018 | NLR, AGR |
| Dilley et al. (48) | 2000.01–2021.12 | USA | 446 | 315 | 415 | TKA or THA | 62.43 | RCS | 485/245 | CH | ICM 2013 | NLR |
| Wang et al. (49) | 2016.01–2021.03 | China | 164 | 74 | 88 | TKA or THA | 65.62 | RCS | 54/108 | AC, CH | ICM 2013 | AGR |
AGR, albumin-to-globulin ratio; AC, acute; CH, chronic; MSIS, Musculoskeletal Infection Society; NLR, neutrophil-to-lymphocyte ratio; RCS, retrospective cohort study.
Results of quality assessment
Figure 2 presents the results of the included studies as assessed using the QUADAS-2 tool. The quality of the included studies was high, as the percentage of high risk was less than 25% in each key area.
Quality assessment of included studies using QUADAS-2 tool criteria (10, 12, 13, 14, 15, 16, 17, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50). Red in the figure indicates high risk, yellow represents unclear risk, and green means low risk. QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies, version 2.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Diagnostic value of NLR for PJI
As shown in Fig. 3, the pooled sensitivity and specificity of NLR for the diagnosis of PJI were 0.73 (95% CI: 0.68–0.77) and 0.72 (95% CI: 0.66–0.77), respectively. Its pooled DOR was 6.89 (95% CI: 5.03–9.43) (Fig. 4), and the AUC was 0.79 (95% CI: 0.75–0.82) (Fig. 5). The I 2 values for sensitivity and specificity were 74.85% (95% CI: 61.69–88.02) and 88.06% (95% CI: 82.96–93.16), respectively, indicating substantial heterogeneity of the included studies. Moreover, the Deek’s funnel plot asymmetry test (Supplementary Fig. 1, see section on supplementary materials given at the end of this article) yielded a value of 0.57, indicating the absence of publication bias.
Forest plots showing the sensitivities and specificities of NLR for the diagnosis of PJI with 95% CIs. The meta-analysis for NLR generated a pooled sensitivity of 73% (95% CI: 68–77) and a pooled specificity of 72% (95% CI: 66–77) (12, 13, 14, 15, 16, 17, 39, 40, 43, 44, 45, 46, 47, 48 ). NLR, neutrophil-to-lymphocyte ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
The sROC curve presenting the pooled sensitivity of 73% (95% CI: 68–77) and pooled specificity of 72% (95% CI: 66–77) of NLR for the diagnosis of PJI (12, 13, 14, 15, 16, 17, 39, 40, 43, 44, 45, 46, 47, 48). sROC, summary receiver operating characteristic curve; NLR, neutrophil-to-lymphocyte ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Diagnostic value of AGR for PJI
As shown in Fig. 6, the pooled sensitivity and specificity of AGR for the diagnosis of PJI were 0.80 (95% CI: 0.70–0.88) and 0.83 (95% CI: 0.79–0.87), respectively. Its pooled DOR was 17.69 (95% CI: 10.76–29.07) (Fig. 7) and AUC was 0.88 (95% CI: 0.85–0.91) (Fig. 8). The I 2 values for sensitivity and specificity were 83.07% (95% CI: 73.54–92.59) and 74.00% (95% CI: 57.65–90.35), respectively, indicating heterogeneity of the included studies. The Deek’s funnel plot asymmetry test performed to visually assess potential publication bias (Supplementary Fig. 2) yielded a value of 0.45, indicating the absence of publication bias.
Forest plots showing the sensitivities and specificities of AGR for the diagnosis of PJI with 95% CIs. The meta-analysis for AGR generated a pooled sensitivity of 0.80 (95% CI: 0.70–0.88) and a pooled specificity of 0.83 (95% CI: 0.79–0.87) (10, 12, 16, 17, 40, 41, 42, 47, 49, 50). AGR, albumin-to-globulin ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
The SROC curve presenting the pooled sensitivity of 0.80 (95% CI: 0.70–0.88) and pooled specificity of 0.83 (95% CI: 0.79–0.87) of AGR for the diagnosis of PJI (10, 12, 16, 17, 40, 41, 42, 47, 49, 50). sROC, summary receiver operating characteristic curve; AGR, albumin-to-globulin ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Figures 9 and 10 show the subgroup analysis of the studies that only included the chronic PJI. The pooled sensitivity and specificity of NLR for the diagnosis of chronic PJI were 0.77 (95% CI: 0.72–0.81) and 0.74 (95% CI: 0.66–0.81). The I2 value for sensitivity and specificity was 65.20% (95% CI: 37.03–93.37) and 91.56% (95% CI: 86.82–96.31), respectively. The pooled sensitivity and specificity of AGR for the diagnosis of chronic PJI were 0.83 (95% CI: 0.70–0.99) and 0.81 (95% CI: 0.76–0.86), respectively. The I2 value for sensitivity and specificity was 84.14% (95% CI: 69.51–98.76) and 50.26% (95% CI: 0.00–100.00).
Forest plots indicating the sensitivities and specificities of NLR for the diagnosis of chronic PJI with 95% CIs. The meta-analysis for NLR generated a pooled sensitivity of 0.77 (95% CI: 0.72–0.81) and a pooled specificity of 0.74 (95% CI: 0.66–0.81) (13, 14, 15, 17, 40, 43, 48). AGR, albumin-to-globulin ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Forest plots showing the sensitivities and specificities of AGR for the diagnosis of chronic PJI with 95% CIs. The meta-analysis for AGR generated a pooled sensitivity of 0.83 (95% CI: 0.70–0.99) and a pooled specificity of 0.81 (95% CI: 0.76–0.86) (10, 17, 40, 47). AGR, albumin-to-globulin ratio; PJI, periprosthetic joint infection.
Citation: EFORT Open Reviews 9, 12; 10.1530/EOR-23-0206
Discussion
In the 19 included studies, the pooled sensitivity of the NLR and AGR for the diagnosis of PJI was 0.73 (95% CI: 0.68–0.77) and 0.80 (95% CI: 0.69–0.88), respectively. Their pooled specificity was 0.72 (95% CI: 0.66–0.77) and 0.83 (95% CI: 0.79–0.87), respectively. Both the sensitivity and specificity of AGR were higher than those of NLR. Moreover, the AUC of AGR was higher than that of NLR (0.88 vs 0.79), indicating that AGR is a more reliable single marker than NLR for the diagnosis of PJI. Currently, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) are adapted as serum biomarkers in recent MSIS criteria (6). Compared with NLR and AGR, the sensitivity and specificity for the CRP were 0.82 and 0.77 (26), and the sensitivity and specificity of the ESR were 0.64 and 0.96 (15).
Although PJI is a rare complication after joint replacement, it is challenging for orthopedic surgeons because of its high morbidity and mortality (27). However, the early detection of PJI remains difficult (28). The MSIS criteria for PJI diagnosis have been widely accepted as the gold standard since 2013 (6); nevertheless, these criteria may not be suitable for the clinical diagnosis of acute PJIs because of their high threshold. The symptoms of patients with low-grade infections may resemble those of patients undergoing aseptic revision surgery. However, the medical strategies differ for these two types of patients (29, 30). Hence, a diagnostic test with higher sensitivity and specificity is necessary for detecting PJI. In contrast to the MSIS criteria, the EBJIS criteria have limited discussion of serum biomarkers, with only a CRP level >1 mg/dL used as a screening indicator for PJI. This suggests that the EBJIS standard may not fully incorporate the role of serum biomarkers in PJI diagnosis. Therefore, it may be necessary to comprehensively assess the value of other serum markers to enhance the accurate diagnosis of PJI. The CRP level and ESR are the two major serum biomarkers as per the MSIS 2018 guideline (6). However, the fair diagnostic value of CRP levels for the detection of acute postoperative PJI has been debatable (31). Moreover, the diagnostic power of ESR was found to be inferior to that of the CRP level, preventing the use of ESR as a reliable single marker for the diagnosis of PJI (32). In the current MSIS criteria, the diagnostic thresholds for CRP differ between acute and chronic PJI, with 1 mg/dL for chronic infections and 10 mg/dL for acute infections. While ESR is recommended for use in chronic PJI, there is still no consensus on its cutoff value for acute infections.
NLR, a ratio of absolute neutrophil to lymphocyte count, serves as a novel biomarker reflecting inflammatory burden and is linked to infectious diseases like bacteremia (33). Neutrophils, crucial in pathogen elimination, increase with infection, amplifying NLR and raising infection concerns (34). Conversely, AGR, with high specificity, reduces PJI misdiagnosis rates (16). Albumin levels, reflecting nutritional status, decline during inflammation, while globulin level increases (35). This inverse relationship mirrors inflammatory status. Despite comparable sensitivity and specificity to CRP, our study emphasizes NLR and AGR's diagnostic utility in acute and chronic PJI detection. These cost-effective, easily accessible biomarkers, either alone or combined with CRP, offer valuable insights in clinical practice.
NLR and AGR may not replace ESR and CRP but can complement these biomarkers to enhance diagnostic accuracy. Given the cost-effectiveness of NLR and AGR, incorporating them into the current diagnostic criteria for PJI is feasible. A study by Choe et al. (36) suggests that combining CRP with AGR could improve the accuracy of PJI diagnoses. However, there are few studies on integrating multiple serum biomarkers to enhance PJI diagnosis, likely due to the complexity of conducting large-scale studies evaluating multiple biomarkers simultaneously. Nevertheless, emerging evidence indicates that combining multiple biomarkers may offer a more comprehensive diagnostic approach, potentially enhancing the sensitivity and specificity of PJI diagnosis (37, 38). Further research is necessary to evaluate the actual impact of combining biomarkers on PJI diagnosis accuracy.
Our study has several strengths. First, the control groups of the included studies consisted of patients who underwent aseptic revision surgery. Compared with the studies of Festa et al. (40) and Tang et al. (41), the control groups of some studies on NLR consisted of patients who were uninfected after their first TJA or were readmitted due to several reasons. This may lead to high heterogeneity of results. Because patients with PJI and aseptic periprosthetic failure require different management approaches, differentiating patients with aseptic failure from uninfected patients would be reasonable. Secondly, AGR is a novel biomarker for the diagnosis of PJI. This is the first meta-analysis of AGR for the diagnosis of PJI. Although some questions about the mechanism underlying the association between AGR and PJI remain unanswered, the high sensitivity and specificity of AGR make it a reliable biomarker for the diagnosis of PJI. These findings provide a new reference index for clinical practice and have important clinical implications. Thirdly, all the included studies referred to the MSIS criteria for the diagnosis of PJI. These two criteria, particularly the MSIS criteria, are considered the gold standard for the diagnosis of PJI. The appropriate choice of reference standard could reduce the bias of this diagnostic test accuracy review.
Our study also has some limitations. First, the ideal cut-off values of the NLR and AGR tests in PJI diagnosis is still unclear. We could not perform a threshold analysis for these two serum biomarkers. Overestimation of the diagnostic accuracy of these serum biomarkers could not be avoided. Secondly, most of the included studies on AGR were from China. Area subgroup analysis could not be performed because studies in other areas were rare. This may lead to high heterogeneity in our results. Thirdly, in the initial version of the MSIS criteria, there was no distinction between chronic and acute PJI. It was only in subsequent revised versions that recommendations for distinguishing between chronic and acute infections were added. Furthermore, EBJIS does not provide a clear definition for chronic infection. As a result, some of the studies we included may not have been able to differentiate between acute and chronic infections if they relied on the initial version of the MSIS criteria or EBJIS criteria for diagnosing PJI. Since the majority of included studies enrolled patients who underwent both THA and TKA, we were unable to conduct separate analyses for patients based on their surgery site. Moreover, the included studies were retrospective because of the lack of randomized controlled trials or prospective cohort studies on the diagnostic accuracy of these biomarkers for PJI.
Conclusion
NLR and AGR can be used as serum biomarkers combined with traditional serum biomarkers for the detection of PJI. Future research is warranted to determine the diagnostic value of these markers in combination with CRP levels and ESR in order to improve the accuracy of PJI detection in clinical practice.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/EOR-23-0206.
ICMJE Conflict of Interest Statement
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding Statement
The authors are grateful to Wan Fang Hospital (Grant number 111-wf-eva-26) for financially supporting this research.
References
- 1↑
Sloan M, Premkumar A, & Sheth NP. Projected volume of primary total joint arthroplasty in the U.S., 2014 to 2030. Journal of Bone and Joint Surgery 2018 100 1455–1460. (https://doi.org/10.2106/JBJS.17.01617)
- 2↑
Kapadia BH, Berg RA, Daley JA, Fritz J, Bhave A, & Mont MA. Periprosthetic joint infection. Lancet 2016 387 386–394. (https://doi.org/10.1016/S0140-6736(14)61798-0)
- 3↑
Wang F-D, Wang Y-P, Chen C-F, & Chen H-P. The incidence rate, trend and microbiological aetiology of prosthetic joint infection after total knee arthroplasty: a 13 years’ experience from a tertiary medical center in Taiwan. Journal of Microbiology, Immunology, and Infection 2018 51 717–722. (https://doi.org/10.1016/j.jmii.2018.08.011)
- 4↑
Namba RS, Inacio MC, & Paxton EW. Risk factors associated with deep surgical site infections after primary total knee arthroplasty: an analysis of 56,216 knees. Journal of Bone and Joint Surgery 2013 95 775–782. (https://doi.org/10.2106/JBJS.L.00211)
- 5↑
Osmon DR, Berbari EF, Berendt AR, Lew D, Zimmerli W, Steckelberg JM, Rao N, Hanssen A, Wilson WR & Infectious Diseases Society of America. Diagnosis and management of prosthetic joint infection: clinical practice guidelines by the infectious diseases society of America. Clinical Infectious Diseases 2013 56 e1–e25. (https://doi.org/10.1093/cid/cis803)
- 6↑
Parvizi J, Tan TL, Goswami K, Higuera C, Della Valle C, Chen AF, & Shohat N. The 2018 definition of periprosthetic hip and knee infection: an evidence-based and validated criteria. Journal of Arthroplasty 2018 33 1309–1314.e2. (https://doi.org/10.1016/j.arth.2018.02.078)
- 7↑
Parvizi J, & Della Valle CJ. AAOS clinical practice guideline: diagnosis and treatment of periprosthetic joint infections of the hip and knee. Journal of the American Academy of Orthopaedic Surgeons 2010 18 771–772. (https://doi.org/10.5435/00124635-201012000-00007)
- 8↑
McNally M, Sousa R, Wouthuyzen-Bakker M, Chen AF, Soriano A, Vogely HC, Clauss M, Higuera CA, & Trebše R. The EBJIS definition of periprosthetic joint infection. Bone and Joint Journal 2021 103–B 18–25. (https://doi.org/10.1302/0301-620X.103B1.BJJ-2020-1381.R1)
- 9↑
Gölge UH, Kaymaz B, Pazarcı Ö, Kılınç S, Öztemur Z, & Bulut O. Neutrophil to lymphocyte ratio may be a diagnostic marker for prosthetic joint infection. Journal of Clinical and Analytical Medicine 2016 7 218–221)
- 10↑
Ye Y, Chen W, Gu M, Xian G, Pan B, Zheng L, Zhang Z, & Sheng P. Serum globulin and albumin to globulin ratio as potential diagnostic biomarkers for periprosthetic joint infection: a retrospective review. Journal of Orthopaedic Surgery and Research 2020 15 459. (https://doi.org/10.1186/s13018-020-01959-1)
- 11↑
Uslu AU, Küçük A, Şahin A, Ugan Y, Yılmaz R, Güngör T, Bağcacı S, & Küçükşen S. Two new inflammatory markers associated with Disease Activity Score-28 in patients with rheumatoid arthritis: neutrophil-lymphocyte ratio and platelet-lymphocyte ratio. International Journal of Rheumatic Diseases 2015 18 731–735. (https://doi.org/10.1111/1756-185X.12582)
- 12↑
Wu H, Pan L, Meng Z, Liu H, Yang X, & Cao Y. C-reactive protein (CRP)/albumin-to-globulin ratio (AGR) is a valuable test for diagnosing periprosthetic joint infection: a single-center retrospective study. Journal of Orthopaedics and Traumatology 2022 23 36. (https://doi.org/10.1186/s10195-022-00657-4)
- 13↑
Klemt C, Tirumala V, Smith EJ, Xiong L, & Kwon YM. Complete blood platelet and lymphocyte ratios increase diagnostic accuracy of periprosthetic joint infection following total hip arthroplasty. Archives of Orthopaedic and Traumatic Surgery 2022.
- 14↑
Maimaiti Z, Xu C, Fu J, Chai W, Zhou Y, & Chen J. The potential value of monocyte to lymphocyte ratio, platelet to mean platelet volume ratio in the diagnosis of periprosthetic joint infections. Orthopaedic Surgery 2022 14 306–314. (https://doi.org/10.1111/os.12992)
- 15↑
Ye Y, Chen W, Gu M, Liu Q, Xian G, Pan B, Zheng L, Chen X, Zhang Z, & Sheng P. Limited value of serum neutrophil-to-lymphocyte ratio in the diagnosis of chronic periprosthetic joint infection. Journal of Orthopaedics and Traumatology 2021 22 37. (https://doi.org/10.1186/s10195-021-00599-3)
- 16↑
Wang H, Zhou H, Jiang R, Qian Z, Wang F, & Cao L. Globulin, the albumin-to-globulin ratio, and fibrinogen perform well in the diagnosis of periprosthetic joint infection. BMC Musculoskeletal Disorders 2021 22 583. (https://doi.org/10.1186/s12891-021-04463-7)
- 17↑
Jiao JB, Huang JC, Chen X, & Jin Y. Albumin to globulin ratio, Neutrophil to lymphocyte ratio, and globulin levels do not outperform ESR or CRP when diagnosing periprosthetic joint infection. BMC Musculoskeletal Disorders 2022 23 404. (https://doi.org/10.1186/s12891-022-05357-y)
- 18↑
Lv GY, An L, Sun XD, Hu YL, & Sun DW. Pretreatment albumin to globulin ratio can serve as a prognostic marker in human cancers: a meta-analysis. Clinica Chimica Acta 2018 476 81–91. (https://doi.org/10.1016/j.cca.2017.11.019)
- 19↑
Gabay C, & Kushner I. Acute-phase proteins and other systemic responses to inflammation. New England Journal of Medicine 1999 340 448–454. (https://doi.org/10.1056/NEJM199902113400607)
- 20↑
Soeters PB, Wolfe RR, & Shenkin A. Hypoalbuminemia: pathogenesis and clinical significance. JPEN 2019 43 181–193. (https://doi.org/10.1002/jpen.1451)
- 21↑
Infusino I, & Panteghini M. Serum albumin: accuracy and clinical use. Clinica Chimica Acta 2013 419 15–18. (https://doi.org/10.1016/j.cca.2013.01.005)
- 22↑
Leeflang MM, Deeks JJ, Gatsonis C, Bossuyt PM & Cochrane Diagnostic Test Accuracy Working Group. Systematic reviews of diagnostic test accuracy. Annals of Internal Medicine 2008 149 889–897. (https://doi.org/10.7326/0003-4819-149-12-200812160-00008)
- 23↑
Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, & Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Medicine 2009 6 e1000100. (https://doi.org/10.1371/journal.pmed.1000100)
- 24↑
Parvizi J, Gehrke T & International Consensus Group on Periprosthetic Joint Infection. Definition of periprosthetic joint infection. Journal of Arthroplasty 2014 29 1331. (https://doi.org/10.1016/j.arth.2014.03.009)
- 25↑
Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MMG, Sterne JAC, Bossuyt PMM & QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of Internal Medicine 2011 155 529–536. (https://doi.org/10.7326/0003-4819-155-8-201110180-00009)
- 26↑
Yuan K, Chen HL, & Cui ZM. Diagnostic accuracy of C-reactive protein for periprosthetic joint infection: a meta-analysis. Surgical Infections 2014 15 548–559. (https://doi.org/10.1089/sur.2013.066)
- 27↑
Tsai J-C, Sheng W-H, Lo W-Y, Jiang C-C, & Chang S-C. Clinical characteristics, microbiology, and outcomes of prosthetic joint infection in Taiwan. Journal of Microbiology, Immunology, and Infection 2015 48 198–204. (https://doi.org/10.1016/j.jmii.2013.08.007)
- 28↑
Tseng S-W, Chi C-Y, Chou C-H, Wang Y-J, Liao C-H, Ho C-M, Lin P-C, Ho M-W, & Wang J-H. Eight years experience in treatment of prosthetic joint infections at a teaching hospital in Central Taiwan. Journal of Microbiology, Immunology, and Infection 2012 45 363–369. (https://doi.org/10.1016/j.jmii.2011.12.014)
- 29↑
Dabaghi A, Saleme J, & Ochoa L. Evaluation and treatment of prosthetic hip dislocation. Acta Ortopédica Mexicana 2014 28 137–144.
- 30↑
Miller R, Higuera CA, Wu J, Klika A, Babic M, & Piuzzi NS. Periprosthetic joint infection: a review of antibiotic treatment. JBJS Reviews 2020 8 e1900224. (https://doi.org/10.2106/JBJS.RVW.19.00224)
- 31↑
Rohe S, Böhle S, Matziolis G, Jacob B, Wassilew G, & Brodt S. C-reactive protein during the first 6 postoperative days after total hip arthroplasty cannot predict early periprosthetic infection. Archives of Orthopaedic and Traumatic Surgery 2022.
- 32↑
Yin H, Xu D, & Wang D. Diagnostic value of next-generation sequencing to detect periprosthetic joint infection. BMC Musculoskeletal Disorders 2021 22 252. (https://doi.org/10.1186/s12891-021-04116-9)
- 33↑
Jiang W, Xu H, Wang X, Xie J, Huang Q, Zhou Z, & Pei F. Poor performance of monocyte-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, and fibrinogen when screening for occult infection among patients with sequelae of suppurative hip arthritis before total hip arthroplasty. International Orthopaedics 2022 46 1929–1935. (https://doi.org/10.1007/s00264-022-05474-2)
- 34↑
Mortaz E, Alipoor SD, Adcock IM, Mumby S, & Koenderman L. Update on neutrophil function in severe inflammation. Frontiers in Immunology 2018 9 2171. (https://doi.org/10.3389/fimmu.2018.02171)
- 35↑
Vincent J-L, Dubois M-J, Navickis RJ, & Wilkes MM. Hypoalbuminemia in acute illness: is there a rationale for intervention?: A meta-analysis of cohort studies and controlled trials. Annals of Surgery 2003 237 319–334. (https://doi.org/10.1097/01.SLA.0000055547.93484.87)
- 36↑
Choe H, Kobayashi N, Abe K, Hieda Y, Tezuka T, & Inaba Y. Evaluation of serum albumin and globulin in combination with C-reactive protein improves serum diagnostic accuracy for low-grade periprosthetic joint infection. Journal of Arthroplasty 2023 38 555–561. (https://doi.org/10.1016/j.arth.2022.09.011)
- 37↑
Festa E, Ascione T, Bernasconi A, Di Gennaro D, Basso MA, Guarino A, & Balato G. Diagnostic performance of neutrophil to lymphocyte ratio, monocyte to lymphocyte ratio, platelet to lymphocyte ratio, and platelet to mean platelet volume ratio in periprosthetic hip and knee infections: A systematic review and meta-analysis. Diagnostics 2022 12. (https://doi.org/10.3390/diagnostics12092033)
- 38↑
Tang H, Xu J, Yuan W, Wang Y, Yue B, & Qu X. Reliable diagnostic tests and thresholds for preoperative diagnosis of non-inflammatory arthritis periprosthetic joint infection: A meta-analysis and systematic review. Orthopaedic Surgery 2022 14 2822–2836. (https://doi.org/10.1111/os.13500)
- 39↑
Xu H, Xie J, Zhang S, Wang D, Huang Z, & Zhou Z. Potential blood biomarkers for diagnosing periprosthetic joint infection: A single-center, retrospective study. Antibiotics 2022 11. (https://doi.org/10.3390/antibiotics11040505)
- 40↑
Choe H, Kobayashi N, Abe K, Hieda Y, Tezuka T, & Inaba Y. Evaluation of serum albumin and globulin in combination with C-reactive protein improves serum diagnostic accuracy for low-grade periprosthetic joint infection. Journal of Arthroplasty 2023 38 555–561. (https://doi.org/10.1016/j.arth.2022.09.011)
- 41↑
Zhang H, Xie S, Li Y, Li J, Deng P, Zeng H, Cao H, Liu M, Li J & Feng W et al. The potential performance of serum albumin to globulin ratio, albumin and globulin in the diagnosis of periprosthetic joint infection and prediction of reinfection following reimplantation. BMC Musculoskeletal Disorders 2022 23 730. (https://doi.org/10.1186/s12891-022-05533-0)
- 42↑
Shang G, Fei Z, Xu H, Wang Y, & Xiang S. Globulin and albumin to globulin ratio precisely diagnose periprosthetic joint infection and determine the timing of second-stage reimplantation. Journal of Orthopaedic Surgery and Research 2022 17 12. (https://doi.org/10.1186/s13018-021-02899-0)
- 43↑
Tirumala V, Klemt C, Xiong L, Chen W, van den Kieboom J, & Kwon YM. Diagnostic utility of platelet count/lymphocyte count ratio and platelet count/mean platelet volume ratio in periprosthetic joint infection following total knee arthroplasty. Journal of Arthroplasty 2021 36 291–297. (https://doi.org/10.1016/j.arth.2020.07.038)
- 44↑
Shi W, Jiang Y, Tian H, Wang Y, Zhang Y, Yu T, & Li T. C-reactive protein-to-albumin ratio (CAR) and C-reactive protein-to-lymphocyte ratio (CLR) are valuable inflammatory biomarker combination for the accurate prediction of periprosthetic joint infection. Infection and Drug Resistance 2023 16 477–486. (https://doi.org/10.2147/IDR.S398958)
- 45↑
Balato G, Ascione T, Festa E, Di Gennaro D, Pandolfo G, & Pagliano P. The diagnostic accuracy of neutrophils to lymphocytes ratio, platelets to lymphocytes ratio, monocytes to lymphocytes ratio, and platelets to mean platelet volume ratio in diagnosing periprosthetic knee infections: are gender-specific cutoff values needed? Journal of Arthroplasty 2023 38 918–924. (https://doi.org/10.1016/j.arth.2022.11.014)
- 46↑
Balta O, Astan S, Altınayak H, Uçar C, Aytekin FY, & Kurnaz R. Can C-reactive protein-lymphocyte ratio be used as a screening tool to confirm the diagnosis of periprosthetic joint infection? Clinics in Orthopedic Surgery 2023 15 917–927. (https://doi.org/10.4055/cios22313)
- 47↑
Li Z, Maimaiti Z, Fu J, Li Z-Y, Hao L-B, Xu C, & Chen J-Y. The superiority of immune-inflammation summary index for diagnosing periprosthetic joint infection. International Immunopharmacology 2023 118 110073. (https://doi.org/10.1016/j.intimp.2023.110073)
- 48↑
Dilley JE, Seetharam A, Meneghini RM, & Kheir MM. Synovial fluid absolute neutrophil count and neutrophil-to-lymphocyte ratio are not superior to polymorphonuclear percentage in detecting periprosthetic joint infection. Journal of Arthroplasty 2023 38 146–151. (https://doi.org/10.1016/j.arth.2022.07.005)
- 49↑
Wang R, Shi G, Zhang H, Wang T, Ren W, & Jiao Q. Globulin and albumin/globulin ratios as potential biomarkers for the diagnosis of acute and chronic peri-prosthetic joint infections: a retrospective study. Surgical Infections 2023 24 58–65. (https://doi.org/10.1089/sur.2022.215)
- 50↑
Dong M, Wang Y, Fan H, Yang D, Wang R, & Feng Y. The albumin to globulin ratio performs well for diagnosing periprosthetic joint infection: a single-center retrospective study. Journal of Arthroplasty 2024 39 229–235.e4. (https://doi.org/10.1016/j.arth.2023.08.002)
