Lam K, van Asten SA, Nguyen T, et al.: Diagnostic accuracy of probe to bone to detect osteomyelitis in the diabetic foot: a systematic review. Clin Infect Dis 63: 944, 2016.
Aragon-Sanchez J, Lipsky BA, Lazaro-Martinez JL: Diagnosing diabetic foot osteomyelitis: is the combination of probe-to-bone test and plain radiography sufficient for high-risk inpatients? Diabet Med 28: 191, 2011.
Alvaro-Afonso FJ, Lazaro-Martinez JL, Garcia-Morales E, et al.: Cortical disruption is the most reliable and accurate plain radiographic sign in the diagnosis of diabetic foot osteomyelitis. Diabet Med 36: 258, 2019.
Butalia S, Palda VA, Sargeant RJ, et al.: Does this patient with diabetes have osteomyelitis of the lower extremity? JAMA 299: 806, 2008.
La Fontaine J, Bhavan K, Lam K, et al.: Comparison between Tc-99m WBC SPECT/CT and MRI for the diagnosis of biopsy-proven diabetic foot osteomyelitis. Wounds 28: 271, 2016.
Lipsky BA, Senneville E, Abbas ZG, et al.: Guidelines on the diagnosis and treatment of foot infection in persons with diabetes (IWGDF 2019 update). Diabetes Metab Res Rev 36(suppl 1): e3280, 2020.
Senneville E, Lipsky BA, Abbas ZG, et al.: Diagnosis of infection in the foot in diabetes: a systematic review. Diabetes Metab Res Rev 36(suppl 1): e3281, 2020.
Sybenga AB, Jupiter DC, Speights VO, et al.: Diagnosing osteomyelitis: a histology guide for pathologists. J Foot Ankle Surg 59: 75, 2020.
Victoria van Asten SA, Geradus Peters EJ, Xi Y, et al.: The role of biomarkers to diagnose diabetic foot osteomyelitis: a meta-analysis. Curr Diabetes Rev 12: 396, 2016.
Jiang N, Ma YF, Jiang Y, et al.: Clinical characteristics and treatment of extremity chronic osteomyelitis in Southern China: a retrospective analysis of 394 consecutive patients. Medicine 94: e1874, 2015.
Khan MH, Smith PN, Rao N, et al.: Serum C-reactive protein levels correlate with clinical response in patients treated with antibiotics for wound infections after spinal surgery. Spine J 6: 311, 2006.
Radtke K, Tetzlaff T, Vaske B, et al.: Arthroplasty-center related retrospective analysis of risk factors for periprosthetic joint infection after primary and after revision total hip arthroplasty. Technol Health Care 24: 721, 2016.
Yoon SH, Chung SK, Kim KJ, et al.: Pyogenic vertebral osteomyelitis: identification of microorganism and laboratory markers used to predict clinical outcome. Eur Spine J 19: 575, 2010.
Ryan EC, Ahn J, Wukich DK, et al.: Diagnostic utility of erythrocyte sedimentation rate and C-reactive protein in osteomyelitis of the foot in persons without diabetes. J Foot Ankle Surg 58: 484, 2019.
Bristow I: Foot ulceration in a non-diabetic population: a cross-sectional audit of staff in one health district. J Wound Care 17: 445, 2008.
Haji Zaine N, Hitos K, Vicaretti M, et al.: Characteristics of non-diabetic foot ulcers in Western Sydney, Australia. J Foot Ankle Res 9: 6, 2016.
Lavery LA, Walker SC, Harkless LB, et al.: Infected puncture wounds in diabetic and nondiabetic adults. Diabetes Care 18: 1588, 1995.
Wunderlich RP, Armstrong DG, Husain K, et al.: Defining loss of protective sensation in the diabetic foot. Adv Wound Care 11: 123, 1998.
Lavery LA, Armstrong DG, Vela SA, et al.: Practical criteria for screening patients at high risk for diabetic foot ulceration. Arch Intern Med 158: 157, 1998.
Ghanem E, Antoci V Jr, Pulido L, et al.: The use of receiver operating characteristics analysis in determining erythrocyte sedimentation rate and C-reactive protein levels in diagnosing periprosthetic infection prior to revision total hip arthroplasty. Int J Infect Dis 13: e444, 2009.
Greidanus NV, Masri BA, Garbuz DS, et al.: Use of erythrocyte sedimentation rate and C-reactive protein level to diagnose infection before revision total knee arthroplasty: a prospective evaluation. J Bone Joint Surg Am 89: 1409, 2007.
Tsai CE, Lee FT, Chang MC, et al.: Primary cervical osteomyelitis. J Chin Med Assoc 76: 640, 2013.
Wang C, Ao Y, Fan X, et al.: C-reactive protein and erythrocyte sedimentation rate changes after arthroscopic anterior cruciate ligament reconstruction: guideline to diagnose and monitor postoperative infection. Arthroscopy 30: 1110, 2014.
Aulich J, Cho YH, Januszewski AS, et al.: Associations between circulating inflammatory markers, diabetes type and complications in youth. Pediatr Diabetes 20: 1118, 2019.
Chuengsamarn S, Rattanamongkolgul S, Sittithumcharee G, et al.: Association of serum high-sensitivity C-reactive protein with metabolic control and diabetic chronic vascular complications in patients with type 2 diabetes. Diabetes Metab Syndr 11: 103, 2017.
Aryan Z, Ghajar A, Faghihi-Kashani S, et al.: Baseline high-sensitivity C-reactive protein predicts macrovascular and microvascular complications of type 2 diabetes: a population-based study. Ann Nutr Metab 72: 287, 2018.
George MD, Giles JT, Katz PP, et al.: Impact of obesity and adiposity on inflammatory markers in patients with rheumatoid arthritis. Arthritis Care Res (Hoboken) 69: 1789, 2017.
Sudhakar M, Silambanan S, Chandran AS, et al.: C-reactive protein (CRP) and leptin receptor in obesity: binding of monomeric CRP to leptin receptor. Front Immunol 9: 1167, 2018.
Rashad NM, El-Shabrawy RM, Sabry HM, et al.: Interleukin-6 and hs-CRP as early diagnostic biomarkers for obesity-related peripheral polyneuropathy in non-diabetic patients. Egypt J Immunol 25: 153, 2018.
Objective: To investigate the predictive value of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) in persons with and without diabetes with osteomyelitis (OM).
Methods: We evaluated 455 patients in a retrospective cohort study of patients admitted to the hospital with diabetic foot OM (n = 177), diabetic foot soft-tissue infections (STIs) (n = 176), nondiabetic OM (n = 51), and nondiabetic STIs (n = 51). Infection diagnosis was determined through bone culture, histopathologic examination for OM, and/or imaging (magnetic resonance imaging/single-photon emission computed tomography) for STI. The optimal cutoff values of ESR and CRP in predicting OM were determined by receiver operating characteristic curve analysis. Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios were determined through contingency tables.
Results: In persons without diabetes with STI or OM, the mean ESR and CRP differences were 10.0 mm/h and 2.6 mg/dL, respectively. In contrast, persons with diabetes had higher levels of each: 24.8 mm/h and 6.8 mg/dL, respectively. As a result, ESR and CRP predicted OM better in patients with diabetes. However, when patients were stratified by neuropathy status, ESR remained predictive of OM in diabetic patients with neuropathy (75% sensitivity, 58% specificity) but not in diabetic patients without neuropathy (50% sensitivity, 44% specificity). Also, CRP remained predictive irrespective of neuropathy status. A similar trend was observed in patients without diabetes.
Conclusions: Previous studies have reported that ESR and CRP are predictive of OM. However, this study suggests that neuropathy influences the predictive value of inflammatory biomarkers. The underlying mechanisms require further study.