Do Platelet to Lymphocyte Ratio and Neutrophil to Lymphocyte Ratio Predict the Hardness of Kidney Stone

Year 2021, Volume: 12 Issue: 43, 59 - 64, 19.08.2021

Onur Karslı , Murat Üstüner , Ahmed Ömer Halat , Levent Özcan , Fatih Gokalp , Ömer Koraş , Bekir Voyvoda , Ömür Memik

https://doi.org/10.17944/mkutfd.873615

Abstract

Objective: The Hounsfield unit (HU) is the most common value to assess the stone formation and a predictive factor for the management success. In this study, it was aimed to investigate the prediction of the hardness of the stone using systemic inflammatory response markers.Methods: 192 patients (61 female and 131 male) patients who underwent conventional percutaneous nephrolithotomy (PCNL) between 2015 and 2020 were reviewed retrospectively. Patients with malignancy and history of preoperative urinary tract infection were excluded from this study. Patients’ neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and HU of the kidney Stone, which was obtained from NCCT, were recorded to data.Results: The mean age was 47.2 ± 14.11 (11-82) years. The average HU value of the patients’ stones was 1135.47 ± 362.19 (348-2096). The location of the stones was grouped as pelvis (n:64, 33.3%), single calyx (n:14, 7.2%), two calyces (n:93, 48.4%) and staghorn (n:21, 10.9%). In subgroup analysis, when divided by stone location, a negative correlation was found between the HU and N/L ratio in the single calyceal stone group, and a positive correlation was found between the HU and N/L ratio for pelvis and staghorn stones. Among these correlations, only the positive correlation between the HU and N/L ratio in the pelvic stone group was statistically significant (r=0.318, p=0.03). Assuming an arbitrary cut-off value for HU below 1000, there was no significant correlation between NLR and HU (r=0.266, p=0.171). However, HU above 1000, there was a significant positive correlation between NLR and HU (r=0.145, p=0.045).Conclusion: The findings suggest that NLR could be used as a biomarker to choose appropriate management and be helpful to anticipate the hardness of kidney stones by predicting the HU value.

Keywords

Kidney Calculi, Hounsfield Unit, Urolithiasis, Neutrophil

Supporting Institution

None

Trombosit-Lenfosit Oranı ve Nötrofil-Lenfosit Oranı Böbrek Taşının Sertliğini Öngörür mü?

Abstract

Amaç: Hounsfield ünitesi (HU), taş oluşumunu değerlendirmek için en yaygın değer ve aynı zamanda yönetim başarısı için öngörücü bir faktördür. Bu çalışmada, sistemik inflamatuar yanıt belirteçleri kullanarak taşın sertliğini tahmin etmeyi amaçladık.Yöntem: 2015 ve 2020 yılları arasında konvansiyonel perkütan nefrolitotomi uygulanan 192 hastaya (61 kadın ve 131 erkek) ait veri retrospektif olarak gözden geçirildi. Malignite, preoperatif idrar kültürü pozitif olan hastalar çalışma dışı bırakıldı. Hastaların nötrofil lenfosit oranı (NLR), trombosit lenfosit oranı (PLR) ve NCCT’den elde edilen böbrek taşı Hounsfield Ünitesi (HU) verilere kaydedildi.Bulgular: Ortalama yaş 47,2 ± 14,11 (11-82) yıldı. Hastaların taşlarının ortalama HU değeri 1135,47 ± 362,19 (348-2096) olarak bulundu. Taşların yeri pelvis (n: 64, %33,3), tek kaliks (n: 14, %7,2), iki kaliks (n: 93, %48,4) ve staghorn (n: 21, %10,9) olarak gruplandı. Alt grup analizinde taş lokalizasyonuna göre, pelvis ve staghorn taşlar için HU ve NLR arasında pozitif bir korelasyon bulundu. Bu korelasyonlar arasında sadece pelvis taş grubunda HU ve NLR arasındaki pozitif korelasyon istatistiksel olarak anlamlıydı (r=0.318, p=0.03). HU için 1000’in altında bir kesme değeri varsayıldığında ise, NLR ve HU arasında anlamlı bir korelasyon yoktu (r=0.266, p=0.171). Bununla birlikte, HU 1000’in üzerinde, NLR ve HU arasında anlamlı bir pozitif korelasyon vardır (r=0.145, p=0.045).Sonuç: Bu çalışma, NLR’nin uygun tedaviyi seçmek için bir biyobelirteç olarak kullanabileceğini ve HU değerini tahmin ederek böbrek taşının sertliğini tahmin etmeye yardımcı olabileceğini gösterdi.

Keywords

Böbrek Taşı, Hounsfield Ünitesi, Ürolitiyazis, Nötrofil

References

• Ziemba JB, Matlaga BR. Epidemiology and economics of nephrolithiasis. Investig Clin Urol. 2017 Sep;58(5):299-306. https://doi.org/10.4111/icu.2017.58.5.299
• Zisman AL. Effectiveness of Treatment Modalities on Kidney Stone Recurrence. Clin J Am Soc Nephrol. 2017 Oct;12(10):1699-708. https://doi.org/10.2215/CJN.11201016
• Mahalingam H, Lal A, Mandal AK, Singh SK, Bhattacharyya S, Khandelwal N. Evaluation of low-dose dual energy computed tomography for in vivo assessment of renal/ureteric calculus composition. Korean J Urol [Internet]. 2015/08/10. 2015 Aug;56(8):587-93. Available from: https://pubmed.ncbi.nlm.nih.gov/26279828 https://doi.org/10.4111/kju.2015.56.8.587
• Joseph P, Mandal AK, Singh SK, Mandal P, Sankhwar SN, Sharma SK. Computerized tomography attenuation value of renal calculus: can it predict successful fragmentation of the calculus by extracorporeal shock wave lithotripsy? A preliminary study. J Urol. 2002 May;167(5):1968-71. https://doi.org/10.1016/S0022-5347(05)65064-1
• Anastasiadis A, Onal B, Modi P, Turna B, Duvdevani M, Timoney A, et al. Impact of stone density on outcomes in percutaneous nephrolithotomy (PCNL): an analysis of the clinical research office of the endourological society (CROES) pcnl global study database. Scand J Urol. 2013 Dec;47(6):509-14. https://doi.org/10.3109/21681805.2013.803261
• Torricelli FCM, De S, Liu X, Calle J, Gebreselassie S, Monga M. Can 24-Hour Urine Stone Risk Profiles Predict Urinary Stone Composition? J Endourol [Internet]. 2014 Jan 27;28(6):735-8. https://doi.org/10.1089/end.2013.0769
• Mulay SR, Kulkarni OP, Rupanagudi K V, Migliorini A, Darisipudi MN, Vilaysane A, et al. Calcium oxalate crystals induce renal inflammation by NLRP3-mediated IL-1β secretion. J Clin Invest [Internet]. 2012/12/10. 2013 Jan;123(1):236-46. Available from: https://pubmed.ncbi.nlm.nih.gov/23221343 https://doi.org/10.1172/JCI63679
• Proctor MJ, McMillan DC, Morrison DS, Fletcher CD, Horgan PG, Clarke SJ. A derived neutrophil to lymphocyte ratio predicts survival in patients with cancer. Br J Cancer. 2012 Aug;107(4):695-9. https://doi.org/10.1038/bjc.2012.292
• Tang K, Liu H, Jiang K, Ye T, Yan L, Liu P, et al. Predictive value of preoperative inflammatory response biomarkers for metabolic syndrome and post-PCNL systemic inflammatory response syndrome in patients with nephrolithiasis. Oncotarget [Internet]. 2017 Aug 18;8(49):85612-27. Available from: https://pubmed.ncbi.nlm.nih.gov/29156745 https://doi.org/10.18632/oncotarget.20344
• Abou Heidar N, Labban M, Bustros G, Nasr R. Inflammatory serum markers predicting spontaneous ureteral stone passage. Clin Exp Nephrol. 2020 Mar;24(3):277-83. https://doi.org/10.1007/s10157-019-01807-5
• Koras O, Bozkurt IH, Yonguc T, Degirmenci T, Arslan B, Gunlusoy B, et al. Risk factors for postoperative infectious complications following percutaneous nephrolithotomy: a prospective clinical study. Urolithiasis. 2015 Feb;43(1):55-60. https://doi.org/10.1007/s00240-014-0730-8
• Sen V, Bozkurt IH, Aydogdu O, Yonguc T, Yarimoglu S, Sen P, et al. Significance of preoperative neutrophil-lymphocyte count ratio on predicting postoperative sepsis after percutaneous nephrolithotomy. Kaohsiung J Med Sci. 2016 Oct;32(10):507-13. https://doi.org/10.1016/j.kjms.2016.08.008
• Zahorec R. Ratio of neutrophil to lymphocyte counts--rapid and simple parameter of systemic inflammation and stress in critically ill. Bratisl Lek Listy. 2001;102(1):5-14.
• Motomura T, Shirabe K, Mano Y, Muto J, Toshima T, Umemoto Y, et al. Neutrophil-lymphocyte ratio reflects hepatocellular carcinoma recurrence after liver transplantation via inflammatory microenvironment. J Hepatol. 2013 Jan;58(1):58-64. https://doi.org/10.1016/j.jhep.2012.08.017
• Goodman DA, Goodman CB, Monk JS. Use of the neutrophil:lymphocyte ratio in the diagnosis of appendicitis. Am Surg. 1995 Mar;61(3):257-9.
• Tamhane UU, Aneja S, Montgomery D, Rogers E-K, Eagle KA, Gurm HS. Association between admission neutrophil to lymphocyte ratio and outcomes in patients with acute coronary syndrome. Am J Cardiol. 2008 Sep;102(6):653-7. https://doi.org/10.1016/j.amjcard.2008.05.006
• Patel SR, Haleblian G, Zabbo A, Pareek G. Hounsfield units on computed tomography predict calcium stone subtype composition. Urol Int. 2009;83(2):175-80. https://doi.org/10.1159/000230020
• Newhouse JH, Prien EL, Amis ESJ, Dretler SP, Pfister RC. Computed tomographic analysis of urinary calculi. AJR Am J Roentgenol. 1984 Mar;142(3):545-8. https://doi.org/10.2214/ajr.142.3.545
• Mostafavi MR, Ernst RD, Saltzman B. Accurate determination of chemical composition of urinary calculi by spiral computerized tomography. J Urol. 1998 Mar;159(3):673-5. https://doi.org/10.1016/S0022-5347(01)63698-X
• Saw KC, McAteer JA, Monga AG, Chua GT, Lingeman JE, Williams JCJ. Helical CT of urinary calculi: effect of stone composition, stone size, and scan collimation. AJR Am J Roentgenol. 2000 Aug;175(2):329-32. https://doi.org/10.2214/ajr.175.2.1750329
• Matlaga BR, Kawamoto S, Fishman E. Dual source computed tomography: a novel technique to determine stone composition. Urology. 2008 Nov;72(5):1164-8. https://doi.org/10.1016/j.urology.2008.03.051
• Wisenbaugh ES, Paden RG, Silva AC, Humphreys MR. Dual-energy vs conventional computed tomography in determining stone composition. Urology. 2014 Jun;83(6):1243-7. https://doi.org/10.1016/j.urology.2013.12.023
• Valente P, Castro H, Pereira I, Vila F, Araújo PB, Vivas C, et al. Metabolic syndrome and the composition of urinary calculi: is there any relation? Cent Eur J Urol [Internet]. 2019/09/16. 2019;72(3):276-9. Available from: https://pubmed.ncbi.nlm.nih.gov/31720030