scholarly journals Can Preoperative Neutrophil-Lymphocyte Ratio and Platelet-Lymphocyte Ratio Predict Systemic Inflammatory Response Syndrome That Develops After Percutaneous Nephrolithotomy?

2021 ◽  
Author(s):  
Uygar Miçooğulları ◽  
Orçun Çelik ◽  
Mehmet Çağlar Çakıcı ◽  
Erdem Kısa ◽  
Cem Yücel ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Percutaneous Nephrolithotomy ◽  
Systemic Inflammatory Response ◽  
Blood Transfusions ◽  
Multivariate Logistic Regression ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Platelet Lymphocyte Ratio

Objective: First objective of this study was to find out factors influencing development of postoperative systemic inflammatory response syndrome (SIRS) after percutaneous nephrolithotomy (PNL). Secondary objective was to point out the role of preoperative neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in SIRS estimation. Method: The data of 756 patients that underwent PNL for kidney stones between 2012 and 2019 were evaluated retrospectively. Patients were divided into 2 groups as non-SIRS and SIRS group. The effects of NLR, PLR and other operative and demographic variables on development of SIRS were investigated. Multivariate logistic regression analysis that was performed on variables that were significant in the univariate analyses was used to establish independent risk factor for post-PNL SIRS. Results: Univariate analysis revealed a significant association between presence of SIRS and preoperative PLR (p<0.001), preoperative NLR (p<0.001), blood transfusion (p<0.001), stone volume (p=0.03), staghorn stone (p<0.001), and preoperative creatinine levels (<0.001). Multivariate logistic regression analyses of these risk factors showed that NLR (p<0.001), PLR (p<0.001), and blood transfusions (p<0.001) were independently associated with SIRS. When the cut-off value of PLR was 120.5, the development of SIRS was predicted with 80.1% specificity and 81% sensitivity. When the cut-off value of NLR was 2.75, the development of SIRS was predicted with 64% specificity and 63.7% sensitivity. Conclusion: Preoperative PLR and NLR are effective and inexpensive biomarkers that can be used to predict SIRS and sepsis after PNL. We recommend that patients with PLR >120.5, NLR >2.75, and blood transfusions should be monitored closely due to the possible development of serious complications.

scholarly journals A sustained systemic inflammatory response syndrome is associated with shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage

2019 ◽  
Vol 130 (6) ◽  
pp. 1984-1991 ◽  
Author(s):  
Aaron P. Wessell ◽  
Matthew J. Kole ◽  
Gregory Cannarsa ◽  
Jeffrey Oliver ◽  
Gaurav Jindal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Subarachnoid Hemorrhage ◽  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Regression Model ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Systemic Inflammatory Response ◽  
Multivariate Logistic Regression ◽  
Shunt Placement ◽  
Shunt Dependence

OBJECTIVEThe authors sought to evaluate whether a sustained systemic inflammatory response was associated with shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage.METHODSA retrospective analysis of 193 consecutive patients with aneurysmal subarachnoid hemorrhage was performed. Management of hydrocephalus followed a stepwise algorithm to determine the need for external CSF drainage and subsequent shunt placement. Systemic inflammatory response syndrome (SIRS) data were collected for all patients during the first 7 days of hospitalization. Patients who met the SIRS criteria every day for the first 7 days of hospitalization were considered as having a sustained SIRS. Univariate and multivariate regression analyses were used to determine predictors of shunt dependence.RESULTSSixteen percent of patients required shunt placement. Sustained SIRS was observed in 35% of shunt-dependent patients compared to 14% in non–shunt-dependent patients (p = 0.004). On multivariate logistic regression, female sex (OR 0.35, 95% CI 0.142–0.885), moderate to severe vasospasm (OR 3.78, 95% CI 1.333–10.745), acute hydrocephalus (OR 21.39, 95% CI 2.260–202.417), and sustained SIRS (OR 2.94, 95% CI 1.125–7.689) were significantly associated with shunt dependence after aneurysmal subarachnoid hemorrhage. Receiver operating characteristic analysis revealed an area under the curve of 0.83 for the final regression model.CONCLUSIONSSustained SIRS was a predictor of shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage even after adjustment for potential confounding variables in a multivariate logistic regression model.

Establishment of Predictive Model for Related Factors of Systemic Inflammatory Response Syndrome (SIRS) After Percutaneous Nephrolithotomy (PCNL)

2020 ◽  
Author(s):  
Min Ju ◽  
Jin Zheng ◽  
li Ying Pan ◽  
lin Lin Gao
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Percutaneous Nephrolithotomy ◽  
Operative Time ◽  
Univariate Analysis ◽  
Infection Process ◽  
Systemic Inflammatory Response ◽  
Related Factors

Abstract Background:The percutaneous nephrolithotomy (PCNL) is a primary method of stone treatment, but the infection is a very common postoperative complication. The systemic inflammatory response syndrome (SIRS) is a stage of the infection process and a very important early clinical manifestation of sepsis, so identifying the risk factors associated with SIRS after PCNL plays an important role in ensuring patients’ safety and preventing sepsis. Methods:Between September 2016 and September 2017,there were total 352 patients who were diagnosed as renal stone and were treated with PCNL, andincluded in this study at last.Patients were divided into two groups according to whether SIRS occurred or not.The univariate analysis was performed on the related risk factors such as patients' age, gender, number of stone, diabetes et al. Then logistic regression was used for multivariate analysis and established a prediction model.Results:There are 352renal stone patients were treated with PCNL, and 106 patients (30.1%) suffered SIRS after operation.It was found that the operative time, preoperative fever and diabetes could be deemed as risk factors, and the Then logistic regression results indicated that diabetes (OR=2.049, 95%CI 1.008～4.166) and operative time (OR=1.011, 95%CI 1.003～1.019) entered the regression equation.Conclusion: Diabetes and operative time are independent risk factors for SIRS after PCNL, so the probability of SIRS after PCNL can be determined in accordance with these two indicators.

scholarly journals Establishment of a Predictive Model for Factors Related to Systemic  Inflammatory Response Syndrome (SIRS) after Percutaneous Nephrolithotomy (PCNL)

2020 ◽  
Author(s):  
Min Ju ◽  
Jin Zheng ◽  
Lin Lin Gao ◽  
Li Ying Pan
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Predictive Model ◽  
Percutaneous Nephrolithotomy ◽  
Operative Time ◽  
Univariate Analysis ◽  
Renal Stones ◽  
Systemic Inflammatory Response

Abstract Background: Percutaneous nephrolithotomy (PCNL) is a primary treatment method for renal stones, but infection is a very common postoperative complication. Systemic inflammatory response syndrome (SIRS) is a stage of the infection process and a very important early clinical manifestation of sepsis, so identifying the risk factors associated with SIRS after PCNL is important for ensuring patient safety and preventing sepsis.Objective: To analyze the risk factors for SIRS after PCNL, identify the predictive factors, and perform risk factor analysis.Methodology: Between September 2016 and September 2017, 352 patients who were diagnosed with renal stones and treated with PCNL were included in this study. The patients were divided into two groups according to whether SIRS occurred. Univariate analysis was performed on the related risk factors, including patient age; gender; body mass index; urine culture; number, types and quantity of rental stones; diabetes; blood glucose; complications; hospital stay; residual stones; and Guy’s degree. Then, logistic regression was used to perform multivariate analysis and establish a predictive model.Results: A total of 352 patients with renal stones were treated with PCNL, and 106 patients (30.1%) developed SIRS after surgery. Operative time, preoperative fever and diabetes were found to be risk factors, and the logistic regression results indicated that diabetes (OR=2.049, 95%CI 1.008~4.166) and operative time (OR=1.011, 95%CI 1.003~1.019) could be entered into the regression equation. Therefore, the predictive regression model was P=1/[1+e-(-2.097+0.712 diabetes + 0.012 operative time)].Conclusion: Diabetes and operative time are independent risk factors for SIRS after PCNL, so the probability of SIRS after PCNL can be determined according to these two indicators.

scholarly journals Correlation between Prolactin Serum with Neutrophil Lymphocyte Ratio (NLR) in Systemic Inflammatory Response Syndrome

2021 ◽  
Vol 2 (1) ◽  
pp. 10-13
Author(s):  
Dwi Retnoningrum ◽  
Meita Hendrianingtyas ◽  
Hermawan Istiadi ◽  
Ardhea Jaludamascena
Keyword(s):  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Cost Effective ◽  
Systemic Inflammatory Response ◽  
Serum Prolactin ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cross Sectional ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Spearman Test

Background: Systemic inflammatory response syndrome (SIRS) is a state of systemic inflammatory activation by various causes. SIRS have a high mortality rate. Prolactin is known to regulate cellular function of immune system.  Neutrophil-lymphocyte ratio (NLR) is simple, cost effective and easy parameter that currently used as inflammation marker.Objective: The aims of this study is to determine the correlation between prolactin serum with NLR in SIRS patients.Methods: A cross sectional study was conducted on 50 clinically SIRS patients. Prolactin serum was measured by enzyme linked immunosorbent assay (ELISA) and NLR was calculated manually from absolute neutrophil and lymphocyte count measured by automatic hematology analyzer. Non-parametric Spearman test was used to analyze the correlation between prolactin with NLR.Results: Median value of serum prolactin level was 11.32 ng/mL (2.76-194.81), whereas the mean value NLR was 16.36 ± 11.58. The correlation between prolactin levels with NLR was r = 0.345, p = 0.014.Conclusion: There is a weak positive significant correlation between prolactin with neutrophil lymphocyte ratio in SIRS

scholarly journals CORRELATION OF MONOCYTE COUNT, MLR AND NLCR WITH PRESEPSIN LEVEL IN SIRS (Hubungan Jumlah Monosit, MLR dan NLCR dengan Kadar Presepsin pada SIRS)

2018 ◽  
Vol 22 (3) ◽  
pp. 212
Author(s):  
Nurmalia PS ◽  
N. Suci W ◽  
Imam BW
Keyword(s):  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Enzyme Immunoassay ◽  
Lymphocyte Count ◽  
Systemic Inflammatory Response ◽  
Monocyte Count ◽  
Lymphocyte Ratio ◽  
Count Ratio ◽  
Hematology Analyzer ◽  
Chemiluminescent Enzyme Immunoassay

Systemic Inflammatory Response Syndrome (SIRS) mempunyai kebahayaan tinggi terjadi sepsis dan kematian. Nilai jumlahkeseluruhan leukosit merupakan salah satu peramal pasien SIRS dengan bakteriemia. Pemeriksaan jumlah monosit, angka bandinglimfosit Monocyte-Lymphocyte Ratio (MLR), Neutrophil-Lymphocyte Count Ratio (NLCR) dapat diketahui dengan pemeriksaan leukosit.Presepsin telah diteliti untuk mencerminkan kondisi sepsis. Penelitian ini bertujuan untuk mengetahui keberadaan hubungan jumlahmonosit, MLR dan NLCR dengan presepsin di SIRS lewat pembuktian. Ada 34 pasien SIRS di ICU RSUP Dr. Kariadi, diambil secaraberturutan antara selama bulan Januari−Februari 2014. Pemeriksaan darah rutin dengan hematology analyzer. MLR dan NLCR dihitung secara manual. Kadar presepsin ditentukan dengan metode Chemiluminescent Enzyme Immunoassay (CLEIA). Uji kenasabanPearson untuk hubungan MLR dan NLCR dengan presepsin. Uji kenasaban Spearman untuk jumlah monosit dengan presepsin. Kadarpresepsin subjek penelitian 286–15687 pg/mL. Terdapat 23(67,8%) subjek yang mempunyai jumlah monosit dalam rentang nilai rujukan.24(70,6%) dan memiliki jumlah neutrofil absolut lebih besar dari rentang nilai rujukan, sedangkan 21(61,8%) mempunyai jumlahlimfosit absolut dalam rentang nilai rujukan. Hubungan jumlah monosit dengan presepsin mempunyai nilai r= -0,204; p=0,247;yang terkait MLR dengan presepsin r=0,163; p=0,358; sedangkan NLCR dengan presepsin r=0,345; p=0,046. Didasari telitian ini,dapat disimpulkan tidak terdapat hubungan bermakna antara jumlah monosit dan MLR dengan presepsin, selain itu didapatkan pulahubungan positif berarti antara NLCR dan presepsin di SIRS.

Abstract 11053: The Association Between the Systemic Immune-Inflammation Index with the Duration of Cardiopulmonary Bypass in Cardiac Surgery: A Retrospective, Single-Center Study

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Yanan Hu ◽  
Yi Liu ◽  
Yongzhe Liu ◽  
Hui Chen ◽  
Wei Jiang ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Inflammatory Response ◽  
Hospital Stay ◽  
Time Course ◽  
Ischemia Reperfusion ◽  
Systemic Inflammatory Response ◽  
Surgical Trauma ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Immune Inflammation

Introduction: Systemic inflammatory response evoked by cardiac surgery involving a cardio-pulmonary bypass (CPB) in combination of surgical trauma, ischemia/reperfusion injury, hypothermia, and endotoxin release contributed to the postoperative morbidity and mortality. This study aimed to explore the potential of neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) as novel markers to evaluate and predict the adverse clinical outcomes after longer CPB time in cardiac surgery. Methods: Patients who underwent cardiac surgery with or without CPB were allocated into two groups, CPB group (n=11) and N-CPB group (n=21). The time course of NLR, PLR, SII, and C-reactive protein (CPR) were analyzed at preoperative day 1 and postoperative day 1, 3, and 7. The baseline and postoperative parameters, the ICU and hospital stay were recorded. Results: There were no differences of baseline parameters between groups. The level of NLR, PLR, SII, and CPR at postoperative day 1 was higher than that in the preoperative day 1 in both groups (p < 0.01). The level of NLR, SII and CPR at postoperative day 3 was higher than that in the preoperative day 1 in both groups (p < 0.05). The NLR and SII at postoperative day 3 were higher in CPB group than that in N-CPB group (p < 0.05). The ICU and hospital stay was longer in CPB group than N-CPB group (p < 0.05). Conclusions: The longer duration of CPB time induced higher systemic inflammatory response characterized by higher level of NLR, PLR and SII. The SII predicted the poor outcome after longer CPB. The peak of systemic inflammatory response occurred on the third day after cardiac surgery.

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