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.

scholarly journals Systemic Immune-Inflammation Index Predicts the Outcome After Aneurysmal Subarachnoid Hemorrhage

2021 ◽  
Author(s):  
Fushu Luo ◽  
Yuanyou Li ◽  
Yutong Zhao ◽  
Mingjiang Sun ◽  
Qiuguang He ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Subarachnoid Hemorrhage ◽  
Inflammatory Response ◽  
Early Stage ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Area Under The Curve ◽  
Systemic Inflammatory Response ◽  
Unfavorable Outcome ◽  
Operating Characteristics ◽  
Immune Inflammation

Abstract Objectives: Systemic inflammatory response is closely related to the pathogenesis and prognosis in critical patients. Recently, systemic immune-inflammation index (SII), an indicator of systemic inflammatory response, was proved to predict the outcome in cancerous and non-cancerous diseases. The aim of this study is to evaluate the relationship between SII on admission and 6-month outcome in patients with aneurysmal subarachnoid hemorrhage (aSAH).Methods: The clinical data and prognosis of 76 patients with aSAH was analyzed. Patients were divided into high SII group and low SII group. The 6-month outcome was assessed by the modified Rankin scale (mRS).The unfavorable outcome was defined as mRS score ≥3. Receiver operating characteristics (ROC), area under the curve (AUC) and logistic regression were used to examine the relations between SII levels and 6-month clinical outcomes.Results: Thirty-six patients (47.4%) in our study had a unfavorable outcome (mRS ≥3) at 6 months, and twenty-four (66.7%) of them had high SII. Spearman correlation analysis showed that the SII was correlated with mRS (r=0.418, P＜0.05). Binary logistic regression showed that there was an independent association between SII on admission and 6-month clinical outcome (OR=4.271, 95%CI: 1.047-17.422, P＜0.05). The AUC of the SII for predicting unfavorable outcome was 0.692(95% CI:0.571–0.814, P＜0.05).Conclusion: Systemic immune-inflammation index (SII) could be a novel independent prognostic factor for aSAH patients at the early stage of the disease.

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.

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.

Systemic Inflammatory Response Syndrome as Predictor of Poor Outcome in Nontraumatic Subarachnoid Hemorrhage Patients

2018 ◽  
Vol 46 (12) ◽  
pp. e1152-e1159 ◽  
Author(s):  
Verena Rass ◽  
Max Gaasch ◽  
Mario Kofler ◽  
Alois Josef Schiefecker ◽  
Bogdan-Andrei Ianosi ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Systemic Inflammatory Response Syndrome ◽  
Inflammatory Response ◽  
Systemic Inflammatory Response ◽  
Poor Outcome

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.

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