Predictive Factors For Intraoperative Blood Loss During Percutaneous Nephrolithotomy

Mithani, M. Hammad; Khan, Shariq Anis; Khalid, Salman; Majeed, Irfan; Awan, Adnan Siddiq; Mithani, Shoaib

doi:10.29271/jcpsp.2018.08.623

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Urinary tract stones pose a signi cant burden on both individuals and society,often manifesting through symptoms such as pain and hematuria.Prolonged presence of stones can lead to complications like renal insu ciency and even renal cancer [19][20] .With its minimal invasiveness and high success rate,PCNL has emerged as a standard intervention for stone-related surgical procedures.Beyond effectively alleviating symptoms like pain and hematuria,PCNL also offers substantial relief from the emotional distress and anxiety associated with urinary stones [21] .However,factors such as patient conditions,surgical circumstances,and stone characteristics can contribute to post-PCNL bleeding,leading to increased treatment costs and hospitalization time [22] .Currently,most studies on postoperative bleeding in PCNL rely on clinically relevant variables,the predictive e cacy of which remains uncertain [23][24][25] .Therefore,it is imperative to forecast the likelihood of bleeding following PCNL.…”

Section: Discussionmentioning

confidence: 99%

Preoperative prediction of bleeding complications in percutaneous nephrolithotomy using a machine learning model based on CT radiomics and clinical variables

Zou,

Yuan,

Zhou

et al. 2024

Preprint

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Background and objective Radiomics and machine learning play a significant role in clinical medical research, particularly in the development of prediction models.This study aims to utilize radiomic features and clinical variables in combination with machine learning to predict the risk of postoperative bleeding after percutaneous nephrolithotomy (PCNL). Materials and Methods A retrospective study analyzed 151 patients who had PCNL at the Second Affiliated Hospital of Nanchang University.Clinical variables linked to postoperative bleeding were identified using univariate analysis,and radiomic features were screened using the least absolute shrinkage and selection operator algorithm(lasso regression).Logistic regression,Random Forest(RF),and Support Vector Machine(SVM) were then used to develop prediction models based on the correlated clinical variables and radiomic features.The predictive accuracy of these models was assessed through identification and calibration. Results The postoperative statistics revealed that the postoperative bleeding rate was 31.1%(n=47),the blood transfusion rate was 1.42%(n=3),and the final probability of requiring vascular embolization was 0.94%(n=2).The accuracy rates for predicting postoperative bleeding in patients with PCNL using logistic regression,RF and SVM algorithms were 75.6%,75.6%,and 71.1% respectively.The corresponding area under the curve AUC(95% CI) were 0.76(0.72-0.81),0.74(0.69-0.79) and 0.63(0.54-0.68).The top four prediction importance scores in logistic regression and RF algorithms were wavelet-HLH_glrlm_ShortRunLowGrayLevelEmphasis,wavelet-HLH_glrlm_LowGrayLevelRunEmphasis,stone shape,operation time and stone shape,stone diameter,operation time,Wavelet-HLH_glrlm_ShortRunLowGrayLevelEmphasis. Conclusion The logistic regression model demonstrated the highest efficiency in predicting postoperative bleeding in PCNL.Our study successfully developed an effective machine learning model that can assist urological surgeons in making appropriate treatment decisions for predicting postoperative bleeding in PCNL.

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Section: Discussionmentioning

confidence: 99%

Preoperative prediction of bleeding complications in percutaneous nephrolithotomy using a machine learning model based on CT radiomics and clinical variables

Zou,

Yuan,

Zhou

et al. 2024

Preprint

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“…7 It has been reported that many factors are associated with increased blood loss in PCNL procedures, including surgeon experience and technique, prolonged operation time, preoperative anemia, diabetes, patient age, high BMI, increased stone burden, need for multiple or larger access tracts and history of previous renal surgery. 8,9 The literature review shows that there is no knowledge about the relation between increased blood loss and used antibiotics in the PCNL.…”

Section: Discussionmentioning

confidence: 99%

Can antibiotic preference affect bleeding in percutaneous nephrolithotomy? Retrospective comparative study of two commonly used antibiotics

Akkoç¹,

Aydın

Uçar³

et al. 2020

Pak J Med Sci

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Objective: Bleeding is one of the most common and alarming complication of percutaneous nephrolithotomy (PCNL). In this study, we aimed to compare the effects of ciprofloxacin and cefuroxime on the bleeding in PCNL procedures. Methods: The study was a retrospective analysis of 97 patients who underwent PCNL between February 2011 and June 2017. We just included the patients who had single tract lower pole PCNL for more objective evaluation of bleeding in the study. The patients were divided into two groups as ciprofloxacin group (Group-I, n:40) and cefuroxime group (Group-II, n:56) according to the type of antibiotic used in the operation. Patient age, gender, body mass index, stone size, preoperative INR, preoperative and postoperative platelet counts and difference, operative time, need for blood transfusion, postoperative fever, hospital stay, postoperative hemoglobin and hematocrit drop were analyzed. Results: There was no statistically significant difference in patients’ gender distribution, body mass index, preoperative INR, preoperative and postoperative platelet counts, preoperative and postoperative platelet difference, duration of operation, hospital stay, postoperative fever and need for postoperative blood transfusion between two antibiotic groups (p > 0.05). Mean patient age was 42,75±16,97 in Group-I and 35,54±14,71 in Group-II (p < 0.05). The mean stone size of Group-I and Group-II were 27,23±7,05 mm and 30,59±8,20, respectively (p < 0.05). The mean postoperative hemoglobin and hematocrit drop were significantly higher in Group-I than in Group-II. The mean hemoglobin drop was 1,73±0,95 for Group-I and 1,28±0,67 for Group-II (p < 0.05). The mean hematocrit drop was 5,17±2,76 for Group-I and 3,80±1,99 for Group-II (p < 0.05). Conclusion: On the basis of the results of the initial study, the antibiotic preference in patients undergoing surgery may be one of the bleeding factors during and after PCNL. doi: https://doi.org/10.12669/pjms.36.4.1977 How to cite this:Akkoc A, Aydin C, Ucar M, Topcuoglu M. Can antibiotic preference affect bleeding in percutaneous nephrolithotomy? Retrospective comparative study of two commonly used antibiotics. Pak J Med Sci. 2020;36(4):---------. doi: https://doi.org/10.12669/pjms.36.4.1977 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Analysis of factors affecting intraoperative hemorrhage during percutaneous nephrolithotomy and establishment of nomogram model

Xu,

Ji,

et al. 2024

Urolithiasis

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Predictive Factors For Intraoperative Blood Loss During Percutaneous Nephrolithotomy

Abstract: BMI, stone size, and operative time were strongly associated with intraoperative blood loss during PCNL.

Cited by 4 publications

References 13 publications

Preoperative prediction of bleeding complications in percutaneous nephrolithotomy using a machine learning model based on CT radiomics and clinical variables

Preoperative prediction of bleeding complications in percutaneous nephrolithotomy using a machine learning model based on CT radiomics and clinical variables

Can antibiotic preference affect bleeding in percutaneous nephrolithotomy? Retrospective comparative study of two commonly used antibiotics

Analysis of factors affecting intraoperative hemorrhage during percutaneous nephrolithotomy and establishment of nomogram model

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