Prediction of Surgical Intervention for Distal Ureteral Stones

Modai, Jonathan; Avda, Yuval; Shpunt, Igal; Abu-Ghanem, Yasmin; Leibovici, Dan; Shilo, Yaniv

doi:10.1089/end.2019.0187

Cited by 9 publications

(18 citation statements)

References 19 publications

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“…Age has been considered to negatively affect stone expulsion 9 , 13 presumably due to decreased ureteral peristalsis with aging 13 . That correlation, however, was not confirmed by the results of the present study nor by those of others 4 , 10 – 12 , 14 . recent study found that females tend to undergo a surgical intervention more often than males 9 , however many studies, including the present one, failed to demonstrate that finding 4 , 10 – 14 .…”

Section: Discussioncontrasting

confidence: 99%

“…Three studies examined previous spontaneous stone passage (SSP) and the likelihood of surgical intervention, and reached 3 different conclusions. While one study, similar to our findings, found no correlation 10 , another observed that a past history of nephrolithiasis directly correlated with higher odds for surgical intervention 11 . A third study reported a negative association between a previous SSP and the likelihood of surgical intervention 13 .…”

Section: Discussionsupporting

confidence: 83%

“…The relevant images (i.e., ultrasound [US] and computerized tomography [CT]) contained in each medical record were re-evaluated by a single fellowship-trained senior endourologist (DEZ). The stone’s maximal diameter was evaluated on the coronal CT plane as described elsewhere 10 . Given the retrospective nature of this study, informed consent has been waived by the Chaim Sheba Medical Center ethics committee.…”

Section: Methodsmentioning

confidence: 99%

“…We conducted a meticulous review of the relevant English literature in order to identify all possible factors that could predict spontaneous stone passage and built our database in accordance with variables that had been associated with stone expulsion or were explored in earlier studies on such a possible association. The variables that were extracted and included in our current analysis were : age and sex 9 – 14 , body mass index (BMI) 13 , the presence of concomitant diabetes mellitus (DM)/hypertension (HTN)/dyslipidemia 11 , 12 , history of ureteral stones 11 , 13 , hydronephrosis on imaging studies 9 , 10 , 12 , 15 , perinephric stranding on imaging studies 10 , 12 , 15 , ureteral side 14 , stone location (proximal/distal ureter) 3 , 5 , 9 , 12 , 14 , serum white blood cell (WBC) count 11 , 13 , 16 , neutrophil percentage (polymorphonuclears [PMN]) 10 , 16 , 17 , creatinine level 10 – 13 , C-reactive protein (CRP) level 13 , 17 , 18 , and length of hospital stay 9 . Additional variables included vital signs on admission (pulse, systolic/diastolic blood pressure) as well as the total number of visits to the emergency room before the index admission.…”

Section: Methodsmentioning

confidence: 99%

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A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

Haifler

Kleinmann

Haramaty

et al. 2022

Sci Rep

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A 75–89% expulsion rate is reported for ureteric stones ≤ 5 mm. We explored which parameters predict justified surgical intervention in cases of pain caused by < 5 mm ureteral stones. We retrospectively reviewed all patients with renal colic caused by ureteral stone < 5 mm admitted to our urology department between 2016 and 2021. Data on age, sex, body mass index, the presence of associated hydronephrosis/stranding on images, ureteral side, stone location, medical history, serum blood count, creatinine, C-reactive protein, and vital signs were obtained upon admission. XGboost (XG), a machine learning model has been implemented to predict the need for intervention. A total of 471 patients (median age 49, 83% males) were reviewed. 74% of the stones were located in the distal ureter. 160 (34%) patients who sustained persistent pain underwent surgical intervention. The operated patients had proximal stone location (56% vs. 10%, p < 0.001) larger stones (4 mm vs. 3 mm, p < 0.001), longer length of stay (3.5 vs. 3 days, p < 0.001) and more emergency-room (ER) visits prior to index admission (2 vs. 1, p = 0.007) compared to those who had no surgical intervention. The model accuracy was 0.8. Larger stone size and proximal location were the most important features in predicting the need for intervention. Altogether with pulse and ER visits, they contributed 73% of the final prediction for each patient. Although a high expulsion rate is expected for ureteral stones < 5 mm, some may be painful and drawn out in spontaneous passage. Decision-making for surgical intervention can be facilitated by the use of the present prediction model.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionsupporting

confidence: 83%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

Haifler

Kleinmann

Haramaty

et al. 2022

Sci Rep

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“…The consideration of patient factors is an important element when making treatment decisions for renal colic [13].In accordance with previous reports [14][15][16], our present analysis demonstrated that the duration of pain symptoms is a signi cant clinical predictor for surgical intervention. We found that patients with <4 days of pain were more likely to be treated effectively by conservative techniques, while those with ≥4 days of pain were more likely to undergo surgical intervention.…”

Section: Discussionsupporting

confidence: 91%

The identification of pregnant women with renal colic who may need surgical intervention

Maomao

Lei

Lin

et al. 2021

Preprint

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Objectives: To analyze clinical data and stone-related factors to identify predictive factors for surgical intervention in pregnant women with renal colic. Methods: We conducted a retrospective review of 212 pregnant women presenting with renal colic between 1st January 2009 and 31st December 2019. Patients were grouped according to surgical intervention and a range of demographic, clinical, laboratory, and ultrasound data were obtained. Univariate and multivariate analyses identified a range of predictive variables for surgical intervention. In addition, we used receiver operating characteristic (ROC) curve analysis to evaluate the predictive power of our model and created a nomogram for clinical application. Results: Of the 212 patients presenting with acute renal colic in pregnancy, 100 patients (47.2%) underwent surgical intervention and 112 patients (52.8%) were treated conservatively. Univariate analysis identified significant differences between the two groups with regards to fever, the duration of pain, white blood cells (WBCs), C-reactive protein (CRP), ureteral stone size, hydronephrosis, and stone location. Multivariate analysis further identified a number of independent predictors for surgical intervention, including fever, a duration of pain ≥4 days, a ureteral stone size ≥ 8 mm, and moderate or severe hydronephrosis.Conclusions: We identified several independent predictors for surgical intervention for renal colic in pregnancy. Fever, a duration of pain ≥4 days, a ureteral stone size ≥8 mm, and moderate/severe hydronephrosis, play significant roles in predicting surgical intervention. Our nomogram can help to calculate the probability of surgical intervention in a simple and efficient manner. Prospective studies are now required to validate our model.

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What is the role of inflammatory markers in predicting spontaneous ureteral stone passage?

Senel

Aykanat²,

Asfuroglu

et al. 2022

Aktuelle Urol

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Purpose: To investigate the role of inflammatory markers in predicting the spontaneous passage of ureteral stones. Methods: We retrospectively reviewed 279 patients with ureteral stones sized 4–10 mm that were managed conservatively. The patients were divided into two groups: Group 1 consisted of 137 patients who passed the stone spontaneously; Group 2 comprised 142 patients without spontaneous stone passage. The groups were compared using the Mann-Whitney U and chi-square tests. In addition, univariate and multivariate analyses were performed to identify the significance of the parameters. Results: The mean age of the patients was 41.2 years. The patients in Group 1 had a significantly lower mean stone size, white blood cell count and neutrophil count. In addition, stone location, presence of hydronephrosis and history of urolithiasis were significantly different between the groups. Neutrophil percentage, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were insignificantly lower in Group 1. In a multivariate analysis, stone size, distal location and hydronephrosis status significantly predicted the spontaneous stone passage. However, inflammatory markers including white blood cell count, neutrophil count and neutrophil-to-lymphocyte ratio could not determine the likelihood of spontaneous stone passage. Conclusion: Our results suggest that inflammatory markers are no meaningful parameters for the prediction of spontaneous stone passage.

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Prediction of Surgical Intervention for Distal Ureteral Stones

Cited by 9 publications

References 19 publications

A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

The identification of pregnant women with renal colic who may need surgical intervention

What is the role of inflammatory markers in predicting spontaneous ureteral stone passage?

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Prediction of Surgical Intervention for Distal Ureteral Stones

Cited by 9 publications

References 19 publications

A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

The identification of pregnant women with renal colic who may need&nbsp;surgical intervention

What is the role of inflammatory markers in predicting spontaneous ureteral stone passage?

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The identification of pregnant women with renal colic who may need surgical intervention