A Serum C-Reactive Protein and Procalcitonin-Based Risk Score to Predict Urinary Infection in Patients with Obstructive Urolithiasis Undergoing Decompression

Abstract

Objective:

The aim of this study was to develop a risk score utilizing C-reactive protein (CRP) and procalcitonin to better predict a clinical infection for patients with obstructive urolithiasis.

Methods:

A retrospective review was performed of patients presenting to the emergency room from December 2017 to February 2019 and who underwent upper urinary tract decompression due to concern for infection in the setting of obstructing urolithiasis. Over 30 clinical parameters were assessed and a composite risk score was created. Univariate and multivariate, forward, stepwise regression analyses were performed to identify predictors of true urinary tract infection (UTI).

Results:

Ninety-eight patients met inclusion criteria, of which a true UTI was identified in 50 (51%). The standard model of serum white blood cells >15 or temperature >38°C had an area under curve (AUC) of only 0.67 to predict UTI. A multivariable regression-based 4-point risk score (1 point for each of the following: positive urinary Gram stain, perinephric fat stranding on CT, serum CRP >21.95, and serum procalcitonin >0.36) had an AUC of 0.91 to predict UTI. Individually, these components had an AUC of 0.68, 0.68, 0.80, and 0.77, respectively. The chances of confirmed UTI were 8%, 11%, 68%, and 100% for risk scores of 0, 1, 2, and 3 to 4, respectively (p < 0.001).

Conclusions:

Only 50% of patients with a suspected UTI and an obstructing stone were ultimately confirmed to have a UTI. A risk score consisting of Gram stain, perinephric fat stranding, CRP, and procalcitonin can improve UTI prediction and warrants further study.

Introduction

Urolithiasis has a prevalence of 10% in the United States and costs over $2 billion per year.^1,2 The combination of obstructive urolithiasis and infected urine can become life threatening, and prompt renal decompression and antibiotics are the gold standard.^3
–5 It is often difficult to discern a urinary tract infection (UTI) from signs and symptoms associated with an acute stone episode, and the definitive diagnosis is typically made with a positive urine culture. However, cultures often take over 24 hours to result and the clinician is left to make the decision for renal decompression based on oft-conflicting surrogate clinical indicators.

Prior studies analyzing the utility of such surrogate indicators have demonstrated poor accuracy.^6
–8 With limited data, an American Urological Association (AUA) update suggested the use of clinical fever or serum white blood cells (WBCs) to trigger surgical decompression.³ A prior study by Rohloff and colleagues found that the combination of gender, urinalysis (UA) nitrite, UA leukocyte esterase, and pyuria predicted positive urine culture with 87% accuracy.⁶ However, the model was heavily reliant on urinary markers and therefore may not capture upstream infection in the setting of a completely obstructive stone.

In the context of these limitations, we explored the utility of C-reactive protein (CRP) and procalcitonin as serum inflammatory markers that may assist with prediction of a UTI in the setting of an acute stone. Preliminary studies with CRP and procalcitonin (PCT) have shown promise and they may outperform traditional markers for predicting urosepsis.^9,10 However, to our knowledge, a comprehensive UTI prediction model that incorporates these markers has not been created.

Herein, we use serum, urine, and radiographic markers to develop a UTI risk score for patients undergoing renal decompression due to suspected infection in the context of an obstructing urinary stone.

Methods

Patient cohort

A retrospective chart review was performed of patients presenting to the emergency department at our institution from December 2017 to February 2019 with an acute obstructing stone episode. Patients were identified through a review of the electronic medical record based on ICD-9 and ICD-10 codes for a principal diagnosis of urinary calculus (592 and N20–N23, respectively) and were only included if they underwent decompression with ureteral stent placement (common procedural technology [CPT] 52332) or percutaneous nephrostomy tube placement (CPT 50432) for concern of infection. This was determined based on review of clinical documentation and procedure indications. Patients undergoing urinary decompression for other indications (e.g., intractable pain and acute kidney injury), as well as pregnant patients, were excluded.

Variables analyzed

Patient demographics, risk factors, clinical presentation, serum laboratory values, urine laboratory values, and imaging findings were included. All patients underwent evaluation in the emergency department, including vital sign assessment, urine testing, serum complete blood count, metabolic panel, and CT scan of the abdomen and pelvis. Additional evaluation varied dependent upon individual clinician preference. We considered both borderline (1–3 bacteria/slide) and positive (≥4 bacteria/slide) Gram stain findings to be positive for our analysis. We defined pyuria as ≥50 WBCs/high-power field. The upper limit of normal for procalcitonin and CRP at our institution is 0.08 ng/mL and 8.0 mg/mL, respectively. Fat stranding was positive if the CT radiology report included mention of perinephric or periureteral stranding. For clinical risk factors, tobacco use and diabetes diagnosis were based on recorded medical history, and recurrent UTIs were defined as ≥3 patient-reported or clinically documented infections within the 12 months before the emergency department visit. The decision to perform decompression was determined by the physician at the time of evaluation based on concern for upper tract infection.

Primary outcome

The primary outcome was clinically significant UTI (csUTI), defined as the presence of either of the following: (1) >100,000 colony-forming units of a single organism obtained from bladder or upper urinary tract or positive blood cultures or (2) the presence of frankly purulent output at renal decompression. The term “clinically significant” was used for the purposes of nomenclature to identify patients meeting the above definition, but it should be noted that all patients in our cohort already had enough suspicion to warrant urgent decompression.

Secondary outcome

Given the often subjective nature of categorizing drainage proximal to the stone as purulent, a secondary analysis was performed with an alternative definition of a csUTI: >100,000 colony-forming units of a single organism obtained from bladder or upper urinary tract or positive blood cultures (Supplementary Data).

Statistical analyses

Patient demographics, risk factors, clinical presentation, urinary markers, serum markers, and imaging findings were compared between patients with and without a csUTI. Categorical variables were compared using chi-squared and continuous variables with t-tests/Wilcoxon rank-sum tests. Univariable logistic regression was then performed with the primary outcome of csUTI. For each variable found to have a significant association with csUTI, a receiver operating characteristic was created and the area under the curve reported. In addition, the positive predictive value and negative predictive value were tabulated, for which continuous variables were converted to binary variables. Cut points of 15 × 10⁹/L, 21.95 mg/L, and 0.36 ng/mL were selected for serum WBCs, CRP, and procalcitonin, respectively. The WBC cut point was chosen based on recommendations from the 2008 AUA update series published by Dr. Pearle.¹¹ The cut points for CRP and procalcitonin were not based on the upper threshold of normal as these values have no proven significance in the setting of suspected UTI, but rather were based on Youden's J statistic to identify the optimal threshold for conversion of a continuous variable to binary form.

A forward, stepwise, multivariable logistic regression was performed, including the variables that were found to be associated with csUTI on univariable analysis. Stepwise regression was performed with forward selection based on likelihood ratio improvement, with a threshold for entry and exit of 0.10. The factors remaining in the regression were used to create a predictive model for csUTI. All statistical analyses were performed using SPSS, v25.

Results

Cohort identification

Three thousand six patients presented to the emergency department with a diagnosis of urolithiasis from December 2017 to February 2019. Among these, 234 were admitted for decompression with stent or nephrostomy tube placement. One hundred thirty-six patients were excluded as they underwent decompression for noninfectious indications. The remaining 98 patients were included in the analysis as all underwent decompression for suspected infection within 24 hours of evaluation. The majority of patients had serum markers, including CRP (n = 88), PCT (n = 88), and lactate (n = 56). Similarly, UA with microscopy was collected from all patients; however, urine dipstick and Gram stain were collected for most patients (n = 62; n = 83).

Of the 98 patients, only 51% (n = 50) were found to have a csUTI. Specifically, identification of a csUTI was based on the observation of purulence, bladder culture, proximal urine culture, blood culture, or a combination of the above in 14% (n = 7), 16% (n = 8), 6% (n = 3), 2% (n = 1), and 62% (n = 31) of patients, respectively. Among the 43 (86%) patients with culture-proven infection, 15 (35%) patients had E. coli, 6 (14%) had Proteus, and 5 (12%) had Enterococcus.

Baseline characteristics

There were no significant differences in baseline characteristics among patients with or without csUTI, including age, gender, race, body mass index, history of recurrent UTIs, tobacco use, diabetes, or stone size (Table 1). Patients with csUTI were more likely to have a heart rate >90 BPM and maximum temperature >38°C at presentation. Urinary markers, including nitrite, leukocyte esterase, Gram stain, pyuria, and bacteria, were all significantly more likely to be positive for patients with csUTI. Similarly, WBCs, CRP, and procalcitonin were higher in the csUTI group. Perinephric or periureteral fat stranding on CT scan was associated with csUTI.

Table 1.

Baseline Characteristics

	Noninfected (n = 48)	Infected (n = 50)	p-Value
Patient factors
Age (years), mean (95% CI)	52 (47–58)	58 (53–63)	0.1
Gender, n (%)			0.86
Male	22 (46)	22 (44)
Female	26 (54)	28 (56)
Race, n (%)			0.56
Black	0 (0)	0 (0)
Hispanic	2 (4)	5 (5)
Not Hispanic	46 (96)	46 (92)
Unknown	0 (0)	1 (2)
Body mass index, mean (95% CI)	30.9 (28.2–33.7)	33.7 (31.0–36.3)	0.16
Maximum temperature >38°C, n (%)			<0.01^a
Yes	2 (4)	12 (24)
No	46 (96)	38 (76)
Unknown	0 (0)	0 (0)
SBP <90 mm Hg, n (%)			0.1
Yes	1 (2)	5 (10)
No	47 (98)	45 (90)
Unknown	0 (0)	0 (0)
HR >90 BPM, n (%)			0.01^a
Yes	8 (17)	20 (40)
No	40 (83)	30 (60)
Unknown	0 (0)	0 (0)
Recurrent UTI, n (%)			0.68
Yes	2 (4)	3 (6)
No	46 (96)	47 (94)
Unknown	0 (0)	0 (0)
Tobacco use, n (%)			0.63
Current	5 (11)	6 (12)
Prior	4 (8)	7 (14)
None	39 (81)	37 (74)
Unknown	0 (0)	0 (0)
Diabetes			0.11
Yes	7 (15)	14 (28)
No	41 (85)	36 (72)
Unknown	0 (0)	0(0)
Urinary markers
UA nitrite, n (%)			<0.01^a
Positive	1 (2)	10 (20)
Negative	34 (71)	17 (34)
Unknown	13 (17)	23 (46)
UA LE, n (%)			<0.01^a
Positive	8 (17)	22 (44)
Negative	27 (56)	6 (12)
Unknown	13 (17)	22 (44)
UA Gram stain, n (%)			<0.01^a
Positive	3 (6)	18 (36)
Negative	39 (81)	23 (46)
Unknown	6 (13)	9 (18)
UA WBCs >50/hpf, n (%)			<0.01^a
Yes	4 (8)	18 (36)
No	44 (92)	32 (64)
Unknown	0 (0)	0 (0)
UA bacteria+, n (%)			<0.01^a
Yes	7 (15)	24 (48)
No	17 (35)	10 (20)
Unknown	24 (50)	16 (32)
Serum markers
WBCs (10(9)/L), mean (95% CI) (n = 98)	10.2 (9.0–11.3)	12.3 (11.2–13.4)	0.01^a
C-reactive protein (mg/L), mean (95% CI) (n = 88)	21.6 (16.3–26.9)	105.7 (81.5–129.8)	<0.01^a
Procalcitonin (ng/mL), mean (95% CI) (n = 88)	0.2 (0.1–0.3)	10.5 (4.8–16.1)	0.01^a
Lactate (mmol/L), mean (95% CI) (n = 56)	1.9 (1.2–2.6)	2.2 (1.6–2.7)	0.54
Imaging
CT fat stranding, n (%)			<0.01^a
Yes	18 (38)	35 (70)
No	30 (62)	13 (26)
Unknown	0 (0)	2 (4)
Size of obstructing stone (mm), mean (95% CI)	6.4 (4.3–8.6)	9.5 (7.3–11.6)	0.05

Indicates significant values.

CI = confidence interval; HR = heart rate; LE = leukocyte esterase; SBP = systolic blood pressure; UA = urinalysis; UTI = urinary tract infection; WBC = white blood cell.

Univariable associations with csUTI

The results of the univariable logistic regression are summarized in Table 2 and Figure 1. Eleven factors were significantly associated with csUTI on univariable analysis: maximum temperature >38°C (odds ratio [OR] 7.3; 95% confidence interval [CI] 1.5–34.5), heart rate >90 beats per minute (OR 3.3; 95% CI 1.3–8.6), UA with positive nitrite (OR 20.0; 95% CI 2.36–169.39), leukocyte esterase (OR 12.4; 95% CI 3.7–41.0), Gram stain (OR 10.2; 95% CI 2.7–38.3), bacteriuria (OR 5.8; 95% CI 1.8–18.4), pyuria (OR 6.2; 95% CI 1.9–20.0), elevated serum WBCs (OR 1.1; 95% CI 1.0–1.3), CRP (OR 1.02; 95% CI 1.0–1.03), and procalcitonin (OR 2.0; 95% CI 1.1–3.6). In addition, perinephric and periureteral fat stranding was also found to be significantly associated with csUTI (OR 4.5; 95% CI 1.9–10.6). The area under curve (AUC), negative predictive value, and positive predicted value (PPV) for each of the above variables are reported in Figure 1.

FIG. 1.

Univariable prediction of clinically significant infection. AUC, area under curve; CRP, C-reactive protein; HR, heart rate; LE, leukocyte esterase; NPV, negative predictive value; PPV, positive predictive value; UA, urinalysis; WBC, white blood cell.

Table 2.

Univariable Logistic Regression

	OR (95% CI)	p-Value
Patient factors
Age		0.36
<65 years	Constant
≥65 years	1.49 (0.6–3.6)
Gender		0.86
Male	Constant
Female	1.1 (0.5–2.4)
Race		0.67
Not Hispanic	Constant
Black/Hispanic	1.5 (0.2–9.4)
Maximum temperature >38°C	7.3 (1.5–34.5)	0.01^a
SBP <90 mm Hg	5.2 (0.6–46.5)	0.14
HR >90 BPM	3.3 (1.3–8.6)	0.01^a
Recurrent UTI	1.5 (0.2–9.2)	0.68
Tobacco use	1.3 (0.7–2.5)	0.34
Diabetes	1.8 (0.8–3.7)	0.14
Urinary markers
UA nitrite+	20.0 (2.36–169.39)	0.01^a
UA LE+	12.4 (3.7–41.0)	<0.01^a
UA Gram stain+	10.2 (2.7–38.3)	<0.01^a
UA WBCs >50/hpf	6.2 (1.9–20.0)	<0.01^a
UA bacteria+	5.8 (1.8–18.4)	<0.01^a
Serum markers
WBCs	1.1 (1.0–1.3)	0.01^a
CRP	1.02 (1.0–1.03)	<0.01^a
Procalcitonin	2.0 (1.1–3.6)	0.02^a
Lactate	1.1 (0.8–1.6)	0.54
Imaging
CT fat stranding	4.5 (1.9–10.6)	<0.01^a
Size of stone (0–5 mm; 5–10 mm; or >10 mm)	1.3 (0.8–2.2)	0.31

Indicates significant values.

CRP = C-reactive protein; OR = odds ratio.

Multivariable analysis

On forward, stepwise, multivariable logistic regression, the following four variables remained in the model: UA Gram stain (OR 12.8; 95% CI 2.0–80.8), serum CRP (OR 1.02; 95% CI 1.0–1.04), serum procalcitonin (OR 2.8; 95% CI 0.4–20.7), and perinephric/periureteral fat stranding on CT scan (OR 5.3; 95% CI 1.2–24.2). The AUC for the four-variable regression model was 0.91 (Fig. 2). Since the model retained procalcitonin despite its OR's 95% CI overlapping with 1, another regression model without procalcitonin was created, which just included Gram stain, serum CRP, and perinephric/periureteral fat stranding, and this was found to have an AUC of 0.89.

FIG. 2.

ROC curve comparison. PCT, procalcitonin; ROC, receiver operating characteristic.

Both of these models had a higher AUC than only using the AUA update parameters (temperature >38°C and WBCs >15) to predict csUTI, which was found to be 0.67 (Fig. 2).

csUTI risk score

A csUTI risk score was created using the four variables retained in our model. The PPV of a csUTI increased incrementally as a function of the number of model variables found to be positive such that the PPV was 0.08, 0.11, 0.68, and 1.0 for 0 (n = 13), 1 (n = 18), 2 (n = 22), and 3–4 (n = 10, n = 4) positive model variables, respectively (Fig. 3).

FIG. 3.

Clinically significant infection prediction model.

Discussion

In a cohort of patients undergoing renal decompression for a suspected UTI during an acute stone episode, only 50% had a csUTI—highlighting the need to improve the detection of UTI in the context of obstructing stones. We developed a risk score for csUTI that performed well in our cohort (AUC = 0.91). A score of 0 or 1 was associated with a negative predictive value of about 90%, and further study may validate this score's utility in triaging patients with obstructing stones and equivocal signs and symptoms of infection. On the other hand, a score of 2 to 4 was associated with 70% chance or greater of a UTI, and we hypothesize that these patients may be more likely to benefit from urgent decompression.

Compared with other UTI prediction models, our model has unique strengths. For instance, Rohloff et al.'s model relied almost exclusively on urinary indicators of infection and is thus susceptible to errors.⁶ For instance, in the presence of a stone with high-grade obstruction, there may be no urine passing distal to the stone, thereby leading to a false negative bladder specimen. Our model uses a combination of serum, urine, and radiographic findings that evaluate the patient in a multifaceted manner and thus is conceptually less subject to missing an infection.

The utility of procalcitonin has been previously demonstrated in the setting of infection. Zheng and colleagues studied 267 patients undergoing percutaneous nephrolithotomy and found that PCT levels predicted postoperative sepsis with improved accuracy (AUC = 0.96) compared with WBCs alone (AUC = 0.63).¹² Furthermore, Ko and colleagues studied 49 patients who had urosepsis in the presence of an obstructing stone and found that procalcitonin improved prediction of those who would progress to septic shock (AUC = 0.93).¹⁰ A study by Papagiannopoulos et al. examined 22 patients with an obstructing stone and found that PCT had an AUC of 0.81 for predicting a positive culture.⁹ This complemented our assessment in which the AUC of procalcitonin for predicting UTI was 0.77.

Serum CRP is another indicator used in our model, and this agrees with prior literature.^13,14 A recent study demonstrated that CRP was a predictor of progression from sepsis to septic shock in patients with urinary obstruction.¹⁵ A prior study found that CRP had an AUC of 0.86 in predicting the need for urgent decompression in the setting of an obstructing stone, and the cutoff for elevated CRP was 28mg/L.¹⁶ This is similar to our study, in which CRP had an AUC of 0.80 in predicting a UTI at a cutoff of 22mg/L.

Our score also incorporates radiographic assessment of perinephric fat stranding, a finding identified in about 40% to 50% of patients with obstructing urinary stones.^17,18 A previous study by Farrell and colleagues on 148 patients presenting with an acute stone episode found that perinephric fat stranding was not associated with a positive urine culture.¹⁹ However, it is important to note that this was for all stone episodes and not for patients in which there was enough concern for infection to warrant renal decompression. Thus, in our cohort, the AUC of perinephric fat stranding for UTI prediction was 0.68 and its inclusion significantly improved the accuracy of our model.

This study also highlights clinical variables that were not independently associated with a positive urine culture. For instance, temperature over 38°C had an AUC of only 0.60 with a negative predictive value of 55%. Similarly, serum WBCs had an AUC of only 0.64 with a negative predictive value of 55%. Therefore, many patients with an underlying UTI in the presence of an obstructing stone may not have the more conventional signs of infection.

Given the emphasis placed on value-based care, it is important to consider associated costs. In particular, procalcitonin and CRP are likely not as commonly incorporated into standard practice as the other indicators in our model. However, based on the Healthcare Common Procedure Coding System (HCPCS), both procalcitonin (HCPCS 84145) and CRP (HCPCS 86140) are relatively inexpensive with Medicare reimbursement rates of $29.77 and $5.75, respectively.

This study is not without limitations. As a retrospective review, not all data points were available for all patients, reflecting practice patterns particular to our institution. Furthermore, only patients who underwent decompression were included in the study and therefore the true denominator is unknown. In addition, the definition of csUTI, specifically the return of frank pus on upper tract decompression, is a subjective finding and could lead to an interobserver reliability error. However, only 14% of csUTIs were based solely on frank pus without a concurrently positive culture. To further address this potential limitation, a secondary analysis was performed excluding return of frank pus on decompression as part of the definition of csUTI and nearly identical associations on univariable analysis were found, further supporting our primary results. On stepwise regression, two of the same variables (procalcitonin and positive gram stain) remained in the model. Further external validation of our risk score is planned using larger cohorts encompassing a broader range of scenarios pertaining to acute stone episodes.

Conclusions

Within a cohort of patients with suspected UTI and obstructing urolithiasis undergoing decompression, only 50% of patients were ultimately confirmed to have a csUTI. A risk score consisting of urine gram stain, perinephric fat stranding, CRP, and procalcitonin improved csUTI prediction. Future study is warranted to determine if such a score can inform the decision for urinary decompression in a suspected UTI and potentially reduce costs while improving care.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was obtained for this project.

Supplementary Material

Supplementary Data

Abbreviations Used

References

Scales

, Smith

, Hanley

, et al. Prevalence of kidney stones in the United States. Eur Urol, 2012; 62:160–165.

Pearle

, Calhoun

, Curhan

, et al. Urologic diseases in America project: Urolithiasis. J Urol, 2005; 173:848–857.

Pearle

, Goldfarb

, Assimos

, et al. Medical management of kidney stones: AUA guideline. J Urol, 2014; 192:316–324.

Mokhmalji

, Braun

, Martinez Portillo

, et al. Percutaneous nephrostomy versus ureteral stents for diversion of hydronephrosis caused by stones: A prospective, randomized clinical trial. J Urol, 2001; 165:1088–1092.

Pearle

, Pierce

, Miller

, et al. Optimal method of urgent decompression of the collecting system for obstruction and infection due to ureteral calculi. J Urol, 1998; 160:1260–1264.

Rohloff

, Shakuri-Rad

, McElrath

, et al. Which objective parameters are associated with a positive urine culture in the setting of ureteral calculi: The ureteral calculi urinary culture calculator. J Endourol, 2018; 32:1168–1172.

Mambatta

, Jayarajan

, Rashme

, et al. Reliability of dipstick assay in predicting urinary tract infection. J Fam Med Prim Care, 2015; 4:265–268.

dos Santos

, Weber

, Perez

LRR

. Evaluation of urinalysis parameters to predict urinary-tract infection. Braz J Infect Dis, 2007; 11:479–481.

Papagiannopoulos

, Whelan

, Ahmad

, et al. Procalcitonin is a strong predictor of urine culture results in patients with obstructing ureteral stones: A prospective, pilot study. Urol Ann, 2016; 8:277–280.

10.

, Ji

, Park

S-Y

, et al. Procalcitonin determined at emergency department as an early indicator of progression to septic shock in patient with sepsis associated with ureteral calculi. Int Braz J Urol, 2016; 42:270–276.

11.

Pearle

. Management of the acute stone event. Lesson 30, 2008; 27:281–292.

12.

Zheng

, Li

, Fu

, et al. Procalcitonin as an early diagnostic and monitoring tool in urosepsis following percutaneous nephrolithotomy. Urolithiasis, 2015; 43:41–47.

13.

Yilmaz

, Batislam

, Basar

, et al. The comparison and efficacy of 3 different alpha1-adrenergic blockers for distal ureteral stones. J Urol, 2005; 173:2010–2012.

14.

Wolff

, Boeckmann

, Mattelaer

, et al. Early detection of infected ureteral obstruction after SWL employing C-reactive protein. J Endourol, 1996; 10:523–526.

15.

Yamamichi

, Shigemura

, Kitagawa

, et al. Comparison between non-septic and septic cases in stone-related obstructive acute pyelonephritis and risk factors for septic shock: A multi-center retrospective study. J Infect Chemother, 2018; 24:902–906.

16.

Angulo

, Gaspar

, Rodríguez

, et al. The value of C-reactive protein determination in patients with renal colic to decide urgent urinary diversion. Urology, 2010; 76:301–306.

17.

Katz

, Lane

, Sommer

. Unenhanced helical CT of ureteral stones: Incidence of associated urinary tract findings. AJR Am J Roentgenol, 1996; 166:1319–1322.

18.

Yaqoob

, Usman

, Bari

, et al. Unenhanced helical CT of ureterolithiasis: Incidence of secondary urinary tract findings. J Pak Med Assoc, 2004; 54:2–5.

19.

Farrell

, Papagiannopoulos

, Ebersole

, et al. Perinephric fat stranding is associated with elevated creatinine among patients with acutely obstructing ureterolithiasis. J Endourol, 2018; 32:891–895.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB