Impact of elevated urine leukocyte and bacteria count per high-power field on the in-hospital outcome of patients with liver cirrhosis
Original Article

Impact of elevated urine leukocyte and bacteria count per high-power field on the in-hospital outcome of patients with liver cirrhosis

Dan Han1,2*, Ran Wang1,2*, Yang Yu1, Sien-Sing Yang3, Sebastian Mueller4, Fernando Gomes Romeiro5, Tingxue Song1,2, Han Deng2, Jing Li2, Zhong Peng2,6, Yibing Li7, Xiaozhong Guo1,2#, Xingshun Qi2#

1Postgraduate College, Liaoning University of Traditional Chinese Medicine, Shenyang 110032, China; 2Liver Cirrhosis Study Group, Department of Gastroenterology, General Hospital of Shenyang Military Area, Shenyang 110840, China; 3Liver Unit, Cathay General Hospital, Taipei, Taiwan; 4Department of Medicine and Center for Alcohol Research, Salem Medical Center, University of Heidelberg, Heidelberg, Germany; 5Department of Internal Medicine Botucatu Medical School, Universidade Estadual Paulista (UNESP), São Paulo State, Brazil; 6Postgraduate College, Dalian Medical University, Dalian 116044, China; 7Department of Nephrology, General Hospital of Shenyang Military Area, Shenyang 110840, China

Contributions: (I) Conception and design: X Qi, X Guo; (II) Administrative support: X Guo, X Qi; (III) Provision of study materials or patients: X Guo, X Qi; (IV) Collection and assembly of data: D Han, R Wang, T Song, H Deng, J Li, Z Peng; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

*These authors contributed equally to this work.

#These authors are the joint senior authors.

Correspondence to: Prof. Xiaozhong Guo; Dr. Xingshun Qi. Department of Gastroenterology, General Hospital of Shenyang Military Area, No. 83 Wenhua Road, Shenyang 110840, China. Email: guo_xiao_zhong@126.com; xingshunqi@126.com.

Background: Liver cirrhosis is prone to the development of urinary tract infection (UTI). Urine culture is a golden standard for the diagnosis of UTI, but it is often missing in routine clinical practice. Urinalysis may be an alternative. This study aimed to evaluate the prevalence of abnormal urinalysis and its impact on the in-hospital outcome of liver cirrhosis.

Method: Cirrhotic patients (n=2,067) who were admitted between July 2010 and June 2014 and underwent urinalyses were retrospectively enrolled. A urine leukocyte count of >4.33 and/or a urine bacteria count of >975 per high-power field were defined as abnormal urinalysis. Receiver-operator characteristic (ROC) curve analysis was performed to identify the capacity of urine leukocyte and bacteria count per high-power field for predicting the in-hospital death. The area under the ROC curve (AUROC) was calculated.

Results: The prevalence of elevated urine leukocyte and bacteria count per high-power field was 25.8% and 6.7%, respectively. The AUROC of urine leukocyte and bacteria count per high-power field for predicting the in-hospital death were 0.600 (P=0.015) and 0.600 (P=0.014), respectively. The best cut-off value of urine leukocyte per high-power field was 8.19 with a sensitivity of 34.5% and a specificity of 84.8%. The best cut-off value of urine bacteria per high-power field was 142.04 with a sensitivity of 38.6% and a specificity of 84.19%.

Conclusions: Abnormal urinalysis is common in liver cirrhosis and may be a predictor for the in-hospital death.

Keywords: Infection; liver cirrhosis; urinalysis; urine culture; death


Received: 07 June 2017; Accepted: 11 August 2017; Published: 30 August 2017.

doi: 10.21037/jphe.2017.08.02


Introduction

Bacterial infection is one of the most significant complications in patients with decompensated liver cirrhosis (1). Spontaneous bacterial peritonitis (SBP) and urinary tract infection (UTI) are the most common types of bacterial infections in cirrhotic patients (2). The proportion of UTI in all bacterial infections is 20–25% (3), and the most common bacteria that cause UTI are Escherichia coli (4). Bacterial infections confer to a 4-fold increase in the mortality of cirrhosis (5). However, it remains unclear whether or not UTI increases the risk of mortality in cirrhotic patients (6).

The golden standard for diagnosis of UTI is a urine culture with significant colony counts of a single organism in a sterile manner (7). However, urine culture is not frequently used in clinical practice, especially in outpatient settings (8), for several reasons. First, a urine culture is time consuming requiring 48 hours for the growth and identification of the pathogen and additional 48–72 hours for determining its antimicrobial susceptibility. Second, a large number of cirrhotic patients with UTI are asymptomatic so that a urine culture is often not obtained (9). Third, the clinicians often use their clinical judgment rather than the standard diagnostic criteria for bacterial infections (10).

By comparison, urinalysis, microscopy, and bedside urine dipsticks are readily and rapidly available, which allows the clinicians to initiate empiric treatment for suspected UTI while awaiting urine culture results (11). Fernandez et al. also put forward that uncountable leukocytes can be used as a basis for the diagnosis of UTI, even without the urine culture result (1).

Considering that urine culture is hardly available in the clinical setting, the present study aimed to analyze the results of routine urinalysis, exploring the prevalence of abnormal urinalysis and its effect on the in-hospital outcome of cirrhotic patients.


Methods

Patients

All patients with liver cirrhosis who were consecutively admitted to our hospital between July 2010 and June 2014 and underwent urinalyses at their admission were potentially eligible, but patients with hepatocellular carcinoma and other malignancies were excluded. The study protocol was approved by the ethic committee of our hospital. The number of ethical approval was k (2017) 02. Patients’ informed consents were waived. Demographic data, clinical presentation, regular laboratory tests, Child-Pugh class, and model for end-stage liver diseases (MELD) score were also collected.

Urinalyses

A clean-catch midstream urine specimen was taken to undergo the urinalyses. Data regarding urine leukocyte and bacteria count per high-power field were collected. Their reference ranges were 0.1–4.33 and 0.1–975, respectively. We defined the results of abnormal urinalysis as a urine leukocyte count per high-power field of >4.33 and/or a urine bacteria count per high-power field of >975. If two or more urinalyses were performed, the highest urine leukocyte and bacteria count per high-power field were selected.

Statistical analyses

Continuous data were expressed as the mean ± standard deviation and the median with minimum and maximum and were compared by non-parametric Mann-Whitney-Wilcoxon tests. Categorical data were expressed as the frequency (percentage) and were compared by Chi-square test. In all comparisons, a P value of <0.05 was considered statistically significant. Risk factors associated with elevated urine leukocyte and bacteria count per high-power field were assessed by logistic regression analyses. Statistically significant variables shown in univariate analyses were entered into the multivariate analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Receiver-operator characteristic (ROC) curve analyses were performed to identify the capacity of the urine leukocyte and bacteria count per high-power field in predicting the in-hospital mortality. Areas under the ROCs curve (AUROCs) with 95% CIs were calculated. The best cut-off value was selected as the sum of sensitivity and specificity was the maximum. Sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), and negative predictive value (NPV) with 95% CIs were reported. SPSS statistics 17.0.0 and MedCalc version 11.4.2.0 were employed for all statistical analysis.


Results

Patients

A total of 2,067 cirrhotic patients underwent the urinalyses, of whom 2,056 had the data regarding urine leukocyte count per high-power field (Table 1) and 2,031 had the data regarding urine bacteria count per high-power field (Table 2).

Table 1

Comparison between normal versus abnormal urine leukocyte count per high–power field in regular urine tests

Variables Total (n=2,056) Normal (n=1,526) Abnormal (n=530) P value
No. Pts available Mean ± SD or frequency (percentage) Median (range) No. Pts available Mean ± SD or frequency (percentage) Median (range) No. Pts available Mean ± SD or frequency (percentage) Median (range)
Sex (male/female), n (%) 2,056 1,357 (66.0%)/699 (34.0%) 1,526 1,135 (74.4%)/391 (25.6%) 530 222 (41.9%)/308 (58.1%) <0.0001
Age (years) 2,056 56.51±12.14 55.96 (6.20–89.23) 1,526 56.09±11.92 55.65 (6.20–89.23) 530 57.73±12.70 57.25 (14.37–86.84) 0.002
Etiology of liver diseases, n (%) 2,056 1,526 530 <0.0001
   HBV 592 (28.8%) 443 (29.0%) 149 (28.1%) 0.688
   HCV 134 (6.5%) 86 (5.6%) 48 (9.1%) 0.006
   HBV + HCV 14 (0.7%) 8 (0.5%) 6 (1.1%) 0.215
   Alcohol 482 (23.4%) 405 (26.5%) 77 (14.5%) <0.0001
   HBV + Alcohol 155 (7.5%) 133 (8.7%) 22 (4.2%) 0.001
   HCV + Alcohol 23 (1.1%) 17 (1.1%) 6 (1.1%) 0.973
   HBV + HCV + Alcohol 3 (0.1%) 1 (0.1%) 2 (0.4%) 0.165
   Others 210 (10.2%) 129 (8.5%) 81 (15.3%) <0.0001
   Unknown 443 (21.5%) 304 (19.9%) 139 (26.2%) 0.002
Ascites, n (%) 2,039 1,516 523 0.635
   No 1,034 (50.7%) 764 (50.4%) 270 (51.6%) 0.628
   Mild 270 (13.2%) 197 (13.0%) 73 (14.0%) 0.575
   Moderate to severe 735 (36.0%) 555 (36.6%) 180 (34.4%) 0.368
HE, n (%) 2,039 1,516 523 0.538
   No 1,895 (92.9%) 1,407 (92.8%) 488 (93.3%) 0.702
   Grade I–II 119 (5.8%) 88 (5.8%) 31 (5.9%) 0.918
   Grade III–IV 25 (1.2%) 21 (1.4%) 4 (0.8%) 0.266
Laboratory tests
   RBC (1012/L) 2,033 3.13±0.84 3.06 (0.90–6.80) 1,512 3.15±0.85 3.10 (0.90–6.80) 521 3.09±0.79 3 (1.10–5.90) 0.331
   Hb (g/L) 2,035 95.18±29.37 94 (23–218) 1,514 95.50±30.12 94 (23–218) 521 94.24±27.09 92 (29–176) 0.557
   WBC (109/L) 2,036 5.24±3.89 4.20 (0.30–46.10) 1,515 5.15±3.75 4.10 (0.50–33) 521 5.50±4.27 4.40 (0.30–46.10) 0.140
   PLT (109/L) 2,033 100.65±82.27 78 (10–1,278) 1,512 100.71±83.83 77 (11–1,278) 521 100.47±77.65 79 (10–545) 0.823
   TBIL (μmol/L) 2,027 40.83±65.33 22.10 (2–903) 1,508 40.71±62.16 22.40 (2–679.10) 519 41.19±73.85 21.50 (2.40–903) 0.435
   ALB (g/L) 1,990 32.19±6.87 32.20 (0.40–52.80) 1,483 32.59±6.82 32.60 (0.40–52.80) 507 1.03±6.87 30.80 (12.40–52.10) <0.0001
   ALT (U/L) 2,023 42.46±79.20 27 (4–1,460) 1,505 42.56±80.31 27 (5–1,460) 518 42.19±75.98 26 (4–1,064) 0.607
   AST (U/L) 2,023 58.53±92.46 37 (7–1,399) 1,505 56.12±76.77 36 (7–1,366) 518 65.53±127.38 37 (9–1,399) 0.445
   Ammonia (umol/L) 948 50.47±41.93 42 (8–480) 707 50.88±42.28 43 (8–480) 241 49.27±40.95 42 (8–236) 0.443
   ALP (U/L) 2,021 115.74±99.36 87 (12.80–980) 1,504 115.01±99.09 87.25 (12.80–980) 517 117.87±100.21 86 (17–889) 0.852
   PT (second) 1,996 16.36±4.54 15.40 (10.50–94.60) 1,480 16.26±4.03 15.40 (10.70–62.80) 516 16.65±5.77 15.40 (10.50–94.60) 0.981
   APTT (second) 1,994 43.17±10.34 41.80 (21.90–181) 1,479 42.76±8.91 41.70 (26.90–181) 515 44.34±13.60 42 (21.90–181) 0.148
   INR 1,993 1.35±0.56 1.22 (0.76–13.40) 1,478 1.33±0.48 1.22 (0.76–7.96) 515 1.39±0.76 1.22 (0.76–13.40) 0.902
   GGT (U/L) 2,019 115.89±202.22 50 (5–4,562) 1,502 121.50±216.86 51 (6–4,562) 517 99.62±150.90 47 (5–1,486) 0.037
   BUN (mmol/L) 1,990 7.54±6.13 5.81 (1.58–62.45) 1,474 7.20±5.38 5.74 (1.58–61.88) 516 8.52±7.82 6.07 (1.72–62.45) 0.004
   Cr (μmol/L) 1,990 82.17±106.60 59 (15–1,473) 1,474 76.57±91.49 60 (21–1473) 516 98.16±140 58.80 (15–1,069) 0.993
   K (mmol/L) 2,014 4.04±0.53 4 (2.26–8.28) 1,498 4.05±0.52 4 (2.26–6.85) 516 4.01±0.56 3.96 (2.27–8.28) 0.015
   Na (mmol/L) 2,014 138.40±4.40 139 (116.30–160.80) 1,498 138.40±4.16 138.90 (121–152.40) 516 138.37±5.06 139 (116.30–160.80) 0.443
   Ca (mmol/L) 983 2.10±0.22 2.10 (1.05–2.94) 720 2.10±0.22 2.11 (1.05–2.89) 263 2.09±0.21 2.09 (1.35–2.94) 0.186
Child–Pugh class, n (%) 1,912 1,427 485 0.467
   A 690 (36.1%) 515 (36.1%) 175 (36.1%) 0.998
   B 896 (46.9%) 677 (47.4%) 219 (45.2%) 0.383
   C 326 (17.1%) 235 (16.5%) 91 (18.8%) 0.246
Child–Pugh score 1,912 7.54±2.04 7 (5–15) 1,427 7.51±2 7 (5–15) 485 7.63±2.16 7 (5–14) 0.490
MELD score 1,936 7.50±7.39 6.14 (−9.67–54.94) 1,433 7.29±6.70 6.17 (–8.25–42.04) 503 8.12±9.07 6.11 (–9.67–54.94) 0.769
HPF–WBC (HPF) 2,056 24.25±255.62 1.46 (0.02–8,946.90) 1,526 1.25±1.02 0.92 (0.02–4.28) 530 90.49±497.90 10.95 (4.43–8,946.90) <0.0001
HPF–Bacteria (HPF) 2,031 272.53±1,107.03 7.13 (0.07–15,329.21) 1,506 106.16±538.29 3.98 (0.07–9,608.11) 525 749.75±1,899.42 42.19 (0.32–15,329.21) <0.0001
Death, n (%) 2,056 58 (2.8%) 1,526 35 (2.3%) 530 23 (4.3%) 0.014

ALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; APTT, activated partial thromboplastin time; AST, aspartate aminotransferase; BUN, blood urea nitrogen; Ca, calcium ion; Cr, creatinine; GGT, gamma–glutamyl transpeptidase; Hb, hemoglobin; HE, hepatic encephalopathy; HPF, high–power field; INR, international normalized ratio; K, potassium; MELD, model for end stage liver disease; Na, sodium ion; PLT, platelet; PT, prothrombin time; Pts, patients; RBC, red blood cell; TBIL, total bilirubin; WBC, white blood cell.

Table 2

Comparison between normal versus abnormal urine bacteria count per high–power field in regular urine tests

Variables Total (n=2,031) Normal (n=1894) Abnormal (n=137) P value
No. Pts available Mean ± SD or frequency (percentage) Median (range) No. Pts available Mean ± SD or frequency (percentage) Median (range) No. Pts available Mean ± SD or frequency (percentage) Median (range)
Sex (male/female), n (%) 2,031 1,342 (66.1%)/689 (33.9%) 1,894 1,298 (68.5%)/596 (31.5%) 137 44 (32.1%)/93 (67.9%) <0.0001
Age (years) 2,031 56.46±12.15 55.96 (6.20–89.23) 1,894 56.16±12.13 55.66 (6.20–89.23) 137 60.73±11.63 61.02 (30.30–85.38) <0.0001
Etiology of liver diseases, n (%) 2,031 1,894 137 0.001
   HBV 583 (28.7%) 546 (28.8%) 37 (27.0%) 0.649
   HCV 133 (6.5%) 125 (6.6%) 8 (5.8%) 0.728
   HBV + HCV 14 (0.7%) 12 (0.6%) 2 (1.5%) 0.243
   Alcohol 476 (23.4%) 453 (23.9%) 23 (16.8%) 0.057
   HBV + Alcohol 155 (7.6%) 153 (8.1%) 2 (1.5%) 0.005
   HCV + Alcohol 23 (1.1%) 23 (1.2%) 0 (0.0%) 0.398
   HBV + HCV + Alcohol 3 (0.1%) 3 (0.2%) 0 (0.0%) 1.000
   Others 209 (10.3%) 189 (10.0%) 20 (14.6%) 0.086
   Unknown 435 (21.4%) 390 (20.6%) 45 (32.8%) 0.001
Ascites, n (%) 2,014 1,878 136 0.308
   No 1,021 (50.7%) 953 (50.7%) 68 (50.0%) 0.867
   Mild 268 (13.3%) 255 (13.6%) 13 (9.6%) 0.183
   Moderate to Severe 725 (36.0%) 670 (35.7%) 55 (40.4%) 0.264
HE, n (%) 2,014 1,879 135 0.146
   No 1,870 (92.9%) 1,749 (93.1%) 121 (89.6%) 0.133
   Grade I–II 119 (5.9%) 106 (5.6%) 13 (9.6%) 0.058
   Grade III–IV 25 (1.2%) 24 (1.3%) 1 (0.7%) 1.000
Laboratory tests
   RBC (1012/L) 2,008 3.13±0.84 3.06 (0.93–6.78) 1,876 3.14±0.84 3.08 (0.93–6.78) 132 2.98±0.81 2.88 (1.25–5.57) 0.028
   Hb (g/L) 2,008 95.13±29.33 93 (23–218) 1,876 95.56±29.40 94 (23–218) 132 88.97±27.73 86 (29–159) 0.011
   WBC (109/L) 2,008 5.24±3.90 4.20 (0.30–46.10) 1,876 5.25±3.92 4.20 (0.50–46.10) 132 5.17±3.72 4.20 (0.30–26.30) 0.661
   PLT (109/L) 2,008 100.70±82.38 77.50 (10–1278) 1,876 101.10±83.23 78 (10–1278) 132 94.99±69.23 74.50 (13–443) 0.641
   TBIL (μmol/L) 2,003 40.56±64.85 22 (2–903) 1,869 39.99±64.12 22.20 (2–903) 134 48.58±74.14 20.70 (5.30–383.20) 0.827
   ALB (g/L) 1,967 32.22±6.84 32.20 (0.40–52.80) 1,837 32.33±6.85 32.40 (0.40–52.80) 130 30.60±6.48 30.50 (15.20–47.30) 0.004
   ALT (U/L) 1,999 42.49±79.62 27 (4–1,460) 1,865 42.17±77.74 27 (4–1460) 134 46.94±102.54 24 (7–748) 0.186
   AST (U/L) 1,999 58.35±92.63 37 (7–1,399) 1,865 57.04±82.75 37 (7–1366) 134 76.56±180.47 36 (10–1,399) 0.801
   Ammonia (μmol/L) 1,999 58.35±92.63 37 (7–1,399) 1,865 57.04±82.75 37 (7–1366) 134 76.56±180.47 36 (10–1,399) 0.801
   ALP (U/L) 903 52.05±42.15 43 (9–480) 847 51.68±42.05 43 (9–480) 56 57.70±43.63 48 (9–236) 0.241
   PT (second) 1,973 16.35±4.51 15.40 (10.50–94.60) 1,838 16.35±4.56 15.40 (10.50–94.60) 135 16.39±3.76 15.50 (11.50–38.90) 0.598
   APTT (second) 1,968 42.96±8.87 41.80 (21.90–152.70) 1,834 42.92±8.84 41.80 (21.90–152.70) 134 43.53±9.31 41.50 (28–81.70) 0.610
   INR 1,970 1.35±0.56 1.22 (0.76–13.40) 1,835 1.35±0.57 1.22 (0.76–13.40) 135 1.34±0.43 1.23 (0.84–4.13) 0.615
   GGT (U/L) 1,994 115.94±203.16 50 (5–4,562) 1,860 117.91±208.15 50 (5–4,562) 134 88.59±110.11 51.50 (8–709) 0.348
   BUN (mmol/L) 1,967 7.55±6.14 5.82 (1.58–62.45) 1,835 7.48±6.05 5.80 (1.58–62.45) 132 8.53±7.28 6.25 (1.95–44.34) 0.035
   Cr (μmol/L) 1,967 81.72±105.07 59 (15–1,473) 1,835 81.35±103.68 60 (15–1,473) 132 86.99±123.10 56 (29–919) 0.301
   K (mmol/L) 1,992 4.04±0.53 4 (2.26–8.28) 1,858 4.04±0.53 4 (2.27–8.28) 134 3.96±0.47 3.96 (2.26–5.38) 0.075
   Na (mmol/L) 1,992 138.38±4.56 139 (83–160.80) 1,858 138.42±4.50 139 (83–160.80) 134 137.85±5.37 138.90 (116.30–148) 0.484
   Ca (mmol/L) 970 2.10±0.22 2.10 (1.05–2.94) 895 2.09±0.22 2.10 (1.05–2.94) 75 2.12±0.20 2.10 (1.76–2.62) 0.341
Child–Pugh class, n (%) 1,891 1,764 127 0.516
   A 685 (36.2%) 643 (36.5%) 42 (33.1%) 0.444
   B 884 (46.7%) 825 (46.8%) 59 (46.5%) 0.946
   C 322 (17.0%) 296 (16.8%) 26 (20.5%) 0.285
Child–Pugh score 1,891 7.54±2.04 7 (5–15) 1,764 7.52±2.03 7 (5–15) 127 7.83±2.18 8 (5–14) 0.149
MELD score 1,915 7.46±7.35 6.11 (−9.67–54.94) 1,787 7.43±7.31 6.12 (–9.67–54.94) 128 7.90±7.93 6.11 (–4.56–35.30) 0.795
HPF–WBC (HPF) 2,031 24.50±257.18 1.44 (0.02–8,946.90) 1,894 10.69±74.88 1.35 (0.02–2,417.09) 137 215.38±932.64 14.09 (0.20–8,946.90) <0.0001
HPF–Bacteria (HPF) 2,031 272.53±1,107.03 7.13 (0.07–15,329.21) 1,894 56.18±139.60 5.58 (0.07–965.90) 137 3,263.51±2,890.99 2,213.55 (992.68–15,329.21) <0.0001
Death, n (%) 2,031 57 (2.8%) 1,894 47 (2.5%) 137 10 (7.3%) 0.004

ALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; APTT, activated partial thromboplastin time; AST, aspartate aminotransferase; BUN, blood urea nitrogen; Ca, calcium ion; Cr, creatinine; GGT, gamma–glutamyl transpeptidase; Hb, hemoglobin; HE, hepatic encephalopathy; HPF, high–power field; INR, international normalized ratio; K, potassium; MELD, model for end stage liver disease; Na, sodium ion; PLT, platelet; PT, prothrombin time; Pts, patients; RBC, red blood cell; TBIL, total bilirubin; WBC, white blood cell.

Urine leukocyte count per high-power field

The prevalence of elevated urine leukocyte count per high-power field was 25.8% (530/2,056). Elevated urine leukocyte count per high-power field was significantly associated with female, etiology of liver diseases, older age, higher blood urea nitrogen (BUN), and lower albumin (ALB), potassium, and gamma-glutamyl transpeptidase (GGT) (Table 1). Logistic regression multivariate analysis demonstrated that female (P<0.0001, OR =4.71), ALB (P<0.0001, OR =0.97), and BUN (P<0.0001, OR =1.05) were independently associated with elevated urine leukocyte count per high-power field (Table 3).

Table 3

Univariable and multivariable logistic analysis of abnormal urine leukocyte count per high–power field

Variables Univariable analysis Multivariable analysis
OR (95% CI) P OR (95% CI) P
HCV as an etiology of liver diseases
   Sex 4.03 (3.27–4.96) <0.0001 4.76 (3.77–6.00) <0.0001
   Age 1.01 (1.00–1.02) 0.007 0.99 (0.98–1.00) 0.071
   HCV 0.60 (0.42–0.87) 0.006 0.77 (0.51–1.15) 0.195
   ALB 0.97 (0.95–0.98) <0.0001 0.97 (0.95–0.98) <0.0001
   GGT 0.99 (0.99–1.00) 0.032 1.00 (0.99–1.00) 0.311
   BUN 1.03 (1.02–1.05) <0.0001 1.05 (1.03–1.06) <0.0001
   K 0.85 (0.70–1.02) 0.086
Alcohol as an etiology of liver diseases
   Sex 4.03 (3.27–4.96) <0.0001 4.64 (3.62–5.95) <0.0001
   Age 1.01 (1.00–1.02) 0.007 0.99 (0.98–1.00) 0.085
   Alcohol 2.13 (1.63–2.78) <0.0001 1.13 (0.83–1.55) 0.436
   ALB 0.97 (0.95–0.98) <0.0001 0.97 (0.95–0.98) <0.0001
   GGT 0.99 (0.99–1.00) 0.032 1.00 (0.99–1.00) 0.322
   BUN 1.03 (1.02–1.05) <0.0001 1.05 (1.03–1.06) <0.0001
   K 0.85 (0.70–1.02) 0.086
HBV + Alcohol as an etiology of liver diseases
   Sex 4.03 (3.27–4.96) <0.0001 4.74 (3.75–6.01) <0.0001
   Age 1.01 (1.00–1.02) 0.007 0.99 (0.98–1.00) 0.080
   HBV + Alcohol 2.21 (1.39–3.50) 0.001 1.16 (0.71–1.89) 0.563
   ALB 0.97 (0.95–0.98) <0.0001 0.97 (0.95–0.98) <0.0001
   GGT 0.99 (0.99–1.00) 0.032 1.00 (0.99–1.00) 0.260
   BUN 1.03 (1.02–1.05) <0.0001 1.05 (1.03–1.06) <0.0001
   K 0.85 (0.70–1.02) 0.086

ALB, albumin; BUN, blood urea nitrogen; GGT, gamma–glutamyl transpeptidase; HBV, hepatitis B virus; HCV, hepatitis C virus; K, potassium.

Elevated urine leukocyte count per high-power field was significantly associated with higher in-hospital mortality. In ROC analysis, the AUROC of urine leukocyte count per high-power field for predicting the in-hospital death was 0.600 (95% CI: 0.579–0.622, P=0.015) (Figure 1). The best cut-off value of urine leukocyte count per high-power field was 8.19, with a sensitivity of 34.5% (95% CI: 22.5–48.1%) and a specificity of 84.8% (95% CI: 83.1–86.3%). PLR and NLR were 2.27 (95% CI: 1.6–3.2) and 0.77 (95% CI: 0.6–1.0), respectively. PPV and NPV were 6.2% (95% CI: 3.8–9.4%) and 97.8% (95% CI: 97.0–98.4%), respectively.

Figure 1 ROC analysis of the urine leukocyte count per high-power field for predicting the in-hospital mortality. ROC, receiver-operator characteristic.

Urine bacteria count per high-power field

The prevalence of elevated urine bacteria count per high-power field was 6.7% (137/2,031). Elevated urine bacteria count per high-power field was significantly associated with female, etiology of liver diseases, higher age and BUN, and lower red blood cells, hemoglobin, and ALB (Table 2). Logistic regression multivariate analysis demonstrated that female (P<0.0001, OR =3.73), age (P=0.027, OR =1.02), and ALB (P=0.019, OR =0.96) were independently associated with elevated urine bacteria count per high-power field (Table 4).

Table 4

Univariable and multivariable logistic analysis of abnormal urine bacteria count per high–power field

Variables Univariable analysis Multivariable analysis
OR (95% CI) P OR (95% CI) P
Sex 4.60 (3.18–6.67) <0.0001 3.73 (2.50–5.58) <0.0001
Age 1.03 (1.02–1.05) <0.0001 1.02 (1.00–1.03) 0.027
HBV + Alcohol 5.93 (1.45–24.19) 0.013 2.34 (0.56–9.82) 0.245
ALB 0.96 (0.94–0.99) 0.005 0.96 (0.93–0.99) 0.019
RBC 0.79 (0.64–0.99) 0.037 1.33 (0.81–2.19) 0.262
Hb 0.99 (0.99–1.00) 0.013 0.99 (0.98–1.00) 0.095
BUN 1.02 (0.99–1.05) 0.062

ALB, albumin; BUN, blood urea nitrogen; Hb, hemoglobin; HBV, hepatitis B virus; RBC, red blood cell.

Elevated urine bacteria count per high-power field was significantly associated with higher in-hospital mortality. In ROC analysis, the AUROC of urine bacteria count per high-power field for predicting the in-hospital death was 0.600 (95% CI: 0.578–0.622, P=0.014) (Figure 2). The best cut-off value of urine bacteria count per high-power field was 142.04, with a sensitivity of 38.6% (95% CI: 26.0–52.4%) and a specificity of 84.19% (95% CI: 82.5–85.8%). PLR and NLR were 2.44 (95% CI: 1.8–3.4) and 0.73 (95% CI: 0.6–0.9), respectively. PPV and NPV were 6.6% (95% CI: 4.2–9.8%) and 97.9% (95% CI: 97.1–98.6%), respectively.

Figure 2 ROC analysis of the urine bacteria count per high-power field for predicting the in-hospital mortality. ROC, receiver-operator characteristic.

Discussion

We here demonstrate on a large single-center cohort a high prevalence of elevated urine leukocyte and bacteria count per high-power field of 25.8% and 6.7%, respectively. In addition, these simple screening tests predicted the in-hospital death with a moderate diagnostic accuracy. Although their sensitivity was low, they showed an excellent specificity of >80%.

Urinalysis represents a non-invasive, technically simple, and economic screening tool (12). Lee et al. suggested that the presence of at least 5 urine leukocyte counts per high-power field from urine specimen should be pyuria, which was observed in 67% (165/247) of patients(13). Cantey et al. pointed that urinalysis was positive if >10 leukocytes per oil immersion field were seen (14). Gieteling et al. indicated that the presence of ≥10 leucocytes per high-power field should be helpful for a diagnosis of UTI (15). Thus, urinalysis, such as urine leukocyte and bacteria count per high-power field, may be helpful to establish a rapid diagnosis of UTI in the absence of urine culture. If possible, empirical antibiotic treatment can be rapidly guided by abnormal urinalyses.

The prevalence of UTI in liver cirrhosis patients is 20–25%, which is confirmed on our cohort (3). We included a large number of cirrhotic patients over a 4-year period of time. Therefore, our data may be more generalizable.

The association between UTI and severity of liver dysfunction remained controversial. Previous studies demonstrated that the occurrence of UTI was associated with Child-Pugh score (9,16) and ascites (6,17). By contrast, our and Amato et al.’s (18) studies demonstrated that the prevalence of UTI was not significantly associated with liver disease severity. This discrepancy might be explained by the heterogeneity in the sample size, the patient characteristics and the use of diuretics.

It is generally accepted that patients with cirrhosis are susceptible to the development of infectious diseases and that bacterial infection may aggravate the deterioration of patients’ conditions, even leading them to death (19). Our study found a significant association between abnormal urinalysis (i.e., elevated urine leukocyte and/or bacteria count per high-power field count) and in-hospital mortality of cirrhotic patients. Indeed, in our patients, 23 of 58 deaths had an elevated urine leukocyte count per high-power field. Similarly, a retrospective observational cohort study also demonstrated an association of UTI with increased short-term mortality in patients with advanced cirrhosis (6). Despite the direct contribution of UTI to the risk of death in cirrhotic patients remained uncertain, abnormal urinalysis might be a predictor of worse prognosis. Evidence suggested that 42% of advanced liver disease patients with UTI have systemic inflammatory response syndrome (20) and that UTI is a strong reason for progressive renal failure in cirrhosis (21).

Our study had some limitations. First, we recorded urine leukocyte count per high-power field of >4.33. Abnormal urinalysis is not exactly equal to positive urine culture (22). Thus, our study could not accurately identify the diagnosis of UTI. Second, there was a potential risk of urine specimens’ contamination. Third, the symptoms related to UTI (i.e., fever, urinary frequency, and urinary urgency) were missing.

In conclusion, an elevated urine leukocyte and/or bacteria count per high-power field may be an adjuvant diagnostic criterion for UTI and should be a predictor for the in-hospital death in patients with liver cirrhosis. In future, some novel noninvasive screening tools for liver damage, such as M30 levels (23), or for liver fibrosis, such as transient elastography (24), should be combined with UTI to further evaluate the disease progression and outcome of liver cirrhosis.


Acknowledgments

Funding: This study was partially supported by the grants from the Natural Science Foundation of Liaoning Province (no. 2015020409) and China Postdoctoral Science Foundation (2015M582886) for Dr Xingshun Qi.


Footnote

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jphe.2017.08.02). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).The study protocol was approved by the ethic committee of our hospital. The number of ethical approval was k (2017) 02. Patients’ informed consents were waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

  1. Fernandez J, Navasa M, Gomez J, et al. Bacterial infections in cirrhosis: epidemiological changes with invasive procedures and norfloxacin prophylaxis. Hepatology 2002;35:140-8. [Crossref] [PubMed]
  2. Bajaj JS, O'Leary JG, Wong F, et al. Bacterial infections in end-stage liver disease: current challenges and future directions. Gut 2012;61:1219-25. [Crossref] [PubMed]
  3. Bunchorntavakul C, Chamroonkul N, Chavalitdhamrong D. Bacterial infections in cirrhosis: A critical review and practical guidance. World J Hepatol 2016;8:307-21. [Crossref] [PubMed]
  4. Xu Y, Wang JB, Wang S. Zhonghua Gan Zang Bing Za Zhi 2016;24:478-80. [Association between chronic urinary tract infection and primary biliary cirrhosis]. [PubMed]
  5. Arvaniti V, D'Amico G, Fede G, et al. Infections in patients with cirrhosis increase mortality four-fold and should be used in determining prognosis. Gastroenterology 2010;139:1246-56, 1256.e1-5.
  6. Reuken PA, Stallmach A, Bruns T. Mortality after urinary tract infections in patients with advanced cirrhosis - Relevance of acute kidney injury and comorbidities. Liver Int 2013;33:220-30. [Crossref] [PubMed]
  7. Yamasaki Y, Uemura O, Nagai T, et al. Pitfalls of diagnosing urinary tract infection in infants and young children. Pediatr Int 2017; [Crossref] [PubMed]
  8. Foxman B. Epidemiology of urinary tract infections: incidence, morbidity, and economic costs. Am J Med 2002;113:5S-13S. [Crossref] [PubMed]
  9. Borzio M, Salerno F, Piantoni L, et al. Bacterial infection in patients with advanced cirrhosis: a multicentre prospective study. Dig Liver Dis 2001;33:41-8. [Crossref] [PubMed]
  10. Caterino JM, Leininger R, Kline DM, et al. Accuracy of Current Diagnostic Criteria for Acute Bacterial Infection in Older Adults in the Emergency Department. J Am Geriatr Soc 2017; [Crossref] [PubMed]
  11. Felt JR, Yurkovich C, Garshott DM, et al. The Utility of Real-Time Quantitative Polymerase Chain Reaction Genotype Detection in the Diagnosis of Urinary Tract Infections in Children. Clin Pediatr (Phila) 2017;9922817706144 [PubMed]
  12. Sidler D, Huynh-Do U. Urinalysis in the 21st century: anything but obsolete! Praxis (Bern 1994) 2015;104:349-52.
  13. Lee JR, Bang H, Dadhania D, et al. Independent risk factors for urinary tract infection and for subsequent bacteremia or acute cellular rejection: a single-center report of 1166 kidney allograft recipients. Transplantation 2013;96:732-8. [Crossref] [PubMed]
  14. Cantey JB, Gaviria-Agudelo C, McElvania TeKippe E, et al. Lack of clinical utility of urine gram stain for suspected urinary tract infection in pediatric patients. J Clin Microbiol 2015;53:1282-5. [Crossref] [PubMed]
  15. Gieteling E, van de Leur JJ, Stegeman CA, et al. Accurate and fast diagnostic algorithm for febrile urinary tract infections in humans. Neth J Med 2014;72:356-62. [PubMed]
  16. Cadranel JF, Denis J, Pauwels A, et al. Prevalence and risk factors of bacteriuria in cirrhotic patients: a prospective case-control multicenter study in 244 patients. J Hepatol 1999;31:464-8. [Crossref] [PubMed]
  17. Bercoff E, Dechelotte P, Weber J, et al. Urinary tract infection in cirrhotic patients, a urodynamic explanation. Lancet 1985;1:987. [Crossref] [PubMed]
  18. Amato A, Precone DF, Carannante N, et al. Infez Med 2005;13:103-8. [Prevalence and risk factors for bacteriuria in patients with cirrhosis]. [PubMed]
  19. Christou L, Pappas G, Falagas ME. Bacterial infection-related morbidity and mortality in cirrhosis. Am J Gastroenterol 2007;102:1510-7. [Crossref] [PubMed]
  20. Cazzaniga M, Dionigi E, Gobbo G, et al. The systemic inflammatory response syndrome in cirrhotic patients: relationship with their in-hospital outcome. J Hepatol 2009;51:475-82. [Crossref] [PubMed]
  21. Kim JH, Lee JS, Lee SH, et al. Renal Dysfunction Induced by Bacterial Infection other than Spontaneous Bacterial Peritonitis in Patients with Cirrhosis: Incidence and Risk Factor. Gut Liver 2009;3:292-7. [Crossref] [PubMed]
  22. Waseem M, Chen J, Paudel G, et al. Can a simple urinalysis predict the causative agent and the antibiotic sensitivities? Pediatr Emerg Care 2014;30:244-7. [Crossref] [PubMed]
  23. Mueller S, Nahon P, Rausch V, et al. Caspase-cleaved keratin-18 fragments increase during alcohol withdrawal and predict liver-related death in patients with alcoholic liver disease. Hepatology 2017;66:96-107. [Crossref] [PubMed]
  24. Mueller S, Sandrin L. Liver stiffness: a novel parameter for the diagnosis of liver disease. Hepat Med 2010;2:49-67. [Crossref] [PubMed]
doi: 10.21037/jphe.2017.08.02
Cite this article as: Han D, Wang R, Yu Y, Yang SS, Mueller S, Romeiro FG, Song T, Deng H, Li J, Peng Z, Li Y, Guo X, Qi X. Impact of elevated urine leukocyte and bacteria count per high-power field on the in-hospital outcome of patients with liver cirrhosis. J Public Health Emerg 2017;1:73.

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