Evidence map›Paper›PMID 37436572›Full record

ArticleInternational urology and nephrology2023

Establishment of a new predictive model for the recurrence of upper urinary tract stones.

Kaiguo Xia, Yuexian Xu, Qiao Qi, Qingfeng Huang, Rui Yao, Junzhi Zhang, Zongyao Hao

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Article in International urology and nephrology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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3 · Its place in the literature

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6 citing papers in PubMed.

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5 · Who and what money

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7 authors.

Kaiguo Xia *Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Yuexian Xu *Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Qiao Qi *Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Qingfeng HuangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Rui YaoDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Junzhi ZhangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Zongyao HaoDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China. haozongyao@163.com.ORCID http://orcid.org/0000-0003-3399-3689

Funding

National Natural Science Foundation of China 82070724Natural Science Foundation of Anhui Province 1908085MH246
6 · The paper itself

Abstract

purposeTo construct a nomogram for evaluation of the recurrence risk of upper urinary tract stones in patients.

methodsWe retrospectively reviewed the clinical data of 657 patients with upper urinary tract stones and divided them into stone recurrence group and non-recurrence group. Blood routine, urine routine, biochemical, and urological CT examinations were searched from the electronic medical record, relevant clinical data were collected, including age, BMI, stones number and location, maximum diameter, hyperglycemia, hypertension, and relevant blood and urine parameters. The Wilcoxon rank-sum test, independent sample t test, and Chi-square test were used to preliminarily analyze the data of the two groups, then LASSO and logistic regression analysis were used to find out the significant difference indicators. Finally, R software was used to draw a nomogram to construct the model, and ROC curve was drawn to evaluate the sensitivity and specificity.

resultsThe results showed that multiple stones (OR: 1.832, 95% CI 1.240-2.706), bilateral stones (OR: 1.779, 95% CI 1.226-2.582), kidney stones (OR: 3.268, 95% CI 1.638-6.518), and kidney ureteral stones (OR: 3.375, 95% CI 1.649-6.906) were high risk factors. And the stone recurrence risk was positively correlated with creatinine (OR: 1.012, 95% CI 1.006-1.018), urine pH (OR: 1.967, 95% CI 1.343-2.883), Apo B (OR: 4.189, 95% CI 1.985-8.841) and negatively correlated with serum phosphorus (OR: 0.282, 95% CI 0.109-0.728). In addition, the sensitivity and specificity of the prediction model were 73.08% and 61.25%, diagnosis values were greater than any single variable.

conclusionThe nomogram model can effectively evaluate the recurrence risk of upper urinary stones, especially suitable for stone postoperative patients, to help reduce the possibility of postoperative stone recurrence.

Indexed as

Kidney CalculiUrinary CalculiUrinary TractHumansRetrospective StudiesRisk FactorsIndicatorsModelNomogramRecurrenceUpper urinary tract stones

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