Simplified calculation of bile cholesterol saturation index

Fen-Ming Zhang, Xin Jiang, Sha Li, Long-Gui Ning, Fang-Fang Guo, Guo-Qiang Xu

Department of Gastroenterology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310 0 03, China

Gallstones (cholelithiasis) are masses in the gallbladder or biliary tract that are caused by abnormally high levels of either cholesterol or bilirubin in bile [1] . It is a multifactorial disease and the main pathogenesis is the increased secretion of bile cholesterol, which can increase the cholesterol saturation index (CSI) of bile. Patients with CSI greater than 1 are more likely to develop gallstones. Bile is a kind of dark green to yellowish-brown liquid containing＞90% water. Cholesterol, lecithin and bile salts are the three main lipid species in bile and combined to form the main components of gallstones [1] .

Martin C. Carey’s group did an excellent job of generating critical tables for calculating the cholesterol saturation of native bile.They described a simple method for the rigorous derivation of lithogenic index or percent cholesterol saturation, embodying both relative and total lipid concentrations. They generated relative tables providing precise values for the maximal amount of cholesterol that would be soluble in bile at any total lipid concentration and bile salt-lecithin ratio, and allowing for rapid and accurate calculation of lithogenic index or percent cholesterol saturation from the molar concentration of cholesterol actually present in hepatic, gallbladder, and duodenal bile [2] . When calculating the CSI of bile, we all applied the method that Carey et al. proposed. The details are as follows: 1) calculate the molar concentration (mol%) of cholesterol, bile acid and lecithin, respectively, according to the molecular weight; 2) calculate the ratio of [lecithin]/[lecithin + bile acid]; 3) according to the ratio obtained in the previous step, consult Carey’s table to get the theoretical molar concentration of cholesterol; and 4) CSI = actual molar concentration of cholesterol theoretical molar concentration of cholesterol.

It seems to be a little complicated and time-consuming. Thus,we developed a software named “Biliary CSI Calculator” to simplify the calculation process, using a programming language named Python [3] and a GUI framework called PyQt5 [4] . The copyright of this software was applied. The specific method to get the software (Biliary CSI Calculator) can be found in the supplementary material (Fig. S1, S2). The interface of the software is shown in Fig. 1 .

For getting one CSI result, just input the molar concentration of bile acid, lecithin, cholesterol and the original mass concentration of total biliary lipid. Then, press the “Calc” button, and the CSI result will be calculated immediately and shown in the “CSI” text box, as shown in Fig. 2 . If you want to input new data to calculate, just press the “Clear”button.

For batch data, as shown in Fig. 3 , you should sequentially input all the data to the file “CSI-BatchData.csv” in advance,then press the “Calc from File in Batches” button, and results will be shown in the file of “CSI-BatchResult.csv”. Both the “CSIBatchData.csv”and “CSI-BatchResult.csv” can be open by Microsoft Excel.

In conclusion, we greatly appreciate and recognize the work by Carey et al. and our biliary CSI calculator can greatly simplify the calculation process.

Fig. 1. The software interface of “Biliary CSI Calculator”. BA: bile acid; PL: lecithin;Ch: cholesterol; TL: total biliary lipid; CSI: cholesterol saturation index.

Fig. 2. Software operation example. BA: bile acid; PL: lecithin; Ch: cholesterol; TL:total biliary lipid; CSI: cholesterol saturation index.

Fig. 3. Software operation example of a lot of data. BA: bile acid; PL: lecithin; Ch: cholesterol; TL: total biliary lipid; CSI: cholesterol saturation index.

Acknowledgments

None.

CRediT authorship contribution statement

Fen-Ming Zhang: Methodology, Writing - original draft. Xing Jiang: Data curation, Writing - review & editing. Sha Li: Format analysis, Supervision. Fang-Fang Guo: Software, Writing - review& editing. Guo-Qiang Xu: Conceptualization, Supervision, Funding acquisition, Writing - review & editing.

Funding

This study was supported by a grant from the National Natural Science Foundation of China (81870433).

Ethical approval

Not needed.

Competing interest

No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.hbpd.2022.01.001 .