PERBEDAAN RERATA KADAR SERUM GLUTAMIC PYRUVATE TRANSAMINASE PADA PRIA DAN WANITA PENDERITA NON-ALCOHOLIC FATTY LIVER
DOI:
https://doi.org/10.46984/sebatik.v27i1.2260Keywords:
Liver, Metode Statistik, Penyakit, Kadar SGPT, NAFLDAbstract
Non-alcoholic fatty liver (NAFLD) atau penyakit hati berlemak non-alkohol adalah penyakit kerusakan hati yang umum ditemui dan tidak disebabkan oleh konsumsi alkohol. Peningkatan kadar Serum glutamic pyruvic transaminase (SGPT) yang merupakan salah satu enzim hati adalah temuan umum pada pasien NAFLD. Tujuan penelitian adalah ntuk mengetahui apakah terdapat perbedaan rerata kadar SGPT yang bermakna pada pria dan wanita penderita non alcoholic fatty liver (NAFLD) yang dilakukan menggunakan pendekatan analisis statistik. Studi ini dilakukan dengan menganalisis metode analisis data sekunder yang dipelajari sebelumnya. Penelitian ini dilakukan dengan metode analitik dengan pendekatan cross sectional menggunakan data sekunder. Sampel diambil dengan cara total population sampling yang memenuhi kriteria inklusi dan eksklusi. Kriteria inklusi adalah semua pasien dengan NAFLD yang terdiagnosis dengan abdominal ultrasound atau CT scan abdomen. Berdasarkan 63 sampel terkumpul analisis dilakukan dengan uji Mann Whitney, dengan tingkat kepercayaan 95%, didapatkan p-value = 0.015. Kesimpulan didapatkan perbedaan rerata kadar SGPT yang bermakna antara laki-laki dan perempuan penderita NAFLD. Hal ini dapat disebabkan oleh eksklusi asupan alkohol mungkin menyebabkan lebih banyak laki-laki yang terkena penyakit ini karena tingginya prevalensi asupan alkohol pada laki-laki. Resistensi insulin, lemak visceral, kadar SGPT, nilai trigliserida, rentang hati, status pendidikan rendah, dan aktivitas fisik adalah faktor potensial lain yang berkontribusi terhadap perbedaan yang diamati.
References
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Candia-Rivera, D., & Valenza, G. (2022). Cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney statistical tests. SoftwareX, 19, 101170. https://doi.org/10.1016/j.softx.2022.101170
Castera, L., Friedrich-Rust, M., & Loomba, R. (2019). Noninvasive Assessment of Liver Disease in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology, 156(5), 1264-1281.e4. https://doi.org/10.1053/j.gastro.2018.12.036
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Dumitrascu, D. L., & Neuman, M. G. (2018). NON-ALCOHOLIC FATTY LIVER DISEASE: AN UPDATE ON DIAGNOSIS. Medicine and Pharmacy Reports, 91(2), 147–150. https://doi.org/10.15386/cjmed-993
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Jung, T. Y., Kim, M. S., Hong, H. P., Kang, K. A., & Jun, D. W. (2020). Comparative Assessment and External Validation of Hepatic Steatosis Formulae in a Community-Based Setting. Journal of Clinical Medicine, 9(9), 2851. https://doi.org/10.3390/jcm9092851
Lazarus, J. V., Mark, H. E., Villota-Rivas, M., Palayew, A., Carrieri, P., Colombo, M., Ekstedt, M., Esmat, G., George, J., Marchesini, G., Novak, K., Ocama, P., Ratziu, V., Razavi, H., Romero-Gómez, M., Silva, M., Spearman, C. W., Tacke, F., Tsochatzis, E. A., … Sinkala, E. (2022). The global NAFLD policy review and preparedness index: Are countries ready to address this silent public health challenge? Journal of Hepatology, 76(4), 771–780. https://doi.org/10.1016/j.jhep.2021.10.025
Lee, C.-O., Li, H.-L., Tsoi, M.-F., Cheung, C.-L., & Cheung, B. M. Y. (2021). Association between the liver fat score (LFS) and cardiovascular diseases in the national health and nutrition examination survey 1999–2016. Annals of Medicine, 53(1), 1067–1075. https://doi.org/10.1080/07853890.2021.1943514
Liu, J., Ma, S., Xu, W., & Zhu, L. (2022). A generalized Wilcoxon–Mann–Whitney type test for multivariate data through pairwise distance. Journal of Multivariate Analysis, 190, 104946. https://doi.org/10.1016/j.jmva.2022.104946
Liu, Y., Liu, C., Li, J., Kim, T. H., Enomoto, H., & Qi, X. (2022). Risk stratification of decompensation using liver stiffness and platelet counts in compensated advanced chronic liver disease (CHESS2102). Journal of Hepatology, 76(1), 248–250. https://doi.org/10.1016/j.jhep.2021.10.006
Loosen, S. H., Kostev, K., Keitel, V., Tacke, F., Roderburg, C., & Luedde, T. (2022). An elevated FIB-4 score predicts liver cancer development: A longitudinal analysis from 29,999 patients with NAFLD. Journal of Hepatology, 76(1), 247–248. https://doi.org/10.1016/j.jhep.2021.08.030
Mertens, J., Weyler, J., Dirinck, E., Vonghia, L., Kwanten, W. J., Mortelmans, L., Peleman, C., Chotkoe, S., Spinhoven, M., Vanhevel, F., Van Gaal, L. F., De Winter, B. Y., De Block, C. E. M., & Francque, S. M. (2023). Prevalence, risk factors and diagnostic accuracy of non-invasive tests for NAFLD in people with type 1 diabetes. JHEP Reports, 100753. https://doi.org/10.1016/j.jhepr.2023.100753
Oh, T. R., Choi, H. S., Kim, C. S., Bae, E. H., Ma, S. K., Sung, S.-A., Kim, Y.-S., Oh, K. H., Ahn, C., & Kim, S. W. (2019). Hyperuricemia has increased the risk of progression of chronic kidney disease: propensity score matching analysis from the KNOW-CKD study. Scientific Reports, 9(1), 6681. https://doi.org/10.1038/s41598-019-43241-3
Puneem, U. S., Ramakrishnan, S. M. R., Sindgi, V. M., & Nagasubramanian, V. R. (2021). Gender differences in relation to hyperuricemia and nonalcoholic fatty liver disease among Type 2 diabetics in Telangana, India. Clinical Epidemiology and Global Health, 12, 100879. https://doi.org/10.1016/j.cegh.2021.100879
Reichelt, S., Pratschke, J., Engelmann, C., Neumann, U. P., Lurje, G., & Czigany, Z. (2022). Body composition and the skeletal muscle compartment in liver transplantation: Turning challenges into opportunities. American Journal of Transplantation, 22(8), 1943–1957. https://doi.org/10.1111/ajt.17089
Smida, Z., Cucala, L., Gannoun, A., & Durif, G. (2022). A Wilcoxon-Mann-Whitney spatial scan statistic for functional data. Computational Statistics & Data Analysis, 167, 107378. https://doi.org/10.1016/j.csda.2021.107378
Soto, E., Echagüe, J. V., & Vega, R. (1989). Computer program for statistical Mann-Whitney U nonparametric analysis of neuronal spike activity. Computer Methods and Programs in Biomedicine, 28(3), 197–200. https://doi.org/10.1016/0169-2607(89)90150-8
Venkatrao, M., Nagarathna, R., Majumdar, V., Patil, S. S., Rathi, S., & Nagendra, H. (2020). Prevalence of Obesity in India and Its Neurological Implications: A Multifactor Analysis of a Nationwide Cross-Sectional Study. Annals of Neurosciences, 27(3–4), 153–161. https://doi.org/10.1177/0972753120987465
Vuppalanchi, R., Siddiqui, M. S., Van Natta, M. L., Hallinan, E., Brandman, D., Kowdley, K., Neuschwander‐Tetri, B. A., Loomba, R., Dasarathy, S., Abdelmalek, M., Doo, E., Tonascia, J. A., Kleiner, D. E., Sanyal, A. J., & Chalasani, N. (2018). Performance characteristics of vibration‐controlled transient elastography for evaluation of nonalcoholic fatty liver disease. Hepatology, 67(1), 134–144. https://doi.org/10.1002/hep.29489
Wai-Sun Wong, V., Ekstedt, M., Lai-Hung Wong, G., & Hagström, H. (2023). Changing epidemiology, global trends and implications for outcomes of NAFLD. Journal of Hepatology. https://doi.org/10.1016/j.jhep.2023.04.036
Younossi, Z., Anstee, Q. M., Marietti, M., Hardy, T., Henry, L., Eslam, M., George, J., & Bugianesi, E. (2018). Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nature Reviews Gastroenterology & Hepatology, 15(1), 11–20. https://doi.org/10.1038/nrgastro.2017.109
Younossi, Z. M. (2019). Non-alcoholic fatty liver disease – A global public health perspective. Journal of Hepatology, 70(3), 531–544. https://doi.org/10.1016/j.jhep.2018.10.033
Zhao, F., Zhu, K., Zhao, Q., Liu, Q., Cao, J., Xia, G., Liu, Z., & Li, C. (2021). Holothuria leucospilota polysaccharides alleviate liver injury via AMPK and NF-κB signaling pathways in type 2 diabetic rats. Journal of Functional Foods, 85, 104657. https://doi.org/10.1016/j.jff.2021.104657
Atri, A., Jiwanmall, S. A., Nandyal, M. B., Kattula, D., Paravathareddy, S., Paul, T. V, Thomas, N., & Kapoor, N. (2020). The Prevalence and Predictors of Non-alcoholic Fatty Liver Disease in Morbidly Obese Women – A Cross-sectional Study from Southern India. European Endocrinology, 16(2), 152. https://doi.org/10.17925/EE.2020.16.2.152
Berzigotti, A., Tsochatzis, E., Boursier, J., Castera, L., Cazzagon, N., Friedrich-Rust, M., Petta, S., & Thiele, M. (2021). EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis – 2021 update. Journal of Hepatology, 75(3), 659–689. https://doi.org/10.1016/j.jhep.2021.05.025
Candia-Rivera, D., & Valenza, G. (2022). Cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney statistical tests. SoftwareX, 19, 101170. https://doi.org/10.1016/j.softx.2022.101170
Castera, L., Friedrich-Rust, M., & Loomba, R. (2019). Noninvasive Assessment of Liver Disease in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology, 156(5), 1264-1281.e4. https://doi.org/10.1053/j.gastro.2018.12.036
Caussy, C., Reeder, S. B., Sirlin, C. B., & Loomba, R. (2018). Noninvasive, Quantitative Assessment of Liver Fat by MRI‐PDFF as an Endpoint in NASH Trials. Hepatology, 68(2), 763–772. https://doi.org/10.1002/hep.29797
Cheung, C.-L., Lam, K. S., Wong, I. C., & Cheung, B. M. (2014). Non-invasive score identifies ultrasonography-diagnosed non-alcoholic fatty liver disease and predicts mortality in the USA. BMC Medicine, 12(1), 154. https://doi.org/10.1186/s12916-014-0154-x
Ciardullo, S., & Perseghin, G. (2022). Prevalence of elevated liver stiffness in patients with type 1 and type 2 diabetes: A systematic review and meta-analysis. Diabetes Research and Clinical Practice, 190, 109981. https://doi.org/10.1016/j.diabres.2022.109981
Dumitrascu, D. L., & Neuman, M. G. (2018). NON-ALCOHOLIC FATTY LIVER DISEASE: AN UPDATE ON DIAGNOSIS. Medicine and Pharmacy Reports, 91(2), 147–150. https://doi.org/10.15386/cjmed-993
Eslam, M., Newsome, P. N., Sarin, S. K., Anstee, Q. M., Targher, G., Romero-Gomez, M., Zelber-Sagi, S., Wai-Sun Wong, V., Dufour, J.-F., Schattenberg, J. M., Kawaguchi, T., Arrese, M., Valenti, L., Shiha, G., Tiribelli, C., Yki-Järvinen, H., Fan, J.-G., Grønbæk, H., Yilmaz, Y., … George, J. (2020). A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. Journal of Hepatology, 73(1), 202–209. https://doi.org/10.1016/j.jhep.2020.03.039
Ferraioli, G., & Monteiro, L. B. S. (2019). Ultrasound-based techniques for the diagnosis of liver steatosis. World Journal of Gastroenterology, 25(40), 6053–6062. https://doi.org/10.3748/wjg.v25.i40.6053
Jung, T. Y., Kim, M. S., Hong, H. P., Kang, K. A., & Jun, D. W. (2020). Comparative Assessment and External Validation of Hepatic Steatosis Formulae in a Community-Based Setting. Journal of Clinical Medicine, 9(9), 2851. https://doi.org/10.3390/jcm9092851
Lazarus, J. V., Mark, H. E., Villota-Rivas, M., Palayew, A., Carrieri, P., Colombo, M., Ekstedt, M., Esmat, G., George, J., Marchesini, G., Novak, K., Ocama, P., Ratziu, V., Razavi, H., Romero-Gómez, M., Silva, M., Spearman, C. W., Tacke, F., Tsochatzis, E. A., … Sinkala, E. (2022). The global NAFLD policy review and preparedness index: Are countries ready to address this silent public health challenge? Journal of Hepatology, 76(4), 771–780. https://doi.org/10.1016/j.jhep.2021.10.025
Lee, C.-O., Li, H.-L., Tsoi, M.-F., Cheung, C.-L., & Cheung, B. M. Y. (2021). Association between the liver fat score (LFS) and cardiovascular diseases in the national health and nutrition examination survey 1999–2016. Annals of Medicine, 53(1), 1067–1075. https://doi.org/10.1080/07853890.2021.1943514
Liu, J., Ma, S., Xu, W., & Zhu, L. (2022). A generalized Wilcoxon–Mann–Whitney type test for multivariate data through pairwise distance. Journal of Multivariate Analysis, 190, 104946. https://doi.org/10.1016/j.jmva.2022.104946
Liu, Y., Liu, C., Li, J., Kim, T. H., Enomoto, H., & Qi, X. (2022). Risk stratification of decompensation using liver stiffness and platelet counts in compensated advanced chronic liver disease (CHESS2102). Journal of Hepatology, 76(1), 248–250. https://doi.org/10.1016/j.jhep.2021.10.006
Loosen, S. H., Kostev, K., Keitel, V., Tacke, F., Roderburg, C., & Luedde, T. (2022). An elevated FIB-4 score predicts liver cancer development: A longitudinal analysis from 29,999 patients with NAFLD. Journal of Hepatology, 76(1), 247–248. https://doi.org/10.1016/j.jhep.2021.08.030
Mertens, J., Weyler, J., Dirinck, E., Vonghia, L., Kwanten, W. J., Mortelmans, L., Peleman, C., Chotkoe, S., Spinhoven, M., Vanhevel, F., Van Gaal, L. F., De Winter, B. Y., De Block, C. E. M., & Francque, S. M. (2023). Prevalence, risk factors and diagnostic accuracy of non-invasive tests for NAFLD in people with type 1 diabetes. JHEP Reports, 100753. https://doi.org/10.1016/j.jhepr.2023.100753
Oh, T. R., Choi, H. S., Kim, C. S., Bae, E. H., Ma, S. K., Sung, S.-A., Kim, Y.-S., Oh, K. H., Ahn, C., & Kim, S. W. (2019). Hyperuricemia has increased the risk of progression of chronic kidney disease: propensity score matching analysis from the KNOW-CKD study. Scientific Reports, 9(1), 6681. https://doi.org/10.1038/s41598-019-43241-3
Puneem, U. S., Ramakrishnan, S. M. R., Sindgi, V. M., & Nagasubramanian, V. R. (2021). Gender differences in relation to hyperuricemia and nonalcoholic fatty liver disease among Type 2 diabetics in Telangana, India. Clinical Epidemiology and Global Health, 12, 100879. https://doi.org/10.1016/j.cegh.2021.100879
Reichelt, S., Pratschke, J., Engelmann, C., Neumann, U. P., Lurje, G., & Czigany, Z. (2022). Body composition and the skeletal muscle compartment in liver transplantation: Turning challenges into opportunities. American Journal of Transplantation, 22(8), 1943–1957. https://doi.org/10.1111/ajt.17089
Smida, Z., Cucala, L., Gannoun, A., & Durif, G. (2022). A Wilcoxon-Mann-Whitney spatial scan statistic for functional data. Computational Statistics & Data Analysis, 167, 107378. https://doi.org/10.1016/j.csda.2021.107378
Soto, E., Echagüe, J. V., & Vega, R. (1989). Computer program for statistical Mann-Whitney U nonparametric analysis of neuronal spike activity. Computer Methods and Programs in Biomedicine, 28(3), 197–200. https://doi.org/10.1016/0169-2607(89)90150-8
Venkatrao, M., Nagarathna, R., Majumdar, V., Patil, S. S., Rathi, S., & Nagendra, H. (2020). Prevalence of Obesity in India and Its Neurological Implications: A Multifactor Analysis of a Nationwide Cross-Sectional Study. Annals of Neurosciences, 27(3–4), 153–161. https://doi.org/10.1177/0972753120987465
Vuppalanchi, R., Siddiqui, M. S., Van Natta, M. L., Hallinan, E., Brandman, D., Kowdley, K., Neuschwander‐Tetri, B. A., Loomba, R., Dasarathy, S., Abdelmalek, M., Doo, E., Tonascia, J. A., Kleiner, D. E., Sanyal, A. J., & Chalasani, N. (2018). Performance characteristics of vibration‐controlled transient elastography for evaluation of nonalcoholic fatty liver disease. Hepatology, 67(1), 134–144. https://doi.org/10.1002/hep.29489
Wai-Sun Wong, V., Ekstedt, M., Lai-Hung Wong, G., & Hagström, H. (2023). Changing epidemiology, global trends and implications for outcomes of NAFLD. Journal of Hepatology. https://doi.org/10.1016/j.jhep.2023.04.036
Younossi, Z., Anstee, Q. M., Marietti, M., Hardy, T., Henry, L., Eslam, M., George, J., & Bugianesi, E. (2018). Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nature Reviews Gastroenterology & Hepatology, 15(1), 11–20. https://doi.org/10.1038/nrgastro.2017.109
Younossi, Z. M. (2019). Non-alcoholic fatty liver disease – A global public health perspective. Journal of Hepatology, 70(3), 531–544. https://doi.org/10.1016/j.jhep.2018.10.033
Zhao, F., Zhu, K., Zhao, Q., Liu, Q., Cao, J., Xia, G., Liu, Z., & Li, C. (2021). Holothuria leucospilota polysaccharides alleviate liver injury via AMPK and NF-κB signaling pathways in type 2 diabetic rats. Journal of Functional Foods, 85, 104657. https://doi.org/10.1016/j.jff.2021.104657
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2023-06-06
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Mulyono, H. A., Martin, A., Johan, J. and Hadisono, H. (2023) “PERBEDAAN RERATA KADAR SERUM GLUTAMIC PYRUVATE TRANSAMINASE PADA PRIA DAN WANITA PENDERITA NON-ALCOHOLIC FATTY LIVER”, Sebatik, 27(1), pp. 355–362. doi: 10.46984/sebatik.v27i1.2260.
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