Clinical significance of Serum APOC2 in type 2 diabetes mellitus combined with pyogenic liver abscess

Clinical significance of Serum APOC2 in type 2 diabetes mellitus combined with pyogenic liver abscess | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical significance of Serum APOC2 in type 2 diabetes mellitus combined with pyogenic liver abscess Ying Huang, Xiaoqin Chen, Hongyan Guo, Xin Zhang, Yuhai Hu, Tianbin Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4800290/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To investigate the diagnostic value of serum APOC2 in patients with diabetes mellitus combined with pyogenic liver abscess. Methods: From April 2023 to July 2023, 77 type 2 diabetes mellitus patients were included in The First Affiliated Hospital, Fujian Medical University which divided into two groups: diabetes mellitus (n=55) and diabetes mellitus combined with pyogenic liver abscess (n=22). Additionally, 27 healthy individuals served as the control group. Serum APOC2 levels were detected and compared among the groups. ROC curve and logistic regression analysis were performed to evaluate the diagnostic value of serum APOC2. Results: Serum APOC2 levels were significantly higher in diabetes mellitus patients compared to the healthy control group (4.681 vs 3.490 mg/dL, P =0.008). In diabetes mellitus combined with pyogenic liver abscess patients, APOC2 levels were significantly reduced (4.681 vs 2.470 mg/dL, P <0.001), but increased post-treatment (2.470 vs 4.323 mg/dL, P <0.001). ROC curve analysis showed high diagnostic accuracy for serum APOC2 in diabetes mellitus combined with pyogenic liver abscess (AUC=0.945, 95% CI: 0.870-0.999). Logistic regression analysis revealed that reduced serum APOC2 levels are a risk factor for diabetes mellitus combined with pyogenic liver abscess (OR=0.02, 95% CI=0.01~0.16, P =0.012). The diabetes mellitus combined with pyogenic liver abscess patients with lower APOC2 levels had higher ALT (101 U/L vs 31 U/L, P =0.038) and AST levels (55 U/L vs 28 U/L, P =0.007), suggesting that reduced serum APOC2 levels are associated with liver function damage. Conclusion: Serum APOC2 levels were significantly decreased in patients with diabetes mellitus combined with pyogenic liver abscess, serving as a potential marker for predicting the occurrence of this condition. Lower levels of APOC2 are strongly linked to liver function impairment. Diabetes mellitus Pyogenic liver abscess Serum APOC2 Liver damage Figures Figure 1 Figure 2 1. Introduction Pyogenic liver abscess (PLA) is an intrahepatic infection caused by purulent bacteria with an incidence of 12 ~ 18 patients per 100,000 population annually in Asian countries and an estimated mortality rate of 2 ~ 31% [ 1 ] 。Typical PLA symptoms include upper right abdominal pain, fever and vomiting, along with nausea, vomiting, loss of appetite, and weight loss. The overuse of antibiotics and an ageing populations have altered the clinical manifestations of PLA, making it easy to miss or misdiagnose [ 2 ] . Diabetes mellitus is one of the high-risk factors for PLA and 29.3%~44.3% of diabetes mellitus patients also have PLA [ 3 , 4 ] . When diabetes mellitus complicated with PLA, it often comes with vascular and neural complications which reduce the body's sensitivity to pain, resulting in atypical local symptoms making early diagnosis more difficult [ 5 ] . If not diagnosed and treated promptly, diabetes mellitus combined with PLA may lead to widespread suppurative infections, causing conditions such as endophthalmitis, uveitis, lung abscesses, brain abscesses, and suppurative meningitis, potentially leading to death [ 6 ] . Therefore, finding early diagnostic markers for diabetes mellitus combined with PLA is essential for their treatment and prognosis evaluation. APOC2 is a member of the apolipoprotein gene family found on triglyceride-rich lipoproteins (TRL), such as chylomicrons (CM) and very low-density lipoproteins (VLDL), and high-density lipoproteins (HDL). It can activate lipoprotein lipase (LPL) to hydrolyses triglycerides, providing free fatty acids [ 7 ] . Elevated serum APOC2 levels are closely linked with diabetes mellitus [ 8 – 10 ] , atherosclerosis, and metabolic syndrome [ 11 , 12 ] and are positively correlated with cardiovascular mortality [ 13 ] . APOC2 is specifically expressed in the liver, and its expression levels are influenced by liver function [ 7 ] . Studies have shown that elevated serum APOC2 levels are noted in diabetic mellitus patients [ 8 , 9 ] , however, how its expression changes when diabetes mellitus is complicated by PLA, and whether it can serve as a marker for predicting the occurrence of PLA in diabetes mellitus patients, has not been studied. Therefore, this study evaluates serum APOC2 levels in diabetes mellitus patients at the First Affiliated Hospital of Fujian Medical University from April 2023 to July 2023, to determine its potential as an early diagnostic marker for diabetes mellitus combined with PLA. 2. Materials and Methods 2.1 Patients This retrospective case-control study included 77 diabetes mellitus patients visited the First Affiliated Hospital of Fujian Medical University from April 2023 to July 2023, among which 22 were diabetes mellitus combined with PLA. Simultaneously, 27 healthy individuals from the hospital's physical examination center served as the control group. The diabetes mellitus group comprised 30 males and 25 females, aged 59 (52.5 ~ 70.5) years. The diabetes mellitus combined with PLA group included 17 males and 5 females, aged 59 (52.25 ~ 67.75) years. The healthy control group consisted of 14 males and 13 females, aged 50 (44.5 ~ 54.5) years. There were no significant gender differences among the three groups. Additionally, we also gathered basic information (age, gender, hospitalization duration and underlying diseases), symptoms (fever and abdominal pain), laboratory tests, imaging studies (ultrasound and CT for lesion size), complications, and etiological examinations in diabetes mellitus patients combined with PLA. Inclusion criteria for diabetes mellitus: all patients met the 1999 WHO diagnostic criteria for type 2 diabetes mellitus. Diagnostic criteria for PLA: (1) typical imaging changes such as B-ultrasound, CT, or MRI showing liver abscess; (2) confirmed by liver puncture or surgical evidence; (3) in the absence of typical imaging and etiological evidence, abscess shrinks, disappears, and symptoms alleviate after antibiotic treatment. Those patients with tuberculous liver abscess, amoebic liver abscess, hydatid disease of the liver, concomitant tumors, hematological system diseases, autoimmune diseases, chronic liver or kidney diseases and thyroid diseases were excluded. This study was authorized by the Ethics Committee of the First Affiliated Hospital of Fujian Medical University (approval number [2022]075). Informed consent was obtained from all participants. 2.2 Data Collection Data were obtained from the hospital medical electronic records system. For each enrolled patient, the following clinical data were documented: demographic data(age and gender), clinical symptoms, underlying conditions, laboratory results, imaging findings and outcomes. Fasting venous blood of patients was extracted within 24 hours of admission and analyzed by using Roche Cobas c 702 analyzer. In addition, serum APOC2 levels on day 1 and at discharge were measured. 2.3 Statistical analysis Statistical analysis was performed using SPSS software. Normally distributed quantitative data are presented as Mean ± SD, while non-normally distributed quantitative data are shown as median (Interquartile Range). The independent sample t -test was used for comparisons between two groups with normally distributed data, and one-way ANOVA for three groups. For non-normally distributed data, the Mann-Whitney U test was used for two-group comparisons, and the Kruskal-Wallis H test for three group comparisons. Categorical data are shown as case numbers (%), with group comparisons made using the χ ² test or Fisher's exact test. P value of less than 0.05 was considered statistically significant. 3. Results 3.1 Demographic Data The baseline data among the diabetes mellitus, diabetes mellitus combined with PLA, and the healthy control were compared as shown in Table 1 . There were no significant differences in gender among the groups ( P > 0.05). Serum APOC2 levels in diabetes mellitus patients were significantly higher than those in healthy controls (4.681 (4.114 ~ 5.712) vs 3.490 (2.967 ~ 3.845) mg/dL, P = 0.008). However, in diabetes mellitus combined with PLA, serum APOC2 levels were significantly lower than those in diabetes mellitus patients (2.470 (2.202 ~ 3.034) vs 4.681 (4.114 ~ 5.712) mg/dL, P < 0.001) (Fig. 1 A). In patients with diabetes mellitus combined with PLA, paired t -tests showed a significant increase in serum APOC2 levels before and after treatment (2.470 (2.202 ~ 3.034) vs 4.323 (3.719 ~ 4.776) mg/dL, P < 0.001) (Fig. 1 B). These results indicate that serum APOC2 levels significantly decrease when diabetes mellitus is combined with PLA but significantly increase and return to normal after treatment. Table 1 Comparison of clinical baseline data among the diabetes mellitus, diabetes mellitus combined with PLA and healthy control Variables Healthy Control (n = 27) Diabetes mellitus (n = 55) Diabetes mellitus combined with PLA (n = 22) P1 P2 P3 Sex, n (%) 0.132 1 0.112 female 13 (48.148) 25 (45.455) 5 (22.727) male 14 (51.852) 30 (54.545) 17 (77.273) Age (years), Median (Q1,Q3) 50 (44.5, 54.5) 59 (52.5, 70.5) 59 (52.25, 67.75) 0.002 < 0.001 0.817 TBIL (µmol/L), Median (Q1,Q3) 10 (7.8, 11.1) 9.5 (7.2, 13.9) 8.6 (6.2, 29.2) 0.943 0.834 0.761 ALB (g/L), Median (Q1,Q3) 44.7 (43.7, 47.8) 43.1 (40.15, 45.1) 34.1 (27.5, 37) < 0.001 < 0.001 < 0.001 ALT (U/L), Median (Q1,Q3) 15 (13, 19) 22 (14.25, 34) 35 (26.5, 102.75) < 0.001 0.002 < 0.001 AST (U/L), Median (Q1,Q3) 18 (17, 18.5) 22 (18, 28.75) 34.5 (26.25, 57.5) < 0.001 0.002 < 0.001 GGT (U/L), Median (Q1,Q3) 17 (13, 21) 23 (14, 40) 131 (96.5, 191.75) < 0.001 0.009 < 0.001 ALP (U/L), Median (Q1,Q3) 68 (55, 76.5) 69 (55, 82) 156.5 (119.75, 221.25) < 0.001 0.593 < 0.001 TCHO(mmol/L), Median (Q1,Q3) 4.09 (3.835, 4.525) 4.57 (3.85, 5) 3.25 (2.985, 3.585) < 0.001 0.054 < 0.001 Tg(mmol/L), Median (Q1,Q3) 1.01 (0.785, 1.255) 1.47 (1.105, 2.23) 1.16 (0.85, 1.585) < 0.001 < 0.001 0.034 HDL(mmol/L), Median (Q1,Q3) 1.319 ± 0.142 1.207 ± 0.351 0.801 ± 0.293 < 0.001 0.114 < 0.001 LDL(mmol/L), Median (Q1,Q3) 2.62 (2.42, 2.985) 2.67 (2.15, 3.24) 1.92 (1.445, 2.335) 0.001 0.798 0.001 APOA1(g/L), Median (Q1,Q3) 1.42 (1.355, 1.535) 1.335 (1.19, 1.53) 0.68 (0.48, 0.765) < 0.001 0.203 < 0.001 APOB (g/L), Median (Q1,Q3) 0.83 (0.76, 0.925) 0.985 (0.85, 1.192) 0.85 (0.735, 0.995) 0.002 < 0.001 0.018 APOC2 (mg/dL), Median (Q1,Q3) 3.49 (2.967, 3.845) 4.681 (4.114, 5.712) 2.470 (2.202, 3.034) < 0.001 < 0.001 < 0.001 GLU (mmol/L), Median (Q1,Q3) 4.55 (4.34, 4.885) 7.29 (5.99, 8.59) 6.535 (5.49, 9.75) < 0.001 < 0.001 0.594 HBA1c (%), Median (Q1,Q3) 5.6 (5.175, 6.225) 7.4 (6.7, 8.8) 7 (6.15, 8.8) < 0.001 < 0.001 0.48 P1 : One-Way ANOVA of diabetes mellitus, diabetes mellitus with PLA, and healthy control group, P2 : Comparison between diabetes mellitus and healthy control, P3 : Comparison between diabetes mellitus and diabetes mellitus combined with PLA 3.2 The diagnostic value of serum APOC2 in diabetes mellitus combined with PLA The ROC curve analysis shows that APOC2 has an AUC of 0.94 (95% CI: 0.870 ~ 0.999) for diagnosing diabetes mellitus combined with PLA, with an optimal cutoff value of 3.403 mg/dL, and both sensitivity and specificity are 0.909 (Fig. 2 ). Furthermore, through univariate and multivariate logistic regression analysis, it was found that after adjusting for gender and age, a decrease in serum APOC2 is a risk factor for PLA in diabetes mellitus patients (OR = 0.02 (0.01, 0.16), P = 0.012) (Table 2 ). Table 2 Univariable and multivariate logistic regression analysis to predict PLA in diabetes mellitus Baseline variable Univariate analysis Multivariate analysis OR(95%CI) P value OR(95%CI) P value Sex female — — — — male 2.833(0.916–8.768) 0.071 30.5(0.85–1113) 0.12 Age (years) 1.007(0.973–1.043) 0.671 1.07(0.97, 1.24) 0.3 TBIL (µmol/L) 1.073(1.006–1.144) 0.033 — — ALB (g/L) 0.661(0.542–0.806) < 0.001 0.41(0.14, 0.72) 0.023 ALT (U/L) 1.038(1.015–1.062) 0.001 — — AST (U/L) 1.062(1.017–1.109) 0.006 — — GGT (U/L) 1.036(1.02–1.054) < 0.001 — — ALP (U/L) 1.042(1.02–1.064) < 0.001 — — TCHO(mmol/L) 0.154(0.057–0.418) < 0.001 — — Tg(mmol/L) 0.553(0.264–1.157) 0.116 — — HDL(mmol/L) 0.013(0.001–0.124) < 0.001 — — LDL(mmol/L) 0.334(0.161–0.694) 0.003 — — APOA1(g/L) 0.001(0.001–0.003) 0.001 — — APOB (g/L) 0.042(0.003–0.646) 0.023 — — APOC2 (mg/dL 0.104(0.035–0.307) < 0.001 0.02(0.00, 0.16) 0.012 GLU (mmol/L) 0.989(0.827–1.181) 0.9 — — HBA1c (%) 0.952(0.717–1.263) 0.731 — — OR: Odds ratio 3.3 Correlation between serum APOC2 levels and baseline variables of diabetes mellitus combined with PLA Based on the median levels of APOC2, diabetes mellitus combined with PLA were divided into high and low APOC2 level groups. As shown in Table 3 , in the low-APOC2 level group, ALT levels (101 (43.5 ~ 131.5) vs 31 (21 ~ 34) U/L, P = 0.038) and AST levels were significantly elevated (55 (39.5 ~ 103.5) vs 28 (24 ~ 34), U/L, P = 0.007), indicating that reduced serum APOC2 levels are closely associated with liver function damage. Table 3 Correlation between serum APOC2 levels and baseline variables of diabetes mellitus combined with PLA Variables Total (n = 22) APOC2 median (n = 11) P Sex, n (%) 0.311 Female 5 (22.727) 4 (36.364) 1 (9.091) Male 17 (77.273) 7 (63.636) 10 (90.909) Age 59.909 ± 11.731 55.455 ± 9.554 64.364 ± 12.412 0.075 Hospital stays (d) 18.048 ± 7.883 20.182 ± 8.953 15.7 ± 6.111 0.194 Hypertension, n (%) 0.635 No 16 (72.727) 9 (81.818) 7 (63.636) Yes 6 (27.273) 2 (18.182) 4 (36.364) Maximal body temperature (℃) 38.214 ± 0.98 38.064 ± 1.155 38.38 ± 0.771 0.467 Abdominal pain (%) 0.199 No 12 (54.545) 4 (36.364) 8 (72.727) Yes 10 (45.455) 7 (63.636) 3 (27.273) Vomit (%) 0.149 No 16 (72.727) 6 (54.545) 10 (90.909) Yes 6 (27.273) 5 (45.455) 1 (9.091) Maximal diameter of abscess (cm) 5.5 (4.35, 6.45) 5.7 (5.425, 6.55) 5.025 (4.025, 5.575) 0.14 TBIL (µmol/L),Median (Q1,Q3) 8.6 (6.2, 29.2) 8.2 (6.7, 38.4) 8.85 (5.95, 26.175) 0.418 ALB (g/L), Median (Q1,Q3) 32.995 ± 5.495 32.391 ± 5.494 33.66 ± 5.713 0.611 ALT (U/L), Median (Q1,Q3) 35 (26.5, 102.75) 101 (43.5, 131.5) 31 (21, 34) 0.038 AST (U/L), Median (Q1,Q3) 34.5 (26.25, 57.5) 55 (39.5, 103.5) 28 (24, 34) 0.007 GGT (U/L), Median (Q1,Q3) 156.5 (119.75, 221.25) 165 (126.5, 222.5) 146 (113, 219) 0.603 ALP (U/L), Median (Q1,Q3) 152.5 ± 88.114 140.818 ± 67.391 166.778 ± 111.111 0.55 TCHO(mmol/L),Median (Q1,Q3) 3.361 ± 0.818 3.048 ± 0.624 3.708 ± 0.899 0.087 Tg(mmol/L),Median (Q1,Q3) 1.16 (0.85, 1.585) 1.015 (0.84, 1.22) 1.27 (0.97, 1.93) 0.211 HDL(mmol/L),Median (Q1,Q3) 0.801 ± 0.293 0.825 ± 0.329 0.776 ± 0.266 0.704 LDL(mmol/L),Median (Q1,Q3) 1.928 ± 0.844 1.851 ± 0.674 2.014 ± 1.037 0.694 APOA1(g/L), Median (Q1,Q3) 0.641 ± 0.256 0.573 ± 0.2 0.717 ± 0.3 0.245 APOB (g/L), Median (Q1,Q3) 0.864 ± 0.187 0.844 ± 0.198 0.886 ± 0.183 0.64 GLU(mmol/L),Median (Q1,Q3) 6.535 (5.49, 9.75) 7.105 (5.01, 9.93) 6.535 (6.13, 8.38) 0.579 HBA1c (%),Median (Q1,Q3) 7.86 ± 2.396 8.044 ± 2.512 7.583 ± 2.414 0.728 CRP (g/L), Mean ± SD 148.857 ± 99.837 165.415 ± 80.177 132.3 ± 117.898 0.451 4. Discussion PLA patients have a variety of clinical manifestations, and the classic triad of fever and right upper abdominal pain doesn't always show up, making early diagnosis a challenge for clinicians [ 4 ] . Compared to patients without type 2 diabetes mellitus, those with type 2 diabetes mellitus are more prone to PLA and their clinical symptoms are less typical, mainly featuring chills and high fever rather than noticeable abdominal pain, leading to a higher rate of missed or incorrect diagnoses [ 14 ] . With the rise in cases of diabetes mellitus combined with PLA, early diagnosis has become increasingly urgent and crucial. This study find that serum APOC2 levels are significantly decreased in diabetes mellitus patients combined with PLA compared to diabetes mellitus patients. Further, APOC2 levels significantly increased post-treatment in diabetes mellitus patients combined with PLA. In addition, ROC curve analysis and logistic regression analysis revealed that reduced serum APOC2 levels are a risk factor and had high diagnostic accuracy for diabetes mellitus combined with PLA. Therefore, APOC2 could be a potential marker for predicting the occurrence of PLA in diabetic patients, providing a new clue for early diagnosis. Liver is the body's APOC2 synthesis organ. In this study, diabetes mellitus combined with PLA patients are divided into two groups based on the levels of APOC2. PLA patients in low-APOC2 group have higher ALT and AST, which are the indication of liver damage. In addition, we find that the abscess diameter of the patients in the low-APOC2 group are larger than that in the high-APOC2 group. Our study indicates that PLA could affect the production of APOC2.Therefore, continuous dynamic monitoring APOC2 may provide references for the treatment and prognosis of diabetes mellitus combined with PLA. This study has some limitations. Firstly, there are few cases of diabetes mellitus combined with PLA, and the study is single-centered. In the future, more multi-centered samples will be added to further clarify the diagnostic value of serum APOC2. Secondly, this study only collected serum APOC2 results within 24 hours of admission and at discharge, without continuous dynamic monitoring. Continuous follow-up results might better understand the relationship between APOC2 and infection process. Lastly, the role of serum APOC2 in diabetes mellitus combined with PLA still need more in vitro/in vivo experiments to exemplify. In summary, serum APOC2 is significantly reduced in diabetes mellitus combined with PLA, with a more notable reduction when liver function is abnormal. It can return to normal levels after treatment and recovery, making it a potential biomarker for early diagnosis and prognosis of diabetes mellitus combined with PLA. Declarations Conflict of interest The authors declared no conflict of interest. Ethical Approval This single-center retrospective study was approved by the Research Ethics Committee of the First Affiliated Hospital of Fujian Medical University and followed the principles of the Declaration of Helsinki. Informed Consent Written informed consent was obtained from all the patients for their consent to participate in this study and for their data to be used for research purposes and all private information of the included patients was erased. Author Contribution Tianbin Chen designed and supervised the study. Ying Huang and Xiaoqin Chen collected clinical information and performed measurement of laboratory data. Hongyan Guo and Xin Zhang contributed to the data analysis and interpretation. Yuhai Hu and Tianbin Chen contributed to the drafting and revision of the article. The corresponding authors attest that all listed authors met the authorship criteria and that no others meeting the criteria were omitted. All listed authors read and approved the final version of the manuscript. Acknowledgement This study was supported by National Natural Science Foundation of China (grant numbers: 82272420) and Education Scientific Research Projects for Middle-aged Young Teachers from the Education Department Fujian Province(No.JAT200130). Data Availability The datasets and supporting materials of this article are available on reasonable request. References Yin D, Ji C, Zhang S, et al. Clinical characteristics and management of 1572 patients with pyogenic liver abscess: A 12-year retrospective study [J]. Liver international: official J Int Association Study Liver. 2021;41(4):810–8. Lederman ER, Crum NF. Pyogenic liver abscess with a focus on Klebsiella pneumoniae as a primary pathogen: an emerging disease with unique clinical characteristics [J]. Am J Gastroenterol. 2005;100(2):322–31. Tian LT, Yao K, Zhang XY, et al. 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Hsu CC, Kanter JE, Kothari V, et al. Quartet of APOCs and the Different Roles They Play in Diabetes [J]. Arterioscler Thromb Vasc Biol. 2023;43(7):1124–33. Beliard S, Nogueira JP, Maraninchi M, et al. Parallel increase of plasma apoproteins C-II and C-III in Type 2 diabetic patients [J]. Diabet Med. 2009;26(7):736–9. Wang S, Lu Z, Wang Y et al. Metalloproteins and apolipoprotein C: candidate plasma biomarkers of T2DM screened by comparative proteomics and lipidomics in ZDF rats [J]. Nutr Metab (Lond), 2020, 17(66. Kei AA, Filippatos TD, Tsimihodimos V, et al. A review of the role of apolipoprotein C-II in lipoprotein metabolism and cardiovascular disease [J]. Metabolism. 2012;61(7):906–21. Chen WL, Tain YL, Chen HE et al. Cardiovascular Disease Risk in Children With Chronic Kidney Disease: Impact of Apolipoprotein C-II and Apolipoprotein C-III [J]. Front Pediatr, 2021, 9(706323. Silbernagel G, Chen YQ, Rief M, et al. Inverse association between apolipoprotein C-II and cardiovascular mortality: role of lipoprotein lipase activity modulation [J]. Eur Heart J. 2023;44(25):2335–45. Du Z, Zhou X, Zhao J, et al. Effect of diabetes mellitus on short-term prognosis of 227 pyogenic liver abscess patients after hospitalization [J]. BMC Infect Dis. 2020;20(1):145. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4800290","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332194861,"identity":"8a6c1a23-f235-4cf1-8401-a0b52f243a75","order_by":0,"name":"Ying Huang","email":"","orcid":"","institution":"Longyan Hospital of Traditional Chinese Medicine Affiliated To Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Huang","suffix":""},{"id":332194862,"identity":"20e31d2d-25af-42be-9b9f-c7fea17adc33","order_by":1,"name":"Xiaoqin Chen","email":"","orcid":"","institution":"Wuping County Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqin","middleName":"","lastName":"Chen","suffix":""},{"id":332194863,"identity":"be2662c6-5018-452f-82f7-ddb3be19bde0","order_by":2,"name":"Hongyan Guo","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongyan","middleName":"","lastName":"Guo","suffix":""},{"id":332194864,"identity":"dabdc313-ed2b-49f9-b10b-0e4a9d49e474","order_by":3,"name":"Xin Zhang","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zhang","suffix":""},{"id":332194865,"identity":"716c907b-b086-4e57-8e6b-a58eaafbbe2c","order_by":4,"name":"Yuhai Hu","email":"","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuhai","middleName":"","lastName":"Hu","suffix":""},{"id":332194866,"identity":"234d9251-e3f6-40d5-8c9b-2f254300fd26","order_by":5,"name":"Tianbin Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYDACZh4QeYDBgL2x8cEHUrRIGPAcbjacQZw1MC0S6W3SHMRoMGfnPfjhQ82dOnPJhw3SDAx2croNBLRYNvMlS8449kzCcnZig3EBQ7Kx2QECWgwO8xhI8zYcljC4ndiQPIPhQOI2IrQY/wZruXmw4TAPkVrMILbcYGxsJlqL5YxjhyV39iQ2M84wIMYv588Y3/hQc5jfnP348x8fKuzkCGpBN4E05aNgFIyCUTAKcAAAHNtESXixfxgAAAAASUVORK5CYII=","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tianbin","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-07-25 08:36:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4800290/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4800290/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61809153,"identity":"ae8990b7-ddb8-4946-a3be-7c938e5e8f9d","added_by":"auto","created_at":"2024-08-05 20:14:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76166,"visible":true,"origin":"","legend":"\u003cp\u003eA: Serum APOC2 levels in healthy controls, diabetes mellitus, and diabetes mellitus combined with PLA. B: Serum APOC2 levels in diabetes mellitus combined with PLA patients before and after treatment\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4800290/v1/6c5589735d52ed03a28fcad7.png"},{"id":61809155,"identity":"256da67e-e32f-4f82-a05d-bbf25addfce6","added_by":"auto","created_at":"2024-08-05 20:14:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36806,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of serum APOC2 for the prediction of PLA in diabetes mellitus patients\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4800290/v1/267091ac5e21fb489cff68c0.png"},{"id":61810741,"identity":"57497acf-e37f-43f2-b523-e6ffabd88e20","added_by":"auto","created_at":"2024-08-05 20:22:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":797355,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4800290/v1/7c37f07a-9e30-41fa-8447-db2c71e0fe12.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical significance of Serum APOC2 in type 2 diabetes mellitus combined with pyogenic liver abscess","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePyogenic liver abscess (PLA) is an intrahepatic infection caused by purulent bacteria with an incidence of 12\u0026thinsp;~\u0026thinsp;18 patients per 100,000 population annually in Asian countries and an estimated mortality rate of 2\u0026thinsp;~\u0026thinsp;31%\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e。Typical PLA symptoms include upper right abdominal pain, fever and vomiting, along with nausea, vomiting, loss of appetite, and weight loss. The overuse of antibiotics and an ageing populations have altered the clinical manifestations of PLA, making it easy to miss or misdiagnose\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Diabetes mellitus is one of the high-risk factors for PLA and 29.3%~44.3% of diabetes mellitus patients also have PLA\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. When diabetes mellitus complicated with PLA, it often comes with vascular and neural complications which reduce the body's sensitivity to pain, resulting in atypical local symptoms making early diagnosis more difficult\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. If not diagnosed and treated promptly, diabetes mellitus combined with PLA may lead to widespread suppurative infections, causing conditions such as endophthalmitis, uveitis, lung abscesses, brain abscesses, and suppurative meningitis, potentially leading to death\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Therefore, finding early diagnostic markers for diabetes mellitus combined with PLA is essential for their treatment and prognosis evaluation.\u003c/p\u003e \u003cp\u003eAPOC2 is a member of the apolipoprotein gene family found on triglyceride-rich\u003c/p\u003e \u003cp\u003elipoproteins (TRL), such as chylomicrons (CM) and very low-density lipoproteins (VLDL), and high-density lipoproteins (HDL). It can activate lipoprotein lipase (LPL) to hydrolyses triglycerides, providing free fatty acids\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Elevated serum APOC2 levels are closely linked with diabetes mellitus\u003csup\u003e[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, atherosclerosis, and metabolic syndrome\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e and are positively correlated with cardiovascular mortality\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAPOC2 is specifically expressed in the liver, and its expression levels are influenced by liver function\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that elevated serum APOC2 levels are noted in diabetic mellitus patients\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, however, how its expression changes when diabetes mellitus is complicated by PLA, and whether it can serve as a marker for predicting the occurrence of PLA in diabetes mellitus patients, has not been studied. Therefore, this study evaluates serum APOC2 levels in diabetes mellitus patients at the First Affiliated Hospital of Fujian Medical University from April 2023 to July 2023, to determine its potential as an early diagnostic marker for diabetes mellitus combined with PLA.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patients\u003c/h2\u003e \u003cp\u003eThis retrospective case-control study included 77 diabetes mellitus patients visited the First Affiliated Hospital of Fujian Medical University from April 2023 to July 2023, among which 22 were diabetes mellitus combined with PLA. Simultaneously, 27 healthy individuals from the hospital's physical examination center served as the control group. The diabetes mellitus group comprised 30 males and 25 females, aged 59 (52.5\u0026thinsp;~\u0026thinsp;70.5) years. The diabetes mellitus combined with PLA group included 17 males and 5 females, aged 59 (52.25\u0026thinsp;~\u0026thinsp;67.75) years. The healthy control group consisted of 14 males and 13 females, aged 50 (44.5\u0026thinsp;~\u0026thinsp;54.5) years. There were no significant gender differences among the three groups.\u003c/p\u003e \u003cp\u003eAdditionally, we also gathered basic information (age, gender, hospitalization duration and underlying diseases), symptoms (fever and abdominal pain), laboratory tests, imaging studies (ultrasound and CT for lesion size), complications, and etiological examinations in diabetes mellitus patients combined with PLA.\u003c/p\u003e \u003cp\u003eInclusion criteria for diabetes mellitus: all patients met the 1999 WHO diagnostic criteria for type 2 diabetes mellitus. Diagnostic criteria for PLA: (1) typical imaging changes such as B-ultrasound, CT, or MRI showing liver abscess; (2) confirmed by liver puncture or surgical evidence; (3) in the absence of typical imaging and etiological evidence, abscess shrinks, disappears, and symptoms alleviate after antibiotic treatment.\u003c/p\u003e \u003cp\u003eThose patients with tuberculous liver abscess, amoebic liver abscess, hydatid disease of the liver, concomitant tumors, hematological system diseases, autoimmune diseases, chronic liver or kidney diseases and thyroid diseases were excluded. This study was authorized by the Ethics Committee of the First Affiliated Hospital of Fujian Medical University (approval number [2022]075). Informed consent was obtained from all participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data Collection\u003c/h2\u003e \u003cp\u003eData were obtained from the hospital medical electronic records system. For each enrolled patient, the following clinical data were documented: demographic data(age and gender), clinical symptoms, underlying conditions, laboratory results, imaging findings and outcomes. Fasting venous blood of patients was extracted within 24 hours of admission and analyzed by using Roche Cobas c 702 analyzer. In addition, serum APOC2 levels on day 1 and at discharge were measured.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.3 Statistical analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eStatistical analysis was performed using SPSS software. Normally distributed quantitative data are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, while non-normally distributed quantitative data are shown as median (Interquartile Range). The independent sample \u003cem\u003et\u003c/em\u003e-test was used for comparisons between two groups with normally distributed data, and \u003cem\u003eone-way ANOVA\u003c/em\u003e for three groups. For non-normally distributed data, the \u003cem\u003eMann-Whitney U\u003c/em\u003e test was used for two-group comparisons, and the \u003cem\u003eKruskal-Wallis H\u003c/em\u003e test for three group comparisons. Categorical data are shown as case numbers (%), with group comparisons made using the \u003cem\u003eχ\u003c/em\u003e\u0026sup2; test or \u003cem\u003eFisher's exact\u003c/em\u003e test. \u003cem\u003eP\u003c/em\u003e value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cb\u003e3.1 Demographic Data\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe baseline data among the diabetes mellitus, diabetes mellitus combined with PLA, and the healthy control were compared as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no significant differences in gender among the groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Serum APOC2 levels in diabetes mellitus patients were significantly higher than those in healthy controls (4.681 (4.114\u0026thinsp;~\u0026thinsp;5.712) vs 3.490 (2.967\u0026thinsp;~\u0026thinsp;3.845) mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). However, in diabetes mellitus combined with PLA, serum APOC2 levels were significantly lower than those in diabetes mellitus patients (2.470 (2.202\u0026thinsp;~\u0026thinsp;3.034) vs 4.681 (4.114\u0026thinsp;~\u0026thinsp;5.712) mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In patients with diabetes mellitus combined with PLA, paired \u003cem\u003et\u003c/em\u003e-tests showed a significant increase in serum APOC2 levels before and after treatment (2.470 (2.202\u0026thinsp;~\u0026thinsp;3.034) vs 4.323 (3.719\u0026thinsp;~\u0026thinsp;4.776) mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). These results indicate that serum APOC2 levels significantly decrease when diabetes mellitus is combined with PLA but significantly increase and return to normal after treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical baseline data among the diabetes mellitus, diabetes mellitus combined with PLA and healthy control\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy Control\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiabetes mellitus combined with PLA (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP1\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP3\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (48.148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (45.455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (22.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (51.852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (54.545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (77.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (44.5, 54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (52.5, 70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (52.25, 67.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTBIL (\u0026micro;mol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (7.8, 11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5 (7.2, 13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6 (6.2, 29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.7 (43.7, 47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.1 (40.15, 45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.1 (27.5, 37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (13, 19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (14.25, 34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35 (26.5, 102.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (17, 18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (18, 28.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.5 (26.25, 57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (13, 21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (14, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e131 (96.5, 191.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (55, 76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (55, 82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e156.5 (119.75, 221.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTCHO(mmol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.09 (3.835, 4.525)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.57 (3.85, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.25 (2.985, 3.585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg(mmol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.785, 1.255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47 (1.105, 2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.16 (0.85, 1.585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.319\u0026thinsp;\u0026plusmn;\u0026thinsp;0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.207\u0026thinsp;\u0026plusmn;\u0026thinsp;0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.801\u0026thinsp;\u0026plusmn;\u0026thinsp;0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62 (2.42, 2.985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.67 (2.15, 3.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.92 (1.445, 2.335)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOA1(g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42 (1.355, 1.535)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.335 (1.19, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.48, 0.765)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOB (g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.76, 0.925)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.985 (0.85, 1.192)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.735, 0.995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOC2 (mg/dL), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.49 (2.967, 3.845)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.681 (4.114, 5.712)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.470 (2.202, 3.034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLU (mmol/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.55 (4.34, 4.885)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.29 (5.99, 8.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.535 (5.49, 9.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6 (5.175, 6.225)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.4 (6.7, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (6.15, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eP1\u003c/em\u003e: One-Way ANOVA of diabetes mellitus, diabetes mellitus with PLA, and healthy control group, \u003cem\u003eP2\u003c/em\u003e: Comparison between diabetes mellitus and healthy control, \u003cem\u003eP3\u003c/em\u003e: Comparison between diabetes mellitus and diabetes mellitus combined with PLA\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.2 The diagnostic value of serum APOC2 in diabetes mellitus combined with PLA\u003c/h2\u003e \u003cp\u003eThe ROC curve analysis shows that APOC2 has an AUC of 0.94 (95% CI: 0.870\u0026thinsp;~\u0026thinsp;0.999) for diagnosing diabetes mellitus combined with PLA, with an optimal cutoff value of 3.403 mg/dL, and both sensitivity and specificity are 0.909 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, through univariate and multivariate logistic regression analysis, it was found that after adjusting for gender and age, a decrease in serum APOC2 is a risk factor for PLA in diabetes mellitus patients (OR\u0026thinsp;=\u0026thinsp;0.02 (0.01, 0.16), \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariate logistic regression analysis to predict PLA in diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBaseline variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.833(0.916\u0026ndash;8.768)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.5(0.85\u0026ndash;1113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.007(0.973\u0026ndash;1.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07(0.97, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTBIL (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.073(1.006\u0026ndash;1.144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.661(0.542\u0026ndash;0.806)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41(0.14, 0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.038(1.015\u0026ndash;1.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.062(1.017\u0026ndash;1.109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.036(1.02\u0026ndash;1.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.042(1.02\u0026ndash;1.064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTCHO(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.154(0.057\u0026ndash;0.418)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.553(0.264\u0026ndash;1.157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.013(0.001\u0026ndash;0.124)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.334(0.161\u0026ndash;0.694)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOA1(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001(0.001\u0026ndash;0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.042(0.003\u0026ndash;0.646)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOC2 (mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.104(0.035\u0026ndash;0.307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02(0.00, 0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLU (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.989(0.827\u0026ndash;1.181)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.952(0.717\u0026ndash;1.263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR: Odds ratio\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Correlation between serum APOC2 levels and baseline variables of diabetes mellitus combined with PLA\u003c/h2\u003e \u003cp\u003eBased on the median levels of APOC2, diabetes mellitus combined with PLA were divided into high and low APOC2 level groups. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, in the low-APOC2 level group, ALT levels (101 (43.5\u0026thinsp;~\u0026thinsp;131.5) vs 31 (21\u0026thinsp;~\u0026thinsp;34) U/L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038) and AST levels were significantly elevated (55 (39.5\u0026thinsp;~\u0026thinsp;103.5) vs 28 (24\u0026thinsp;~\u0026thinsp;34), U/L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), indicating that reduced serum APOC2 levels are closely associated with liver function damage.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between serum APOC2 levels and baseline variables of diabetes mellitus combined with PLA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAPOC2\u0026thinsp;\u0026lt;\u0026thinsp;median (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAPOC2\u0026thinsp;\u0026gt;\u0026thinsp;median (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (22.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (36.364)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (9.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (77.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (63.636)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (90.909)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.909\u0026thinsp;\u0026plusmn;\u0026thinsp;11.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.455\u0026thinsp;\u0026plusmn;\u0026thinsp;9.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.364\u0026thinsp;\u0026plusmn;\u0026thinsp;12.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital stays (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.048\u0026thinsp;\u0026plusmn;\u0026thinsp;7.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.182\u0026thinsp;\u0026plusmn;\u0026thinsp;8.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (72.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (81.818)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (63.636)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (27.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (18.182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (36.364)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximal body temperature (℃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.214\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.064\u0026thinsp;\u0026plusmn;\u0026thinsp;1.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal pain (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (54.545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (36.364)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (72.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (45.455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (63.636)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (27.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVomit (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (72.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (54.545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (90.909)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (27.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (45.455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (9.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximal diameter of abscess (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.5 (4.35, 6.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7 (5.425, 6.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.025 (4.025, 5.575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTBIL (\u0026micro;mol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.6 (6.2, 29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.2 (6.7, 38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.85 (5.95, 26.175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.995\u0026thinsp;\u0026plusmn;\u0026thinsp;5.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.391\u0026thinsp;\u0026plusmn;\u0026thinsp;5.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.66\u0026thinsp;\u0026plusmn;\u0026thinsp;5.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (26.5, 102.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101 (43.5, 131.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (21, 34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.5 (26.25, 57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55 (39.5, 103.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (24, 34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156.5 (119.75, 221.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e165 (126.5, 222.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146 (113, 219)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e152.5\u0026thinsp;\u0026plusmn;\u0026thinsp;88.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140.818\u0026thinsp;\u0026plusmn;\u0026thinsp;67.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166.778\u0026thinsp;\u0026plusmn;\u0026thinsp;111.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTCHO(mmol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.361\u0026thinsp;\u0026plusmn;\u0026thinsp;0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.048\u0026thinsp;\u0026plusmn;\u0026thinsp;0.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.708\u0026thinsp;\u0026plusmn;\u0026thinsp;0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg(mmol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.16 (0.85, 1.585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.015 (0.84, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27 (0.97, 1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.801\u0026thinsp;\u0026plusmn;\u0026thinsp;0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.825\u0026thinsp;\u0026plusmn;\u0026thinsp;0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.776\u0026thinsp;\u0026plusmn;\u0026thinsp;0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.928\u0026thinsp;\u0026plusmn;\u0026thinsp;0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.851\u0026thinsp;\u0026plusmn;\u0026thinsp;0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.014\u0026thinsp;\u0026plusmn;\u0026thinsp;1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOA1(g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.641\u0026thinsp;\u0026plusmn;\u0026thinsp;0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.573\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.717\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOB (g/L), Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.864\u0026thinsp;\u0026plusmn;\u0026thinsp;0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.844\u0026thinsp;\u0026plusmn;\u0026thinsp;0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.886\u0026thinsp;\u0026plusmn;\u0026thinsp;0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLU(mmol/L),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.535 (5.49, 9.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.105 (5.01, 9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.535 (6.13, 8.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%),Median (Q1,Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.044\u0026thinsp;\u0026plusmn;\u0026thinsp;2.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.583\u0026thinsp;\u0026plusmn;\u0026thinsp;2.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (g/L), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148.857\u0026thinsp;\u0026plusmn;\u0026thinsp;99.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e165.415\u0026thinsp;\u0026plusmn;\u0026thinsp;80.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.3\u0026thinsp;\u0026plusmn;\u0026thinsp;117.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePLA patients have a variety of clinical manifestations, and the classic triad of fever and right upper abdominal pain doesn't always show up, making early diagnosis a challenge for clinicians\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Compared to patients without type 2 diabetes mellitus, those with type 2 diabetes mellitus are more prone to PLA and their clinical symptoms are less typical, mainly featuring chills and high fever rather than noticeable abdominal pain, leading to a higher rate of missed or incorrect diagnoses\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. With the rise in cases of diabetes mellitus combined with PLA, early diagnosis has become increasingly urgent and crucial. This study find that serum APOC2 levels are significantly decreased in diabetes mellitus patients combined with PLA compared to diabetes mellitus patients. Further, APOC2 levels significantly increased post-treatment in diabetes mellitus patients combined with PLA. In addition, ROC curve analysis and logistic regression analysis revealed that reduced serum APOC2 levels are a risk factor and had high diagnostic accuracy for diabetes mellitus combined with PLA. Therefore, APOC2 could be a potential marker for predicting the occurrence of PLA in diabetic patients, providing a new clue for early diagnosis.\u003c/p\u003e \u003cp\u003eLiver is the body's APOC2 synthesis organ. In this study, diabetes mellitus combined with PLA patients are divided into two groups based on the levels of APOC2. PLA patients in low-APOC2 group have higher ALT and AST, which are the indication of liver damage. In addition, we find that the abscess diameter of the patients in the low-APOC2 group are larger than that in the high-APOC2 group. Our study indicates that PLA could affect the production of APOC2.Therefore, continuous dynamic monitoring APOC2 may provide references for the treatment and prognosis of diabetes mellitus combined with PLA.\u003c/p\u003e \u003cp\u003eThis study has some limitations. Firstly, there are few cases of diabetes mellitus combined with PLA, and the study is single-centered. In the future, more multi-centered samples will be added to further clarify the diagnostic value of serum APOC2. Secondly, this study only collected serum APOC2 results within 24 hours of admission and at discharge, without continuous dynamic monitoring. Continuous follow-up results might better understand the relationship between APOC2 and infection process. Lastly, the role of serum APOC2 in diabetes mellitus combined with PLA still need more in vitro/in vivo experiments to exemplify.\u003c/p\u003e \u003cp\u003eIn summary, serum APOC2 is significantly reduced in diabetes mellitus combined with PLA, with a more notable reduction when liver function is abnormal. It can return to normal levels after treatment and recovery, making it a potential biomarker for early diagnosis and prognosis of diabetes mellitus combined with PLA.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declared no conflict of interest.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical Approval\u003c/strong\u003e \u003cp\u003e This single-center retrospective study was approved by the Research Ethics Committee of the First Affiliated Hospital of Fujian Medical University and followed the principles of the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInformed Consent\u003c/strong\u003e \u003cp\u003eWritten informed consent was obtained from all the patients for their consent to participate in this study and for their data to be used for research purposes and all private information of the included patients was erased.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTianbin Chen designed and supervised the study. Ying Huang and Xiaoqin Chen collected clinical information and performed measurement of laboratory data. Hongyan Guo and Xin Zhang contributed to the data analysis and interpretation. Yuhai Hu and Tianbin Chen contributed to the drafting and revision of the article. The corresponding authors attest that all listed authors met the authorship criteria and that no others meeting the criteria were omitted. All listed authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was supported by National Natural Science Foundation of China (grant numbers: 82272420) and Education Scientific Research Projects for Middle-aged Young Teachers from the Education Department Fujian Province(No.JAT200130).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets and supporting materials of this article are available on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYin D, Ji C, Zhang S, et al. Clinical characteristics and management of 1572 patients with pyogenic liver abscess: A 12-year retrospective study [J]. Liver international: official J Int Association Study Liver. 2021;41(4):810\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLederman ER, Crum NF. Pyogenic liver abscess with a focus on Klebsiella pneumoniae as a primary pathogen: an emerging disease with unique clinical characteristics [J]. Am J Gastroenterol. 2005;100(2):322\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian LT, Yao K, Zhang XY, et al. Liver abscesses in adult patients with and without diabetes mellitus: an analysis of the clinical characteristics, features of the causative pathogens, outcomes and predictors of fatality: a report based on a large population, retrospective study in China [J]. Clin Microbiol Infect. 2012;18(9):E314\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhim G, Em S, Mo S, et al. Liver abscess: diagnostic and management issues found in the low resource setting [J]. Br Med Bull. 2019;132(1):45\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi W, Chen H, Wu S, et al. A comparison of pyogenic liver abscess in patients with or without diabetes: a retrospective study of 246 cases [J]. BMC Gastroenterol. 2018;18(1):144.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Wang X, Di Y. Surgery combined with antibiotics for the treatment of endogenous endophthalmitis caused by liver abscess [J]. BMC Infect Dis. 2020;20(1):661.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolska A, Dunbar RL, Freeman LA, et al. Apolipoprotein C-II: New findings related to genetics, biochemistry, and role in triglyceride metabolism [J]. Atherosclerosis. 2017;267:49\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu CC, Kanter JE, Kothari V, et al. Quartet of APOCs and the Different Roles They Play in Diabetes [J]. Arterioscler Thromb Vasc Biol. 2023;43(7):1124\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeliard S, Nogueira JP, Maraninchi M, et al. Parallel increase of plasma apoproteins C-II and C-III in Type 2 diabetic patients [J]. Diabet Med. 2009;26(7):736\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang S, Lu Z, Wang Y et al. Metalloproteins and apolipoprotein C: candidate plasma biomarkers of T2DM screened by comparative proteomics and lipidomics in ZDF rats [J]. Nutr Metab (Lond), 2020, 17(66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKei AA, Filippatos TD, Tsimihodimos V, et al. A review of the role of apolipoprotein C-II in lipoprotein metabolism and cardiovascular disease [J]. Metabolism. 2012;61(7):906\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen WL, Tain YL, Chen HE et al. Cardiovascular Disease Risk in Children With Chronic Kidney Disease: Impact of Apolipoprotein C-II and Apolipoprotein C-III [J]. Front Pediatr, 2021, 9(706323.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilbernagel G, Chen YQ, Rief M, et al. Inverse association between apolipoprotein C-II and cardiovascular mortality: role of lipoprotein lipase activity modulation [J]. Eur Heart J. 2023;44(25):2335\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDu Z, Zhou X, Zhao J, et al. Effect of diabetes mellitus on short-term prognosis of 227 pyogenic liver abscess patients after hospitalization [J]. BMC Infect Dis. 2020;20(1):145.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetes mellitus, Pyogenic liver abscess, Serum APOC2, Liver damage","lastPublishedDoi":"10.21203/rs.3.rs-4800290/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4800290/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo investigate the diagnostic value of serum APOC2 in patients with diabetes mellitus combined with pyogenic liver abscess.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFrom April 2023 to July 2023, 77 type 2 diabetes mellitus patients were included in The First Affiliated Hospital, Fujian Medical University which divided into two groups: diabetes mellitus (n=55) and diabetes mellitus combined with pyogenic liver abscess (n=22). Additionally, 27 healthy individuals served as the control group. Serum APOC2 levels were detected and compared among the groups. ROC curve and logistic regression analysis were performed to evaluate the diagnostic value of serum APOC2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eSerum APOC2 levels were significantly higher in diabetes mellitus patients compared to the healthy control group (4.681 vs 3.490 mg/dL, \u003cem\u003eP\u003c/em\u003e=0.008). In diabetes mellitus combined with pyogenic liver abscess patients, APOC2 levels were significantly reduced (4.681 vs 2.470 mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), but increased post-treatment (2.470 vs 4.323 mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). ROC curve analysis showed high diagnostic accuracy for serum APOC2 in diabetes mellitus combined with pyogenic liver abscess (AUC=0.945, 95% CI: 0.870-0.999). Logistic regression analysis revealed that reduced serum APOC2 levels are a risk factor for diabetes mellitus combined with pyogenic liver abscess (OR=0.02, 95% CI=0.01~0.16, \u003cem\u003eP\u003c/em\u003e=0.012). The diabetes mellitus combined with pyogenic liver abscess patients with lower APOC2 levels had higher ALT (101 U/L vs 31 U/L,\u003cem\u003e P\u003c/em\u003e=0.038) and AST levels (55 U/L vs 28 U/L, \u003cem\u003eP\u003c/em\u003e=0.007), suggesting that reduced serum APOC2 levels are associated with liver function damage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eSerum APOC2 levels were significantly decreased in patients with diabetes mellitus combined with pyogenic liver abscess, serving as a potential marker for predicting the occurrence of this condition. Lower levels of APOC2 are strongly linked to liver function impairment.\u003c/p\u003e","manuscriptTitle":"Clinical significance of Serum APOC2 in type 2 diabetes mellitus combined with pyogenic liver abscess","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-05 20:14:00","doi":"10.21203/rs.3.rs-4800290/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b8f9c43-8c3d-44e4-969b-6593a5492ca5","owner":[],"postedDate":"August 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T20:14:00+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-05 20:14:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4800290","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4800290","identity":"rs-4800290","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}