INTRODUCTION
Hypertriglyceridemia, defined as serum triglycerides ≥150 mg/dL (1.7 mmol/L), is a common clinical problem, with a prevalence of 25%–30% in the adult population in developed countries (1,2 1,2 3,4 2,5 6,7 8,9
The risk of acute pancreatitis has been shown to increase progressively with serum triglycerides > 500 mg/dL (5.6 mmol/L) (8,10 11 12
Growing evidence has demonstrated that intraindividual visit-to-visit variability in cardiovascular risk factors may be potential prognostic markers for adverse outcomes, independent of their mean absolute values (13,14 15 16–19
METHODS
Data source
In this retrospective cohort study, we used data from the Chang Gung Research Database (CGRD), which is a multi-institutional medical records database of the Chang Gung Memorial Hospital (CGMH) system (20,21 22 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM ) codes before 2016 and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM ) codes thereafter. The CGRD encrypts all personal identifiable information of the patients to ensure anonymity, and therefore, the need for informed consent was waived.
Study population and design
Patients who were diagnosed with hyperlipidemia (ICD-9-CM code: 272; ICD-10-CM code: E78) in the CGRD between January 1, 2007, and December 31, 2013, and had at least 1 triglyceride measurement annually for 4 consecutive years after the initial diagnosis were identified for further analysis. This 4-year period after the diagnosis of hyperlipidemia was defined as the run-in period. The day after the end of the run-in period was defined as the index date. The diagnosis of hyperlipidemia was ascertained by any prescription of lipid-lowering drugs or at least 1 test for serum triglycerides ≥150 mg/dL during the run-in period. The flowchart of patient inclusion is shown in Figure 1 . Of the 288,725 patients who were diagnosed with hyperlipidemia, we excluded those who were younger than 18 years (n = 1,162), those who did not have annual triglyceride tests during the 4-year run-in period (n = 162,903) or at least 1 test for triglycerides ≥150 mg/dL and no prescription of lipid-lowering drugs during the run-in period (n = 10,471), and those who were lost to follow-up during the first year after the index date (n = 5,560). To avoid confounding caused by other etiologies of acute pancreatitis, we excluded patients with gallstones (n = 2,805) and alcoholism or alcohol-related diseases (n = 6,599). To minimize the potential impact of reverse causality, patients with a prior history of acute or chronic pancreatitis before the index date (including those who developed incident acute pancreatitis during the run-in period) were also excluded (n = 406). Finally, the remaining 98,819 patients were eligible for analysis in this study.
Figure 1.: Inclusion and exclusion of the study patients. A total of 98,819 patients who were diagnosed with hyperlipidemia and had at least 1 triglyceride measurement annually for 4 consecutive years were eligible for further analysis.
Visit-to-visit triglyceride variability
In the CGMH system, patients are required to fast for 12 hours overnight before receiving blood tests for serum glucose and lipids. Lipid parameters including triglycerides were measured by standard laboratory procedures using automated analyzer kits (Minaris Medical, Fuji Plant, Japan). Visit-to-visit triglyceride variability was determined during the 4-year run-in period. According to the study design, each patient had 4 or more triglyceride measurements to assess triglyceride variability, which was defined as the variability independent of the mean (VIM). VIM was calculated as 100 × SD/meanβ , where β is the regression coefficient, based on the natural logarithm of the SD over the natural logarithm of the mean. VIM was chosen as the variability index because other indexes, such as average real variability or SD, are known to be strongly correlated with the mean level over visits (23
Covariates
The covariates included demographic characteristics, vital signs, comorbidities, prior cardiovascular events, medications, and laboratory test results. Comorbidities, including obesity (defined as body mass index [BMI] ≥25 kg/m2 in Asian populations) (24
Follow-up and outcomes
All patients were followed from the index date until the occurrence of acute pancreatitis, the date of death, the date of the last visit in the CGMH system, or the end of the follow-up period (December 31, 2019), whichever occurred first. The primary outcome in this study was first attack of acute pancreatitis, which was identified from inpatient diagnosis records and further confirmed by elevations in serum amylase and/or lipase levels by at least 3 times the upper limit of the normal levels, and computed tomography findings. Secondary outcomes included the risks of recurrent acute pancreatitis and death after acute pancreatitis. The ICD-9-CM and ICD-10-CM diagnosis codes for acute pancreatitis were 577.0 and K85.0, K85.8, and K85.9, respectively. The ICD-9-CM diagnosis code 577.0 is an unspecified code for acute pancreatitis, and there are no specific ICD-9-CM codes for different etiologies of acute pancreatitis. To ensure that the outcomes were more related to serum triglycerides than other etiologies, we further excluded biliary (K85.1), alcohol-induced (K85.2), and drug-induced acute pancreatitis (K85.3) from the outcome analysis. Patients with biliary disease on imaging studies were also excluded. In addition, information on death was obtained by linking the CGRD with the Taiwan Death Registry.
Statistical analysis
The baseline characteristics of the study patients were described across triglyceride VIM quartiles. The linear trend of the ordinal triglyceride VIM quartiles over the baseline characteristics was tested using linear contrast in a general linear model for continuous variables, the Jonckheere-Terpstra test for serum creatinine (because it was apparently skewed), and the Cochran-Armitage test for categorical variables. The risk of first acute pancreatitis in patients with different levels of triglyceride VIM was compared using Cox proportional hazard models. Several Cox models were conducted with a gradual adjustment of covariates. Model 1 was the unadjusted model. Model 2 adjusted for demographics, vital signs, comorbidities, baseline medications, and all laboratory data on the index date, including the baseline triglyceride level. Model 3 adjusted for variables in model 2 and laboratory data in the run-in period, including the mean values of triglycerides, LDL-C, HDL-C, total cholesterol, WBC count, and NLR. According to the inclusion criteria, some of the study patients may have a diagnosis of hyperlipidemia without true hypertriglyceridemia in the run-in period. A sensitivity analysis was performed in patients with mean triglycerides ≥150 mg/dL in the run-in period.
In the alternative model 3, in which the triglyceride VIM was treated as a continuous variable, several subgroup analyses were performed according to the mean values of triglycerides, WBC count, and NLR in the run-in period, and diabetes, BMI, statins, and the use of other lipid-lowering drugs at baseline. The possible linear and nonlinear relationships between triglyceride variability or mean NLR during the run-in period and the risk of first acute pancreatitis were explored using a Cox model, where triglyceride VIM and NLR were treated as a flexible restricted cubic spline. The number of knots was 4, with the location at the 5th, 35th, 65th, and 95th percentiles, respectively. The same covariates were adjusted as those in model 3. In addition, the data were imputed using the single expectation-maximization algorithm because a substantial number of values for the continuous parameters were missing.
A 2-sided P value <0.05 was considered to be statistically significant. The restricted cubic spline analysis was conducted using R version 4.0.2 (R Development Core Team) and the rms package (version 6.3-0). The other statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).
RESULTS
Patient characteristics
Among the 98,819 patients, the mean age was 62.4 ± 11.9 years at baseline, and 52,104 (52.7%) were male. During a mean follow-up of 5.9 ± 2.5 years, 825 patients were newly diagnosed with acute pancreatitis, with an incidence of 14.1 events per 10,000 person-years (95% confidence interval [CI] 13.2–15.1). The mean triglyceride levels of the study population were 148.4 ± 87.2 mg/dL at baseline (the index date) and 160.5 ± 82.0 mg/dL in the run-in period. Table 1 shows the baseline characteristics of the study participants according to quartiles of triglyceride variability. Compared with the patients in the first to third triglyceride VIM quartiles, those in the highest quartile (Q4) were younger, more predominantly male, had lower BMI and blood pressure but higher heart rate, higher prevalence of current smoking, alcohol drinking, and a higher Charlson Comorbidity Index score. Statins were more frequently prescribed in the Q1 group, whereas fibrates were more frequently prescribed in the Q4 group. On the index date, the Q4 group had higher HDL-C and estimated glomerular filtration rate, but lower levels of triglycerides, total cholesterol, creatinine, uric acid, aminotransferases, and WBC count. During the run-in period, the mean triglyceride level was highest in the Q1 group, followed by the Q4, Q2, and Q3 groups. Notably, the trend in the mean NLR in the run-in period was in the opposite direction to the mean WBC count, and the Q4 group had the highest mean NLR and the lowest WBC count. The mean NLR on the index date was not calculated as only a small number of test results were available.
Table 1.: Clinical characteristics of patients at baseline and run-in period according to the quartile of triglyceride variability
Triglyceride variability and the risk of first attack of acute pancreatitis
The incidence rates and risk estimates of acute pancreatitis stratified by the quartiles of triglyceride variability are shown in Table 2 . The incidence rates of acute pancreatitis were 11.9 (95% CI 10.2–13.7), 12.8 (95% CI 11.0–14.6), 15.0 (95% CI 13.0–17.0), and 16.8 (95% CI 14.7–19.0) events per 10,000 person-years in the Q1, Q2, Q3, and Q4 groups, respectively. In the multivariable Cox regression models, triglyceride VIM was significantly associated with an increased risk of first acute pancreatitis, even after adjusting for baseline triglycerides on the index date and mean triglycerides during the run-in period (Q4 vs Q1 in model 3: adjusted hazard ratio [HR], 1.28; 95% CI 1.05–1.57; P for trend = 0.006). Figure 2 illustrates the cumulative incidence rates (the fitted one minus survival rates) of first acute pancreatitis according to the quartiles of triglyceride variability. Consistent with the main analysis, a sensitivity analysis in the patients with mean triglycerides ≥150 mg/dL in the run-in period showed an independent association between high triglyceride VIM and the risk of first acute pancreatitis (Q4 vs Q1 in model 3: adjusted HR, 1.33; 95% CI 1.03–1.73; P for trend = 0.013; see Supplementary Table 1, Supplementary Digital Content 1, https://links.lww.com/AJG/C876
Table 2.: Association between triglyceride variability and the risk of first attack of acute pancreatitis in various adjustment models
Figure 2.: Cumulative incidence rates (the fitted one minus survival rates) of first attack of acute pancreatitis in the patients stratified by quartiles of visit-to-visit triglyceride variability. Patients with high triglyceride variability were associated with an increased risk of first acute pancreatitis. Q, quartile.
Triglyceride variability and the risks of recurrent acute pancreatitis and death after acute pancreatitis
The incidence rates and risk estimates of recurrent acute pancreatitis and death after acute pancreatitis are summarized in Supplementary Table 2 (see Supplementary Digital Content 1, https://links.lww.com/AJG/C876 P trend < 0.001). However, no significant association was observed between triglyceride VIM and the risk of death after acute pancreatitis, probably because of the low incidence of death. No adjustment for covariates was performed for risk estimates because both outcomes were rare in our cohort.
Subgroup analyses
The results of subgroup analysis are illustrated in a forest plot (Figure 3 ). In general, triglyceride variability was positively associated with the risk of first attack of acute pancreatitis across subgroups stratified by mean triglycerides, diabetes, obesity, the use of statins or other lipid-lowering drugs, and WBC count. However, a significant interaction existed between NLR tertiles and the association between triglyceride variability and the risk of first acute pancreatitis. The impact of high triglyceride variability on first acute pancreatitis was more pronounced in the patients in the middle and upper tertiles of NLR than in those in the lower tertile of NLR (P for interaction = 0.022). We used restricted cubic splines to visualize the relationships between triglyceride variability (Figure 4a ) or NLR (Figure 4b ) and the risk of first acute pancreatitis. The results demonstrated that both increasing triglyceride variability and NLR on continuous scales were associated almost linearly with an increased risk of first acute pancreatitis (P for linearity = 0.007 for triglyceride VIM and 0.033 for NLR, respectively).
Figure 3.: Forest plot illustrating subgroup analyses of the association between triglyceride variability and the risk of incidence acute pancreatitis. The impact of high triglyceride variability on the risk of first attack of acute pancreatitis was more pronounced in the patients in the middle and upper tertiles of NLR than in those in the lower tertile of NLR (P for interaction = 0.022). CI, confidence interval; HR, hazard ratio; NLR, neutrophil-to-lymphocyte ratio; TG, triglyceride; VIM, variability independent of the mean; WBC, white blood cell.
Figure 4.: Triglyceride variability and neutrophil-to-lymphocyte ratios on continuous scales and the risk of first attack of acute pancreatitis. Restricted cubic splines showed an almost linear relationship between triglyceride variability independent of the mean (a ) and neutrophil-to-lymphocyte ratio (b ) and the hazard ratio for acute pancreatitis (solid line) with 95% confidence intervals (dotted lines).
DISCUSSION
In this retrospective multi-institutional study of 98,819 patients who were diagnosed with hyperlipidemia, visit-to-visit triglyceride variability was independently associated with the risk of first attack of acute pancreatitis. Our study adds new significance regarding triglyceride management and primary prevention of acute pancreatitis—namely, not only casual triglyceride concentration but also visit-to-visit triglyceride variability has an impact on the occurrence of acute pancreatitis. We also found that the association between triglyceride variability and the risk of acute pancreatitis was more prominent among the patients with a higher NLR, suggesting that subclinical inflammation may be involved in the mechanistic link between triglyceride variability and acute pancreatitis.
To the best of our knowledge, this study is the first to demonstrate that visit-to-visit triglyceride variability, independent of the absolute values, is a predictive factor for acute pancreatitis. Triglyceride variability may serve as an additional component in the recently proposed holistic prevention of pancreatitis (HPP) framework, which comprehensively integrates primary, secondary, and tertiary prevention strategies to reduce the burden of pancreatitis and its sequelae (25 26
To avoid confounding and to better delineate the association between triglyceride variability and acute pancreatitis, patients with concomitant gallstones or alcoholism, 2 major causes of acute pancreatitis, were excluded from this study. To minimize the possible effects of reverse causality, that is, acute pancreatitis leading to high triglyceride variability, we also excluded those with a history of pancreatitis or incident acute pancreatitis in the run-in period. We found that visit-to-visit triglyceride VIM was independently associated with first attack of acute pancreatitis, even after adjusting for multiple comorbidities, the use of medications including lipid-lowering therapy, and a wide range of laboratory data, including baseline triglycerides on the index date and mean triglycerides during the run-in period.
There is currently no consensus on a gold-standard approach to measure visit-to-visit variability in cardiovascular risk factors. VIM is a commonly used measurement of variability in cardiovascular risk factors that has no correlation with the mean levels over visits (27 23
The exact mechanism for how triglyceride variability contributes to the development of acute pancreatitis remains to be elucidated. In this study, subgroup analyses showed a more prominent association between triglyceride variability and the risk of acute pancreatitis in the patients with a higher NLR. Restricted cubic splines showed that the HR for acute pancreatitis was linearly associated with both triglyceride variability and NLR on a continuous scale. We hypothesize that the risk of acute pancreatitis associated with increased triglyceride variability may be partly mediated by subclinical inflammation. NLR is the ratio between neutrophil and lymphocyte counts in peripheral blood, and it reflects the balance of inflammation (as indicated by the neutrophil count) and adaptive immunity (as indicated by the lymphocyte count) in the immune system (28 29–31 32,33 34
Despite a long-recognized relationship between lipids and inflammation (35 36,37 38–40
It is possible that high triglyceride variability is a marker of individuals repeatedly experiencing triglyceride surges through excessive dietary fat intake or alcohol consumption, and hence, acute pancreatitis developed via increased transportation of chylomicrons into pancreatic tissue, liberation of toxic free fatty acids, and ultimately inflammation and autodigestion in the pancreas. High triglyceride variability may also be an epiphenomenon of other metabolic factors, such as diabetes and obesity, that may predispose to the development of acute pancreatitis if poorly controlled (41,42 43,44 45
Our study has several limitations. First, due to the observational nature of the study design, we cannot establish the causal relationship between triglyceride variability and the risk of acute pancreatitis. Triglyceride variability may merely be a predictor rather than a causal factor, until it is assessed as a target for intervention. Although patients with prior pancreatitis were excluded, bias from reverse causality could not be completely eliminated. The study results were adjusted for multiple covariates, but residual or unmeasured confounding may have affected the results. Factors that may influence visit-to-visit triglyceride variability or have an impact on the risk of acute pancreatitis, such as dietary habits and the amount and duration of alcohol consumption or cigarette smoking, could not be captured in the CGRD. Second, patients with hypertriglyceridemia-related acute pancreatitis are usually diagnosed in their 40s and often do not have annual triglyceride tests before the events (46,47 ICD-9 code. Third, the CGRD did not contain comprehensive data for severity stratification. We could not find a statistically significant association between triglyceride variability and mortality, a proxy for severe acute pancreatitis, or recurrent acute pancreatitis because the incidences of these events were low in our cohort. Fourth, although day-to-day biologic variability in triglycerides has been recognized for years, we could not determine how it may have impacted the risk of acute pancreatitis, given that lipid tests were rarely performed on a daily basis in the real-world practice. Fifth, we used VIM as a summary measure of triglyceride variability instead of a full triglyceride trajectory over time. This approach has been commonly adopted in previous studies; however, it may oversimplify triglyceride fluctuations in long-term follow-up. Sixth, less than 10% of the study patients had blood tests for high-sensitivity C-reactive protein, and therefore, it was not analyzed in this study. Finally, the study patients were identified from the CGRD using the diagnosis of hyperlipidemia. Our findings may not be directly generalizable to the general Taiwanese population or other ethnic groups. The incidence rate of acute pancreatitis may have been underestimated because some patients who developed acute pancreatitis may not have visited the CGMH system. Our findings should be further examined in future studies.
In this retrospective multi-institutional cohort study, high triglyceride variability was associated with an increased risk of first attack of acute pancreatitis, independent of baseline and mean triglyceride levels. The association between triglyceride variability and acute pancreatitis may be partly mediated by subclinical inflammation.
CONFLICTS OF INTEREST
Guarantor of the article: Pao-Hsien Chu, MD.
Specific author contributions: Y.-C.T. and P.-H.C.: designed the study. Y.-C.T.: drafted the manuscript. F.-C.H., C.-P.L., C.-T.H., T.-J.H., H.-Y.C., and P.H.C.: analyzed the data, interpreted the results, and revised the manuscript. All authors approved the final version of the paper.
Financial support: None to report.
Potential competing interests: None to report.
Ethical approval: This study was approved by the Institutional Review Board at Linkou Chang Gung Memorial Hospital, Taiwan (No. 201902047B0W001).
Data availability statement: Data are available on request from the corresponding authors at [email protected] [email protected]
Study Highlights
WHAT IS KNOWN
✓ Hypertriglyceridemia is the third most common etiology of acute pancreatitis. The risk of acute pancreatitis increases progressively with serum triglycerides >500 mg/dL (5.6 mmol/L), and serum triglycerides >1,000 mg/dL (11.3 mmol/L) are generally considered to be causative for acute pancreatitis.
✓ More recent data have shown that mild to moderate hypertriglyceridemia (177–885 mg/dL or 2–10 mmol/L) also significantly, albeit modestly, increases the risk of acute pancreatitis.
WHAT IS NEW HERE
✓ This study is the first to investigate whether visit-to-visit triglyceride variability is an independent predictor for acute pancreatitis. Triglyceride variability, defined as variability independent of the mean, was significantly associated with first attack of acute pancreatitis, even after adjusting for baseline and mean triglyceride levels and underlying comorbidities, medications, and a wide range of laboratory data.
✓ The impact of high triglyceride variability on first attack of acute pancreatitis was more pronounced in patients in the middle and upper tertiles of neutrophil-to-lymphocyte ratio than in those in the lower tertile of neutrophil-to-lymphocyte ratio, suggesting that subclinical inflammation may be involved in the mechanistic link between triglyceride variability and acute pancreatitis.
ACKNOWLEDGMENT
The authors thank Alfred Hsing-Fen Lin for his assistance in the statistical analysis.
REFERENCES
1. Miller M, Stone NJ, Ballantyne C, et al. Triglycerides and cardiovascular disease: A scientific statement from the American Heart Association. Circulation 2011;123:2292–333.
2. Nordestgaard BG. Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: New insights from epidemiology, genetics, and biology. Cir Res 2016;118:547–63.
3. Fortson MR, Freedman SN, Webster PD III. Clinical assessment of hyperlipidemic pancreatitis. Am J Gastroenterol 1995;90:2134–9.
4. Pedersen SB, Langsted A, Nordestgaard BG. Nonfasting mild-to-moderate hypertriglyceridemia and risk of acute pancreatitis. JAMA Intern Med 2016;176:1834–42.
5. Varbo A, Benn M, Tybjærg-Hansen A, et al. Remnant cholesterol as a causal risk factor for ischemic heart disease. J Am Coll Cardiol 2013;61:427–36.
6. Saharia P, Margolis S, Zuidema G, et al. Acute pancreatitis with hyperlipemia: Studies with an isolated perfused canine pancreas. Surgery 1977;82:60–7.
7. Kimura W, Mössner J. Role of hypertriglyceridemia in the pathogenesis of experimental acute pancreatitis in rats. Int J Pancreatol 1996;20:177–84.
8. Valdivielso P, Ramírez-Bueno A, Ewald N. Current knowledge of hypertriglyceridemic pancreatitis. Eur J Intern Med 2014;25:689–94.
9. Ewald N, Hardt PD, Kloer HU. Severe hypertriglyceridemia and pancreatitis: Presentation and management. Curr Opin Lipidol 2009;20:497–504.
10. Cappell MS. Acute pancreatitis: Etiology, clinical presentation, diagnosis, and therapy. Med Clin North Am 2008;92:889–923.
11. Scherer J, Singh V, Pitchumoni C, et al. Issues in hypertriglyceridemic pancreatitis-an update. J Clin Gastroenterol 2014;48:195.
12. Tsuang W, Navaneethan U, Ruiz L, et al. Hypertriglyceridemic pancreatitis: Presentation and management. Am J Gastroenterol 2009;104:984–91.
13. Simpson WG. Biomarker variability and cardiovascular disease residual risk. Curr Opin Cardiol 2019;34:413–7.
14. Messerli FH, Hofstetter L, Rimoldi SF, et al. Risk factor variability and cardiovascular outcome: JACC review topic of the week. J Am Coll Cardiol 2019;73:2596–603.
15. Bookstein L, Gidding SS, Donovan M, et al. Day-to-day variability of serum cholesterol, triglyceride, and high-density lipoprotein cholesterol levels. Arch Intern Med 1990;150:1653–7.
16. Waters DD, Bangalore S, Fayyad R, et al. Visit-to-visit variability of lipid measurements as predictors of cardiovascular events. J Clin Lipidol 2018;12:356–66.
17. Wan EY, Yu EY, Chin WY, et al. Greater variability in lipid measurements associated with cardiovascular disease and mortality: A 10-year diabetes cohort study. Diabetes Obes Metab 2020;22:1777–88.
18. Bardini G, Innocenti M, Rotella CM, et al. Variability of triglyceride levels and incidence of microalbuminuria in type 2 diabetes. J Clin Lipidol 2016;10:109–15.
19. Matsuoka-Uchiyama N, Uchida HA, Okamoto S, et al. The association of postprandial triglyceride variability with renal dysfunction and microalbuminuria in patients with type 2 diabetic mellitus: A retrospective and observational study. J Diabetes Res 2022;2022:3157841.
20. Shao SC, Chan YY, Kao Yang YH, et al. The Chang Gung Research Database—A multi-institutional electronic medical records database for real-world epidemiological studies in Taiwan. Pharmacoepidemiol Drug Saf 2019;28:593–600.
21. Tsai M-S, Lin M-H, Lee C-P, et al. Chang Gung Research Database: A multi-institutional database consisting of original medical records. Biomed J 2017;40:263–9.
22. Tung YC, Lin CP, Hsiao FC, et al. Comparative effectiveness of generic nifedipine versus Adalat long-acting nifedipine for hypertension treatment: A multi-institutional cohort study. J Clin Hypertens 2022;24:621–9.
23. Yano Y. Visit-to-visit blood pressure variability—What is the current challenge? Am J Hypertens 2017;30:112–4.
24. WHO. The Asia-Pacific perspective: Redefining obesity and its treatment. 2000.
25. Petrov MS, Yadav D. Global epidemiology and holistic prevention of pancreatitis. Nat Rev Gastroenterol Hepatol 2019;16:175–84.
26. Goldstein BA, Navar AM, Pencina MJ, et al. Opportunities and challenges in developing risk prediction models with electronic health records data: A systematic review. J Am Med Inform Assoc 2017;24:198–208.
27. Rothwell PM, Howard SC, Dolan E, et al. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet 2010;375:895–905.
28. Song M, Graubard BI, Rabkin CS, et al. Neutrophil-to-lymphocyte ratio and mortality in the United States general population. Sci Rep 2021;11:464.
29. Bhat T, Teli S, Rijal J, et al. Neutrophil to lymphocyte ratio and cardiovascular diseases: A review. Expert Rev Cardiovasc Ther 2013;11:55–9.
30. Imtiaz F, Shafique K, Mirza SS, et al. Neutrophil lymphocyte ratio as a measure of systemic inflammation in prevalent chronic diseases in Asian population. Int Arch Med 2012;5:1–6.
31. Templeton AJ, McNamara MG, Šeruga B, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: A systematic review and meta-analysis. J Natl Cancer Inst 2014;106:dju124.
32. Azab B, Jaglall N, Atallah JP, et al. Neutrophil-lymphocyte ratio as a predictor of adverse outcomes of acute pancreatitis. Pancreatology 2011;11:445–52.
33. Li Y, Zhao Y, Feng L, et al. Comparison of the prognostic values of inflammation markers in patients with acute pancreatitis: A retrospective cohort study. BMJ Open 2017;7:e013206.
34. Hansen SE, Madsen CM, Varbo A, et al. Low-grade inflammation in the association between mild-to-moderate hypertriglyceridemia and risk of acute pancreatitis: A study of more than 115000 individuals from the general population. Clin Chem 2019;65:321–32.
35. Gallin JI, Kaye D, O'Leary WM. Serum lipids in infection. N Engl J Med 1969;281:1081–6.
36. Zhao L, Xu T, Li Y, et al. Variability in blood lipids affects the neutrophil to lymphocyte ratio in patients undergoing elective percutaneous coronary intervention: A retrospective study. Lipids Health Dis 2020;19:1–8.
37. Lee S, Zhou J, Wong WT, et al. Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning. BMC Endocr Disord 2021;21:1–15.
38. Keirns BH, Sciarrillo CM, Koemel NA, et al. Fasting, non-fasting and postprandial triglycerides for screening cardiometabolic risk. J Nutr Sci 2021;10:e75.
39. Rosenson RS, Wolff DA, Huskin AL, et al. Fenofibrate therapy ameliorates fasting and postprandial lipoproteinemia, oxidative stress, and the inflammatory response in subjects with hypertriglyceridemia and the metabolic syndrome. Diabetes Care 2007;30:1945–51.
40. Zilversmit DB. Atherogenic nature of triglycerides, postprandial lipidemia, and triglyceride-rich remnant lipoproteins. Clin Chem 1995;41:153–8.
41. Noel RA, Braun DK, Patterson RE, et al. Increased risk of acute pancreatitis and biliary disease observed in patients with type 2 diabetes: A retrospective cohort study. Diabetes Care 2009;32:834–8.
42. Martinez J, Johnson C, Sanchez-Paya J, et al. Obesity is a definitive risk factor of severity and mortality in acute pancreatitis: An updated meta-analysis. Pancreatology 2006;6:206–9.
43. Ko J, Al-Ani Z, Long K, et al. Intrapancreatic, liver, and skeletal muscle fat depositions in first attack of acute pancreatitis versus health. Am J Gastroenterol 2022;117:1693–701.
44. Petrov MS, Taylor R. Intra-pancreatic fat deposition: Bringing hidden fat to the fore. Nat Rev Gastroenterol Hepatol 2022;19:153–68.
45. Singh RG, Yoon HD, Wu LM, et al. Ectopic fat accumulation in the pancreas and its clinical relevance: A systematic review, meta-analysis, and meta-regression. Metabolism 2017;69:1–13.
46. Pothoulakis I, Paragomi P, Archibugi L, et al. Clinical features of hypertriglyceridemia-induced acute pancreatitis in an international, multicenter, prospective cohort (APPRENTICE consortium). Pancreatology 2020;20:325–30.
47. Vipperla K, Somerville C, Furlan A, et al. Clinical profile and natural course in a large cohort of patients with hypertriglyceridemia and pancreatitis. J Clin Gastroenterol 2017;51:77–85.
