无创检测评分预测重症急性胰腺炎的研究进展
Research Progress of Noninvasive Test Score in Predicting Severe Acute Pancreatitis
DOI: 10.12677/acm.2025.15123433, PDF, HTML, XML,   
作者: 黄 梦, 刘成成, 龚 欢, 赵婷婷:西安医学院研工部,陕西 西安;贺 娜*:西安医学院第一附属医院消化内科,陕西 西安
关键词: 重症急性胰腺炎评分系统血清学指标早期预测Severe Acute Pancreatitis Scoring System Serological Index Early Prediction
摘要: 重症急性胰腺炎(severe acute pancreatitis, SAP)是一种严重的消化系统疾病,死亡率高且早期识别难度较大。近年来,提出了多种临床评分系统、影像学评分系统和生物标志物预测模型,以期提高对SAP预测的准确性。本文就目前预测重症急性胰腺炎的无创血清学指标及评分系统进行综述。
Abstract: Severe acute pancreatitis (SAP) is a serious digestive system disease characterized by high mortality and difficulty in early identification. In recent years, various clinical scoring systems, imaging scoring systems, and biomarker-based prediction models have been proposed to improve the accuracy of SAP prediction. This article reviews the current non-invasive serological indicators and scoring systems for predicting severe acute pancreatitis.
文章引用:黄梦, 刘成成, 龚欢, 赵婷婷, 贺娜. 无创检测评分预测重症急性胰腺炎的研究进展[J]. 临床医学进展, 2025, 15(12): 462-469. https://doi.org/10.12677/acm.2025.15123433

1. 引言

急性胰腺炎(acute pancreatitis, AP)是一种常见的急腹症,若干预不及时约30%的患者可进展为重症急性胰腺炎(severe acute pancreatitis, SAP),SAP病情进展迅速,常伴有器官功能障碍甚至死亡[1]。根据修订的亚特兰大分类标准,SAP定义为伴有持续性(>48小时)器官功能衰竭的AP [2]。影响AP患者结局的主要因素在于早期识别危重症征象,积极干预防范其重症化倾向,而在基层医院及社区卫生中心,医疗条件受限,早期诊断多有滞后,因此,找到方便、可靠又经济的方法来识别发展为重症胰腺炎的危险因素对于全科医生及基层社区诊疗尤为重要。本文总结了目前用于预测重症胰腺炎的血清学指标和评分系统,以期为临床早期识别重症胰腺炎提供一定的参考。

2. 血清学指标

2.1. C反应蛋白(C Reactive Protein, CRP)

CRP是一种非特异性急性期反应蛋白,已被广泛用于预测重症急性胰腺炎。研究表明,CRP48小时预测SAP的临界范围为120~160 mg/L [3]。目前,指南建议不要使用单一生物标志物对患者进行分诊,但入院48小时内的CRP水平≥150 mg/dL仍被认为是AP患者预后较差的预测因素[4]。Stirling等[5]发现,入院后48小时内的CRP升高大于90 mg/L预示AP病情进展。Cardoso等[6]表明,入院24小时内CRP ≤ 60 mg/L的患者不会发展为SAP,出现死亡和并发症的风险降低。CRP在临床实践中具有很高的适用性,但在酒精性肝病或肥胖引起的AP患者中的预测性能可能会下降,且其特异性不高,升高水平与感染程度没有相关性,不能作为预测重症胰腺炎症的充分标志物[7]

2.2. 白细胞介素6 (Interleukin-6, IL-6)

IL-6在组织损伤后由多种细胞释放,在体内外刺激肝脏合成急性期蛋白,其水平随AP的严重程度而增加,研究表明,AP发病48小时内测定的IL-6水平≥28.90 pg/ml是预测SAP的最佳生物标志物,在预测感染性胰腺坏死及死亡率方面也具有一定优势[8] [9]。Kumar等[10]的研究也得出相同的结论,IL-6 (入院第1天) > 137 pg/mL及IL-6 (入院第2天) > 77.3 pg/mL预测重度AP的敏感性及特异性分别为100%和88.4%,与CRP相比,是SAP的最佳预测因子。然而,IL-6的血清浓度下降非常快,测量难度大,且成本较高。

2.3. 血清降钙素原(Procalcitonin, PCT)

降钙素原是全身细菌感染和败血症的早期标志物,约24小时达到峰值,是判断AP合并感染的重要辅助指标,已被证实可用于预测SAP [11]。He等[3]的研究中,将发病48小时内的降钙素原、CRP和D-二聚体作为中重度急性胰腺炎的预测因子,曲线下面积(area under the curve, AUC)分别为0.795、0.768和0.789,敏感性分别为78.20%、72.90%和74.70%,而三个指标的联合检测具有更好的预测价值,该联合模型的灵敏度、Youden指数和AUC高于传统的评分系统,且只需要三项血清指标,从炎症、感染和凝血三个方面反映急性胰腺炎发病时的身体状态。PCT测定法的主要缺点是成本较高。

2.4. D-二聚体(D-Dimer, D-D)

D-二聚体是一种特异性纤溶过程标志物,而AP急性期可能会出现凝血和微循环障碍,因此D-二聚体可能与AP的严重程度和并发症有关,可作为预测患者不良结局的标志物,相关研究发现,其预测SAP的敏感性可达86.5%~92.6% [12]-[14]。D-D水平也与AP患者死亡风险相关,入院时D-D的中位水平处于0.4~0.8 mg/L范围内的患者死亡风险比D-D低水平的患者高11.2倍[15]。然而,D-二聚体水平受多种因素影响包括年龄、怀孕、炎症、癌症和手术,且目前缺乏D-二聚体浓度检测的标准方法,其作为预测SAP的最佳检测方法和相关阈值仍不确定[16]

2.5. 中性粒细胞–淋巴细胞比率(Neutrophil to Lymphocyte Ratio, NLR)

中性粒细胞计数的增加表明机体发生了急性炎症反应,淋巴细胞计数的减少反映了整体健康状况的恶化,NLR已被认为是AP严重程度和预后的预测指标,可以在其他指标难以获取的情况下预测AP患者的病情进展[17] [18]。NLR用于预测重症胰腺炎的截断值为8.59,敏感性为82.7%,特异性为70%,相较于CRP及其他指标,与重症急性胰腺炎的相关性最高,且在预测高甘油三酯血症引起的AP患者的SAP中表现最好[19] [20]。一项Meta分析证明,NLR与Ranson评分等传统的评分系统相比具有相同的预测价值,可能是用于区分重度与轻中度胰腺炎患者的一个潜在标志物[21]

2.6. 未成熟粒细胞计数和未成熟粒细胞百分比

未成熟粒细胞是在成熟期来自骨髓祖细胞的中性粒细胞,在机体发生感染时可进入外周血[22]。Lipiński等[23]的研究发现,未成熟粒细胞计数用于预测SAP的最佳截断值为0.6%,灵敏度为100%,特异度为96.9%,在预测AP严重程度方面优于全身炎症反应综合征(systemic inflammatory response syndrome, SIRS)。但在目前国内外研究中,使用该标志物预测急性胰腺炎严重程度的研究只有少数。

2.7. 其他

AP患者的血清可溶性致瘤性抑制2 (soluble suppression of tumorigenicity 2 protein, sST2)水平显著升高,Logistic回归显示,sST2是SAP的预测因子,临界值为1190 pg/mL,可作为一种新的炎症标记物用于预测AP的严重程度[24]。有研究表明入院时的高密度脂蛋白胆固醇(HDL-C)以及入院时、入院后24小时内的血尿素氮(blood urea nitrogen, BUN)、血肌酐(serum creatinine, Scr)与重症急性胰腺炎显著相关,据此,开发了一个逻辑回归函数(LR模型):入院时−2.25~0.06 HDL-C (mg/dl) + 24 h 0.06 BUN (mg/dl) + 24 h 0.66 Scr (mg/dl) (−2.25~0.06 HDL-C (mg/dl) at admission + 0.06 BUN (mg/dl) at 24 hours+ 0.66 Scr (mg/dl) at 24 hours),若LR模型值≥−1.86,SAP发生概率从8.9%升至47%;若LR模型值<−1.86,SAP发生概率则降至4%,相比BISAP评分及其他SAP预测因子,LR模型展现出更好的预测性能[25]。Kong等[26]使用三种炎症标志物:肝素结合蛋白(heparin‐binding protein, HBP)、CRP和PCT,构建了一个炎症综合逻辑回归模型(HCP),HCP炎症指数模型基于logistic回归结果构建,公式为6.850~0.068 × HBP (ng/mL) − 0.010 × CRP (mg/mL) − 0.029 × PCT (ng/mL),对诊断重症急性胰腺炎具有很高的价值,但仍需要通过多个外部中心进行验证,以扩大其适用性。对以上指标进行总结分析见表1

3. 评分系统

3.1. 兰森评分(Ranson评分)

Ranson评分是首个急性胰腺炎特定多因素评分系统,最初用于预测急性酒精性胰腺炎患者的严重程度,目前在临床上诊断重症AP使用广泛[27]。Ranson评分由入院时及入院后48小时后的11个重要预后参数组成,每个阳性指标记为1分,最终得分≥3分提示SAP,但特异性不高,且评估过程较为漫长,很难实时跟踪和评估疾病的变化,可能会错过早期重症患者的识别[28]

Table 1. Comparison of major serological indicators for predicting severe acute pancreatitis

1. 预测SAP的主要血清学指标比较

指标名称

检测/评估时间

临界值

报告的敏感性/ 特异性范围

成本

操作复杂度

主要优缺点

以及推荐 应用场景

C反应蛋白(CRP)

入院48小时内

120~160 mg/L

敏感性72.9%

低,广泛可用

临床应用广泛,成本低;特异性不高,在酒精性或肥胖性AP中性能可能下降

基层医院常规监测、病情动态评估

白细胞介素-6 (IL-6)

发病48小时内

28.9 pg/mL

敏感性100%,特异性88.4%

高,非普及

SAP最佳预测因子之一,可预测感染性胰腺坏死及死亡率;血清浓度下降快,测量难度大,成本高

有条件医院的早期精准预测、高危患者筛查

降钙素原(PCT)

发病48小时内

-

敏感性78.2%

判断AP合并感染的重要指标,在联合模型中价值高;成本较高

疑似感染或脓毒症并发症的监测

D-二聚体 (D-D)

入院时

-

敏感性86.5%~92.6%

预测SAP敏感性高,与死亡风险相关;受多种因素(年龄、炎症等)影响,缺乏标准检测方法和阈值

评估凝血功能障碍及患者死亡风险

中性粒细胞–淋巴细胞比率(NLR)

入院时

8.59

敏感性82.7%,特异性70%

低,易计算

易于获取,成本效益高,与SAP相关性高,尤其适用于高甘油三酯血症性AP;作为单一指标特异性中等

急诊室快速初筛、资源有限环境下的首选指标

未成熟粒细胞百分比

入院时

0.6%

敏感性100%,特异度96.9%

低,血常规分析

预测SAP灵敏度与特异度极高,优于SIRS;相关研究较少,临床验证不充分

有潜力的早期预警指标,需进一步临床推广

3.2. 急性生理学与慢性健康状况评分系统II (Acute Physiology and Chronic Health Evaluation II, APACHE II)

APACHE II评分包括急性生理学评分、年龄评分及慢性健康状况评分,得分≥8分提示重症胰腺炎,预测SAP的敏感度为71%,特异度为87.5%,阳性预测值和阴性预测值分别为39.3%和96.4%,可作为排除重症胰腺炎的有效指标,但该评分参数复杂,操作繁琐,需要24小时才能完成最终的计算,仅有部分患者具有完整的临床数据,在临床实践中使用有一定的局限性[29] [30]

3.3. 急性胰腺炎严重程度床旁指数(Bedside Index for Severity in Acute Pancreatitis, BISAP)

2008年提出的BISAP评分系统,可预测急性胰腺炎的严重程度、器官衰竭和死亡[31]。BISAP评分用于预测SAP具有与APACHEII相似的敏感度,且相对简化,主要缺点在于它为静态测量,忽略了疾病发展过程中的指标变化,单独使用BISAP分数不再有优势[32]。Lu等[33]将BISAP评分与临床生化指标相结合,以预测早期AP的严重程度,他们的研究表明BISAP、CRP联合NLR显著提高了预测SAP的准确性。有指南提出BISAP评分中的全身炎症反应综合征(SIRS)也可预测AP严重程度,SIRS持续时间超过48小时,急性胰腺炎患者可能会发生多器官衰竭甚至死亡,因此,SIRS可能是SAP的早期预测指标,需要更多研究来证实[34] [35]

3.4. 改良CT严重指数(Modified CT Severity Index, MCTSI)

MCTSI评分在2004年被提出,用于评估AP的严重程度与以下参数密切相关:住院时间、手术或经皮手术的需要以及感染的发生。CT增强扫描是诊断急性胰腺炎的金标准,它对检测胰腺坏死和胰腺外并发症足够敏感,然而,CT扫描的理想时间是症状出现后至少72小时,不建议单纯出于严重程度评估的目的在入院时进行常规CT扫描[36]。而胰腺实质、周围坏死和假性囊肿可能不会发生在疾病的早期,这限制了MCTSI对AP严重程度的早期评估,这可能会延迟SAP的早期诊断[37]

3.5. 无害性急性胰腺炎评分(The Harmless Acute Pancreatitis Score, HAPS)

无害急性胰腺炎评分(HAPS)只需要三个参数,是一个简单、可重复的评分系统,结果可以在入院后大约30分钟内报告。HAPS用于预测重症胰腺炎的灵敏度高,AP患者反跳痛阴性、入院时血清肌酐水平、红细胞压积在正常范围内,则发展为SAP的概率较低[38] [39]。另有研究发现,HAPS评分预测轻症急性胰腺炎的可靠性更高,评分低的患者进展为重症的可能性小,这对简化轻症患者的治疗方案及节约卫生经济资源方面具有临床意义[40]

3.6. 格拉斯哥胰腺炎评分(Glasgow-Imrie)

Ranson评分系统的修改版:Glasgow-Imrie评分,被用于预测急性胰腺炎严重程度。研究发现,与APACHE II及Ranson评分相比,Glasgow-Imrie评分在预测AP严重程度方面的特异性最高,Glasgow-Imrie评分≥3分的患者发生SAP的概率增大,敏感性及特异性分别为56%及83% [41] [42]。Glasgow-Imrie的主要缺点与Ranson评分相似,需要48小时才能完成最后的计算,不能反映病情的动态变化。

3.7. 中国简单评分系统(The New Chinese Simple Scoring System, CSSS)

Wang等[43]提出了中国简单评分系统(CSSS)用于预测SAP,CSSS包含6个变量:血清肌酐、血糖、乳酸脱氢酶、C反应蛋白、心率,以及胰腺坏死程度,评分≥4分发生的患者发生SAP概率升高,≥6分死亡率升高,研究结果显示,与当前广泛使用的四种评分系统(APACHE II、Ranson、BISAP、MCTSI)相比,CSSS在预测SAP的严重程度及死亡率方面表现较好,尤其在预测疾病严重程度上准确性最高。CSSS仅需少量变量即可实现高效预测,数据的采集也更为方便,为临床实践提供了有力的支持,但仍需大量研究证实。对以上评分系统进行总结分析见表2

Table 2. Comparison of clinical scoring systems for predicting severe acute pancreatitis

2. 预测SAP的临床评分系统比较

评分系统名称

检测/评估时间

临界值

报告的敏感性/特异性范围

成本

操作复杂度

主要优缺点

以及推荐应用场景

Ranson评分

入院时及48小时

≥3分

-

首个AP特定评分,临床应用广泛;需48小时完成,不能实时跟踪,特异性不高

住院患者病情回顾性评估

APACHE II评分

入院24小时内

≥8分

敏感度71%,特异度87.5%

预测效能好,可作为排除SAP的有效指标;参数复杂,操作繁琐,需24小时数据

ICU患者综合评估及预后判断

BISAP评分

入院24小时内

-

与APACHE II敏感度相似

相对简化,预测价值与复杂评分相当;静态测量,忽略指标动态变化

急诊室早期快速风险分层,尤其适合与其他指标联用

改良CT严重指数(MCTSI)

症状出现72小时后

-

敏感性86.5%~92.6%

诊断AP金标准,可评估胰腺坏死和胰外并发症;不适用于早期评估,有辐射,价格昂贵

确诊AP后,用于评估并发症和严重程度,非早期预测工具

无害性急性胰腺炎评分(HAPS)

入院30分钟内

-

预测轻症AP可靠性高

简单、快速,可高效识别低风险患者;主要用于排除而非预测重症

急诊分诊,快速识别轻症AP以简化治疗方案、节约资源

Glasgow-Imrie 评分

入院48小时内

≥3分

敏感性56%,特异性83%

预测SAP特异性高;与Ranson评分类似,需48小时,不能动态反映病情

Ranson评分的替代方案,用于48小时病情评估

中国简单评分系统(CSSS)

入院时

≥4分

在预测严重程度及死亡率方面表现良好,准确性高

仅需少量变量,预测效能高,数据采集方便;仍需大量研究证实其普适性

有潜力的新型简化工具,适用于中国人群的临床实践与研究

4. 小结与展望

重症胰腺炎是一种危重疾病,早期诊断和评估患者病情严重程度对于治疗和预后至关重要,传统的评分系统各有优势,但在临床应用中均存在一定局限性。为了更好地识别重症胰腺炎,提出了血清学指标,如CRP、PCT、NLR等,这比评分系统更简便、客观。基于现有证据,建议临床上采取分步式、组合化的评估方法,首先利用HAPS或BISAP评分进行快速初筛,识别低风险患者;继而动态监测NLR、CRP、PCT等易获取的血清学指标,使用临床评分与动态血清学组合,以提高预警能力;对高度疑似患者应及时转入重症监护室或上级医院进行早期干预,同时采用整合多指标模型来预测患者的疾病进展及预后。展望未来,该领域仍存在重要研究空白,包括缺乏针对特定病因的精准预测模型、多数新标志物及复合模型尚缺大规模前瞻性验证,以及成本效益分析的缺失。因此,未来应着力开展多中心前瞻性队列研究,并积极引入机器学习等先进数据分析技术,以处理复杂临床数据、捕捉非线性关系,从而构建更精准、动态且可能实现实时风险分层的新型预测系统,最终提高SAP早期识别的个体化与精准化。

利益冲突

所有作者均声明不存在利益冲突。

NOTES

*通讯作者。

参考文献

[1] Mederos, M.A., Reber, H.A. and Girgis, M.D. (2021) Acute Pancreatitis: A Review. Journal of the American Medical Association, 325, 382-390. [Google Scholar] [CrossRef] [PubMed]
[2] Banks, P.A., Bollen, T.L., Dervenis, C., Gooszen, H.G., Johnson, C.D., Sarr, M.G., et al. (2013) Classification of Acute Pancreatitis—2012: Revision of the Atlanta Classification and Definitions by International Consensus. Gut, 62, 102-111. [Google Scholar] [CrossRef] [PubMed]
[3] He, Q., Ding, J., He, S., Yu, Y., Chen, X., Li, D., et al. (2022) The Predictive Value of Procalcitonin Combined with C-Reactive Protein and D Dimer in Moderately Severe and Severe Acute Pancreatitis. European Journal of Gastroenterology & Hepatology, 34, 744-750. [Google Scholar] [CrossRef] [PubMed]
[4] Leal, C. and Almeida, N. (2019) Predicting Severity in Acute Pancreatitis: A Never-Ending Quest…. GEPortuguese Journal of Gastroenterology, 26, 232-234. [Google Scholar] [CrossRef] [PubMed]
[5] Stirling, A.D., Moran, N.R., Kelly, M.E., Ridgway, P.F. and Conlon, K.C. (2017) The Predictive Value of C-Reactive Protein (CRP) in Acute Pancreatitis—Is Interval Change in CRP an Additional Indicator of Severity? HPB, 19, 874-880. [Google Scholar] [CrossRef] [PubMed]
[6] Cardoso, F.S., Ricardo, L.B., Oliveira, A.M., Horta, D.V., Papoila, A.L., Deus, J.R., et al. (2015) C-Reactive Protein at 24 Hours after Hospital Admission May Have Relevant Prognostic Accuracy in Acute Pancreatitis: A Retrospective Cohort Study. GE Portuguese Journal of Gastroenterology, 22, 198-203. [Google Scholar] [CrossRef] [PubMed]
[7] Párniczky, A., Lantos, T., Tóth, E.M., Szakács, Z., Gódi, S., Hágendorn, R., et al. (2019) Antibiotic Therapy in Acute Pancreatitis: From Global Overuse to Evidence Based Recommendations. Pancreatology, 19, 488-499. [Google Scholar] [CrossRef] [PubMed]
[8] Jain, S., Midha, S., Mahapatra, S.J., Gupta, S., Sharma, M.K., Nayak, B., et al. (2018) Interleukin-6 Significantly Improves Predictive Value of Systemic Inflammatory Response Syndrome for Predicting Severe Acute Pancreatitis. Pancreatology, 18, 500-506. [Google Scholar] [CrossRef] [PubMed]
[9] Li, J., Chen, Z., Li, L., Lai, T., Peng, H., Gui, L., et al. (2022) Interleukin-6 Is Better than C-Reactive Protein for the Prediction of Infected Pancreatic Necrosis and Mortality in Patients with Acute Pancreatitis. Frontiers in Cellular and Infection Microbiology, 12, Article 933221. [Google Scholar] [CrossRef] [PubMed]
[10] Kumar, R.B., Karim, T., Jain, A., Arora, S., Katiyar, V.K. and Patel, G. (2022) Role of Serum Interleukin-6 and C-Reactive Protein in Early Prediction of Severe Acute Pancreatitis. Journal of West African College of Surgeons, 12, 20-26. [Google Scholar] [CrossRef] [PubMed]
[11] Bezmarevic, M., Kostic, Z., Jovanovic, M., Mickovic, S., Mirkovic, D., Soldatovic, I., et al. (2012) Procalcitonin and BISAP Score versus C-Reactive Protein and APACHE II Score in Early Assessment of Severity and Outcome of Acute Pancreatitis. Vojnosanitetski Pregled, 69, 425-431. [Google Scholar] [CrossRef] [PubMed]
[12] Maeda, K., Hirota, M., Ichihara, A., Ohmuraya, M., Hashimoto, D., Sugita, H., et al. (2006) Applicability of Disseminated Intravascular Coagulation Parameters in the Assessment of the Severity of Acute Pancreatitis. Pancreas, 32, 87-92. [Google Scholar] [CrossRef] [PubMed]
[13] Wan, J., Yang, X., He, W., Zhu, Y., Zhu, Y., Zeng, H., et al. (2019) Serum D-Dimer Levels at Admission for Prediction of Outcomes in Acute Pancreatitis. BMC Gastroenterology, 19, Article No. 67. [Google Scholar] [CrossRef] [PubMed]
[14] Yang, N., Hao, J. and Zhang, D. (2017) Antithrombin III and D-Dimer Levels as Indicators of Disease Severity in Patients with Hyperlipidaemic or Biliary Acute Pancreatitis. Journal of International Medical Research, 45, 147-158. [Google Scholar] [CrossRef] [PubMed]
[15] Badhal, S.S., Sharma, S., Saraya, A. and Mukhopadhyay, A.K. (2012) Prognostic Significance of D-Dimer, Natural Anticoagulants and Routine Coagulation Parameters in Acute Pancreatitis. Tropical Gastroenterology, 33, 193-199. [Google Scholar] [CrossRef] [PubMed]
[16] Riley, R.S., Gilbert, A.R., Dalton, J.B., Pai, S. and McPherson, R.A. (2016) Widely Used Types and Clinical Applications of D-Dimer Assay. Laboratory Medicine, 47, 90-102. [Google Scholar] [CrossRef] [PubMed]
[17] Kokulu, K., Gunaydin, Y.K., Akilli, N.B., Koylu, R., Sert, E.T., Koylu, O., et al. (2018) Relationship between the Neutrophil-to-Lymphocyte Ratio in Acute Pancreatitis and the Severity and Systemic Complications of the Disease. The Turkish Journal of Gastroenterology, 29, 684-691. [Google Scholar] [CrossRef] [PubMed]
[18] Tahir, H., Rahman, S., Habib, Z., Khan, Y. and Shehzad, S. (2021) Comparison of the Accuracy of Modified CT Severity Index Score and Neutrophil-to-Lymphocyte Ratio in Assessing the Severity of Acute Pancreatitis. Cureus, 13, e17020. [Google Scholar] [CrossRef] [PubMed]
[19] Park, H.S., In, S.G., Yoon, H., Lee, W.J., Woo, S.H. and Kim, D. (2019) Predictive Values of Neutrophil-Lymphocyte Ratio as an Early Indicator for Severe Acute Pancreatitis in the Emergency Department Patients. Journal of Laboratory Physicians, 11, 259-264. [Google Scholar] [CrossRef] [PubMed]
[20] Huang, L., Chen, C., Yang, L., Wan, R. and Hu, G. (2019) Neutrophil-to-Lymphocyte Ratio Can Specifically Predict the Severity of Hypertriglyceridemia-Induced Acute Pancreatitis Compared with White Blood Cell. Journal of Clinical Laboratory Analysis, 33, e22839. [Google Scholar] [CrossRef] [PubMed]
[21] Kong, W., He, Y., Bao, H., Zhang, W. and Wang, X. (2020) Diagnostic Value of Neutrophil-Lymphocyte Ratio for Predicting the Severity of Acute Pancreatitis: A Meta-Analysis. Disease Markers, 2020, 1-9. [Google Scholar] [CrossRef] [PubMed]
[22] Mare, T.A., Treacher, D.F., Shankar-Hari, M., Beale, R., Lewis, S.M., Chambers, D.J., et al. (2015) The Diagnostic and Prognostic Significance of Monitoring Blood Levels of Immature Neutrophils in Patients with Systemic Inflammation. Critical Care, 19, 1-11. [Google Scholar] [CrossRef] [PubMed]
[23] Lipiński, M. and Rydzewska, G. (2017) Immature Granulocytes Predict Severe Acute Pancreatitis Independently of Systemic Inflammatory Response Syndrome. Gastroenterology Review, 2, 140-144. [Google Scholar] [CrossRef] [PubMed]
[24] Zhang, Y., Cheng, B., Wu, Z., Cui, Z., Song, Y., Chen, S., et al. (2021) Serum Soluble Suppression of Tumorigenicity 2 as a Novel Inflammatory Marker Predicts the Severity of Acute Pancreatitis. World Journal of Gastroenterology, 27, 6489-6500. [Google Scholar] [CrossRef] [PubMed]
[25] Hong, W., Lin, S., Zippi, M., Geng, W., Stock, S., Zimmer, V., et al. (2017) High-Density Lipoprotein Cholesterol, Blood Urea Nitrogen, and Serum Creatinine Can Predict Severe Acute Pancreatitis. BioMed Research International, 2017, 1-7. [Google Scholar] [CrossRef] [PubMed]
[26] Kong, D., Lei, Z., Wang, Z., Yu, M., Li, J., Chai, W., et al. (2023) A Novel HCP (Heparin-Binding Protein-C Reactive Protein-Procalcitonin) Inflammatory Composite Model Can Predict Severe Acute Pancreatitis. Scientific Reports, 13, 9440-9448. [Google Scholar] [CrossRef] [PubMed]
[27] Al-Qahtani, H.H., Alam, M.K. and Waheed, M. (2017) Comparison of Harmless Acute Pancreatitis Score with Ranson’s Score in Predicting the Severity of Acute Pancreatitis. Journal of College of Physicians and Surgeons Pakistan, 27, 75-79.
[28] Chauhan, S. and Forsmark, C.E. (2010) The Difficulty in Predicting Outcome in Acute Pancreatitis. American Journal of Gastroenterology, 105, 443-445. [Google Scholar] [CrossRef] [PubMed]
[29] Silva-Vaz, P., Abrantes, A.M., Castelo-Branco, M., Gouveia, A., Botelho, M.F. and Tralhão, J.G. (2020) Multifactorial Scores and Biomarkers of Prognosis of Acute Pancreatitis: Applications to Research and Practice. International Journal of Molecular Sciences, 21, Article 338. [Google Scholar] [CrossRef] [PubMed]
[30] Park, J.Y., Jeon, T.J., Ha, T.H., Hwang, J.T., Sinn, D.H., Oh, T., et al. (2013) Bedside Index for Severity in Acute Pancreatitis: Comparison with Other Scoring Systems in Predicting Severity and Organ Failure. Hepatobiliary & Pancreatic Diseases International, 12, 645-650. [Google Scholar] [CrossRef] [PubMed]
[31] Hagjer, S. and Kumar, N. (2018) Evaluation of the BISAP Scoring System in Prognostication of Acute Pancreatitis—A Prospective Observational Study. International Journal of Surgery, 54, 76-81. [Google Scholar] [CrossRef] [PubMed]
[32] Papachristou, G.I., Muddana, V., Yadav, D., O’Connell, M., Sanders, M.K., Slivka, A., et al. (2010) Comparison of BISAP, Ranson’s, APACHE-II, and CTSI Scores in Predicting Organ Failure, Complications, and Mortality in Acute Pancreatitis. American Journal of Gastroenterology, 105, 435-441. [Google Scholar] [CrossRef] [PubMed]
[33] Lu, F., Zhang, Y., Yu, J., Ge, Z. and Gu, L. (2023) Clinical Value of BISAP Score Combined with CRP and NLR in Evaluating the Severity of Acute Pancreatitis. Medicine, 102, e35934. [Google Scholar] [CrossRef] [PubMed]
[34] Guidelines APAAP (2013) IAP/APA Evidence-Based Guidelines for the Management of Acute Pancreatitis. Pancreatology, 13, e1-e15.
[35] 肖鹏, 李青云, 梁蓉. SIRS早期预测重症急性胰腺炎价值的再评价[J]. 吉林医学, 2017, 38(6): 1022-1024.
[36] Sahu, B., Abbey, P., Anand, R., Kumar, A., Tomer, S. and Malik, E. (2017) Severity Assessment of Acute Pancreatitis Using CT Severity Index and Modified CT Severity Index: Correlation with Clinical Outcomes and Severity Grading as per the Revised Atlanta Classification. Indian Journal of Radiology and Imaging, 27, 152-160. [Google Scholar] [CrossRef] [PubMed]
[37] Leppäniemi, A., Tolonen, M., Tarasconi, A., Segovia-Lohse, H., Gamberini, E., Kirkpatrick, A.W., et al. (2019) 2019 WSES Guidelines for the Management of Severe Acute Pancreatitis. World Journal of Emergency Surgery, 14, 1-20. [Google Scholar] [CrossRef] [PubMed]
[38] Lankisch, P.G., Weber-Dany, B., Hebel, K., Maisonneuve, P. and Lowenfels, A.B. (2009) The Harmless Acute Pancreatitis Score: A Clinical Algorithm for Rapid Initial Stratification of Nonsevere Disease. Clinical Gastroenterology and Hepatology, 7, 702-705. [Google Scholar] [CrossRef] [PubMed]
[39] Gupta, D., Mandal, N.S., Arora, J.K. and Soni, R.K. (2022) Comparative Evaluation of Harmless Acute Pancreatitis Score (HAPS) and Bedside Index of Severity in Acute Pancreatitis (BISAP) Scoring System in the Stratification of Prognosis in Acute Pancreatitis. Cureus, 14, e32540. [Google Scholar] [CrossRef] [PubMed]
[40] 马小华, 李兰, 金涛, 等. 入院时无害性急性胰腺炎评分可预测轻症急性胰腺炎[J]. 南方医科大学学报, 2020, 40(2): 190-195.
[41] Chauhan, R., Saxena, N., Kapur, N. and Kardam, D. (2022) Comparison of Modified Glasgow-Imrie, Ranson, and Apache II Scoring Systems in Predicting the Severity of Acute Pancreatitis. Polish Journal of Surgery, 95, 1-8. [Google Scholar] [CrossRef] [PubMed]
[42] Nazar, N., Read, P., Bolton, H. and Bailey, C. (2024) ThP5.3—A Clinical Audit on Assessing Severe Acute Pancreatitis: Improving the Use of the Glasgow-Imrie Criteria and Outcomes. British Journal of Surgery, 111, znae197.277. [Google Scholar] [CrossRef
[43] Wang, L., Zeng, Y., Chen, J., Luo, Q., Wang, R., Zhang, R., et al. (2020) A Simple New Scoring System for Predicting the Mortality of Severe Acute Pancreatitis. Medicine, 99, e20646. [Google Scholar] [CrossRef] [PubMed]