切换至 "中华医学电子期刊资源库"
高级检索
中华妇幼临床医学杂志(电子版)

中华妇幼临床医学杂志(电子版) ›› 2023, Vol. 19 ›› Issue (02) : 178 -186. doi: 10.3877/cma.j.issn.1673-5250.2023.02.009

论著

儿童重症监护室脓毒症患儿死亡相关影响因素分析
刘顺利, 田志青, 曹杨, 乔莉娜†()   
  1. 四川大学华西第二医院儿科、出生缺陷与相关妇儿疾病教育部重点实验室、国家卫生健康委员会时间生物学重点实验室(四川大学)，成都　610041
  • 收稿日期:2022-10-15 修回日期:2023-02-10 出版日期:2023-04-01
  • 通信作者: 乔莉娜

Analysis of death-related factors in children with sepsis among Pediatric Intensive Care Unit

Shunli Liu, Zhiqing Tian, Yang Cao, Lina Qiao†()   

  1. Department of Pediatric Intensive Care Unit, Key Laboratory of Birth Defectsand Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, NHC Key Laboratory of Chronobiology (Sichuan University), Chengdu 610041, Sichuan Province, China
  • Received:2022-10-15 Revised:2023-02-10 Published:2023-04-01
  • Corresponding author: Lina Qiao
  • Supported by:
    National Key R & D Plan Project(2021YFC2701705); Developmental Special Project of Sichuan Provincial Central Leading Local Science and Technology(2021ZYD0105)
全文 ( ) 下载PDF ( ) 导出引用
引用本文：

刘顺利, 田志青, 曹杨, 乔莉娜. 儿童重症监护室脓毒症患儿死亡相关影响因素分析[J/OL]. 中华妇幼临床医学杂志(电子版), 2023, 19(02): 178-186.

Shunli Liu, Zhiqing Tian, Yang Cao, Lina Qiao. Analysis of death-related factors in children with sepsis among Pediatric Intensive Care Unit[J/OL]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(02): 178-186.

目的

探讨儿童重症监护病房(PICU)脓毒症患儿死亡相关影响因素。

方法

选择2019年6月至2021年1月，于四川大学华西第二医院PICU收治的234例脓毒症患儿为研究对象。采用回顾性分析方法，按照PICU治疗结局，将其分别纳入死亡组(n＝44)和存活组(n＝190)。对2组患儿临床病例资料、入院24 h内实验室检查结果进行统计学分析。结合已有研究结果及临床经验及单因素分析中差异有统计学意义(P<0.05)因素，对脓毒症患儿死亡相关影响因素进行多因素非条件logistics回归分析，并建立logistic回归方程(预测模型)。绘制不同指标预测脓毒症患儿死亡相关影响因素的受试者工作特征(ROC)曲线，并计算曲线下面积(AUC)。本研究遵循的程序符合2013年修订的《世界医学协会赫尔辛基宣言》的要求。

结果

①2组患儿年龄、脓毒症不同严重程度构成比、使用血管活性药物者占比比较，差异均有统计学意义(P<0.05)；年龄<5岁和≥5岁患儿的脓毒症严重程度占比比较，差异均有统计学意义(P<0.05)。②2组患儿的血清血小板计数(PLT)、丙氨酸转移酶(ALT)、尿素氮、血清肌酐(SCr)、凝血酶原时间(PT)、血清HCO3－、血清乳酸浓度比较，差异均有统计学意义(P<0.05)。③2组患儿的Glasgow评分、儿童序贯器官衰竭评分(pSOFA)和第3代小儿死亡危险(PRISMⅢ)评分比较，差异均有统计学意义(P<0.05)，而2组患儿小儿危重病例评分(PCIS)比较，差异无统计学意义(P>0.05)。④多因素非条件logistics回归分析显示，年龄(OR＝1.011，95%CI：1.005~1.018，P<0.001)、血清乳酸浓度(OR＝1.132，95%CI：1.005~1.275，P＝0.041)是导致脓毒症患儿死亡的独立危险因素。建立的预测脓毒症患儿死亡相关影响因素的logistic回归方程为：y＝0.918－0.312x1+0.124x2+0.011x3(x1为Glasgow评分，x2为血清乳酸浓度，x3为年龄)，对脓毒症患儿死亡具有良好预测价值，其ROC-AUC为0.84(95%CI：0.775~0.904，P<0.05)，预测脓毒症患儿死亡的灵敏度为86.4%，特异度为68.4%。

结论

该logistic回归方程对预测脓毒症患儿预后相关影响因素的灵敏度及综合价值，均优于pSOFA和PRISMⅢ，适用于对脓毒症患儿预后不良的早期筛查。

关键词: 脓毒症, 死亡, 预后, 血清乳酸, 年龄因素, Glasgow评分, Logistic模型, 儿童
Objective

To investigate the death-related factors in children with sepsis among Pediatric Intensive Care Unit (PICU).

Methods

From June 2019 to January 2021, 234 children with sepsis admitted to PICU of West China Second University Hospital, Sichuan University were selected in this study. They were divided into death group (n=44) and survival group (n=190) based on whether they died during PICU stay. Clinical data and laboratory test results within 24 hours of admission were retrospectively analyzed. Based on factors with statistically significant differences (P<0.05) in the univariate analysis and clinical experience, multivariate unconditional logistic regression analysis was conducted to identify the death-related factors of children with sepsis, and a logistic regression equation (predictive model) was established. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of different indicators for mortality risk in children with sepsis, and the area under the curve (AUC) was calculated. The procedures followed in this study was in line with the World Medical Association Declaration of Helsinki revised in 2013.

Results

① There were statistically significant differences in the age, severity of sepsis, and proportion of patients using vasoactive drugs between two groups (P<0.05). There were also statistically significant differences in the proportion of patients with different levels of sepsis severity between patients aged <5 years and those aged ≥5 years (P<0.05). ② There were statistically significant differences in the levels of serum platelet count (PLT), alanine transaminase (ALT), blood urea nitrogen, serum creatinine (SCr), prothrombin time (PT), serum HCO3-, and lactate between two groups (P<0.05). ③ There were statistically significant differences in the Glasgow score, pediatric sequential organ failure assessment (pSOFA), and pediatric risk of mortality Ⅲ(PRISM Ⅲ) scores between two groups (P<0.05), but no statistically significant difference in the pediatric critical illness score (PCIS) score (P>0.05). ④Multivariate unconditional logistic regression analysis showed that age (OR=1.011, 95%CI: 1.005-1.018, P<0.001) and lactate level (OR=1.132, 95%CI: 1.005-1.275, P=0.041) were independent risk factors for prognosis of children with sepsis. The logistic regression equation (y=0.918-0.312x1+ 0.124x2+ 0.011x3, where x1 is the Glasgow score, x2 is the lactate level, and x3 is age) had good predictive value for mortality risk in children with sepsis, with the ROC-AUC of 0.84 (95%CI: 0.775-0.904, P<0.05). Its sensitivity was 86.4%, and its specificity was 68.4%.

Conclusions

The logistic regression equation established in this study has higher sensitivity and comprehensive value in predicting mortality risk in children with sepsis than the pSOFA score and PRISMⅢ score, and are suitable for early screening of poor prognosis in children with sepsis.

Key words: Sepsis, Death, Prognosis, Lactic acid, Age factors, Glasgow score, Logistic models, Child
表1 不同年龄段脓毒症患儿严重程度比较[例数(%)]
不同年龄段 例数 脓毒症 严重脓毒症 脓毒性休克
<5岁 175 35(20.0) 89(50.9) 51(29.1)
≥5岁 59 4(6.8) 38(64.4) 17(28.8)
χ2值   6.12  
P值   0.047  
表2 2组脓毒症患儿一般临床资料比较
组别 例数 性别[例数(%)] 年龄[岁，M (Q1，Q3)] 年龄段[例数(%)] 基础疾病[例数(%)] 使用血管活性药物[例数(%)]
男 女 ≤1岁 1~5岁 ≥5岁 先天性心脏病 早产儿 肿瘤
存活组 190 109(57.4) 81(42.6) 8.0(2.0，22.0) 114(60.0) 33(17.4) 43(22.6) 13(6.8) 24(12.6) 5(2.6) 31(16.3)
死亡组 44 29(68.9) 15(34.1) 16.0(8.2，143.8) 20(45.4) 8(18.2) 16(36.4) 1(2.3) 0(0) 5(11.4) 25(56.8)
统计值   χ2＝0.87 Z＝2.96 χ2＝4.01 χ2＝6.39 χ2＝32.19
P值   0.224 0.003 0.137 0.076 <0.001
组别 例数 脓毒症严重程度[例数(%)] 感染部位[例数(%)] 血培养[例数(%)]
脓毒症 严重脓毒症 脓毒性休克 肺 腹腔 颅内 血液 其他部位 阳性 阴性
存活组 190 37(19.5) 113(59.5) 40(21.0) 82(42.1) 32(16.8) 40(21.0) 23(12.1) 13(6.8) 23(12.1) 167(87.9)
死亡组 44 2(4.5) 14(31.8) 28(63.6) 18(40.9) 4(9.1) 17(38.5) 4(9.1) 1(2.3) 4(9.1) 40(90.9)
统计值   χ2＝32.11 χ2＝7.50 χ2＝0.32
P值   <0.001 0.109 0.397
表3 2组脓毒症患儿PICU治疗24 h内实验室检查指标比较[M(Q1，Q3)]
组别 例数 MAP(mmHg) WBC(×109/L) NLR Hb(g/L) PLT(×109/L) CRP(mg/L)
存活组 190 68.7(60.3，77.2) 10.5(6.0，15.9) 1.6(0.7，3.5) 94.0(77.0，110.0) 286.5(180.5，392.3) 27.2(4.9，96.6)
死亡组 44 64.8(53.5，77.3) 9.5(6.4，14.6) 2.5(0.9，6.0) 98.5(82.5，106.5) 196.5(47.5，352.5) 30.7(4.9，115.9)
Z值   －1.36 －0.51 －1.60 －0.28 －2.47 －0.73
P值   0.175 0.612 0.109 0.777 0.014 0.468
组别 例数 ALT(U/L) TB(mmol/L) 尿素氮(mmol/L) SCr(μmol/L) PT(s) APTT(s)
存活组 190 32.0(22.2，54.5) 12.7(6.8，21.7) 4.3(2.8，7.4) 24.0(18.0，47.5) 13.6(12.2，15.5) 31.6(27.2，37.3)
死亡组 44 50.5(24.8，119.0) 9.3(5.0，26.8) 5.2(4.1，8.9) 35.5(26.8，52.8) 14.2(13.4，18.9) 33.7(27.5，46.6)
Z值   －2.31 －0.59 －3.95 －4.08 －3.49 －1.45
P值   0.021 0.555 <0.001 <0.001 <0.001 0.148
组别 例数 pH值 血糖(mmol/L) 血清HCO3－(mmol/L) 血清乳酸(mmol/L) PCT(ng/mL) 氧合指数
存活组 190 7.4(7.4，7.5) 5.8(4.9，7.0) 21.0(17.2，24.3) 1.6(1.0，2.9) 1.6(0.3，11.6) 312.6(213.9，421.3)
死亡组 44 7.4(7.3，7.5) 6.4(4.9，8.2) 18.0(13.5，23.4) 2.3(1.6，4.9) 3.0(0.5，22.0) 274.9(168.9，4340.0)
Z值   －1.21 －1.05 －2.42 －3.06 －1.38 －1.35
P值   0.228 0.294 0.016 0.002 0.166 0.178
表4 2组脓毒症患儿危重程度评分比较[分，M(Q1，Q3)]
组别 例数 Glasgow评分 pSOFA评分 PRISMⅢ评分 PCIS评分
存活组 190 13.00(10.25，14.00) 4.00(3.00，7.00) 4.00(0，8.00) 76.00(71.00，80.00)
死亡组 44 7.50(3.00，11.25) 5.50(3.75，9.75) 10.00(5.00，17.50) 76.00(68.00，82.00)
Z值   －5.47 －2.94 －5.31 －1.79
P值   <0.001 0.003 <0.001 0.073
表5 脓毒症患儿预后相关影响因素的多因素非条件logistics回归分析
影响因素 B BE Wald值 P值 OR值 OR值95%CI
Glasgow评分 －0.312 0.055 32.345 <0.001 0.732 0.657~0.815
血清乳酸 0.124 0.061 4.157 0.041 1.132 1.005~1.275
年龄 0.011 0.003 12.931 <0.001 1.011 1.005~1.018
常数项 0.981 0.616 2.532 0.112 2.667 —
表6 预测脓毒症患儿预后相关影响因素的ROC曲线分析结果
指标 ROC曲线 灵敏度(%) 特异度(%) 最佳临界值
AUC AUC 95%CI P值
Glasgow评分a 0.760 0.670~0.850 <0.001 65.9 80.5 11分
PCIS评分a 0.588 0.480~0.695 0.069 45.5 77.9 71分
pSOFA评分 0.641 0.549~0.734 0.004 45.4 74.2 7分
PRISMⅢ评分 0.756 0.674~0.838 <0.001 59.1 81.6 10分
血清乳酸 0.648 0.558~0.739 0.002 84.1 46.8 1.5 mmol/L
logistic回归方程(预测模型)b 0.840 0.775~0.904 <0.001 86.4 68.4 —
图1 预测脓毒症患儿死亡风险增高的ROC曲线图注：a本研究建立的预测脓毒症患儿死亡相关影响因素的logistic回归方程(预测模型)为y＝0.918－0.312x1+0.124x2+0.011x3，其中，x1为Glasgow评分，x2为血清乳酸浓度，x3为年龄。ROC为受试者特征曲线。PRISMⅢ评分为第3代小儿死亡危险评分，pSOFA儿童序贯器官衰竭评分，PCIS为小儿危重病例评分
[1]
陈丽妮，乔莉娜. 实验室指标在早期鉴别诊断脓毒症和川崎病中的应用 [J/OL]. 中华妇幼临床医学杂志(电子版), 2022, 18(4) : 460-467. DOI: 10.3877/cma.j.issn.1673-5250.2022.04.012.
[2]
Rudd KE, Johnson SC, Agesa KM, et al. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study [J]. Lancet, 2020, 395(10219): 200-211. DOI: 10.1016/S0140-6736(19)32989-7.
[3]
Djordjevic D, Rondovic G, Surbatovic M, et al. Neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and mean platelet volume-to-platelet count ratio as biomarkers in critically Ⅲ and injured patients: which ratio to choose to predict outcome and nature of bacteremia? [J]. Mediators Inflamm, 2018, 2018: 3758068. DOI: 10.1155/2018/3758068.
[4]
Jiang Z, Bo L, Xu Z, et al. An explainable machine learning algorithm for risk factor analysis of in-hospital mortality in sepsis survivors with ICU readmission [J]. Comput Methods Programs Biomed, 2021, 204: 106040. DOI: 10.1016/j.cmpb.2021.106040.
[5]
Liang P, Yu F. Value of CRP, PCT, and NLR in prediction of severity and prognosis of patients with bloodstream infections and sepsis [J]. Front Surg, 2022, 9: 857218. DOI: 10.3389/fsurg.2022.857218.
[6]
Zhou H, Li Z, Liang H, et al. Thrombocytopenia and platelet count recovery in patients with sepsis-3: a retrospective observational study [J]. Platelets, 2022, 33(4): 612-620. DOI: 10.1080/09537104.2021.1970124.
[7]
曹杨，刘瀚旻. 生物标志物在新生儿脓毒症中的应用研究进展 [J/OL]. 中华妇幼临床医学杂志(电子版)，2021, 17(6): 643-649. DOI: 10.3877/cma.j.issn.1673-5250.2021.06.004.
[8]
林丽曼，柯创宏，黄宇戈. 儿童脓毒性休克低血压参考范围的研究现状[J]. 发育医学电子杂志，2021, 9(5): 386-389. DOI: 10.3969/j.issn.2095-5340.2021.05.011.
[9]
Mohamed El-Mashad G, Said El-Mekkawy M, Helmy Zayan M. Paediatric sequential organ failure assessment (pSOFA) score: a new mortality prediction score in the paediatric intensive care unit [J]. An Pediatr (Engl Ed), 2020, 92(5): 277-285. DOI: 10.1016/j.anpedi.2019.05.018.
[10]
周利兵，陈娇，杜晓晨，等. 探讨3种评分系统对儿童严重脓毒症预后的评估价值[J]. 中国当代儿科杂志，2019, 21(9): 898-903. DOI：10.7499/j.issn.1008-8830.2019.09.011.
[11]
中华医学会儿科学分会急救学组，中华医学会急诊医学分会儿科学组，中国医师协会儿童重症医师分会. 儿童脓毒性休克(感染性休克)诊治专家共识(2015版) [J]. 中华儿科杂志，2015, 53(8): 576-580. DOI: 10.3760/cma.j.issn.0578-1310.2015.08.007
[12]
Pollack MM, Patel KM, Ruttimann UE. PRISM Ⅲ：an updated Pediatric Risk of Mortality score [J]. Crit Care Med, 1996, 24(5): 743-752. DOI: 10.1097/00003246-199605000-00004.
[13]
Matics TJ, Sanchez-Pinto LN. Adaptation and validation of a pediatric sequential organ failure assessment score and evaluation of the Sepsis-3 definitions in critically Ⅲ children [J]. JAMA Pediatr, 2017, 171(10): e172352. DOI: 10.1001/jamapediatrics.2017.2352.
[14]
张慧平，王金会，李思袖，等．胸腔生物电阻抗法无创血流动力学监测对新生儿脓毒症患儿心功能障碍的预测价值 [J/OL]. 中华妇幼临床医学杂志(电子版)，2022, 18(2): 220-227. DOI: 10.3877/cma.j.issn.1673-5250.2022.02.014.
[15]
GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 [J]. Lancet, 2020, 396(10258): 1204-1222. DOI: 10.1016/S0140-6736(20)30925-9.
[16]
Tan B, Wong JJ, Sultana R, et al. Global case-fatality rates in pediatric severe sepsis and septic shock: a systematic review and Meta-analysis [J]. JAMA Pediatr, 2019, 173(4): 352-362. DOI: 10.1001/jamapediatrics.2018.4839. Erratum in: JAMA Pediatr, 2019, 173(4): 401.
[17]
Zhou J, Qian C, Zhao M, et al. Epidemiology and outcome of severe sepsis and septic shock in intensive care units in mainland China [J]. PLoS One, 2014, 9(9): e107181. DOI: 10.1371/journal.pone.0107181
[18]
Hermon MM, Etmayr T, Brandt JB, et al. Pediatric infection and sepsis in five age subgroups: single-center registry [J]. Wien Med Wochenschr, 2021, 171(1-2): 29-35. DOI: 10.1007/s10354-020-00787-6.
[19]
Menon K, Schlapbach LJ, Akech S, et al. Criteria for pediatric Sepsis-A systematic review and Meta-analysis by the Pediatric Sepsis Definition Taskforce [J]. Crit Care Med, 2022, 50(1): 21-36. DOI: 10.1097/CCM.0000000000005294.
[20]
Motzkus CA, Luckmann R. Does infection site matter? A systematic review of infection site mortality in sepsis [J]. J Intensive Care Med, 2017, 32(8): 473-479. DOI: 10.1177/0885066615627778.
[21]
白欢，沈玲，静亮，等. 凝血酶原时间对脓毒症患者病情严重程度判断及预后评估的价值研究 [J]. 中华危重病急救医学，2022, 34(7): 682-688. DOI: 10.3760/cma.j.cn121430-20210614-00876..
[22]
Schupp T, Weidner K, Rusnak J, et al. Diagnostic and prognostic role of platelets in patients with sepsis and septic shock [J]. Platelets, 2023, 34(1): 2131753. DOI: 10.1080/09537104.2022.2131753.
[23]
何新飙，闫素英，丁红叶. 血浆内皮素和凝血功能对脓毒症患者近期预后的判断价值 [J]. 中国危重病急救医学，2009,21(8): 495-496. DOI: 10.3760/cma.j.issn.1003-0603.2009.08.017.
[24]
Schrottmaier WC, Kral JB, Badrnya S, et al. Aspirin and P2Y12 inhibitors in platelet-mediated activation of neutrophils and monocytes [J]. Thromb Haemost, 2015, 114(3): 478-489. DOI: 10.1160/TH14-11-0943.
[25]
Kral JB, Schrottmaier WC, Salzmann M, et al. Platelet interaction with innate immune cells [J]. Transfus Med Hemother, 2016, 43(2): 78-88. DOI: 10.1159/000444807.
[26]
Drews RE, Weinberger SE. Thrombocytopenic disorders in critically ill patients [J]. Am J Respir Crit Care Med, 2000, 162(2 Pt 1): 347-351. DOI: 10.1164/ajrccm.162.2.ncc3-00.
[27]
Claushuis TA, van Vught LA, Scicluna BP, et al. Thrombocytopenia is associated with a dysregulated host response in critically ill sepsis patients [J]. Blood, 2016, 127(24): 3062-3072. DOI: 10.1182/blood-2015-11-680744.
[28]
Ma H, Liu H, Wu C, et al. Diagnostic value of serum heparin binding protein, blood lactic acid combined with hs-CRP in sepsis and its relationship with prognosis [J]. Evid Based Complement Alternat Med, 2021, 2021: 5023733. DOI: 10.1155/2021/5023733.
[29]
Bakker J, Postelnicu R, Mukherjee V. Lactate: where are we now? [J]. Crit Care Clin, 2020, 36(1): 115-124. DOI: 10.1016/j.ccc.2019.08.009.
[30]
Liu Y, Zheng J, Zhang D, et al. Neutrophil-lymphocyte ratio and plasma lactate predict 28-day mortality in patients with sepsis [J]. J Clin Lab Anal, 2019, 33(7): e22942. DOI: 10.1002/jcla.22942.
[31]
Jones AE, Shapiro NI, Trzeciak S, et al. Lactate clearance vs central venous oxygen saturation as goals of early sepsis therapy: a randomized clinical trial [J]. JAMA, 2010, 303(8): 739-746. DOI: 10.1001/jama.2010.158.
[32]
Lee SG, Song J, Park DW, et al. Prognostic value of lactate levels and lactate clearance in sepsis and septic shock with initial hyperlactatemia: a retrospective cohort study according to the Sepsis-3 definitions [J]. Medicine (Baltimore), 2021, 100(7): e24835. DOI: 10.1097/MD.0000000000024835.
[33]
El-Mekkawy MS, Ellahony DM, Khalifa KAE, et al. Plasma lactate can improve the accuracy of the Pediatric Sequential Organ Failure Assessment Score for prediction of mortality in critically ill children: a pilot study [J]. Arch Pediatr, 2020, 27(4): 206-211. DOI: 10.1016/j.arcped.2020.03.004.
[34]
Kc B, Adil MZ. Knowledge of glasgow coma scale among nurses in a tertiary care centre: a descriptive cross-sectional study [J]. JNMA J Nepal Med Assoc, 2022, 60(252): 723-726. DOI: 10.31729/jnma.7673.
[35]
Lin Y, Zhang S, Zhang W, et al. The prediction value of Glasgow coma scale-pupils score in neurocritical patients: a retrospective study [J]. Brain Inj, 2021, 35(5): 547-553. DOI: 10.1080/02699052.2021.1890821.
[36]
Lane DJ, Wunsch H, Saskin R, et al. Epidemiology and patient predictors of infection and sepsis in the prehospital setting [J]. Intensive Care Med, 2020, 46(7): 1394-1403. DOI: 10.1007/s00134-020-06093-4.
[1] 陶宏宇, 叶菁菁, 俞劲, 杨秀珍, 钱晶晶, 徐彬, 徐玮泽, 舒强. 右心声学造影在儿童右向左分流相关疾病中的评估价值[J/OL]. 中华医学超声杂志（电子版）, 2024, 21(10): 959-965.
[2] 许杰, 李亚俊, 韩军伟. 两种入路下腹腔镜根治性全胃切除术治疗超重胃癌的效果比较[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(01): 19-22.
[3] 高杰红, 黎平平, 齐婧, 代引海. ETFA和CD34在乳腺癌中的表达及与临床病理参数和预后的关系研究[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(01): 64-67.
[4] 李代勤, 刘佩杰. 动态增强磁共振评估中晚期低位直肠癌同步放化疗后疗效及预后的价值[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(01): 100-103.
[5] 李伟, 宋子健, 赖衍成, 周睿, 吴涵, 邓龙昕, 陈锐. 人工智能应用于前列腺癌患者预后预测的研究现状及展望[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 541-546.
[6] 赵月, 田坤, 张宗明, 郭震天, 刘立民, 张翀, 刘卓. 降钙素原对老年急性重度胆囊炎发生的预测价值[J/OL]. 中华肝脏外科手术学电子杂志, 2024, 13(06): 801-806.
[7] 韩加刚, 王振军. 梗阻性左半结肠癌的治疗策略[J/OL]. 中华结直肠疾病电子杂志, 2024, 13(06): 450-458.
[8] 刘郁, 段绍斌, 丁志翔, 史志涛. miR-34a-5p 在结肠癌患者的表达及其与临床特征及预后的相关性研究[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 485-490.
[9] 陈倩倩, 袁晨, 刘基, 尹婷婷. 多层螺旋CT 参数、癌胚抗原、错配修复基因及病理指标对结直肠癌预后的影响[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 507-511.
[10] 曾明芬, 王艳. 急性胰腺炎合并脂肪肝患者CT 与彩色多普勒超声诊断参数与其病情和预后的关联性研究[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 531-535.
[11] 沈炎, 张俊峰, 唐春芳. 预后营养指数结合血清降钙素原、胱抑素C及视黄醇结合蛋白对急性胰腺炎并发急性肾损伤的预测价值[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 536-540.
[12] 王景明, 王磊, 许小多, 邢文强, 张兆岩, 黄伟敏. 腰椎椎旁肌的研究进展[J/OL]. 中华临床医师杂志(电子版), 2024, 18(09): 846-852.
[13] 颜世锐, 熊辉. 感染性心内膜炎合并急性肾损伤患者的危险因素探索及死亡风险预测[J/OL]. 中华临床医师杂志(电子版), 2024, 18(07): 618-624.
[14] 丁洪基, 赵长江, 孙鹏飞, 王灿, 王贵珍, 李龙龙. 细胞焦亡与疾病的关系研究进展[J/OL]. 中华临床医师杂志(电子版), 2024, 18(07): 682-686.
[15] 郭曌蓉, 王歆光, 刘毅强, 何英剑, 王立泽, 杨飏, 汪星, 曹威, 谷重山, 范铁, 李金锋, 范照青. 不同亚型乳腺叶状肿瘤的临床病理特征及预后危险因素分析[J/OL]. 中华临床医师杂志(电子版), 2024, 18(06): 524-532.
阅读次数
全文


摘要

版权所有 中华医学会 中华医学电子音像出版社有限责任公司  京ICP备14006079号-1  网络出版服务许可证：(署)网出证(京)字第075号

AI
小
编
AI小编
你好！我是《中华医学电子期刊资源库》AI小编，有什么可以帮您的吗？