基于脓毒性休克治疗期间液体负平衡量建立患者预后预测模型

doi:10.3969/j.issn.1006-5725.2025.11.012

Abstract

Abstract:

Objective To determine the predictive power of negative fluid balance in the risk of death in septic shock patients after fluid resuscitation therapy. Methods The medical records of patients with septic shock admitted to the Intensive Care Department of Tianjin Medical University Cancer Hospital from March 2022 to December 2024 were retrospectively collected， and the final outcome was defined as death within 28 days during hospitalization. The study objects were randomly divided into the training set and the validation set， and then the model was built by Logistic regression method， and the nomogram and receiver operating characteristic curve （ROC curve） were drawn. Hosmer-Lemeshow test was used to evaluate the calibration degree of the prediction model， and the calibration curve was drawn to evaluate the differentiation degree of the prediction model. Decision curve analysis （DCA） was used to test the efficiency of the prediction model. Results A total of 286 patients with septic shock were included in the study， including 200 in the training set and 86 in the verification set， which were comparable. Multivariate Logistic regression analysis showed that negative fluid balance， APACHE II score and SOFA score were independent risk factors for poor survival and prognosis of ICU septic shock patients （all P < 0.05）. Based on the results of multivariate Logistic regression analysis， a nomogram was constructed to predict the survival and prognosis of patients with septic shock in ICU. In the training set and validation set， the area under the curve （AUC） of the ROC curve prediction model was 0.83 （95%CI：0.73 ~ 0.93） and 0.83 （95%CI：0.66 ~ 1.00）， respectively. Hosmer-Lemeshow calibration curve has a good fit （training set P= 0.169； The verification set P = 1.000） is not significant. DCA showed that when the threshold probability of patients was 0.05~0.70， it was more beneficial to use the nomogram prediction model to predict the risk of death in septic shock patients. Conclusion Negative fluid balance after fluid resuscitation is associated with survival and prognosis of patients with septic shock. The predictive model of mortality risk of patients with septic shock was established by combining APACHEⅡ score and SOFA score， which has good predictive ability and clinical practicability.

Key words: septic shock, negative fluid balance, nomogram, prediction model

CLC Number:

R459.7

Zhen ZHANG,Donghao WANG,Yang LYU. A prognostic model for patients was established based on negative fluid balance during septic shock treatment[J]. The Journal of Practical Medicine, 2025, 41(11): 1687-1693.

Figures/Tables 7

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References 24

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变量	总体（n = 286）	验证集（n = 86）	训练集（n = 200）	χ² /t值	P值
身高（x ± s）/cm	167.62 ± 7.32	166.72 ± 6.85	168.00 ± 7.50	-1.36	0.176
年龄（x ± s）/岁	66.06 ± 9.97	66.64 ± 8.85	65.81 ± 10.43	0.64	0.520
体质量（x ± s）/kg	68.02 ± 12.13	68.78 ± 12.39	67.69 ± 12.04	0.69	0.488
NUTRIC评分（x ± s）	4.89 ± 1.67	4.89 ± 1.65	4.89 ± 1.68	-0.00	0.997
乳酸（x ± s）/（mmol/L）	2.99 ± 1.18	2.78 ± 0.75	3.08 ± 1.31	-2.00	0.057
白蛋白（x ± s）/（g/L）	31.48 ± 4.28	31.46 ± 3.93	31.49 ± 4.43	-0.05	0.959
尿素氮（x ± s）/（mmol/L）	7.79 ± 5.78	8.15 ± 6.64	7.62 ± 5.36	0.69	0.493
白细胞计数（x ± s）/（×10⁹/L）	12.99 ± 8.48	11.88 ± 6.57	13.46 ± 9.16	-1.45	0.147
白细胞介素?6（x ± s）/（pg/mL）	1147.71 ± 575.87	792.37 ± 219.31	1298.68 ± 672.46	-0.67	0.506
降钙素原（x ± s）/（ng/mL）	11.33 ± 5.23	10.57 ± 3.95	11.66 ± 5.70	-0.16	0.872
C反应蛋白（x ± s）/（mg/L）	140.84 ± 80.60	145.15 ± 88.11	138.95 ± 77.26	0.57	0.570
住院时间（x ± s）/d	16.80 ± 12.23	15.67 ± 11.26	17.29 ± 12.62	-1.02	0.308
每天平均液体负平衡量（x ± s）/（mL/d）	-254.97 ± 649.98	-224.65 ± 629.48	-268.00 ± 659.72	0.52	0.606
APACHE Ⅱ评分（x ± s）	17.59 ± 7.21	18.27 ± 7.37	17.30 ± 7.14	1.05	0.297
SOFA评分（x ± s）	6.20 ± 3.36	5.98 ± 3.52	6.30 ± 3.29	-0.75	0.456
性别［例（%）］				0.26	0.607
女	74（25.87）	24（27.91）	50（25.00）
男	212（74.13）	62（72.09）	150（75.00）
感染部位［例（%）］				0.61	0.895
肺炎	122（42.81）	36（41.86）	86（43.22）
胸腔感染	26（9.12）	9（10.47）	17（8.54）
腹腔感染	111（38.95）	32（37.21）	79（39.70）
其他部位	26（9.12）	9（10.47）	17（8.54）

变量	单因素					多因素
变量	β	SE	Wald χ² 值	P值	OR（95%CI）	β	SE	Wald χ² 值	P值	OR（95%CI）
液体负平衡量（mL/d）	0.01	0	4.28	< 0.001	1.01（1.01 ~ 1.01）	0.01	0	3.40	< 0.001	1.01（1.01 ~ 1.01）
APACHE Ⅱ评分	0.13	0.03	4.68	< 0.001	1.14（1.08 ~ 1.21）	0.11	0.04	2.79	0.005	1.11（1.03 ~ 1.20）
SOFA评分	0.25	0.06	3.95	< 0.001	1.29（1.14 ~ 1.46）	0.07	0.09	0.77	0.044	1.07（0.90 ~ 1.27）

变量	AUC（95%CI）	约登指数（95%CI）	灵敏度（95%CI）	特异度（95%CI）	阳性预测值（95%CI）	阴性预测值（95%CI）	截断值
训练集	0.83（0.73 ~ 0.93）	0.84（0.79 ~ 0.89）	0.86（0.81 ~ 0.91）	0.74（0.58 ~ 0.91）	0.96（0.92 ~ 0.99）	0.45（0.31 ~ 0.60）	0.16
验证集	0.83（0.66 ~ 1.00）	0.83（0.73 ~ 0.90）	0.84（0.75 ~ 0.92）	0.75（0.51 ~ 0.99）	0.95（0.90 ~ 1.00）	0.43（0.22 ~ 0.64）	0.16

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A prognostic model for patients was established based on negative fluid balance during septic shock treatment

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