The application of mathematical model in the analysis of multi-factor models of admission indicators and prognostic indicators for patients with brain injury

doi:10.3877/cma.j.issn.2096-1537.2019.04.010

Abstract

Abstract:

Objective

To explore the influence of prognosis indicators of multiple indicators and their interactionat hospital admission in patients with brain injury.

Methods

We analyzed the clinical data of 130 patients with craniocerebral trauma who were admitted to the Department of Critical Care Medicine of the Affiliated Hospital of Yangzhou University from January 2013 to August 2017. We performed a mathematical model to identify the correlation between data at hospital admission and outcome. The clinical data of 26 patients with craniocerebral trauma from October 2017 to December 2018 were collected for external validation.

Results

Sedation score (RASS) squared item, Grasse coma (GCS) score and RASS score interaction item, age and acute physiology and chronic health status (APACHEⅡ) score interaction item, heart rate and lactic acid (LAC) interaction term were significantly associated with outcome.

Conclusion

Mathematical models can be used to assess prognostic indicators in patients with brain injury.

Key words: Brain injury, Admission indicators, Prognosis indicators, Mathematical model

Guangfa Wei, Qingbin Zheng, Lijun Meng, Qingling Feng, Wenjie Yuan, Jinlei Ou, Yurong Wang, Jingjing Sun, Weili Liu, Yong Li. The application of mathematical model in the analysis of multi-factor models of admission indicators and prognostic indicators for patients with brain injury[J]. Chinese Journal of Critical Care & Intensive Care Medicine(Electronic Edition), 2019, 05(04): 346-352.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://icu.cma-cmc.com.cn/EN/10.3877/cma.j.issn.2096-1537.2019.04.010

https://icu.cma-cmc.com.cn/EN/Y2019/V05/I04/346

Figures/Tables 8

References 10

1	Jiang JY, Gao GY, Feng JF, et al. Traumatic brain injury in China [J]. Lancet Neurol, 2019, 18(3): 286-295.
2	Stocchetti N, Carbonara M, Citerio G, et al. Severe traumatic brain injury: targeted management in the intensive care unit [J]. Lancet Neurol, 2017, 16(6): 452-464.
3	Kuceyeski A, Shah S, Dyke JP, et al. The application of a mathematical model linking structural and functional connectomes in severe brain injury [J]. Neuroimage Clin, 2016, 11: 635-647.
4	Srinivasan US. A mathematical model for predicting the outcome in moderate head injury [J]. Neurol India, 2006, 54(1): 28-32.
5	Vaughan LE, Ranganathan PR, Kumar RG, et al. A mathematical model of neuroinflammation in severe clinical traumatic brain injury [J]. J Neuroinflammation, 2018, 15(1): 345.
6	Sheikhi S, Saboory E, Farjah GH. Correlation of nerve fibers in corpus callosum and number of neurons in cerebral cortex: an innovative mathematical model [J]. Int J Neurosci, 2018, 128(10): 995-1002.
7	Lord LD, Stevner AB, Deco G, et al. Understanding principles of integration and segregationusing whole-brain computational connectomics: implications for neuropsychiatric disorders [J]. Philos Trans A Math Phys Eng Sci, 2017, 375(2096).pii: 20160283.
8	Shiozaki T, Hayakata T, Tasaki O, et al. Cerebrospinal fluid concentrations of anti-inflammatory mediators inearly-phase severe traumatic brain injury [J]. Shock, 2005, 23(5): 406-410.
9	Porta A, Marchi A, Bari V, et al. Assessing the strength of cardiac and sympathetic baroreflex controls via transfer entropy during orthostatic challenge [J]. Philos Trans A Math Phys Eng Sci, 2017, 375(2096).pii: 20160290.
10	McCullough M, Small M, Iu HHC, et al. Multiscale ordinal network analysis of human cardiac dynamics [J]. Philos Trans A Math Phys Eng Sci, 2017, 375(2096).pii: 20160292.

编号	代码	指标	单位	内部验证数据（±s）	外部验证数据（±s）	P值
1	X₁	年龄	岁	54.60±13.88	57.80±18.62	0.072
2	X₂	APACHEⅡ评分	分	23.94±6.75	21.60±6.34	0.677
3	X₃	GCS	分	6.55±2.66	8.60±3.59	0.011
4	X₄	HR	次/分	84.58±22.15	89.56±31.42	0.025
5	X₅	SBP	mmHg	155.21±38.86	159.96±39.33	0.881
6	X₆	影像学出血量	ml	65.80±31.73	39.48±43.80	0.998
7	X₇	中线偏移	mm	9.26±7.23	7.16±5.54	0.067
8	X₈	PO₂	mmHg	87.19±23.85	90.16±27.89	0.093
9	X₉	PCO₂	mmHg	40.45±11.66	40.92±12.00	0.603
10	X₁₀	Lac	mmol/L	2.89±2.23	2.88±1.52	0.101
11	X₁₁	BG	mmol/L	9.66±3.51	10.88±4.31	0.380
12	X₁₂	RASS镇静评分	分	0.11±2.11	-2.00±2.00	0.497
13	Y	GOS	分	2.74±1.47	3.36±1.32	0.437

编号	代码	指标	单位	内部验证数据（±s）	外部验证数据（±s）	P值
1	X₁	年龄	岁	54.60±13.88	57.80±18.62	0.072
2	X₂	APACHEⅡ评分	分	23.94±6.75	21.60±6.34	0.677
3	X₃	GCS	分	6.55±2.66	8.60±3.59	0.011
4	X₄	HR	次/分	84.58±22.15	89.56±31.42	0.025
5	X₅	SBP	mmHg	155.21±38.86	159.96±39.33	0.881
6	X₆	影像学出血量	ml	65.80±31.73	39.48±43.80	0.998
7	X₇	中线偏移	mm	9.26±7.23	7.16±5.54	0.067
8	X₈	PO₂	mmHg	87.19±23.85	90.16±27.89	0.093
9	X₉	PCO₂	mmHg	40.45±11.66	40.92±12.00	0.603
10	X₁₀	Lac	mmol/L	2.89±2.23	2.88±1.52	0.101
11	X₁₁	BG	mmol/L	9.66±3.51	10.88±4.31	0.380
12	X₁₂	RASS镇静评分	分	0.11±2.11	-2.00±2.00	0.497
13	Y	GOS	分	2.74±1.47	3.36±1.32	0.437

项	偏相关	T检验	P值
r（Y，X₁₂*X₁₂）	-0.3582	4.1674	0.0001
r（Y，X₁*X₂）	-0.3303	3.8014	0.0002
r（Y，X₃*X₇）	-0.3465	4.0132	0.0001
r（Y，X₃*X₈）	0.5916	7.9700	0.0001
r（Y，X₃*X₁₂）	-0.1854	2.0490	0.0427
r（Y，X₄*X₈）	-0.2004	2.2222	0.0282
r（Y，X₄*X₁₀）	-0.3522	4.0872	0.0001
r（Y，X₅*X₆）	-0.3427	3.9622	0.0001
r（Y，X₅*X₇）	0.2808	3.1779	0.0019
r（Y，X₆*X₁₁）	0.2547	2.8606	0.0050
r（Y，X₇*X₁₁）	-0.1851	2.0463	0.0429

项	偏相关	T检验	P值
r（Y，X₁₂*X₁₂）	-0.3582	4.1674	0.0001
r（Y，X₁*X₂）	-0.3303	3.8014	0.0002
r（Y，X₃*X₇）	-0.3465	4.0132	0.0001
r（Y，X₃*X₈）	0.5916	7.9700	0.0001
r（Y，X₃*X₁₂）	-0.1854	2.0490	0.0427
r（Y，X₄*X₈）	-0.2004	2.2222	0.0282
r（Y，X₄*X₁₀）	-0.3522	4.0872	0.0001
r（Y，X₅*X₆）	-0.3427	3.9622	0.0001
r（Y，X₅*X₇）	0.2808	3.1779	0.0019
r（Y，X₆*X₁₁）	0.2547	2.8606	0.0050
r（Y，X₇*X₁₁）	-0.1851	2.0463	0.0429

样本	观测值	拟合值	拟合误差
1	1	1.3094	-0.3094
2	5	4.3413	0.6587
3	3	2.1499	0.8501
4	1	1.7955	-0.7955
5	4	4.0702	-0.0702
6	3	2.5322	0.4678
7	2	2.3195	-0.3195
8	4	3.6383	0.3617
9	1	2.2940	-1.2940
10	1	1.5881	-0.5881
11	1	2.2016	-1.2016
12	5	3.0091	1.9909
13	4	4.2750	-0.2750
14	3	2.8244	0.1756
15	1	1.2850	-0.285
16	3	3.2680	-0.268
17	4	3.8662	0.1338
18	1	1.0000	0
19	5	4.4367	0.5633
20	1	1.8224	-0.8224
21	5	5.0000	0
22	5	4.1995	0.8005
23	3	3.6493	-0.6493
24	1	1.0000	1.0000
25	2	3.2827	-1.2827
26	1	2.5245	-1.5245
27	5	4.5873	0.4127
28	3	3.5043	-0.5043
29	2	1.9846	0.0154
30	1	1.0000	0.0000
31	2	1.4150	0.585
32	4	3.4235	0.5765
33	3	2.0516	0.9484
34	1	1.0000	1.0000
35	4	4.0225	-0.0225
36	1	2.0697	-1.0697
37	3	2.6211	0.3789
38	1	2.2449	-1.2449
39	3	2.8299	0.1701
40	4	3.1361	0.8639
41	5	3.7609	1.2391
42	3	3.4085	-0.4085
43	5	3.3069	1.6931
44	3	3.6481	-0.6481
45	3	3.0972	-0.0972
46	2	3.3202	-1.3202
47	1	1.0000	0
48	2	2.3267	-0.3267
49	1	1.0000	0
50	3	3.1241	-0.1241
51	1	1.5364	-0.5364
52	2	3.1129	-1.1129
53	1	1.3995	-0.3995
54	3	2.6472	0.3528
55	4	3.9615	0.0385
56	5	3.9626	1.0374
57	4	4.1137	-0.1137
58	1	1.3217	-0.3217
59	5	5.0000	0
60	1	1.9954	-0.9954
61	2	2.2912	-0.2912
62	3	3.5790	-0.579
63	4	3.2437	0.7563
64	3	2.9375	0.0625
65	5	4.2667	0.7333
66	4	4.5576	-0.5576
67	5	4.4843	0.5157
68	2	2.3068	-0.3068
69	3	1.8361	1.1639
70	1	1.4134	-0.4134
71	1	1.3807	-0.3807
72	1	1.2379	-0.2379
73	2	2.3563	-0.3563
74	2	2.8986	-0.8986
75	5	4.0512	0.9488
76	2	1.2737	0.7263
77	3	3.7541	-0.7541
78	4	2.8553	1.1447
79	4	4.7874	-0.7874
80	3	3.2123	-0.2123
81	5	4.6262	0.3738
82	5	3.8452	1.1548
83	5	5.2690	-0.2690
84	2	1.4489	0.5511
85	1	1.1753	-0.1753
86	5	3.6253	1.3747
87	4	3.5735	0.4265
88	1	1.5942	-0.5942
89	1	1.0000	0
90	1	2.2918	-1.2918
91	4	3.3102	0.6898
92	5	4.3525	0.6475
93	1	1.0000	0
94	3	2.6012	0.3988
95	2	1.7479	0.2521
96	3	2.4006	0.5994
97	3	2.8533	0.1467
98	1	2.5910	-1.5910
99	3	2.7021	0.2979
100	1	2.2252	-1.2252
101	1	1.0199	-0.0199
102	4	4.4977	-0.4977
103	3	2.3896	0.6104
104	1	1.0997	-0.0997
105	1	1.2433	-0.2433
106	1	1.0833	-0.0833
107	1	1.2784	-0.2784
108	1	2.2542	-1.2542
109	5	4.0411	0.9589
110	3	2.4991	0.5009
111	4	4.3917	-0.3917
112	3	2.7506	0.2494
113	1	1.5952	-0.5952
114	5	5.0000	0
115	3	2.6814	0.3186
116	1	2.6136	-1.6136
117	2	2.0309	-0.0309
118	4	3.7946	0.2054
119	4	3.1958	0.8042
120	4	1.8218	2.1782
121	1	1.0000	0
122	1	1.9108	-0.9108
123	2	2.9382	-0.9382
124	4	3.4696	0.5304
125	1	1.4539	-0.4539
126	4	4.2663	-0.2663
127	2	1.9344	0.0656
128	3	2.5227	0.4773
129	5	5.0000	0
130	4	3.6591	0.3409

Please choose a citation manager

Content to export