Serum S-100B for mild traumatic brain injury: a systematic review and meta-analysis of diagnostic test accuracy

doi:10.3877/cma.j.issn.2095-9141.2022.04.004

Abstract

Abstract:

Objective

To systematically evaluate the diagnostic value of S-100B for intracranial injury in patients with mild traumatic brain injury (mTBI).

Methods

PubMed, EMbase, The Cochrane Library, CNKI, CBM, VIP and WanFang Data databases were searched by computer for diagnostic tests about S-100B as predictors of intracranial injury after mTBI from inception to May 27, 2022. Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data, and assessed methodological quality of included studies by using the Quality Assessment of Diagnostic Accuracy Studies 2 tool, and the diagnostic value of serum S-100B for mTBI was analyzed by Meta-DiSc software (version 1.4).

Results

A total of 21 literature articels involving 8057 patients were included. Meta-analysis showed that diagnostic odds ratio pooled was 5.55 (95%CI: 3.47-8.87), pooled sensitivity was 0.91 (95%CI: 0.88-0.93), pooled specificity was 0.29 (95%CI: 0.28-0.30), pooled positive likelihood ratio was 1.35 (95%CI: 1.25-1.47), pooled negative likelihood ratio was 0.26 (95%CI: 0.16-0.44), and the area under curve of the comprehensive subject working characteristic curve of S-100B diagnosis for intracranial injury with mTBI was 0.760.

Conclusion

S-100B has good predictive value in the screening of intracranial injury among mTBI patients, and can be used as a screening tool for identification of traumatic intracranial lesions in patients with mild TBI.

Key words: Mild traumatic brain injury, Serological marker, S-100B, Meta analysis, Diagnostic test

Junmiao Ge, Jidong Sun, Xiangyu Gao, Dan Liao, Haofuzi Zhang, Erwan Yang, Zhicheng Tian, Xiaofan Jiang, Peng Luo. Serum S-100B for mild traumatic brain injury: a systematic review and meta-analysis of diagnostic test accuracy[J]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2022, 08(04): 209-217.

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Figures/Tables 7

References 38

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第一作者	年份	患者来源	研究设计	标志物	样本量	年龄（岁）	男（%）	GCS占比	患病率（%）	创伤机制
Seidenfaden等^[9]	2021	丹麦	前瞻性队列	S-100B^a	566	62^b	58.1	14：20.0% 15：80.0%	5.6	交通：25.6% 跌落<2 m：62.8% 跌落>2 m：3.1% 暴行：2.5% 其他：5.9%
Kahouadji等^[10]	2020	瑞士	前瞻性队列	S-100B	130	44.8±20.4	82.0	13~14：17% 15：83%	25.0	车祸：10% 滑雪相关：67% 其他运动相关：3% 意外事故：11% 喝酒：4% 其他：5%
Posti等^[11]	2019	芬兰	前瞻性队列	S-100B^a	93	42.8±18.6	64.5	13~15：100%	39.8	不详
Egea-Guerrero等^[12]	2018	西班牙	前瞻性队列	S-100B	260	不详	63.8	15：100%	8.5	交通：23.1% 暴行：6.9% 侵略：10.4% 高处坠落：48.9% 其他：10.7%
David等^[13]	2017	法国	前瞻性研究	S-100B	308	79.1±10.5	49.0	15：97.4% 13~14：2.6%	10.7	地面跌落：94.2% 其他：5.8%
Welch等^[14]	2016	美国,匈牙利	前瞻性队列	S-100B^a	251	45.6±18.4	60.2	9~12：1.6% 13：2.0% 14：6.8% 15：89.6%	14.3	机动车事故：35.9% 袭击：11.6% 坠落：53.4% 运动：3%
Asadollahi等^[15]	2015	伊朗	前瞻性队列	S-100B	158	35.4±15.8	69.6	不详	50.0	交通：57.0% 坠落：16.4% 袭击：14.6% 其他：12.0%
Thaler等^[16]	2015	澳大利亚	前瞻性队列	S-100B	782	83^b	31.3	13：6.1% 14：18.8% 15：75.1%	6.4	坠落：90.0% 交通：3.5% 其他：3.6% 未知：2.0%
Laribi等^[17]	2014	法国	前瞻性研究	S-100B	400	36^b	65.0	13：2% 14：11% 15：87%	6.3	坠落：61.0% 交通：12.3% 袭击：10% 其他：16.7%
Wolf等^[18]	2013	奥地利	前瞻性队列	S-100B^a	107	59±23	56.1	不详	23.4	不详
Bazarian等^[19]	2013	美国	前瞻性队列	S-100B^a	787	38.2±19.5	63.5	13：1.3% 14：6.5% 15：89.2%	5.7	袭击：5.1% 自行车：4.7% 坠落：27.2% 机动车：7.8%
Egea-Guerrero等^[20]	2012	西班牙	前瞻性队列	S-100B	143	49.2±20.6	62.2	15：100%	10.5	交通：19.6% 暴行：8.4% 袭击：7.0% 坠落：56.0% 其他：9.0%
Zongo等^[21]	2012	法国	前瞻性队列	S-100B	1560	57^b	55.8	13：2.5% 14：21.5% 15：76.0%	7.1	交通：14.2% 坠落：42.9% 袭击：10.3% 其他：32.6%
Cervellin等^[22]	2012	意大利	前瞻性研究	S-100B	60	58^b	68.0	14~15：100%	33.3	不详
Kotlyar等^[23]	2011	美国	前瞻性队列	S-100B	346	48±23	62.0	13~14：10.1% 15：87.6%	6.4	跌落：44.8% 机动车事故：30.3% 袭击：10.7% 其他：14.2%
Müller等^[24]	2010	瑞士	前瞻性队列	S-100B	233	48.4^b	61.4	不详	9.4	不详
Morochovic等^[25]	2009	斯洛伐克共和国	前瞻性队列	S-100B	102	42.0±19.7	69.6	13：2.9% 14：22.5% 15：74.6%	17.6	坠落：48.0% 交通：24.5% 袭击：13.7% 不清楚：10.7% 运动相关或未指明：2.9%
Müller等^[26]	2007	欧洲	前瞻性队列	S-100B	226	39^b	74.3	13：7.1% 14：13.3% 15：79.6%	9.3	坠落：56% 交通：24% 袭击：14% 其他：6%
Biberthaler等^[27]	2006	德国	前瞻性队列	S-100B	1309	47^b	35.0	不详	7.1	交通：18.1% 袭击：17.9% 坠落：59.8% 其他：4.2%
Nygren De Boussard等^[28]	2004	瑞典	前瞻性队列	S-100Bª	122	37.3^b	58.0	14：11% 15：89%	46.7	坠落：59% 交通：19% 袭击：7% 不清楚：15%
Mussack等^[29]	2002	德国	前瞻性队列	S-100Bª	139	36^b	76.3	13：2.2% 14：5.0% 15：92.8%	13.7	不详

第一作者	年份	患者来源	研究设计	标志物	样本量	年龄（岁）	男（%）	GCS占比	患病率（%）	创伤机制
Seidenfaden等^[9]	2021	丹麦	前瞻性队列	S-100B^a	566	62^b	58.1	14：20.0% 15：80.0%	5.6	交通：25.6% 跌落<2 m：62.8% 跌落>2 m：3.1% 暴行：2.5% 其他：5.9%
Kahouadji等^[10]	2020	瑞士	前瞻性队列	S-100B	130	44.8±20.4	82.0	13~14：17% 15：83%	25.0	车祸：10% 滑雪相关：67% 其他运动相关：3% 意外事故：11% 喝酒：4% 其他：5%
Posti等^[11]	2019	芬兰	前瞻性队列	S-100B^a	93	42.8±18.6	64.5	13~15：100%	39.8	不详
Egea-Guerrero等^[12]	2018	西班牙	前瞻性队列	S-100B	260	不详	63.8	15：100%	8.5	交通：23.1% 暴行：6.9% 侵略：10.4% 高处坠落：48.9% 其他：10.7%
David等^[13]	2017	法国	前瞻性研究	S-100B	308	79.1±10.5	49.0	15：97.4% 13~14：2.6%	10.7	地面跌落：94.2% 其他：5.8%
Welch等^[14]	2016	美国,匈牙利	前瞻性队列	S-100B^a	251	45.6±18.4	60.2	9~12：1.6% 13：2.0% 14：6.8% 15：89.6%	14.3	机动车事故：35.9% 袭击：11.6% 坠落：53.4% 运动：3%
Asadollahi等^[15]	2015	伊朗	前瞻性队列	S-100B	158	35.4±15.8	69.6	不详	50.0	交通：57.0% 坠落：16.4% 袭击：14.6% 其他：12.0%
Thaler等^[16]	2015	澳大利亚	前瞻性队列	S-100B	782	83^b	31.3	13：6.1% 14：18.8% 15：75.1%	6.4	坠落：90.0% 交通：3.5% 其他：3.6% 未知：2.0%
Laribi等^[17]	2014	法国	前瞻性研究	S-100B	400	36^b	65.0	13：2% 14：11% 15：87%	6.3	坠落：61.0% 交通：12.3% 袭击：10% 其他：16.7%
Wolf等^[18]	2013	奥地利	前瞻性队列	S-100B^a	107	59±23	56.1	不详	23.4	不详
Bazarian等^[19]	2013	美国	前瞻性队列	S-100B^a	787	38.2±19.5	63.5	13：1.3% 14：6.5% 15：89.2%	5.7	袭击：5.1% 自行车：4.7% 坠落：27.2% 机动车：7.8%
Egea-Guerrero等^[20]	2012	西班牙	前瞻性队列	S-100B	143	49.2±20.6	62.2	15：100%	10.5	交通：19.6% 暴行：8.4% 袭击：7.0% 坠落：56.0% 其他：9.0%
Zongo等^[21]	2012	法国	前瞻性队列	S-100B	1560	57^b	55.8	13：2.5% 14：21.5% 15：76.0%	7.1	交通：14.2% 坠落：42.9% 袭击：10.3% 其他：32.6%
Cervellin等^[22]	2012	意大利	前瞻性研究	S-100B	60	58^b	68.0	14~15：100%	33.3	不详
Kotlyar等^[23]	2011	美国	前瞻性队列	S-100B	346	48±23	62.0	13~14：10.1% 15：87.6%	6.4	跌落：44.8% 机动车事故：30.3% 袭击：10.7% 其他：14.2%
Müller等^[24]	2010	瑞士	前瞻性队列	S-100B	233	48.4^b	61.4	不详	9.4	不详
Morochovic等^[25]	2009	斯洛伐克共和国	前瞻性队列	S-100B	102	42.0±19.7	69.6	13：2.9% 14：22.5% 15：74.6%	17.6	坠落：48.0% 交通：24.5% 袭击：13.7% 不清楚：10.7% 运动相关或未指明：2.9%
Müller等^[26]	2007	欧洲	前瞻性队列	S-100B	226	39^b	74.3	13：7.1% 14：13.3% 15：79.6%	9.3	坠落：56% 交通：24% 袭击：14% 其他：6%
Biberthaler等^[27]	2006	德国	前瞻性队列	S-100B	1309	47^b	35.0	不详	7.1	交通：18.1% 袭击：17.9% 坠落：59.8% 其他：4.2%
Nygren De Boussard等^[28]	2004	瑞典	前瞻性队列	S-100Bª	122	37.3^b	58.0	14：11% 15：89%	46.7	坠落：59% 交通：19% 袭击：7% 不清楚：15%
Mussack等^[29]	2002	德国	前瞻性队列	S-100Bª	139	36^b	76.3	13：2.2% 14：5.0% 15：92.8%	13.7	不详

第一作者	年份	检测方法	检测范围（µg/L）	阈值（µg/L）	提前确定阈值	采血方式	样品类型	采血时间	TP	FP	FN	TN
Seidenfaden等^[9]	2021	ECLIA	不详	0.100	是	静脉	血清	108 min^b	32	366	0	168
Kahouadji等^[10]	2020	ECLIA	0.005~39.000	0.100	是	静脉	血清	<3 h	32	86	1	11
Posti等^[11]	2019	ELISA	LLOD:2.7×10^-6	0.168	否	静脉	血浆	<24 h	34	49	3	7
Egea-Guerrero等^[12]	2018	ECLIA	>0.005	0.100	是	静脉	血清	<6 h	21	165	1	73
David等^[13]	2017	ECLIA	0.005~39.000	0.105	是	静脉	血清	<6 h	28	192	5	83
Welch等^[14]	2016	ECLIA	0.000~0.090	0.100	是	静脉	血清	<6 h	29	111	3	88
Asadollahi等^[15]	2015	ECLIA	0.020~30.000	0.115^a	否	静脉	血清	3 h	75	51	4	28
Thaler等^[16]	2015	ECLIA	5~39 000	0.105	是	静脉	血清	125 min^b	49	474	1	258
Laribi等^[17]	2014	ECLIA	0.005~39.000	0.100	是	静脉	血清	<3 h	26	231	0	143
Wolf等^[18]	2013	ECLIA	不详	0.105^a	否	静脉	血清	<3 h	18	52	7	30
Bazarian等^[19]	2013	ECLIA	0.005~39.000	0.100^a	是	静脉	血清	<6 h	39	473	6	264
Egea-Guerre等^[20]	2012	ECLIA	0.005~39.000	0.105^a	是	静脉	血清	<6 h	15	94	0	34
Zongo等^[21]	2012	ECLIA	不详	0.100^a	否	静脉	血浆	<6 h	110	1272	1	177
Cervellin等^[22]	2012	ILMA	0.020~30.000	0.380	否	静脉	血清	<3 h	20	17	0	23
Kotlyar等^[23]	2011	ILMA	0.100~35.000	24.000^a	否	静脉	血清	不详	21	282	1	42
Müller等^[24]	2010	ECLIA	不详	0.105	是	静脉	血清	77 min^b	19	144	3	67
Morochovic等^[25]	2009	ECLIA	LLOD：0.005	0.100	是	静脉	血清	<6 h	15	59	3	25
Müller等^[26]	2007	ILMA	LLOD：0.013	0.100	否	静脉	血清	<12 h	20	141	1	64
Biberthaler等^[27]	2006	ECLIA	0.005~39.000	0.100	否	静脉	血清	不详	92	855	1	361
Nygren De Boussard等^[28] 2004		ILMA	LLOD：0.020	0.150	否	静脉	血清	不详	22	2	35	63
Mussack等^[29]	2002	ILMA	LLOD：0020	0.210	否	静脉	血清	不详	19	60	0	60

第一作者	年份	检测方法	检测范围（µg/L）	阈值（µg/L）	提前确定阈值	采血方式	样品类型	采血时间	TP	FP	FN	TN
Seidenfaden等^[9]	2021	ECLIA	不详	0.100	是	静脉	血清	108 min^b	32	366	0	168
Kahouadji等^[10]	2020	ECLIA	0.005~39.000	0.100	是	静脉	血清	<3 h	32	86	1	11
Posti等^[11]	2019	ELISA	LLOD:2.7×10^-6	0.168	否	静脉	血浆	<24 h	34	49	3	7
Egea-Guerrero等^[12]	2018	ECLIA	>0.005	0.100	是	静脉	血清	<6 h	21	165	1	73
David等^[13]	2017	ECLIA	0.005~39.000	0.105	是	静脉	血清	<6 h	28	192	5	83
Welch等^[14]	2016	ECLIA	0.000~0.090	0.100	是	静脉	血清	<6 h	29	111	3	88
Asadollahi等^[15]	2015	ECLIA	0.020~30.000	0.115^a	否	静脉	血清	3 h	75	51	4	28
Thaler等^[16]	2015	ECLIA	5~39 000	0.105	是	静脉	血清	125 min^b	49	474	1	258
Laribi等^[17]	2014	ECLIA	0.005~39.000	0.100	是	静脉	血清	<3 h	26	231	0	143
Wolf等^[18]	2013	ECLIA	不详	0.105^a	否	静脉	血清	<3 h	18	52	7	30
Bazarian等^[19]	2013	ECLIA	0.005~39.000	0.100^a	是	静脉	血清	<6 h	39	473	6	264
Egea-Guerre等^[20]	2012	ECLIA	0.005~39.000	0.105^a	是	静脉	血清	<6 h	15	94	0	34
Zongo等^[21]	2012	ECLIA	不详	0.100^a	否	静脉	血浆	<6 h	110	1272	1	177
Cervellin等^[22]	2012	ILMA	0.020~30.000	0.380	否	静脉	血清	<3 h	20	17	0	23
Kotlyar等^[23]	2011	ILMA	0.100~35.000	24.000^a	否	静脉	血清	不详	21	282	1	42
Müller等^[24]	2010	ECLIA	不详	0.105	是	静脉	血清	77 min^b	19	144	3	67
Morochovic等^[25]	2009	ECLIA	LLOD：0.005	0.100	是	静脉	血清	<6 h	15	59	3	25
Müller等^[26]	2007	ILMA	LLOD：0.013	0.100	否	静脉	血清	<12 h	20	141	1	64
Biberthaler等^[27]	2006	ECLIA	0.005~39.000	0.100	否	静脉	血清	不详	92	855	1	361
Nygren De Boussard等^[28] 2004		ILMA	LLOD：0.020	0.150	否	静脉	血清	不详	22	2	35	63
Mussack等^[29]	2002	ILMA	LLOD：0020	0.210	否	静脉	血清	不详	19	60	0	60

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