Supplemental Figure 1. Fagan plot for HBP in the diagnosis of sepsis without organ dysfunction (3A) and sepsis with organ dysfunction(3B)

(1)

Appendix

Supplemental Figure 1. Fagan plot for HBP in the diagnosis of sepsis without organ dysfunction (3A) and sepsis with organ dysfunction(3B)

3A. 3B.

(2)

Supplemental Figure 2. Literature search and study selection flow diagram

(3)

Supplemental Figure 3. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) Assessment for Risk of Bias and Applicability of the Included Studies

Study Risk of bias Applicability concern

Patient selection

Index Reference standards

Flow and timing

Patient selection

Index test

Reference standard

Linder Ａ (2009)

☺ ☺ ☺ ☺ ☺ ☺ ☺

Huang A (2013)

? ☺ ☺ ☺ ☺ ☺ ☺

Llewelyn M (2013)

☺ ☺ ☺ ☺ ☺ ☺ ☺

Huang A (2014)

? ☺ ☺ ☺ ☺ ☺ ☺

Liu Y (2014)

 ☺ ☺ ☺ ☺ ☺ ☺

Chen Q (2015)

?  ? ? ☺ ☺ ☺

Linder A (2015)

☺ ☺ ☺ ☺ ☺ ☺ ☺

Xu C (2015)

? ☺ ☺ ? ☺ ☺ ☺

Chen Y (2016)

? ☺ ☺ ? ☺ ☺ ☺

Xue L (2016)

☺ ☺ ☺ ☺ ☺ ☺ ☺

Zanfaly E (2016)

☺ ☺ ☺ ☺ ☺ ☺ ☺

Feng M (2017)

 ☺ ☺ ☺ ☺ ☺ ☺

Ibrahim G (2017)

 ☺ ? ☺ ☺ ☺ ☺

Qian D (2017) ? ? ☺ ☺ ? ? ☺

Yi X(2017)  ☺ ☺ ☺ ☺ ☺ ☺

Zhang H (2017)

 ☺ ☺ ☺ ☺ ☺ ☺

Liu L (2018)

  ☺ ☺ ☺ ☺ ?

(4)

Qin (2018)

 ☺ ☺ ☺ ☺ ☺ ☺

Deng (2018)

 ☺ ☺ ☺ ☺ ☺ ?

Wei R (2018)

 ? ☺ ☺ ☺ ☺ ☺

Zhang G (2018)

 ☺ ☺ ☺ ☺ ☺ ?

Zhang Y (2018)

 ☺ ☺ ☺ ☺ ☺ ☺

Khan F (2019)

☺ ? ☺ ☺ ☺ ? ☺

Yang Y (2019)  ☺ ☺ ☺ ☺ ☺ ☺

Zhang Y (2019)

 ☺ ☺ ☺ ☺ ☺ ☺

Zhou Y (201)  ☺ ☺ ☺ ☺ ☺ ☺

☺ low  high ? unclear

0% 20% 40% 60% 80% 100%

PATIENT SELECTION INDEX TEST REFERENCE STANDARDS FLOW AND TIMING

QUADUS 2 Domain

Proportion of Studies with low, unclear or high CONCERNS regarding APPLICABILITY Proportion of Studies with low, unclear or high

RISK of bias

(5)

Supplemental Figure 4. Trim and fill analysis for PCT sepsis diagnosis

(6)

Supplemental Digital Content 1. Representative search string for PubMed, EMBASE, CNKI and WANGFAN

PubMed EMBASE CNKI WANGFAN

Blood biomarkers

"heparin binding protein"[tw]

OR "azurocidin"[tw] OR

"cationic antimicrobial protein CAP 37,

human"[Supplementary Concept])

‘heparin binding protein'/exp OR 'heparin binding protein' OR 'azurocidin'/exp OR azurocidin OR 'cationic antimicrobial protein cap 37 human'/exp OR 'cationic

antimicrobial protein cap 37 human'

Heparin binding protein

Population of interest

"sepsis"[MeSH] OR "shock, septic"[MeSH] OR "systemic inflammatory response syndrome"[MeSH] OR

"sepsis"[tw] OR "septic shock"[tw] OR "systemic inflammatory response syndrome"[tw] OR

"infection"[MeSH Terms]

'sepsis'/exp OR 'sepsis' OR 'septic shock'/exp OR 'septic shock' OR 'systemic inflammatory response syndrome'/exp OR 'systemic inflammatory response syndrome'

Sepsis Sepsis

(7)

Supplemental Digital Content 2. Details of the included studies

Author (Year)

Study year/

design

Country Sample size

Definitintio of sepsis Outcome

n_outcome Biomarkers tested

Kit Cut-off value HBP (ng/mL) CRP (µg/L) PCT (ng/mL) Lactate (mmol/L) WBC (cells/L)

Prevalence (%)

Linder A (2009)

[37] 2006-2007

/PC

Sweden 233 SIRS/

Severe sepsis

70 Lactate,

CRP, PCT, WBC, HBP

N/A Lactate: 2.5;WBC: 14;

CRP: 100; HBP: 15; PCT:

2

30

Huang A (2013)

[45] 2010-2012/

CC

China 84 SIRS/

Septic shock

30 Lactate,

CRP, WBC, HBP

Boyao

Biotechnology, Shanghai, China

Lactate: 6.3;WBC: 31.35;

CRP: 110.5; HBP: 6.79

36

Llewelyn M (2013) [25]

2010-2011/

PC

United Kingdom

162 SIRS/

sepsis

87 PCT, HBP,

SCD25, PSP, IL6, IL8, IL1B

N/A PCT: 1; HBP: 50 54

Huang A(2014)

[40] 2010-2012/

CC

China 104 SIRS/

Septic shock

23 CRP, WBC,

HBP

Boyao

Biotechnology, Shanghai, China

CRP: 46.5; WBC: 21.4;

HBP: 2.65

22

Liu Y(2014)

[43] 2011-2012/

CC

China 147 SIRS/

Septic shock

39 HBP,

APACHE II, lactate

LifeSpan Biosciences, Seattle, USA

HBP: 18.5; APACHE II:

28; lactate: 2

27

Chen Q (2015)

[42] 2014-2015/

CC

China 81 N/A

sepsis

43 HBP、IL6

、IL10、

IL17A、

IL17F

Bio-Rad, California, USA

HBP 72hr 8.5, 48hr: 10.32, 24hr: 10.38, 0 hr: 15.32

53

(8)

Linder A(2015)

[18] 2011-2012/

PC

Sweden, US

487 SIRS/

Severe sepsis

141 Lactate,

CRP, PCT, WBC, HBP

Axis-Shield Diagnostics, Scotland, UK, Scotland, USA

HBP: 30; PCT: 0.5; CRP:

130; Lactate: 2; WBC: 12 29

Xu C (2015)

[27] 2014/03-

2014/08/

CC

China 196 SIRS/

sepsis

55 PCT, HBP,

CRP

JoinStar, Hangzhou, China

PCT: 1; HBP: 11.5 ; CRP:

15

28

Chen Y(2016) [29]

2014-2015/

PC

China 117 SIRS/

sepsis

22 PCT, HBP JoinStar,

Hangzhou, China

N/A 19

Xue L(2016)

[32] 2015/

PC

China 105 SIRS/

Sepsis

58 HBP, PCT JoinStar,

Hangzhou, China

N/A 55

Zanfaly E (2016) [39]

2014- 2015/PC

Egypt 90 SIRS 49 WBC,

lactate, CRP, PCT, HBP

MyBioSourse, California, USA

WBC: 13.05, lactate: 2.52, CRP:157.5, PCT:1.21, HBP:31.6

54

Feng M (China, 2017)

[33]

2016-2017/

CC

China 207 SIRS/

Sepsis、

Septic shock

Sepsis: 63;

Septic shock: 40

HBP, PCT ZSBio,

Beijing, China

HBP: 9.30 for sepsis;

HBP: 17.08 for septic shock

Sepsis: 30;

Septic shock:

19 Ibrahim G

(2017) [47]

2013-2014/

CC

Egypt 48 SIRS/

Severe sepsis、

mortality

38 HBP N/A Severe sepsis: HBP 0hr

19; 48hr 1.8; 96hr 1.6 Mortality: HBP 0hr 19;

48hr 1.8; 96hr 1.6

79

Qian D (2017)

[34] 2014-

2016/CC

China 96 Sepsis 3/ sepsis 59 HBP N/A HBP: 18.58 61

Yi X(2017) [38]

June-July 2016/

CC

China 90 Sepsis 3/sepsis 33 PCT, CRP,

WBC, HBP

Axis-Shield Diagnostics, Scotland, UK

PCT: 0.5;WBC: 9.5

; CRP: 10; HBP: 14.54

37

(9)

Zhang H (2017)

[48] 2015-2016/

CC

China 118 SIRS/ septic shock

38 HBP, SOFA

score, lactate

Tonyao Biological Technology, Shanghai, China

HBP: 19.13; SOFA score:

19.5; lactate: 2.4

32

Liu L(2018)

[46] 2014-2016/

PC

China 203 SIRS/sepsis + pneumonia

103 CRP, WBC,

HBP, PCT

CRP 72hr 52.4, 48hr 52.6, 24hr 52.6, 0hr 90.5; PCT 72hr 0.14, 48hr: 0.17, 24hr: 0.18, 0 hr: 0.51;

WBC 72hr 8.25, 48hr: 8.8, 24hr: 9.15, 0 hr: 9.85;

HBP 72hr 8.86, 48hr: 8.89, 24hr: 9.78, 0 hr: 14.1

51

Qin B (2018) [28]

2016-2017/

CC

China 142 SIRS/sepsis 70 PCT, HBP Axis-Shield

Diagnostics, Scotland, UK

PCT: 22.46; HBP: 19.66 49

Deng Y (2018)

[30] 2016-2017/

CC

China 161 SIRS/sepsis 39 CRP, PCT,

HBP

CRP: 2.3; PCT: 0.16;

HBP: 27.99

24

Wei R (2018)

[41] 2016-2017/

CC

China 106 Sepsis 3/Sepsis 53 PCT, WBC,

HBP

PCT: 0.69; WBC: 10.94;

HBP: 39.27

50

Zhang G (2018)

[44] 2015-2017/

CC

China 87 SIRS/sepsis 44 HBP, CRP,

WBC

Guang Rui Biological Technology, Shanghai, China

CRP 24hr 16.79, 48hr 15.19, 72hr 7.89; WBC 24hr 0.92, 48hr: 0.67, 72hr: 0.29; HBP 24hr 13.06, 48hr: 8.89, 72hr:

10.32

51

Zhang Y (2018) 2017-2018/ China 96 SIRS/sepsis 36 PCT, lactate, Tonyao PCT: 2; lactate: 14.5 38

(10)

[26] CC HBP Biological Technology, Shanghai, China

; HBP: 10.8

Khan F (2019) [57]

2015 2016 /PC

Sweden, Switzerland and Canada

332 Sepsis 2/Severe sepsis

96 HBP, PCT,

lactate, CRP, WBC

HBP: 15, PCT:0.5, lactate:2 , CRP: 20.1, WBC:10.8

29

Yang Y (2019)

[36] 2016-2017/

PC

China 108 Sepsis 3/Septic shock

14 HBP, SOFA

score

N/A HBP: 89.43; SOFA score:

7.5

13 Zhang Y (2019)

[35] 2018/

CC

China 87 SIRS/Septic

shock, sepsis

26 CRP, WBC,

HBP, PCT

Sepsis

CRP: 3.575, WBC: 9.945, HBP: 7.295, PCT: 0.325

30

Zhou Y(2019)

[31] 2017/

PC

China 181 Sepsis3/sepsis、

septic shock

Sepsis: 93 Septic shock: 37

CRP, PCT, HBP, SOFA score

Sepsis: HBP 28.1; PCT 2.05 ; CRP 151.9

Septic shock: HBP 103.5;

PCT 22.15; SOFA score 5.5

Sepsis: 51 Septic shock:

20

(11)

Supplemental Digital Content 3. Summary characteristics of the included 26 studies

Description Frequency, n (%)

Continent

China 20 (77)

North America/Europe 4 (15)

Egypt 2 (8)

Year of publication

Before 2010 1(4)

2010-2015 7 (27)

2016-2019 18 (69)

Study design

Case control 18 (69)

Cohort 8 (31)

Median sample size (interquartile range, IQR), n (96), 112.5 Population

SIRS: sepsis

SIRS: severe sepsis + septic shock/

Sepsis 3: sepsis + septic shock

12 (46) 15 (58) 4 (15) Serial measurements of heparin-binding protein (HBP) 5 (19) Blood biomarkers tested

heparin-binding protein (HBP) 26 (100)

C-reactive protein (CRP) 14 (54)

Procalcitonin (PCT) 16 (62)

Lactate 8 (31)

Range of prevalence of sepsis (%) 38

Kit

Axis-Shield Diagnostics, Scotland, UK 5 (19) Boyao Biotechnology, Shanghai, China 4 (15)

JoinStar, Hangzhou, China 7 (27)

Other (ZSBio Beijing China, BioRad California USA, MyBioSourse California USA, Tonyao Biological Technology Shanghai China, Guang Rui Biological Technology Shanghai China, LifeSpan Biosciences Seattle USA, )

5 (19)

N/A 5 (19)

Cut-off value (IQR)

HBP (ng/mL) 16.04 (17.95)

CRP (µg/mL) 49.45 (101.63)

PCT (ng/mL) Lactate (mmol/L)

1(1.5) 2.4(0.51) Definition of Sepsis

SIRS 20

Sepsis 3 5 (19)

Sepsis 2 1 (4)

Place of conduction of study

Emergency department 4 (15)

Intensive care unit 10 (38)

Ward 4 (15)

Mixed 7 (27)

(12)

Supplemental Digital Content 4. Pooled accuracy estimates of biomarkers stratified by definition of sepsis

Variable Studies

(patients), n (n)

Sensitivity

(95% CI) Specificity

(95% Cr) AUROC

(95% CI) Positive likelihood

ratio (95% CI)

Negative likelihood ratio

(95% CI)

I² (%) (95% CI)

Publication bias

Sepsis

HBP

[34-38, 43-46, 48, 52, 55- 58]

15 (2428) 0.85

(0.79 - 0.90)

0.91 (0.82 - 0.96)

0.93 (0.90- 0.95)

9.4 (4.3 - 20.4)

0.16 (0.11 - 0.24)

0.12 (0.00 - 0.24)

0.11

PCT

[34-35, 38, 43, 52, 55, 58] 7 (1516) 0.75

(0.62 - 0.85) 0.85

(0.73 - 0.92) 0.87

(0.83- 0.89) 4.8

(2.5 - 9.6) 0.29

(0.18 - 0.49) 0.13,

(0.00 - 0.30) 0.01 CRP

[34-36, 38, 43, 55, 57-58] 8 (1598) 0.75

(0.65 - 0.84) 0.71

(0.63 - 0.77) 0.78

(0.75 - 0.82) 2.6

(1.9 - 3.5) 0.35

(0.22 - 0.54) 0.12,

(0.00 - 0.25) 0.76 Lactate

[34-35, 37-38, 43, 48, 55] 7 (1491) 0.49

(0.35 - 0.64) 0.83

(0.70 - 0.91) 0.71

(0.67 - 0.75) 3.0

(1.8 - 4.9) 0.61

(0.48 - 0.77) 0.14,

(0.00 - 0.28) 0.15 Sepsis-3

HBP

[52, 56-58] 4 (482) 0.81

(0.70 - 0.89) 0.98

(0.52 - 1.00) 0.88

(0.85- 0.91) 36.9

(1.0 - 1338.1) 0.19

(0.12 - 0.31) 0.06,

(0.00 - 0.20) 0.86 Sepsis mortality

prediction

HBP 128 (597) 0.84

(0.73 - 0.90) 0.40

(0.36 - 0.45) 0.46

(0.42- 0.51) 1.4

(1.2 - 1.6) 0.41

(0.25 - 0.68) 0,06

(0.00 - 1.00) 0.79

*p-value < 0.05

(13)

Supplemental Digital Content 5. Summary Estimates of Overall and Subgroup Analyses for Biomarkers for the diagnosis of sepsis

Variable Studies (patients),

n (n)

Sensitivity

(95% CI) Specificity

(95% CI) AUROC

(95% CI) Positive likelihood ratio

(95% CI)

Negative likelihood ratio (95% CI)

I²(%)

(95% CI) Publication bias

Overall 15

(2428) 0.85

(0.79 - 0.90) 0.91

(0.82 - 0.96) 0.93

(0.90 - 0.95) 9.4

(4.3 - 20.4) 0.16

(0.11 - 0.24) 0.12

(0.00 - 0.24) 0.11 Study design

Cohort studies 6 (1431) 0.80 (0.72 - 0.86)

0.85 (0.77 - 0.91)

0.89 (0.86 - 0.92)

5.4 (3.4 - 8.5)

0.23 (0.16 - 0.34)

0.06 (0.00 - 0.14)

0.55

Study settings Intensive care

unit 8 (894) 0.85

(0.78 - 0.89) 0.85

(0.68 - 0.94) 0.89

(0.86 - 0.92) 5.8

(2.3 - 14.3) 0.18

(0.12 - 0.28) 0.05

(0.00 - 0.13) 0.77 Emergency

department 5 (1240) 0.83

(0.70 - 0.91) 0.92

(0.81 - 0.96) 0.93

(0.91 - 0.95) 9.9

(3.9 - 24.9) 0.19

(0.10 - 0.36) 0.13

(0.00 - 0.34) 0.14 Age group

*Pediatric

population 6 (737) 0.86

(0.76 - 0.93) 0.86

(0.74 - 0.93) 0.93

(0.90 - 0.95) 6.2

(2.9 - 13.3) 0.16

(0.08 - 0.31) 0.12

(0.00 - 0.31) 0.13 Assay kit

Axis-Shield 5 (1232) 0.79 (0.68 - 0.87)

0.88 (0.78 - 0.94)

0.87 (0.84 - 0.90)

6.5 (3.3 -12.5)

0.24 (0.15 - 0.38)

0.09 (0.00 - 0.23)

0.30

Joinstar 7 (975) 0.82

(0.74 - 0.88) 0.90

(0.63 - 0.98) 0.90

(0.87 - 0.93) 7.8

(1.9 - 32.7) 0.20

(0.14 - 0.30) 0.06

(0.00 -0.17) 0.11 China vs. non-China studies

Non-China 20 (2642) 0.85

(0.81 - 0.88)

0.85 (0.76 - 0.91)

0.89 (0.86 - 0.92)

5.7 (3.3 - 9.8)

0.18 ( 0.14, 0.24)

0.05 (0.00 - 0.11)

0.18

(14)

China 6 (1190) 0.82

( 0.72, 0.89) 0.86

( 0.66, 0.96) 0.89

(0.86, 0.91) 6.0

(2.0, 18.0) 0.21

( 0.12, 0.36) 0.10

(0.00, 0.24) 0.43 Timing of measurement

0 hour 4

(477)

0.94 (0.90, 0.97) 0.87 (0.72,0.94)

0.96 (0.94 - 0.97)

7.3 ( 3.2, 16.6)

0.07 (0.03, 0.12)

0.00 (0.00-0.06)

0.15

24 hour 4

(477) 0.92 (0.86, 0.96) 0.82

(0.67,0.91) 0.95

(0.92 - 0.96) 5.1

( 2.6, 10.1) 0.10

( 0.05, 0.18) 0.04

(0.00- 0.22) 0.77

48 hour 5

(525) 0.88 (0.77, 0.94) 0.87

(0.63,0.97) 0.93

(0.91 - 0.95) 6.9

(1.9, 24.9) 0.14

( 0.06, 0.30) 0.14

(0.00- 0.37) 0.41

72 hour 4

(477) 0.82 (0.75, 0.87) 0.81

(0.29,0.98) 0.84

(0.80 - 0.87) 4.3

(0.6, 30.7) 0.23

( 0.11, 0.45) 0.02

(0.00- 0.08) 0.69

*The pediatrics population is based on SIRS definition.

(15)

Supplemental Digital Content 6. Translation of reference 65

Abstract:

Aim: To provide a systematic evaluation of heparin-binding protein (HBP) as a diagnostic biomarker for adult sepsis.

Method:

From July 2019, a database was compiled based on relevancy to the diagnostic value of HBP in adult sepsis. The sources of the database include PubMed of the National Library of Medicine, Embase of the Netherlands Medical Abstracts, Cochrane clinical trial database, China Academic Journals, China Science Periodical Database, and China Science and Technology Journal Database. Two independents investigators reviewed the articles and evaluated the quality using QUADAS-2. Meta-analysis was then performed on database using Meta-Disc 1.4 and STATA 12.0, calculated the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio. In addition the diagnostic odds ratio was used to draw a fitted receiver operating characteristic curve (SROC) and calculate the area under the curve (AUC); Deek’s test was used to detect publication bias.

Results:

With a total of 1884 patients, 10 studies were selected for this meta-analysis. All included studies used enzyme-linked immunosorbent assay (ELISA) to detect plasma HBP levels. Meta-analysis results showed that there were heterogeneity and random effect models between the studies. The analysis shows that the combined sensitivity, combined specificity, combined PLR, combined NLR and combined DOR are 0.80 [95% confidence interval (95%CI) 0.77~0.83], 0.80 (95%CI 0.78~0.82), 3.96 (95%CI is 2.45~6.41), 0.28 (95%CI is 0.20~0.39), 14.63 (95%CI is 6.83~31.30); combined AUC is 0.86, Cochran-Q=0.79. To find the source of the heterogeneity, subgroup was formed based on disease severity, diagnostic criteria of sepsis and the region of origin.

No subgroups were found to affect the diagnostic accuracy of HBP, indicating that the heterogeneity is still unexplained. No outliers were found through eliminating studies sequentially based on sensitivity, meaning the results were relatively stable and reliable. The Deek’s test showed that there was no publication bias in the included literature.

Conclusion:

HBP has a good diagnostic value for adult sepsis, but further verification may be required through greater sample size.

摘要：

目的系统评价肝素结合蛋白(HBP)在成人脓毒症诊断中的价值.

方法检索美国国立医学图书馆

PubMed

数据库、荷兰医学文摘

Embase

数据库、Cochrane临床试验数据库、万方数据库、中国知网、维普数据库收录的自建库至

2019

年

7

月发表的有关

HBP

诊断成人脓毒症的中、英文文献.由

2

位研究者独立提取相关资料;采用诊断准确性研究的质量评价工具

QUADAS-2

对文献进行质量评价;用

Meta-Disc 1.4

和

STATA 12.0

软件进行

Deek

检验法检测发表偏倚.结果最终纳入

10

项研究共

1 884

例患者,文献质量

(16)

相对适中.所有研究均采用酶联免疫吸附试验(ELISA)检测血浆中

HBP

水平.

PLR、合并 NLR

和合并

DOR

分别为

0.80

〔95%可信区间

(95%CI)为 0.77~0.83〕、0.80(95%CI

为

0.78~0.82)、3.96(95%CI

为

2.45~6.41)、

0.28(95%CI

为

0.20~0.39)、14.63(95%CI

为

6.83~31.30);合并 AUC

为

0.86,Cochran-Q=0.79.为了探索异质性的潜在来源,对疾病严重程度、脓毒症诊断

标准和地区进行亚组分析,结果显示无方法学上的共变量影响

HBP

的诊断准确性,表明仍存在不能解释的异质性.此外,通过逐个剔除各项研究进行敏感度分析, 未发现异常值研究,结果相对稳定可靠.Deek检验显示纳入文献不存在发表偏倚.

结论 HBP对成人脓毒症具有较好的诊断价值,但仍需进一步扩大样本量进行验证.

(17)

Supplemental Digital Content 7. Summary Estimates of Overall and Subgroup Analyses for Biomarkers for the diagnosis of SIRS + infection

Variable Studies

(patients), n (n)

Sensitivity (95% CI)

Specificity (95% Cr)

AUROC (95% CI)

Positive likelihood ratio (95% CI)

Negative likelihood ratio (95% CI)

I² (%) (95% CI)

Publication bias

SIRS

HBP

[25-26, 49-42, 44, 47, 49, 50-51, 53-54]

12 (1647) 0.82

(0.78 - 0.85)

0.74 (0.61 - 0.84)

0.84 (0.81 - 0.87)

3.1 (1.9 - 5.1)

0.25 (0.18 - 0.33)

0.01, (0.00 - 0.04)

0.45

PCT

[25, 39, 41-42, 47, 49- 51, 54]

9 (1272) 0.79

(0.69 - 0.87)

0.74 (0.64 - 0.81)

0.83 (0.79 - 0.86)

3.0 (2.1 - 4.3)

0.28 (0.17 - 0.46)

0.15, (0.00 - 0.31)

0.48

CRP

[39, 47, 49, 50-51, 53]

6 (879) 0.74

(0.61 - 0.84)

0.70 (0.51 - 0.84)

0.79 (0.75 - 0.82)

2.5 (1.5 - 4.1)

0.37 (0.25 - 0.54)

0.12, (0.00 - 0.28)

0.23

(18)

Supplemental Digital Content 8. Additive effects of HBP in combination with other markers

Studies Uni-marker AUROC Combined markers AUROC

Yang Y (2019) HBP 0.814 HBP+SOFA score 0.829

Zhang Y (2018) HBP 0.758 HBP+PCT+Lactate 0.932

Qin B (2018) HBP 0.980 HBP+PCT 0.993

Yi X (2017) HBP 0.815 HBP+PCT 0.992

Yi X (2017) HBP 0.815 HBP+CRP 0.556

Yi X (2017) HBP 0.815 HBP+WBC 0.868

Chen Y (2016) HBP 0.869 HBP+PCT 0.955

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Supplemental Digital Content 9. Comparison between HBP, PCT and CRP

HBP PCT CRP

Monitor of sepsis patients

Lack of evidence. A decrease of PCT levels more than 80% within 72 hours of ICU admission would predict a 90% survival in the ICU sepsis patients. [1, 2]

A CRP level >100mg/L is associated with a standardized mortality ratio (SMR) of 0.85 for sepsis patients in ICU. [1]

Diagnosis of sepsis

Cut off value: 15ng/mL Sensitivity: 87.1%

Specificity: 95.1%

Khan F (2019)

Cut off value: 22.85ng/mL Sensitivity: 78%

Specificity: 86%

Cutoff value: 0.25 μg/L for patients outside of ICU and 0.5 μg/L for patients with severe illness in ICU. [3]

Sensitivity: 80%

Specificity: 61%

CRP is a non-specific acute responsive phase protein for inflammation. CRP can be used to identify early sepsis and non sepsis, but the level of CRP has no statistical significance in the seriousness of sepsis. [2]

Antibiotics stewardship for sepsis patients

Lack of evidence.

The drop of PCT below 0.25 μg/L or by at least >80%–

90% from the peak was used as stopping rule thresholds.

[3]

Lack of evidence.

reference 1. Linder A, Christensson B, Herwald H, et al.: Heparin-binding

1. Schuetz P, Maurer P, Punjabi V, et al.: Procalcitonin decrease over 72 hours in US critical care units predicts

1.Koozi H, Maria L, Attila Fi.: C-reactive protein as a prognostic factor in intensive care admissions

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protein: an early marker of circulatory failure in sepsis. Clin Infect Dis 2009; 49:1044–1050

2. Kahn F, Tverring J, Mellhammar L, et al.: Heparin-Binding Protein as a Prognostic Biomarker of Sepsis and Disease Severity at the Emergency Department. Shock 2019; 52:e135–e145

fatal outcome in sepsis patients. Crit Care 2013;17(3):R115. Published 2013 Jun 20.

doi:10.1186/cc12787

2. Schuetz P, Birkhahn R, Sherwin R et al.: Serial Procalcitonin Predicts Mortality in Severe Sepsis Patients: Results From the Multicenter Procalcitonin MOnitoring SEpsis (MOSES) Study, Crit Care Med May 2017 - Volume 45 - Issue 5 - p 781-789 doi:

10.1097/CCM.0000000000002321

3. Schuetz P, Beishuizen A, Broyles M, et al.:

Procalcitonin (PCT)-guided antibiotic stewardship: an international experts consensus on optimized clinical use, Clin Chem Lab Med 2019; 57(9), 1308-1318. doi:

https://doi.org/10.1515/cclm-2018-1181

for sepsis: A Swedish multicenter study. J Crit Care 56 2020: 73–79.

https://doi.org/10.1016/j.jcrc.2019.12.009.

2. Tan M, Lu ., Jiang H, et al.: The diagnostic accuracy of procalcitonin and C-reactive protein for sepsis: A systematic review and meta-analysis.

J Cell Biochem 2019;120(4):5852-5859.

doi:10.1002/jcb.27870