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Citation: Wu, Y.-K.; Chung, H.-W.;
Chen, Y.-T.; Chen, H.-C.; Chen, I.-H.;
Su, W.-L. Association of LVV-
Hemorphin-7 with Sepsis and Shock:
Roles of Cathepsin D and G in
Hemoglobin Metabolism in a
Prospective ICU Cohort Study.
Biomedicines 2024,12, 2789. https://
doi.org/10.3390/biomedicines12122789
Academic Editor: Christian Lehmann
Received: 14 November 2024
Revised: 2 December 2024
Accepted: 5 December 2024
Published: 9 December 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Association of LVV-Hemorphin-7 with Sepsis and Shock: Roles
of Cathepsin D and G in Hemoglobin Metabolism in a
Prospective ICU Cohort Study
Yao-Kuang Wu 1 ,2 ,† , Hsueh-Wen Chung 3, Yi-Ting Chen 2, 4, †, Hsing-Chun Chen 5, I-Hung Chen 5
and Wen-Lin Su 1,2,*
1
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Taipei Tzu Chi Hospital,
Buddhist Tzu Chi Medical Foundation, New Taipei 231, Taiwan; drbfci@gmail.com
2School of Medicine, Tzu Chi University, Hualien 970, Taiwan; kateytc@gmail.com
3Department of Nursing, College of Nursing, National Yang Ming Chiao Tung University,
Taipei City 112, Taiwan; snow721103@gmail.com
4Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Hualien Tzu Chi
Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan
5
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Dalin Tzu Chi Hospital,
Buddhist Tzu Chi Medical Foundation, Chiayi County 622, Taiwan; dm689688@tzuchi.com.tw (H.-C.C.);
b89401098@ntu.edu.tw (I.-H.C.)
*Correspondence: williamsu2007@gmail.com; Tel.: +886-2-66289779; Fax: +886-2-66289009
†These authors contributed equally to this work.
Abstract: Background: Sepsis is a leading cause of mortality in intensive care units (ICUs). Cell-free
hemoglobin (CFH) released during sepsis interacts with lysosomal enzymes from neutrophils and
macrophages. This study aims to examine the association of LVV-hemorphin-7 (LVV-H7), cathepsin
D, and cathepsin G with sepsis and shock in ICU patients. Methods: A prospective observational
cohort study was conducted in the medical ICU of a tertiary referral hospital in Taiwan. The patients
with an acute increasing sequential organ failure assessment (SOFA) score
≥
2 between 2022 and 2023.
Blood samples from 40 healthy controls were obtained from the hospital biobank. CFH metabolites,
including LVV-H7 and lysosomal enzyme cathepsin D and cathepsin G, were compared between the
sepsis (definite and probable) and non-sepsis (possible sepsis) groups. Multivariate logistic regression
analyzed factors associated with sepsis and shock. Results: Among 120 patients, 75 were classified as
septic and 45 as non-septic. Significant differences were observed in CFH, cathepsin D, cathepsin
G, and LVV-H7 levels between sepsis and non-sepsis groups. LVV-H7 was a significant predictor
for sepsis (adjusted OR [aOR] 1.009, 95% CI 1.005–1.013; p< 0.001) and shock (aOR 1.005, 95% CI
1.002–1.008; p< 0.05). Cathepsin G predicted non-shock (aOR 0.917, 95% CI 0.848–0.991; p< 0.05),
while cathepsin D predicted septic shock (aOR 1.001, 95% CI 1.000–1.002; p< 0.05). Conclusions:
LVV-H7, cathepsin D, and cathepsin G are associated with the classification of sepsis and shock
episodes in critically ill patients with elevated SOFA scores.
Keywords: sepsis; shock; cathepsin; LVV-hemorphin-7; sequential organ failure assessment score
1. Introduction
Sepsis is an extreme response to an infection that causes significant erythrocyte dam-
age, particularly in intensive care units (ICUs) where patients often develop anemia [
1
–
3
].
During sepsis-induced anemia, cell-free hemoglobin (CFH) is released by erythrocytes
through a series of mechanisms [
4
]. Traditionally, free heme and CFH-damaged tissue
have been observed to worsen sepsis in lipopolysaccharide-induced systemic inflammatory
animal models [
5
,
6
]. Clinical studies have shown that higher levels of CFH in patients with
sepsis are associated with lower survival rates [7,8].
Biomedicines 2024,12, 2789. https://doi.org/10.3390/biomedicines12122789 https://www.mdpi.com/journal/biomedicines
Biomedicines 2024,12, 2789 2 of 15
In infection cases, neutrophils and macrophages are recruited to the infection site to
combat pathogen invasion. Cathepsin G originates from neutrophils [
9
,
10
], while cathepsin
D comes from the lysosomes of macrophages [
11
]. These enzymes are potentially involved
in mechanisms that play a critical role in Hb cleavage during sepsis and the production of
hemorphins [
12
]. Hemorphin-7 (H7), which includes LVV-H7 and VV-H7, is defined as an
Hb metabolite found in thrombotic tissue and abdominal aortic aneurysms that attracts
leukocytes [
13
]. This suggests a synergistic effect between Hb and immune cells during
sepsis and the possible release of LVV-H7 into the blood, attracting leucocyte recruitment.
Recent cell culture studies have shown that LVV-H7 inhibits the angiotensin-converting
enzyme, downregulating angiotensin II and decreasing blood pressure, suggesting a nega-
tive correlation between LVV-H7 levels and shock [
14
]. The LVV-H7 may have synergism
that increases the risk of shock. These findings would justify the need for assessing the
hemoglobin metabolism-related biomarkers of sepsis severity.
This study was the first investigation about CFH, lysosomal enzymes, and LVV-H7 in
critical sepsis cases and compared these biomarkers between sepsis and control groups to
identify potential diagnostic factors for sepsis and shock.
2. Methods
2.1. Study Design and Participant Enrolment
This prospective observational cohort study consisted of patients with suspected
sepsis admitted to the medical intensive care units (ICUs) at a tertiary referral medical
center in Taiwan from 2022 to 2023, as shown in Figure 1.
Biomedicines 2024, 12, x FOR PEER REVIEW 2 of 16
In infection cases, neutrophils and macrophages are recruited to the infection site to
combat pathogen invasion. Cathepsin G originates from neutrophils [9,10], while cathep-
sin D comes from the lysosomes of macrophages [11]. These enzymes are potentially in-
volved in mechanisms that play a critical role in Hb cleavage during sepsis and the pro-
duction of hemorphins [12]. Hemorphin-7 (H7), which includes LVV-H7 and VV-H7, is
defined as an Hb metabolite found in thrombotic tissue and abdominal aortic aneurysms
that aracts leukocytes [13]. This suggests a synergistic effect between Hb and immune
cells during sepsis and the possible release of LVV-H7 into the blood, aracting leucocyte
recruitment. Recent cell culture studies have shown that LVV-H7 inhibits the angiotensin-
converting enzyme, downregulating angiotensin II and decreasing blood pressure, sug-
gesting a negative correlation between LVV-H7 levels and shock [14]. The LVV-H7 may
have synergism that increases the risk of shock. These findings would justify the need for
assessing the hemoglobin metabolism-related biomarkers of sepsis severity.
This study was the first investigation about CFH, lysosomal enzymes, and LVV-H7
in critical sepsis cases and compared these biomarkers between sepsis and control groups
to identify potential diagnostic factors for sepsis and shock.
2. Methods
2.1. Study Design and Participant Enrolment
This prospective observational cohort study consisted of patients with suspected sep-
sis admied to the medical intensive care units (ICUs) at a tertiary referral medical center
in Taiwan from 2022 to 2023, as shown in Figure 1.
Figure 1. Cohort flow diagram of the sepsis study enrollment process. MICU: Medical intensive care
unit; ICU: intensive care unit; SOFA, Sequential Organ Failure Assessment Score.
The study protocol titled “Exploring the anti-inflammation mechanisms of hemoglo-
bin and its metabolites in sepsis” was approved by the Institutional Review Board of Tai-
pei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City, Taiwan,
on 16 March 2020 (Protocol No.: 08-P-134). To evaluate the Hb metabolite concentrations
in the general population, the study titled “Analysis of erythrocyte-related metabolites in
plasma of healthy adults using biobank specimens” was approved by the same board on
11 January 2024 (Protocol No.: 13-IRB006). Forty blood samples previously collected from
healthy participants were applied as healthy controls. The informed consent was waived,
and the Biobank Ethics Commiee approved this application on 12 January 2024 (appli-
cation No: Tzubiobank 2024-05). All study procedures adhered to the ethical standards of
the responsible commiee on human experimentation and the Helsinki Declaration of
Figure 1. Cohort flow diagram of the sepsis study enrollment process. MICU: Medical intensive care
unit; ICU: intensive care unit; SOFA, Sequential Organ Failure Assessment Score.
The study protocol titled “Exploring the anti-inflammation mechanisms of hemoglobin
and its metabolites in sepsis” was approved by the Institutional Review Board of Taipei
Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City, Taiwan, on
16 March 2020 (Protocol No.: 08-P-134). To evaluate the Hb metabolite concentrations in the
general population, the study titled “Analysis of erythrocyte-related metabolites in plasma
of healthy adults using biobank specimens” was approved by the same board on 11 January
2024 (Protocol No.: 13-IRB006). Forty blood samples previously collected from healthy
participants were applied as healthy controls. The informed consent was waived, and the
Biobank Ethics Committee approved this application on 12 January 2024 (application No:
Tzubiobank 2024-05). All study procedures adhered to the ethical standards of the respon-
sible committee on human experimentation and the Helsinki Declaration of 1975. Informed
consents were obtained from participants or their legal agents upon ICU admission.
Biomedicines 2024,12, 2789 3 of 15
Inclusion criteria included patients meeting the sequential organ failure assessment
(SOFA) score
≥
2 and suspected infection since initial ICU admission. Suspected infec-
tions were categorized as definite, probable, or possible based on clinical symptoms and
radiological evidence according to the International Sepsis Forum Criteria [
15
]. The sepsis
classifications were divided into definite, probable, and possible sepsis categories following
the criteria established by Rhee et al. [
16
]. and Mellhammar et al. [
17
], as detailed in
the following.
Definite and probable sepsis were defined by the presence of criterion 1 and either
criterion 2 or 3:
1.
A definite or probable source of infection (e.g., positive cultures or radiographic
evidence with a compatible clinical syndrome).
2.
Organ dysfunction due to infection without any discernable cause other than infection.
3.
Organ dysfunction most likely attributable to infection, although other potential
contributors were present.
Possible sepsis was defined by the presence of either criterion 1 or 2:
1.
Patients were treated for presumed sepsis but lacked definitive evidence of infection.
2. Patients had alternative definite or possible explanations for organ dysfunction.
In our study, the sepsis group included patients classified as having definite or proba-
ble sepsis, while the non-sepsis group included those classified as having possible sepsis.
Exclusion criteria: Patients were excluded if they had co-infections with other viral
or fungal pathogens within 48 h of admission or if the collection of clinical specimens
was delayed beyond 48 h after admission, as these data would not reflect early sepsis
conditions. After applying these exclusion criteria, patients were retrospectively classified
into either the sepsis (definite and probable) or non-sepsis (possible sepsis) groups based
on the established sepsis classification criteria.
Subgroup exclusion criteria: In the “definite and probable sepsis” group, patients
were excluded if no source of microbiologic infection was identified. In the “possible and
non-sepsis” group, patients were excluded if nosocomial infection occurred before ICU
admission or if organ dysfunction progressed due to infection within 48 h.
The identified pathogens from cultures and the primary sources of infection in the
sepsis (definite and probable) group were documented. The causes of organ dysfunction in
the non-sepsis (possible sepsis) group were documented and are available in the following
seven groups.
1.
Acute or chronic renal failure leading to acute pulmonary edema with hypoxemic
respiratory failure or hyperkalemia with bradycardic heart failure.
2.
Cardiac dysfunction-related cardiogenic hypotension, including acute myocardial
infarction, decompensated heart failure, and arrhythmias.
3.
Pulmonary disease causing impaired gas exchange and hypoxemia, such as chronic
obstructive pulmonary disease, asthma, and interstitial lung disease.
4.
Gastrointestinal tract hemorrhage with hypovolemic hypotension, including esophageal
varices bleeding and upper or lower gastrointestinal tract bleeding.
5. Acute pancreatitis with volume depletion and distributive hypotension.
6.
Metabolic acidosis-related hypotension or cardiac suppression, including diabetic
ketoacidosis and hyperglycemic hyperosmolar syndrome.
7. Anaphylaxis resulting in distributive hypotension.
Patients identified as having septic shock were those requiring vasopressors to main-
tain a mean arterial pressure (MAP)
≥
65 mmHg [
18
] due to persistent hypotension with a
serum lactate level > 2 mmol/L (18 mg/dL), despite sufficient volume resuscitation. All
the patients adhered to the standard treatment protocol of the Surviving Sepsis Campaign
guidelines [19].
Biomedicines 2024,12, 2789 4 of 15
2.2. Data Collection
Patient data, including age, sex, initial vital signs, quick SOFA, Glasgow Coma Scale
(GCS), and Charlson Comorbidity Index (CCI) scores [
20
], were collected for demographic
analysis. Regular laboratory blood tests were performed during enrollment. Sources of
infection were documented through cultures of blood, tracheal aspiration, sputum, urine,
body fluid, and pus. All bacteria were subjected to the minimum inhibitory concentration
tests by using the VITEK
®
2 automated system (bioMérieux, Lyon, France). Antibiotic
resistance was manually examined using the BBL Sensi-Disc test or automatically deter-
mined by the VITEK
®
2 automated system in our hospital. Additional tests for pneumonia
pathogens included urine antigens of Legionella pneumoniae and Streptococcus pneumoniae,
and immunoglobulin M of Mycoplasma pneumoniae and Chlamydia pneumoniae. In patients
with sepsis, for the purpose of rapidly tracing multi-drug-resistant organisms, a film array
(BioFire Diagnostics, Salt Lake City, UT, USA) was used as a pneumonia panel for speci-
mens from tracheal aspiration and blood culture identification of bacterial growth in the
blood culture panel at 48 h without definite culture results. Clinical outcomes, including the
length of ICU stay, shock episodes within 48 h of ICU admission, hospitalization duration,
and survival status, were recorded.
2.3. Free Hemoglobin, Cathepsin D, Cathepsin G, LVV-H7, and Angiotensin II Enzyme-Linked
Immunosorbent Assay (ELISA) Analysis
Blood specimens from both ICU and healthy controls were stored at
−
80
◦
C until
analysis. The angiotensin II ELISA (ADI-900-204; Enzo Life Sciences Inc., Farmingdale, NY,
USA) was used, and all procedures were conducted according to the manufacturer’s in-
structions. For Hb metabolism, LVV-H7 was selected as the final stable form. Subsequently,
cathepsin D (ab119586; Abcam, Cambridge, UK), cathepsin G (EC3237-1, Assaypro, St.
Charles, MO, USA), Hb (ab157707; Abcam, Cambridge, UK), and LVV-H7 (MBS8820153;
MyBioSource, San Diego, CA, USA) antibodies were added to the wells. After incubation,
the washing step was repeated, and streptavidin horseradish peroxidase solution was
added. The plate was washed again, tetramethylbenzidine substrate was added, and the
plate was incubated in the dark. A stop solution was used to terminate the reaction, and
450 nm was chosen as the reference wavelength to measure absorbance. All tests were
performed in duplicate.
2.4. Statistical Analysis
Categorical data are presented as frequencies and percentages, and the continuous
data are presented as mean
±
standard deviation. A one-way analysis of variance was
used to compare among the three groups. The two continuous variables were compared
using Student’s t-test, and categorical variables were compared using the chi-square test.
Multivariate logistic regression analysis was performed, and confounding factors were
adjusted using stepwise forward enrollment methods to identify Hb metabolite biomarkers
for predicting sepsis, shock, and septic shock. Statistical analyses were performed using
the IBM SPSS Statistics statistical software for Windows (version 26.0; IBM Corp, Armonk,
NY, USA); statistical significance was set at p< 0.05.
3. Results
3.1. Hb Metabolic Biomarkers Among Sepsis, Non-Sepsis, and Healthy Control Groups
In total, 329 critically ill patients met the inclusion criteria of acute SOFA score
change
≥
2. After applying the exclusion/inclusion criterion, 120 patients were enrolled in
the study (Figure 1), with 75 in the sepsis group and 45 in the non-sepsis groups. The control
group consisted of blood samples from 40 healthy individuals. Post hoc analyses revealed
that CFH levels were significantly higher (p< 0.001) in the sepsis group (
15.3 ±8.8 mg/dL
)
compared to the non-sepsis (9.8
±
3.5 mg/dL) and control (9.3
±
3.9 mg/dL) groups
as Figure 2. Similarly, cathepsin D and LVV-H7 levels were significantly higher in the
sepsis group (849
±
703.1 and 371.7
±
190.5 ng/mL, respectively) (p< 0.001) than in the
Biomedicines 2024,12, 2789 5 of 15
non-sepsis (337.4
±
141.1 and 194.5
±
63.1 ng/mL, respectively) and control (220.4
±
86.5
and
82.3 ±6.4 ng/mL
, respectively) groups. Cathepsin G levels were significantly higher
(p< 0.001) in the sepsis (6.8
±
7.0
µ
g/mL) and non-sepsis (4.5
±
6.3
µ
g/mL) groups than in
the control group (1.2
±
0.3
µ
g/dL). However, angiotensin II levels were significantly lower
in the sepsis (78.5
±
105.8 ng/mL) and non-sepsis (87.8
±
95.5 ng/mL) groups compared
to the control group (527.1
±
625.6 ng/mL). Significant differences in free Hb, cathepsin
D, cathepsin G, LVV-H7, and angiotensin II values were observed between critically ill
patients with acute changes in SOFA scores and the control group.
Biomedicines 2024, 12, x FOR PEER REVIEW 5 of 16
that CFH levels were significantly higher (p < 0.001) in the sepsis group (15.3 ± 8.8 mg/dL)
compared to the non-sepsis (9.8 ± 3.5 mg/dL) and control (9.3 ± 3.9 mg/dL) groups as Fig-
ure 2. Similarly, cathepsin D and LVV-H7 levels were significantly higher in the sepsis
group (849 ± 703.1 and 371.7 ± 190.5 ng/mL, respectively) (p < 0.001) than in the non-sepsis
(337.4 ± 141.1 and 194.5 ± 63.1 ng/mL, respectively) and control (220.4 ± 86.5 and 82.3 ± 6.4
ng/mL, respectively) groups. Cathepsin G levels were significantly higher (p < 0.001) in
the sepsis (6.8 ± 7.0 µg/mL) and non-sepsis (4.5 ± 6.3 µg/mL) groups than in the control
group (1.2 ± 0.3 µg/dL). However, angiotensin II levels were significantly lower in the sep-
sis (78.5 ± 105.8 ng/mL) and non-sepsis (87.8 ± 95.5 ng/mL) groups compared to the control
group (527.1 ± 625.6 ng/mL). Significant differences in free Hb, cathepsin D, cathepsin G,
LVV-H7, and angiotensin II values were observed between critically ill patients with acute
changes in SOFA scores and the control group.
Figure 2. Hemoglobin metabolism among sepsis, non-sepsis, and health controls. (a) CFH, (b) ca-
thepsin D, (c) cathepsin G, (d) LVV-H7 and (e) angiotensin II. CFH: Cell-free hemoglobin; LVV-H7:
Figure 2. Hemoglobin metabolism among sepsis, non-sepsis, and health controls. (a) CFH, (b) cathep-
sin D, (c) cathepsin G, (d) LVV-H7 and (e) angiotensin II. CFH: Cell-free hemoglobin; LVV-H7:
LVV-hemorphin-7. p-values calculated using Student’s t-test are shown above the scatter points.
*p< 0.05, *** p< 0.001, **** p< 0.0001 for the difference between paired scatter points, respectively.
Biomedicines 2024,12, 2789 6 of 15
3.2. The Isolated Microorganisms in the Sepsis Group and the Diagnoses in the Non-Sepsis Group
The distribution of pathogens and the primary sources of infection in the sepsis
(definite and probable) group, along with the diagnoses contributing to organ dysfunction
in the non-sepsis (possible sepsis) group, are presented in Figure 3.
Biomedicines 2024, 12, x FOR PEER REVIEW 6 of 16
LVV-hemorphin-7. p-values calculated using Student’s t-test are shown above the scaer points. * p
< 0.05, *** p < 0.001, **** p < 0.0001 for the difference between paired scaer points, respectively.
3.2. The Isolated Microorganisms in the Sepsis Group and the Diagnoses in the
Non-Sepsis Group
The distribution of pathogens and the primary sources of infection in the sepsis (def-
inite and probable) group, along with the diagnoses contributing to organ dysfunction in
the non-sepsis (possible sepsis) group, are presented in Figure 3.
(A)
(B)
Figure 3. Cont.
Biomedicines 2024,12, 2789 7 of 15
Biomedicines 2024, 12, x FOR PEER REVIEW 7 of 16
(C)
Figure 3. Etiologies of organ dysfunction in sepsis and non-sepsis groups. (A) Distribution of path-
ogens in the sepsis group; (B) Primary sources of infection in the sepsis group; (C) Major causes of
multiple organ dysfunction in the non-sepsis group. The distribution of pathogens in the sepsis
group was as follows: Escherichia coli (n = 29, 23.4%), Klebsiella pneumoniae (n = 25, 20.2%), Enterococcus
faecalis (n = 16, 12.9%), Pseudomonas aeruginosa (n = 10, 8.1%), Staphylococcus aureus (n = 10, 8.1%),
Proteus mirabilis (n = 6, 4.8%), Serratia marcescens (n = 4, 3.2%), and others (n = 24, 19.3%) (Figure 3).
The primary sources of infection in the sepsis group included pneumonia (n = 20, 26.7%), urinary
tract infection (n = 19, 25.3%), abdominal infections other than urinary tract infection (n = 10, 13.3%),
other soft tissue infections or cellulitis (n = 3, 4.0%), and multi-infections (n = 23, 30.7%). The major
causes of multiple organ dysfunction in the non-sepsis group were as follows: cardiac dysfunction
(n = 16, 35.6%), pulmonary disease-related hypoxemia (n = 12, 26.7%), renal failure (n = 7, 15.6%),
gastrointestinal tract hemorrhage (n = 6, 13.3%), acute pancreatitis (n = 2, 4.4%), metabolic acidosis
(n = 1, 2.2%), and anaphylactic hypotension (n = 1, 2.2%).
3.3. Comparisons of Parameters Between Sepsis and Non-Sepsis Groups
Table 1 shows the demographic characteristics of the sepsis and non-sepsis groups.
Significant differences were observed in initial body temperature (BT; 36.99 vs. 36.38 °C,
p < 0.05), MAP (82.5 vs. 97.6 mmHg, p < 0.001), and SOFA score (6.6 vs. 5.1, p < 0.05) be-
tween the sepsis and non-sepsis groups. Clinical variables and outcomes were similar be-
tween the two groups, except for shock episodes, which were significantly higher in the
sepsis group (81.3% vs. 44.4%, p < 0.001).
Table 1. Characteristics of the different sepsis groups of the study population (n = 120).
Variables Definite and Probable Sepsis
(n = 75)
Possible and Non-Sepsis
(n = 45) p-Value
Age (years) 68.81 ± 14.17 71.09 ± 13.56 0.388
c
Sex 0.530
a
Female 31 (41.3%) 16 (35.6%)
Male 44 (58.7%) 29 (64.4%)
Body mass index (kg/m
2
) 22.96 ± 4.73 22.85 ± 4.41 0.900
c
Vital signs
Body temperature (℃) 36.99 ± 1.45 36.38 ± 0.81 0.004
c
*
Respiratory rate (/min) 21.17 ± 5.38 20.76 ± 4.69 0.667
c
Figure 3. Etiologies of organ dysfunction in sepsis and non-sepsis groups. (A) Distribution of
pathogens in the sepsis group; (B) Primary sources of infection in the sepsis group; (C) Major causes
of multiple organ dysfunction in the non-sepsis group. The distribution of pathogens in the sepsis
group was as follows: Escherichia coli (n = 29, 23.4%), Klebsiella pneumoniae (n = 25, 20.2%), Enterococcus
faecalis (n = 16, 12.9%), Pseudomonas aeruginosa (n = 10, 8.1%), Staphylococcus aureus (n = 10, 8.1%),
Proteus mirabilis (n = 6, 4.8%), Serratia marcescens (n = 4, 3.2%), and others (n = 24, 19.3%) (Figure 3).
The primary sources of infection in the sepsis group included pneumonia (n = 20, 26.7%), urinary
tract infection (n = 19, 25.3%), abdominal infections other than urinary tract infection (n = 10, 13.3%),
other soft tissue infections or cellulitis (n = 3, 4.0%), and multi-infections (n = 23, 30.7%). The major
causes of multiple organ dysfunction in the non-sepsis group were as follows: cardiac dysfunction
(n = 16, 35.6%), pulmonary disease-related hypoxemia (n = 12, 26.7%), renal failure (n = 7, 15.6%),
gastrointestinal tract hemorrhage (n = 6, 13.3%), acute pancreatitis (n = 2, 4.4%), metabolic acidosis
(n = 1, 2.2%), and anaphylactic hypotension (n = 1, 2.2%).
3.3. Comparisons of Parameters Between Sepsis and Non-Sepsis Groups
Table 1shows the demographic characteristics of the sepsis and non-sepsis groups.
Significant differences were observed in initial body temperature (BT; 36.99 vs. 36.38
◦
C,
p< 0.05
), MAP (82.5 vs. 97.6 mmHg, p < 0.001), and SOFA score (6.6 vs. 5.1, p< 0.05)
between the sepsis and non-sepsis groups. Clinical variables and outcomes were similar
between the two groups, except for shock episodes, which were significantly higher in the
sepsis group (81.3% vs. 44.4%, p < 0.001).
There were no significant differences between the two groups in red blood cell count,
Hb, platelets, monocytes, sodium (Na), potassium (K), alanine transaminase, aspartate
transaminase, albumin, blood urea nitrogen, creatinine, random glucose, lactate, prothrom-
bin time, international normalized ratio, pH, SaO
2
in arterial blood gas, ratio of arterial
oxygen partial pressure to fractional inspired oxygen, cathepsin G, and angiotensin II levels
(Table 2). However, significantly higher levels of white blood cell (WBC) count (13.16
vs. 9.36
×
10
3
/
µ
L, p< 0.001), total bilirubin (1.71 vs. 0.95 mg/dL, p< 0.05), activated
partial thromboplastin time (aPTT) (32.65 vs. 28.61 s, p< 0.05) levels, neutrophil (10.12 vs.
6.91 ×103/µL
,p< 0.001), C-reactive protein (CRP) (13.50 vs. 5.11 mg/dL, p < 0.001) were
observed in the sepsis group than in the non-sepsis group, respectively. In contrast, lower
lymphocyte levels (0.91 vs. 1.71 ×103/µL, p< 0.05) were detected in the sepsis group.
Biomedicines 2024,12, 2789 8 of 15
Table 1. Characteristics of the different sepsis groups of the study population (n = 120).
Variables Definite and Probable Sepsis
(n = 75)
Possible and Non-Sepsis
(n = 45) p-Value
Age (years) 68.81 ±14.17 71.09 ±13.56 0.388 c
Sex 0.530 a
Female 31 (41.3%) 16 (35.6%)
Male 44 (58.7%) 29 (64.4%)
Body mass index (kg/m2)22.96 ±4.73 22.85 ±4.41 0.900 c
Vital signs
Body temperature (◦C) 36.99 ±1.45 36.38 ±0.81 0.004 c*
Respiratory rate (/min) 21.17 ±5.38 20.76 ±4.69 0.667 c
Heart rate (/min) 106.33 ±25.76 100.16 ±26.57 0.211 c
MAP (mmHg) 82.53 ±22.00 97.58 ±21.33 <0.001 c**
SpO2(%) 94.85 ±4.94 94.36 ±5.03 0.597 c
GCS 12.13 ±4.06 12.27 ±4.08 0.862 c
CCI 5.55 ±2.80 5.38 ±2.31 0.734 c
Comorbidities
Diabetes 33 (44.0%) 18 (40.0%) 0.668 a
Cardiovascular disease 26 (34.7%) 22 (48.9%) 0.124a
Chronic kidney disease 24 (32.0%) 12 (26.7%) 0.537 a
Neurologic diseases 19 (25.3%) 11 (24.4%) 0.913 a
Pulmonary disease 15 (20.0%) 12 (26.7%) 0.397 a
Malignancy 15 (20.0%) 6 (13.3%) 0.352 a
Chronic liver disease 8 (10.7%) 4 (8.9%) 1.000 b
Autoimmune disease 2 (2.7%) 2 (4.4%) 0.630 b
Disease severity
qSOFA 1.09 ±0.83 0.84 ±0.74 0.099 c
SOFA score 6.61 ±2.91 5.11 ±2.80 0.006 c
APACHE II score 23.07 ±9.92 21.36 ±8.40 0.336 c
Oxygenation device status 0.512 a
IMV 35 (46.7%) 26 (57.8%)
NIV 5 (6.7%) 4 (8.9%)
Oxygen supplement 31 (41.3%) 14 (31.1%)
Oxygen not needed 4 (5.3%) 1 (2.2%)
Clinical outcomes
Length of stay in ICU 12.44 ±12.84 15.31 ±14.65 0.263 c
Hospital days 23.20 ±19.71 27.36 ±23.91 0.307 c
Shock episodes 61 (81.3%) 20 (44.4%) <0.001 a**
Survival 54 (72.0%) 35 (79.5%) 0.360 a
a
A chi-square test is used for the comparison of categorical variables,
b
Fisher’s exact test is used for the
comparison of categorical variables,
c
an independent t-test is used for continuous variables between the sepsis
and non-sepsis groups. * p< 0.05; ** p< 0.001. APACHE, Acute Physiology and Chronic Health Evaluation; CCI,
Charlson Comorbidity Index; GCS, Glasgow Coma Scale; MAP, mean arterial pressure; SOFA, Sequential Organ
Failure Assessment; SpO2, saturation from pulse oximeter; qSOFA, Quick Sequential Organ Failure Assessment;
IMV, Invasive Mechanical Ventilation; NIV, Noninvasive Ventilation.
Table 2. Laboratory data from different groups of the study population (n = 120).
Variables Definite and Probable Sepsis
(n = 75)
Possible and Non-Sepsis
(n = 45) p-Value
WBC (103/µL) 13.16 ±7.71 9.36 ±4.27 0.001 *
RBC (106/µL) 3.67 ±0.84 3.60 ±0.92 0.650
Hemoglobin (g/dL) 11.00 ±2.58 10.97 ±2.58 0.948
Platelets (103/µL) 186.84 ±129.37 202.96 ±93.94 0.433
Neutrophil (103/µL) 10.12 ±6.70 6.91 ±3.64 0.001 *
Lymphocyte (103/µL) 0.91 ±0.80 1.71 ±1.96 0.011 *
Monocyte (103/µL) 0.50 ±0.41 0.47 ±0.31 0.602
Na (mEq/L) 135.13 ±6.93 136.76 ±5.22 0.149
K (mEq/L) 4.23 ±1.04 4.17 ±0.84 0.748
Biomedicines 2024,12, 2789 9 of 15
Table 2. Cont.
Variables Definite and Probable Sepsis
(n = 75)
Possible and Non-Sepsis
(n = 45) p-Value
AST (U/L) 92.60 ±167.37 71.24 ±147.65 0.481
ALT (U/L) 41.43 ±59.41 39.49 ±42.64 0.849
Albumin (g/dL) 3.00 ±0.58 3.19 ±0.49 0.075
BUN (mg/dL) 52.77 ±41.87 43.53 ±32.13 0.206
Creatinine (mg/dL) 2.93 ±2.57 2.68 ±3.19 0.642
Random Glucose (mg/dL) 179.30 ±80.1 176.15 ±82.68 0.837
Lactate (mmol/L) 3.62 ±3.49 3.75 ±4.57 0.863
CRP (mg/dL) 13.50 ±11.38 5.11 ±7.53 <0.001 **
PCT (ng/mL) 19.03 ±37.18 14.57 ±43.85 0.553
Total bilirubin (mg/dL) 1.71 ±2.56 0.95 ±0.77 0.019 *
PT (second) 12.30 ±2.49 11.55 ±1.84 0.084
INR (ratio) 1.23 ±0.32 1.18 ±0.32 0.404
aPTT (second) 32.65 ±8.04 28.61 ±6.12 0.002 *
ABG pH 7.36 ±0.12 7.39 ±0.10 0.093
ABG SaO295.89 ±3.43 96.82 ±3.43 0.154
P/F ratio 243.97 ±137.03 289.95 ±148.78 0.088
Hemoglobin catabolism
Free Hemoglobin (mg/dL) 15.27 ±8.81 9.75 ±3.51 <0.001 **
Cathepsin D (ng/mL) 849.19 ±703.08 337.44 ±141.09 <0.001 **
Cathepsin G (µg/mL) 6.79 ±7.04 4.54 ±6.28 0.080
LVV-H7 (ng/mL) 371.68 ±190.52 194.48 ±63.10 <0.001 **
Angiotensin II (pg/mL) 78.50 ±105.78 87.81 ±95.54 0.630
An independent t-test was used to compare continuous variables between the sepsis and non-sepsis groups.
*p< 0.05
; ** p< 0.001. ABG, arterial blood gas; ALT, alanine transaminase; aPTT, activated partial thromboplastin
time; AST, aspartate transaminase; BUN, blood urea nitrogen; CRP, C-reactive protein; INR, international normal-
ized ratio; LVV-H7, LVV-hemorphin 7; PCT, procalcitonin; P/F ratio, ratio of arterial oxygen partial pressure to
fractional inspired oxygen; PT, prothrombin time; RBC, red blood cell count; SaO
2
, arterial oxygen saturation;
WBC, white blood cell.
As shown in Figure 2and Table 2, the sepsis group had significantly higher levels of
free Hb (15.27 vs. 9.75 mg/dL; p < 0.001), cathepsin D (849.19 vs. 337.44 ng/mL; p< 0.001),
and LVV-H7 (371.68 vs. 194.48 ng/mL; p< 0.001) than the non-sepsis group. However, there
were no significant differences observed in cathepsin G or angiotensin II levels between the
two groups.
3.4. Potential Factors for Diagnosis of Sepsis, Shock, or Septic Shock in Critical Ill Patients with
Acute Change of SOFA Score ≥2
Forward stepwise logistic regression identified variables with p< 0.05 as significant
factors associated with sepsis classifications. Significant independent variables were CRP
(odds ratio [OR] 1.086, 95% confidence interval [CI] 1.024–1.153; p< 0.001), aPTT (OR 0.999,
95% CI 0.999–1.163; p< 0.05), and WBC (OR 1.128, 95% CI 1.017–1.251; p< 0.05). After
adjusting for other factors, LVV-H7 (adjusted OR [aOR] 1.009, 95% CI 1.005–1.013; p < 0.001)
was a significant factor for differentiating sepsis classifications (Table 3).
The receiver operating characteristic (ROC) curves were calculated to predict sepsis
using different biomarkers (Table 4and Figure 4). The area under the curve (AUC) was 0.741
for LVV-H7, with the best cutoff point being 316.61 ng/mL (50.7% sensitivity and 100.0%
specificity). The AUC was 0.738 for CRP, and a cutoff point of 5.85 mg/dL (72% sensitivity
and 77.8% specificity. The AUC was 0.639 in WBC, with a cutoff point of
12.03 ×103/µL
(53.3% sensitivity and 82.2% specificity). According to Youden’s J statistic and AUC, LVV-
H7 was the best biomarker for the diagnosing of sepsis, with high specificity and low
sensitivity (Figure 4).
Biomedicines 2024,12, 2789 10 of 15
Table 3. Logistic regression models of sepsis classification factors.
Variables βSE OR
95% CI
p-Value
Lower Upper
LVV-H7 0.009 0.002 1.009 1.005 1.014 <0.001 **
CRP 0.083 0.030 1.086 1.024 1.153 0.006 *
aPTT 0.075 0.039 1.078 0.999 1.163 0.052
WBC 0.121 0.053 1.128 1.017 1.251 0.022 *
*p< 0.05; ** p< 0.001. Logistic regression model with forward stepwise selection for variables such as free
hemoglobin, cathepsin D, cathepsin G, LVV-H7, angiotensin II, SOFA score, initial body temperature, MAP,
Total bilirubin, CRP, aPTT, WBC, neutrophils, and lymphocytes. aPTT, activated partial thromboplastin time; CI,
confidence interval; CRP, C-reactive protein; LVV-H7, LVV-hemorphin 7; OR, odds ratio; SE, standard error; WBC,
white blood cell.
Table 4. ROC curves of different biomarkers of sepsis classifications (n = 120).
Biomarkers
Area
95% CI
p-Value Cuff Point Sensitivity Specificity Youden’s J
Lower Upper
LVV-H7 0.741 0.654 0.827 <0.001 **
316.61 (ng/mL)
0.507 1.000 0.507
CRP 0.738 0.647 0.830 <0.001 ** 5.85 (mg/dL) 0.720 0.778 0.498
WBC 0.639 0.540 0.738 0.011 * 12.03 (103/µL) 0.533 0.822 0.356
Notes: Youden’s J statistic: sensitivity + specificity
−
1. * p< 0.05; ** p< 0.001. CI, confidence interval; CRP,
C-reactive protein; LVV-H7, LVV-hemorphin 7; ROC, receiver operating characteristic; WBC, white blood cell.
Biomedicines 2024, 12, x FOR PEER REVIEW 11 of 16
Figure 4. The receiver operating characteristic (ROC) curve for LVV-H7 in predicting sepsis. The
blue solid line represents the ROC curve of LVV-H7 (LVV-hemorphin-7), illustrating its diagnostic
performance. The red dashed line indicates the 50% area under the curve (AUC), serving as the
reference line for random chance.
4. Discussion
This study is the first to evaluate Hb metabolism biomarkers, including free Hb, ca-
thepsin D, cathepsin G, LVV-H7, and angiotensin II, in relation to sepsis classifications
among critically ill patients with an acute increase in SOFA score ≥ 2.
Our findings demonstrate that critically ill definite and probable sepsis patients had
higher levels of CFH, cathepsin G, cathepsin D, and LVV-H7 compared to possible sepsis
patients and healthy controls, indicating potential metabolic interactions between im-
mune cell lysosome enzymes and CFH during sepsis (Figure 5). These results align with
previous research suggesting that CFH contributes to oxidative and endothelial injury in
sepsis-related acute respiratory distress syndrome [21], a process well-documented in he-
molysis and CFH release [4]. The CFH released into the blood increases the chances of
cathepsin G originating from neutrophils and cathepsin D originating from macrophages
digesting free Hb. Although cathepsin G levels were higher in the definite and probable
sepsis group, it was not significantly different from those in the possible sepsis group,
possibly because cathepsin G is released by neutrophils during inflammation and contrib-
utes to the immune response when the body experiences infection or inflammation [22,23].
Similarly, although cathepsin D levels were significantly higher in the definite and prob-
able sepsis patients, they did not show a positive association in the logistic regression
model for sepsis classification, possibly because cathepsin D is released from macro-
phages in severe acidic environments, leading to variable blood concentrations that may
not accurately reflect sepsis status [24]. Despite the lack of association for cathepsins G
and D in predicting sepsis classifications, these enzymes contribute to the production of
downstream metabolites, such as LVV-H7, which was identified as a stable and predomi-
nant blood biomarker [12,25]. In this study, LVV-H7 was a significant factor for sepsis
classifications (Table 3), although its levels may be influenced by comorbidities like cancer
[26], obesity [27], and diabetes [28]. Here, malignancies, diabetes, and BMI calculations
were investigated, and no differences in their distributions between the different sepsis
groups were found. Notably, LVV-H7 demonstrated high specificity (100%) but low sen-
sitivity (50.7%) for sepsis classifications, suggesting it may be more useful as an
Figure 4. The receiver operating characteristic (ROC) curve for LVV-H7 in predicting sepsis. The
blue solid line represents the ROC curve of LVV-H7 (LVV-hemorphin-7), illustrating its diagnostic
performance. The red dashed line indicates the 50% area under the curve (AUC), serving as the
reference line for random chance.
Forward stepwise logistic regression identified significant independent variables with
p< 0.05 for predicting shock or septic shock. Among the 120 ICU patients, 81 experienced
shock episodes within 48 h of ICU admission. Significant independent variables for pre-
dicting shock were Cathepsin G (aOR 0.917, 95% CI 0.848–0.991; p< 0.05), LVV-H7 (aOR
1.005, 95% CI 1.002–1.008; p< 0.05), SOFA score (OR 1.341, 95% CI 1.103–1.630; p< 0.05),
and aPTT (OR 1.096, 95% CI 1.015–1.184; p< 0.05).
For predicting septic shock, among the 120 ICU patients, 40 were identified within
48 h of ICU admission. Significant independent variables for predicting septic shock were
Biomedicines 2024,12, 2789 11 of 15
cathepsin D (aOR 1.001, 95% CI 1.000–1.002; p< 0.05), lactate (OR 1.182, 95% CI 1.054–1.324;
p< 0.05), and CRP (OR 1.094, 95% CI 1.044–1.147; p< 0.001) (Table 4).
4. Discussion
This study is the first to evaluate Hb metabolism biomarkers, including free Hb,
cathepsin D, cathepsin G, LVV-H7, and angiotensin II, in relation to sepsis classifications
among critically ill patients with an acute increase in SOFA score ≥2.
Our findings demonstrate that critically ill definite and probable sepsis patients had
higher levels of CFH, cathepsin G, cathepsin D, and LVV-H7 compared to possible sepsis
patients and healthy controls, indicating potential metabolic interactions between immune
cell lysosome enzymes and CFH during sepsis (Figure 5). These results align with previous
research suggesting that CFH contributes to oxidative and endothelial injury in sepsis-
related acute respiratory distress syndrome [
21
], a process well-documented in hemolysis
and CFH release [
4
]. The CFH released into the blood increases the chances of cathepsin
G originating from neutrophils and cathepsin D originating from macrophages digesting
free Hb. Although cathepsin G levels were higher in the definite and probable sepsis
group, it was not significantly different from those in the possible sepsis group, possibly
because cathepsin G is released by neutrophils during inflammation and contributes to the
immune response when the body experiences infection or inflammation [
22
,
23
]. Similarly,
although cathepsin D levels were significantly higher in the definite and probable sepsis
patients, they did not show a positive association in the logistic regression model for sepsis
classification, possibly because cathepsin D is released from macrophages in severe acidic
environments, leading to variable blood concentrations that may not accurately reflect
sepsis status [
24
]. Despite the lack of association for cathepsins G and D in predicting sepsis
classifications, these enzymes contribute to the production of downstream metabolites,
such as LVV-H7, which was identified as a stable and predominant blood biomarker [
12
,
25
].
In this study, LVV-H7 was a significant factor for sepsis classifications (Table 3), although its
levels may be influenced by comorbidities like cancer [
26
], obesity [
27
], and diabetes [
28
].
Here, malignancies, diabetes, and BMI calculations were investigated, and no differences
in their distributions between the different sepsis groups were found. Notably, LVV-H7
demonstrated high specificity (100%) but low sensitivity (50.7%) for sepsis classifications,
suggesting it may be more useful as an exclusionary marker rather than a primary diagnos-
tic tool, similar to the role of D-dimer in ruling out pulmonary embolism [29].
Biomedicines 2024, 12, x FOR PEER REVIEW 12 of 16
exclusionary marker rather than a primary diagnostic tool, similar to the role of D-dimer
in ruling out pulmonary embolism [29].
Figure 5. The signal transduction mechanism during sepsis. In sepsis state, RBC release cell-free
hemoglobin due to infection, cathepsin D and cathepsin G degrade CFH, thereby releasing opioid
peptides LVV-H7. The LVV-H7 binding to ANG-II, causing blood pressure decrease in patients with
sepsis. CFH: cell-free hemoglobin; LVV-H7: LVV-hemorphin-7; RBC: red blood cells.
WBC was the traditional biomarker of systemic inflammation response syndrome as
a previous diagnostic criterion of sepsis but was changed to the SOFA score at the 3rd
International Sepsis Conference [18]. Here, WBC count was still a strong predictive factor
for sepsis. In addition, the CRP level was also a traditional prognostic factor for sepsis in
a clinical study [30] and was not included in any disease severity scoring system. Thus,
the CRP level remained a substantial predictive factor for sepsis in this study.
In terms of clinical outcomes, the definite and probable sepsis group experienced sig-
nificantly more shock episodes than the possible sepsis group, although no difference in
the length of ICU stay, hospital stay, and survival. Our analysis of Hb metabolites (LVV-
H7, cathepsin D, cathepsin G, and angiotensin II) in relation to shock and septic shock
revealed that LVV-H7 could predict shock, while cathepsin G showed potential in reduc-
ing shock episodes (Table 5). The relationship between LVV-H7 and angiotensin II levels
suggested dual mechanisms, with LVV-H7 potentially influencing blood pressure regula-
tion through both angiotensin-converting enzyme inhibition and direct targeting of the
angiotensin II type 1 receptor (AT1R) [14]. These mechanisms result in hypotension driven
by LVV-H7, rather than by angiotensin II. Conversely, cathepsin G showed potential to
predict less shock in multivariate logistic regression (Table 5). Cathepsin G traditionally
acts as neutrophil angiotensin II-generating protease with functional control of blood
pressure [31]. Cathepsin G may contribute to angiotensin II production in pig renal tissue
[32], and these mechanisms may explain our clinical results that cathepsin G regulates the
blood pressure with fewer shock episodes. Furthermore, cathepsin D showed potential to
predict septic shock (Table 5). Septic shock has strict criteria of profound shock with lactic
acidosis. Previous studies showed that cathepsin D is released more in acidic environ-
ments [24], suggesting an association with septic shock with lactic acidosis. Therefore, the
lysosomal enzyme (cathepsin G and cathepsin D), CFH metabolites (LVV-H7), and angi-
otensin II may act as different indicators to guide clinical infection outcomes, including
sepsis, shock, or septic shock.
Table 5. Logistic regression models of shock or septic shock factors.
Variables 𝜷 SE OR 95% CI p-Value
Lower Upper
For shock factors
Cathepsin G −0.087 0.040 0.917 0.848 0.991 0.030 *
LVV-H7 0.005 0.002 1.005 1.002 1.008 0.004 *
SOFA score 0.293 0.100 1.341 1.103 1.630 0.003 *
aPTT 0.092 0.039 1.096 1.015 1.184 0.019 *
Figure 5. The signal transduction mechanism during sepsis. In sepsis state, RBC release cell-free
hemoglobin due to infection, cathepsin D and cathepsin G degrade CFH, thereby releasing opioid
peptides LVV-H7. The LVV-H7 binding to ANG-II, causing blood pressure decrease in patients with
sepsis. CFH: cell-free hemoglobin; LVV-H7: LVV-hemorphin-7; RBC: red blood cells.
WBC was the traditional biomarker of systemic inflammation response syndrome as
a previous diagnostic criterion of sepsis but was changed to the SOFA score at the 3rd
International Sepsis Conference [
18
]. Here, WBC count was still a strong predictive factor
for sepsis. In addition, the CRP level was also a traditional prognostic factor for sepsis in a
clinical study [
30
] and was not included in any disease severity scoring system. Thus, the
CRP level remained a substantial predictive factor for sepsis in this study.
Biomedicines 2024,12, 2789 12 of 15
In terms of clinical outcomes, the definite and probable sepsis group experienced
significantly more shock episodes than the possible sepsis group, although no difference in
the length of ICU stay, hospital stay, and survival. Our analysis of Hb metabolites (LVV-H7,
cathepsin D, cathepsin G, and angiotensin II) in relation to shock and septic shock revealed
that LVV-H7 could predict shock, while cathepsin G showed potential in reducing shock
episodes (Table 5). The relationship between LVV-H7 and angiotensin II levels suggested
dual mechanisms, with LVV-H7 potentially influencing blood pressure regulation through
both angiotensin-converting enzyme inhibition and direct targeting of the angiotensin
II type 1 receptor (AT1R) [
14
]. These mechanisms result in hypotension driven by LVV-
H7, rather than by angiotensin II. Conversely, cathepsin G showed potential to predict
less shock in multivariate logistic regression (Table 5). Cathepsin G traditionally acts as
neutrophil angiotensin II-generating protease with functional control of blood pressure [
31
].
Cathepsin G may contribute to angiotensin II production in pig renal tissue [
32
], and these
mechanisms may explain our clinical results that cathepsin G regulates the blood pressure
with fewer shock episodes. Furthermore, cathepsin D showed potential to predict septic
shock (Table 5). Septic shock has strict criteria of profound shock with lactic acidosis.
Previous studies showed that cathepsin D is released more in acidic environments [
24
],
suggesting an association with septic shock with lactic acidosis. Therefore, the lysosomal
enzyme (cathepsin G and cathepsin D), CFH metabolites (LVV-H7), and angiotensin II may
act as different indicators to guide clinical infection outcomes, including sepsis, shock, or
septic shock.
Table 5. Logistic regression models of shock or septic shock factors.
Variables βSE OR
95% CI
p-Value
Lower Upper
For shock factors
Cathepsin G −0.087 0.040 0.917 0.848 0.991 0.030 *
LVV-H7 0.005 0.002 1.005 1.002 1.008 0.004 *
SOFA score 0.293 0.100 1.341 1.103 1.630 0.003 *
aPTT 0.092 0.039 1.096 1.015 1.184 0.019 *
For septic shock factors
Cathepsin D 0.001 0.000 1.001 1.000 1.002 0.026 *
Lactate 0.167 0.058 1.182 1.054 1.324 0.004 *
CRP 0.090 0.024 1.094 1.044 1.147 <0.001 **
*p< 0.05; ** p< 0.001. Logistic regression model with forward stepwise selection for variables such as free
hemoglobin, cathepsin D, cathepsin G, LVV-H7, Angiotensin II, SOFA score, gender, BMI, CCI, APACHE II score,
lactate, oxygenation device status, albumin, CRP, PT, aPTT, INR, WBC, neutrophils, and lymphocytes. APACHE,
Acute Physiology and Chronic Health Evaluation; aPTT, activated partial thromboplastin time; BMI, body mass
index; CCI, Charlson comorbidity index; CI, confidence interval; CRP, C-reactive protein; INR, international
normalized ratio; LVV-H7, LVV-hemorphin 7; OR, odds ratio; PT, prothrombin time, SE, standard error; SOFA,
Sequential Organ Failure Assessment; WBC, white blood cell.
Procalcitonin is a highly sensitive diagnostic marker for sepsis and is also used to
monitor the effectiveness of antibiotic therapy [
33
]. However, in our study, PCT was not
associated with sepsis classifications. The possible reasons are as follows. Our study was
designed to differentiate the causes of systemic inflammatory response syndrome (multiple
organ and tissue hypoperfusion) and the hemoglobin metabolism status between definite,
probable, and possible sepsis. Since all patients met the sepsis criteria, the possible sepsis
group still exhibited high PCT levels. Another reason could be that we excluded cases
where clinical cultures were collected 48 h after ICU admission. This exclusion might
have affected the possible sepsis group, as some patients may have had insidious bacterial
growth leading to high PCT levels. The exclusion was intended to prevent secondary
infections from confounding the study results.
Some limitations of this study include the small sample size of the non-sepsis group.
Although disease severity and comorbidities were similar between the sepsis and non-
sepsis groups, the sample size in the non-sepsis and control groups, which was 50%
Biomedicines 2024,12, 2789 13 of 15
smaller than the sepsis group, may have reduced the statistical power and impacted the
results of LVV-H7 as a less sensitive biomarker. Additionally, the SOFA score, a major
diagnostic criterion for sepsis (acute change > 2), made it challenging for the non-sepsis and
control groups to meet the inclusion criteria, resulting in exclusions based on these criteria.
Increasing the control group size may enhance the statistical power for case–control study
comparisons. Future studies should consider multicenter prospective designs enrolling
sepsis and non-sepsis cases in a 1:1 ratio with SOFA > 2 as control groups. Secondly, in the
sepsis group (n = 75), the diversity of organisms involved in sepsis may have affected the
validation of sepsis biomarkers. Future comparisons between different classifications, such
as Gram-positive vs. Gram-negative, multidrug-resistant organisms vs. non-resistant, and
bacterial vs. viral infections, could help clarify the characteristics of new sepsis biomarkers.
Additionally, we did not test procalcitonin more than once in the non-sepsis group for a
series of comparisons. Procalcitonin is more sensitive to bacterial infection and suitable
for new biomarker comparisons. We suggest routine procalcitonin testing as a follow-up
measure in future sepsis studies.
5. Conclusions
LVV-H7, cathepsin D, and cathepsin G levels serves as potential biomarkers for sepsis
classifications and shock episodes in critically ill patients with acute changes in the SOFA
score
≥
2. LVV-H7 may help exclude definite and probable sepsis when levels are below
normal. Cathepsin G may assist in blood pressure control and reduce shock incidence,
while cathepsin D is more active and associated with septic shock. Further multicenter
prospective studies that enroll other non-sepsis control groups are needed to validate
the clinical utility of cathepsin D, cathepsin G, and LVV-H7 in differentiating sepsis and
septic shock.
Author Contributions: W.-L.S. and Y.-K.W. conceived and designed the study and obtained research
funding. W.-L.S., Y.-T.C., Y.-K.W. and H.-W.C. supervised the study, collected the data, and critically
revised the manuscript. W.-L.S., H.-W.C., H.-C.C., I.-H.C. and Y.-T.C. provided statistical advice
on the study design and analyzed the data, while W.-L.S., H.-W.C., Y.-K.W., Y.-T.C., H.-C.C. and
I.-H.C. conducted data analysis, data interpretation, and manuscript preparation. W.-L.S. and H.-W.C.
aired the Data Oversight Committee. W.-L.S. drafted the manuscript and all authors contributed
substantially to its revision. Y.-T.C. and Y.-K.W. took responsibility for the entire manuscript. All
authors have read and agreed to the published version of the manuscript.
Funding: This work was supported by grants from the Buddhist Tzu Chi Medical Foundation
[TCMF-CP 112-02] and Taipei Tzu Chi Hospital [TCRD-TPE-112-03]. The funding body had no role
in the conceptualization, design, data collection, analysis, decision to publish, or preparation of
the manuscript.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki, and approved by the Institutional Review Board of Taipei Tzu Chi Hospital, Buddhist
Tzu Chi Medical Foundation, New Taipei City, Taiwan on March 16, 2020 (Protocol No.: 08-P-134).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The data supporting the findings of this study are available from
the Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation. Restrictions may apply to the
availability of data used under the license of the current study because they are not publicly available.
However, the data are available from the authors upon reasonable request and with permission from
Taipei Tzu Chi Hospital and the Buddhist Tzu Chi Medical Foundation.
Acknowledgments: The authors appreciate the assistance of the Biobank of Taipei Tzu Chi Hospital
in the collection and processing of clinical specimens. We acknowledge Chih-Yu Chan, the Division
of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Taipei Tzu Chi Hospital,
Buddhist Tzu Chi Medical Foundation, New Taipei, Taiwan, for conducting ELISA to detect cell-free
hemoglobin, cathepsin D, cathepsin G, LVV-H7, and angiotensin II.
Conflicts of Interest: The authors declare that they have no competing interests.
Biomedicines 2024,12, 2789 14 of 15
List of Abbreviations
aHR, adjusted hazard ratio; aOR, adjusted odds ratio; aPTT, activated partial thrombo-
plastin clotting time; AUC: area under the curve; BMI, body mass index; BT: body tempera-
ture; BUN, blood urea nitrogen; CCI, Charlson comorbidity index; CI, confidence interval;
CFH: cell-free hemoglobin; CRP, C-reactive protein; ELISA, enzyme-linked immunosorbent
assay; GCS, Glasgow Coma Scale; Hb, hemoglobin; LVV-H7, LVV-hemorphin-7; MAP,
Mean arterial pressure; PCT, procalcitonin; qSOFA, quick sepsis-related organ failure as-
sessment; RBC: red blood cells; SOFA, Sequential Organ Failure Assessment Score; SpO
2
,
oxygen saturation of pulse oximeter; WBC: white blood cells.
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