SUMMARY
OBJECTIVE:
Neonatal sepsis is a serious disease that needs timely and immediate medical attention. So far, there is no specific prognostic biomarkers or model for dependable predict outcomes in neonatal sepsis. The aim of this study was to establish a predictive model based on readily available laboratory data to assess 30-day mortality in neonatal sepsis.
METHODS:
Neonates with sepsis were recruited between January 2019 and December 2022. The admission information was obtained from the medical record retrospectively. Univariate or multivariate analysis was utilized to identify independent risk factors. The receiver operating characteristic curve was drawn to check the performance of the predictive model.
RESULTS:
A total of 195 patients were recruited. There was a big difference between the two groups in the levels of hemoglobin and prothrombin time. Multivariate analysis confirmed that hemoglobin>133 g/L (hazard ratio: 0.351, p=0.042) and prothrombin time >16.6 s (hazard ratio: 4.140, p=0.005) were independent risk markers of 30-day mortality. Based on these results, a predictive model with the highest area under the curve (0.756) was built.
CONCLUSION:
We established a predictive model that can objectively and accurately predict individualized risk of 30-day mortality. The predictive model should help clinicians to improve individual treatment, make clinical decisions, and guide follow-up management strategies.
KEYWORDS:
Hemoglobin; Model; Mortality; Neonatal sepsis; Prothrombin time
INTRODUCTION
Neonatal sepsis is a serious and life-threatening disease that needs timely and immediate medical attention11 Molloy EJ, Wynn JL, Bliss J, Koenig JM, Keij FM, McGovern M, et al. Neonatal sepsis: need for consensus definition, collaboration and core outcomes. Pediatr Res. 2020;88(1):2-4. https://doi.org/10.1038/s41390-020-0850-5
https://doi.org/10.1038/s41390-020-0850-...
. Despite advances in medical care, neonatal sepsis remains a significant cause of morbidity and mortality in neonates worldwide. The prevalence of neonatal sepsis and mortality rates varies across different regions and healthcare settings, with higher rates reported in low-resource areas22 Ko MH, Chang HY, Li ST, Jim WT, Chi H, Hsu CH, et al. An 18-year retrospective study on the epidemiology of early-onset neonatal sepsis - emergence of uncommon pathogens. Pediatr Neonatol. 2021;62(5):491-8. https://doi.org/10.1016/j.pedneo.2021.02.005
https://doi.org/10.1016/j.pedneo.2021.02...
. Studies have reported that various biomarkers can affect the prognosis of neonatal sepsis, including gestational age, birth weight, presence of comorbidities, blood change, and the type of infecting organism33 Hofer N, Edlinger S, Resch B. Comparison of risk for early-onset sepsis in small-for-gestational-age neonates and appropriate-for-gestational-age neonates based on lower levels of white blood cell, neutrophil, and platelet counts. Pediatr Neonatol. 2014;55(4):323-5. https://doi.org/10.1016/j.pedneo.2013.12.006
https://doi.org/10.1016/j.pedneo.2013.12...
–77 Russell NJ, Stöhr W, Plakkal N, Cook A, Berkley JA, Adhisivam B, et al. Patterns of antibiotic use, pathogens, and prediction of mortality in hospitalized neonates and young infants with sepsis: a global neonatal sepsis observational cohort study (NeoOBS). PLoS Med. 2023;20(6):e1004179. https://doi.org/10.1371/journal.pmed.1004179
https://doi.org/10.1371/journal.pmed.100...
. Early identification and suitable treatment are essential for improving outcomes in patients with sepsis. To neonates, the clinical manifestations of sepsis can be nonspecific. Laboratory investigations, such as blood pressure monitoring, interleukin-18, and elevated neutrophil-to-monocyte ratio, are helpful for clinicians to evaluate the risk of adverse outcomes and guide treatment decisions88 Chawla D. Blood pressure monitoring for predicting mortality in neonatal sepsis. Indian J Pediatr. 2023;90(11):1071-2. https://doi.org/10.1007/s12098-023-04802-7
https://doi.org/10.1007/s12098-023-04802...
–1010 Xia X, Wang Y, Xie M, Qiu S, Zhou J. Elevated neutrophil - to - monocyte ratio as a prognostic marker for poor outcomes in neonatal sepsis. Heliyon. 2022;8(10):e11181. https://doi.org/10.1016/j.heliyon.2022.e11181
https://doi.org/10.1016/j.heliyon.2022.e...
. So far, there is no specific prognostic biomarkers or model for dependable predict outcomes in neonatal sepsis. Our goal is to establish a predictive model based on readily available laboratory data to assess 30-day mortality in neonatal sepsis.
Patients
The investigation recruited neonates who were admitted to the hospital between January 2019 and December 2022. The admission information was obtained from the medical record retrospectively. The neonates were limited to those who were diagnosed with neonatal sepsis, with complete patient information, and aged within 28 days. Finally, 195 patients were recruited in the cohort. The diagnosis of neonatal sepsis was based on the International Consensus on Pediatric Sepsis definition1111 Goldstein B, Giroir B, Randolph A. International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics. Pediatr Crit Care Med. 2005;6(1):2-8. https://doi.org/10.1097/01.PCC.0000149131.72248.E6
https://doi.org/10.1097/01.PCC.000014913...
. The study was approved by the ethics committee at the local hospital and was conducted in accordance with the guidelines set out in the Declaration of Helsinki.
Data
The following admission indexes were gathered in this investigation: age, gender, gestational age, weight, Apgar scores (5 min and 10 min), admission laboratory results, including routine blood test (neutrophils, lymphocyte, monocyte, platelet, hemoglobin), biochemical indicators [alanine aminotransferase (ALT), aspartate transaminase (AST), lactate dehydrogenase (LDH), direct bilirubin (DB), albumin (ALB), urea nitrogen (UREA), creatinine (CREA)], and coagulation function [prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT) and thrombin time (TT)]. The primary outcome of neonatal sepsis was 30-day mortality, and the primary outcome was obtained from medical records or by telephone.
Statistical analysis
All statistical analyses were conducted with SPSS 21.0 (SPSS, Inc., IA, USA). Continuous variables, shown as mean±standard deviation, were compared with t-test and analysis of variance (ANOVA). Categorical variables (numbers and percentages) were compared using the chi-square test. Univariate or multivariate analysis was utilized to identify independent risk factors for 30-day mortality. Patients were divided into two groups according to the primary outcome. The receiver operating characteristic (ROC) curve was drawn to check the performance of the model in predicting the primary events and confirmed the optimal cutoff value of the predictive model. All tests were two-sided, and p-values <0.05 were considered statistically significant.
RESULTS
Baseline characteristics
The basic information of patients is presented in Table 1. Of these patients, the 30-day mortality rate was 17.5%. There were 123 males and 72 females, with a median age of 3 days (ranging from 1 day to 28 days). Compared with the nonsurvivor group, the significant elevated levels of platelet and ALB and the significant declined levels of ALT, AST, UREA, PT, INR, and TT were found in the survivor group (all p<0.05). Beyond that, obvious difference was also found in the numbers of culture positive, the levels of hemoglobin, LDH, DB, and CREA between the two groups, although statistical significance was not reached (all p<0.10) (Table 1).
Independent predictors of 30-day mortality
To further select independent factors of 30-day mortality, we conducted univariate and multivariate analyses on these variables with p<0.1 (Table 1). After adjusted these factors (culture positive, hemoglobin, platelet, ALT, AST, LDH, DB, UREA, CREA, PT, INR, TT, ALB), hemoglobin>133 g/L (hazard ratio (HR): 0.351, 95% confidence interval (CI): 0.128-0.961, p=0.042) and PT >16.6 s (HR: 4.140, 95%CI: 1.523-11.260, p=0.005) were independent risk markers of 30-day mortality (Table 2). Based on these results, a predictive model was built as follows:
Logit p=1.421×PT-1.046×hemoglobin-2.155.
Performance of the predictive model in the prediction of 30-day mortality
Sensitivity and specificity were determined to compare the performance of the predictive model and independent predictors. Figure 1A shows the ROC curve of the predictive model; the predictive model had the highest area under the curve (AUC) (0.756, 95%CI 0.666-0.847, P<0.001). The calibration curve of the predictive model had demonstrated good agreement (Figure 1B). Details of the performance are shown in Supplementary Table 1.
Performance of the predictive model. (A) Receiver operating characteristic curves of factors for predicting mortality. (B) Calibration curves.
In addition, the patients were divided into two groups based on the predictive model. A comparison was made between the two groups; the results showed that the 30-day mortality rate was higher in the predictive model value>0.05588 groups than that in the predictive model value ≤ 0.05588 groups (24.3 vs. 3.40%).
DISCUSSION
In this study, we found a significant association among HB, PT, and the risk of 30-day mortality. Based on independent risk factors, we built a predictive model with good performance. In addition, we found that the 30-day mortality rate was higher in the predictive model value>0.05588 group than that in the predictive model value ≤ 0.05588 group.
Neonatal sepsis refers to a severe bloodstream infection that occurs in neonates. It is often accompanied by a characterized systemic inflammatory response syndrome1212 Jyoti A, Kumar S, Kumar Srivastava V, Kaushik S, Govind Singh S. Neonatal sepsis at point of care. Clin Chim Acta. 2021;521:45-58. https://doi.org/10.1016/j.cca.2021.06.021
https://doi.org/10.1016/j.cca.2021.06.02...
. Inflammation plays a vital role in the pathogenesis and progression of neonatal sepsis1313 Goto T, Hussein MH, Kato S, Daoud GA, Kato T, Kakita H, et al. Endothelin receptor antagonist attenuates inflammatory response and prolongs the survival time in a neonatal sepsis model. Intensive Care Med. 2010;36(12):2132-9. https://doi.org/10.1007/s00134-010-2040-0
https://doi.org/10.1007/s00134-010-2040-...
. During neonatal sepsis, the presence of pathogens triggers an immune response, leading to the release of various pro-inflammatory molecules such as cytokines, chemokines, and acute-phase reactants1414 Chen S, Kuang M, Qu Y, Huang S, Gong B, Lin S, et al. Expression of serum cytokines profile in neonatal sepsis. Infect Drug Resist. 2022;15:3437-45. https://doi.org/10.2147/IDR.S368772
https://doi.org/10.2147/IDR.S368772...
,1515 Machado JR, Soave DF, Silva MV, Menezes LB, Etchebehere RM, Monteiro ML, et al. Neonatal sepsis and inflammatory mediators. Mediators Inflamm. 2014;2014:269681. https://doi.org/10.1155/2014/269681
https://doi.org/10.1155/2014/269681...
. However, the overproduction of pro-inflammatory molecules can result in widespread tissue damage, organ dysfunction, and complications associated with sepsis1616 Liao W, Xiao H, He J, Huang L, Liao Y, Qin J, et al. Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis. Eur J Med Res. 2023;28(1):105. https://doi.org/10.1186/s40001-023-01061-2
https://doi.org/10.1186/s40001-023-01061...
.
Hemoglobin is a major component of red blood cells, and its measurement provides information about anemia and oxygenation status1717 Steinmeyer Z, Delpierre C, Soriano G, Steinmeyer A, Ysebaert L, Balardy L, et al. Hemoglobin concentration; a pathway to frailty. BMC Geriatr. 2020;20(1):202. https://doi.org/10.1186/s12877-020-01597-6
https://doi.org/10.1186/s12877-020-01597...
. In neonatal sepsis, the infection and inflammatory response can impact the hematopoietic system, potentially leading to the development of anemia1818 Kolesnichenko SI, Kadyrova IA, Lavrinenko AV, Zhumadilova ZA, Avdienko OV, Vinogradskaya YV, et al. Mortality risk factors of early neonatal sepsis during COVID-19 pandemic. Infect Drug Resist. 2022;15:6307-16. https://doi.org/10.2147/IDR.S390723
https://doi.org/10.2147/IDR.S390723...
. The release of inflammatory mediators and activation of inflammatory cells may suppress red blood cell production or promote their destruction, thereby reducing hemoglobin levels. Furthermore, sepsis can also cause systemic hemodynamic changes such as tissue hypoperfusion and circulatory disturbances, which can influence blood hemoglobin levels1919 Effenberger-Neidnicht K, Hartmann M. Mechanisms of hemolysis during sepsis. Inflammation. 2018;41(5):1569-81. https://doi.org/10.1007/s10753-018-0810-y
https://doi.org/10.1007/s10753-018-0810-...
. In line with prior studies, our study also confirmed that HB was an independent index. Therefore, monitoring hemoglobin levels in neonates with sepsis can provide valuable information about the severity of anemia, inflammatory response, and overall circulatory status. This aids clinicians in assessing the disease severity, guiding treatment strategies, and monitoring treatment effectiveness.
Prothrombin time, a test that measures the duration taken for the blood to clot, is an important indicator of coagulation function and can provide insights into the body's ability to form blood clots2020 Qiu Q, Li D, Chen Y, Song Y, Lou S, Zhou K, et al. Clinical features and prognostic risk prediction of adult hemophagocytic lymphohistiocytosis: a 9-year retrospective study. Ann Hematol. 2023;102(10):2671-82. https://doi.org/10.1007/s00277-023-05368-2
https://doi.org/10.1007/s00277-023-05368...
. In neonatal sepsis, the inflammatory response and activation of coagulation pathways can lead to alterations in the coagulation system2121 Ostrowski SR, Windeløv NA, Ibsen M, Haase N, Perner A, Johansson PI. Consecutive thrombelastography clot strength profiles in patients with severe sepsis and their association with 28-day mortality: a prospective study. J Crit Care. 2013;28(3):317.e1-11. https://doi.org/10.1016/j.jcrc.2012.09.003
https://doi.org/10.1016/j.jcrc.2012.09.0...
. Sepsis-induced changes in the levels of coagulation factors, platelets, and endothelial cells can affect the clotting process and prolong PT2222 Zeerleder S, Hack CE, Wuillemin WA. Disseminated intravascular coagulation in sepsis. Chest. 2005;128(4):2864-75. https://doi.org/10.1378/chest.128.4.2864
https://doi.org/10.1378/chest.128.4.2864...
,2323 Walsh TS, Stanworth SJ, Prescott RJ, Lee RJ, Watson DM, Wyncoll D, et al. Prevalence, management, and outcomes of critically ill patients with prothrombin time prolongation in United Kingdom intensive care units. Crit Care Med. 2010;38(10):1939-46. https://doi.org/10.1097/CCM.0b013e3181eb9d2b
https://doi.org/10.1097/CCM.0b013e3181eb...
. Additionally, disseminated intravascular coagulation, a severe complication associated with sepsis, can further disrupt the coagulation cascade and contribute to abnormal PT results2424 Iba T, Helms J, Connors JM, Levy JH. The pathophysiology, diagnosis, and management of sepsis-associated disseminated intravascular coagulation. J Intensive Care. 2023;11(1):24. https://doi.org/10.1186/s40560-023-00672-5
https://doi.org/10.1186/s40560-023-00672...
. By monitoring PT in neonates with sepsis, clinicians can gain insights into the coagulation status and identify potential clotting abnormalities. This information is crucial for guiding appropriate treatment strategies, such as the administration of blood products or anticoagulants, and improving patient outcomes. Our study also confirmed this.
For clinical application, it is important to make the assessment of risk factors as convenient as possible. In our study, HB and PT are prevalent in clinical practice and convenient to acquire. They were independent factors demonstrated by multivariate analysis and we built a simple, convincing, and readily available model with good performance. On subgroup analysis, the 30-day mortality rate was higher in the predictive model value>0.05588 groups than that in the predictive model value ≤ 0.05588 groups. Identifying high-risk patients may help clinicians improve the treatment efficacy and clinical outcome.
This study is limited by its retrospective nature and single-center data, which may cause selection bias. Second, only admission biomarkers were included in the present analyses, and it is possible that dynamic changes in biomarkers during the course of treatment might also influence outcomes in neonatal sepsis. Third, there were no test results for inflammatory factors, such as procalcitonin, and interleukin-6 (IL-6). Fourth, there are no external and internal cohorts. Thus, before clinical application, large, multicenter, prospective studies and validation cohort need to be conducted to determine the value of the predictive model.
CONCLUSION
Based on the clinical risk factors identified in this cohort, we established a model that can objectively and accurately predict individualized risk of 30-day mortality. The predictive model should help clinicians to improve individual treatment, make clinical decisions, and guide follow-up management strategies.
-
Funding:
none. -
STATEMENT OF ETHICS
The study was performed to conform with the Declaration of Helsinki and was approved by the Local Ethics Committee of the Hospital (2023-007).
AVAILABILITY OF DATA AND MATERIALS
The datasets are available from the corresponding author on reasonable request.
REFERENCES
-
1Molloy EJ, Wynn JL, Bliss J, Koenig JM, Keij FM, McGovern M, et al. Neonatal sepsis: need for consensus definition, collaboration and core outcomes. Pediatr Res. 2020;88(1):2-4. https://doi.org/10.1038/s41390-020-0850-5
» https://doi.org/10.1038/s41390-020-0850-5 -
2Ko MH, Chang HY, Li ST, Jim WT, Chi H, Hsu CH, et al. An 18-year retrospective study on the epidemiology of early-onset neonatal sepsis - emergence of uncommon pathogens. Pediatr Neonatol. 2021;62(5):491-8. https://doi.org/10.1016/j.pedneo.2021.02.005
» https://doi.org/10.1016/j.pedneo.2021.02.005 -
3Hofer N, Edlinger S, Resch B. Comparison of risk for early-onset sepsis in small-for-gestational-age neonates and appropriate-for-gestational-age neonates based on lower levels of white blood cell, neutrophil, and platelet counts. Pediatr Neonatol. 2014;55(4):323-5. https://doi.org/10.1016/j.pedneo.2013.12.006
» https://doi.org/10.1016/j.pedneo.2013.12.006 -
4Neal SR, Fitzgerald F, Chimhuya S, Heys M, Cortina-Borja M, Chimhini G. Diagnosing early-onset neonatal sepsis in low-resource settings: development of a multivariable prediction model. Arch Dis Child. 2023;108(8):608-15. https://doi.org/10.1136/archdischild-2022-325158
» https://doi.org/10.1136/archdischild-2022-325158 -
5Saini SS, Shrivastav AK, Sundaram V, Dutta S, Kumar P. Early blood pressure changes in neonatal sepsis and the risk of mortality. Indian J Pediatr. 2023;90(11):1096-102. https://doi.org/10.1007/s12098-023-04597-7
» https://doi.org/10.1007/s12098-023-04597-7 -
6Majigo M, Makupa J, Mwazyunga Z, Luoga A, Kisinga J, Mwamkoa B, et al. Bacterial aetiology of neonatal sepsis and antimicrobial resistance pattern at the regional referral hospital, Dar es Salam, Tanzania; a call to strengthening antibiotic stewardship program. Antibiotics (Basel). 2023;12(4):767. https://doi.org/10.3390/antibiotics12040767
» https://doi.org/10.3390/antibiotics12040767 -
7Russell NJ, Stöhr W, Plakkal N, Cook A, Berkley JA, Adhisivam B, et al. Patterns of antibiotic use, pathogens, and prediction of mortality in hospitalized neonates and young infants with sepsis: a global neonatal sepsis observational cohort study (NeoOBS). PLoS Med. 2023;20(6):e1004179. https://doi.org/10.1371/journal.pmed.1004179
» https://doi.org/10.1371/journal.pmed.1004179 -
8Chawla D. Blood pressure monitoring for predicting mortality in neonatal sepsis. Indian J Pediatr. 2023;90(11):1071-2. https://doi.org/10.1007/s12098-023-04802-7
» https://doi.org/10.1007/s12098-023-04802-7 -
9Li X, Li T, Dong G, Wei Y, Xu Z, Yang J. Clinical value of serum interleukin-18 in neonatal sepsis diagnosis and mortality prediction. J Inflamm Res. 2022;15:6923-30. https://doi.org/10.2147/JIR.S393506
» https://doi.org/10.2147/JIR.S393506 -
10Xia X, Wang Y, Xie M, Qiu S, Zhou J. Elevated neutrophil - to - monocyte ratio as a prognostic marker for poor outcomes in neonatal sepsis. Heliyon. 2022;8(10):e11181. https://doi.org/10.1016/j.heliyon.2022.e11181
» https://doi.org/10.1016/j.heliyon.2022.e11181 -
11Goldstein B, Giroir B, Randolph A. International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics. Pediatr Crit Care Med. 2005;6(1):2-8. https://doi.org/10.1097/01.PCC.0000149131.72248.E6
» https://doi.org/10.1097/01.PCC.0000149131.72248.E6 -
12Jyoti A, Kumar S, Kumar Srivastava V, Kaushik S, Govind Singh S. Neonatal sepsis at point of care. Clin Chim Acta. 2021;521:45-58. https://doi.org/10.1016/j.cca.2021.06.021
» https://doi.org/10.1016/j.cca.2021.06.021 -
13Goto T, Hussein MH, Kato S, Daoud GA, Kato T, Kakita H, et al. Endothelin receptor antagonist attenuates inflammatory response and prolongs the survival time in a neonatal sepsis model. Intensive Care Med. 2010;36(12):2132-9. https://doi.org/10.1007/s00134-010-2040-0
» https://doi.org/10.1007/s00134-010-2040-0 -
14Chen S, Kuang M, Qu Y, Huang S, Gong B, Lin S, et al. Expression of serum cytokines profile in neonatal sepsis. Infect Drug Resist. 2022;15:3437-45. https://doi.org/10.2147/IDR.S368772
» https://doi.org/10.2147/IDR.S368772 -
15Machado JR, Soave DF, Silva MV, Menezes LB, Etchebehere RM, Monteiro ML, et al. Neonatal sepsis and inflammatory mediators. Mediators Inflamm. 2014;2014:269681. https://doi.org/10.1155/2014/269681
» https://doi.org/10.1155/2014/269681 -
16Liao W, Xiao H, He J, Huang L, Liao Y, Qin J, et al. Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis. Eur J Med Res. 2023;28(1):105. https://doi.org/10.1186/s40001-023-01061-2
» https://doi.org/10.1186/s40001-023-01061-2 -
17Steinmeyer Z, Delpierre C, Soriano G, Steinmeyer A, Ysebaert L, Balardy L, et al. Hemoglobin concentration; a pathway to frailty. BMC Geriatr. 2020;20(1):202. https://doi.org/10.1186/s12877-020-01597-6
» https://doi.org/10.1186/s12877-020-01597-6 -
18Kolesnichenko SI, Kadyrova IA, Lavrinenko AV, Zhumadilova ZA, Avdienko OV, Vinogradskaya YV, et al. Mortality risk factors of early neonatal sepsis during COVID-19 pandemic. Infect Drug Resist. 2022;15:6307-16. https://doi.org/10.2147/IDR.S390723
» https://doi.org/10.2147/IDR.S390723 -
19Effenberger-Neidnicht K, Hartmann M. Mechanisms of hemolysis during sepsis. Inflammation. 2018;41(5):1569-81. https://doi.org/10.1007/s10753-018-0810-y
» https://doi.org/10.1007/s10753-018-0810-y -
20Qiu Q, Li D, Chen Y, Song Y, Lou S, Zhou K, et al. Clinical features and prognostic risk prediction of adult hemophagocytic lymphohistiocytosis: a 9-year retrospective study. Ann Hematol. 2023;102(10):2671-82. https://doi.org/10.1007/s00277-023-05368-2
» https://doi.org/10.1007/s00277-023-05368-2 -
21Ostrowski SR, Windeløv NA, Ibsen M, Haase N, Perner A, Johansson PI. Consecutive thrombelastography clot strength profiles in patients with severe sepsis and their association with 28-day mortality: a prospective study. J Crit Care. 2013;28(3):317.e1-11. https://doi.org/10.1016/j.jcrc.2012.09.003
» https://doi.org/10.1016/j.jcrc.2012.09.003 -
22Zeerleder S, Hack CE, Wuillemin WA. Disseminated intravascular coagulation in sepsis. Chest. 2005;128(4):2864-75. https://doi.org/10.1378/chest.128.4.2864
» https://doi.org/10.1378/chest.128.4.2864 -
23Walsh TS, Stanworth SJ, Prescott RJ, Lee RJ, Watson DM, Wyncoll D, et al. Prevalence, management, and outcomes of critically ill patients with prothrombin time prolongation in United Kingdom intensive care units. Crit Care Med. 2010;38(10):1939-46. https://doi.org/10.1097/CCM.0b013e3181eb9d2b
» https://doi.org/10.1097/CCM.0b013e3181eb9d2b -
24Iba T, Helms J, Connors JM, Levy JH. The pathophysiology, diagnosis, and management of sepsis-associated disseminated intravascular coagulation. J Intensive Care. 2023;11(1):24. https://doi.org/10.1186/s40560-023-00672-5
» https://doi.org/10.1186/s40560-023-00672-5
Publication Dates
-
Publication in this collection
16 Aug 2024 -
Date of issue
2024
History
-
Received
04 Mar 2024 -
Accepted
24 Mar 2024