Abstract
The objective of this study was to explore correlations between sepsis-associated coagulopathy (SAC) in pediatric septic shock and clinical outcomes. This was a retrospective cohort study of all children admitted to a single, academic pediatric intensive care unit with septic shock over 6 years. The prevalence of SAC was 93.5% with 61% being severe. Those with severe SAC were more likely to have a positive blood culture and have longer median duration of ventilation. All observed mortalities occurred in the severe SAC and indeterminate SAC groups. SAC is highly prevalent in pediatric septic shock and may predict important outcomes.
Keywords: septic shock, disseminated intravascular coagulation, PICU
Introduction
Pediatric severe sepsis and septic shock are significant global health problems with an estimated international prevalence of 8.2 and 25% in-hospital mortality. 1 Smaller studies in the United States reported a similar prevalence, but a lower mortality rate of 8.9 to 12%. 2 3 Importantly, the mortality rate has been down-trending in recent decades despite increasing prevalence worldwide. 1 2 3 4 The rise in prevalence may be related to expanding patient populations with chronic medical conditions, an increase in antibiotic resistant organisms, and increasing recognition through surveillance initiatives. 1 4 5 6 Severe sepsis and septic shock will remain a critical global health problem for the foreseeable future.
Early recognition and treatment are vital in patients with septic shock. In 2001, early goal-directed therapy (EGDT) became the cornerstone of severe sepsis and septic shock management. 7 Adult studies have since called some aspects of EGDT delivery into question. 8 9 10 While the ideal way in which EGDT should be delivered can be debated, there is evidence that early recognition and bundled resuscitation improve mortality for both adults and children. 11 12 13 14 Recognition bundles were recommended in the most recent guidelines for the management of neonates and children with septic shock. 15 To be effective, recognition bundles should be highly sensitive as well as specific and identify those at highest risk of decompensation. Identifying patient factors that predict worse outcomes during early stages of shock is important for the development of these recognition bundles.
Septic shock is commonly associated with a wide spectrum of coagulation abnormalities with the most severe form being disseminated intravascular coagulation (DIC). This is the result of a complex interplay between proinflammatory cytokines, procoagulant factors, anticoagulant factors, and endothelial dysfunction. 16 The incidence of sepsis-associated coagulation dysfunction and DIC in children is not clear, but has been estimated at 50 to 70% and 35%, respectively in adults. 17 DIC is a manifestation of the failure of normal hemostatic mechanisms and can result in additional organ dysfunction secondary to infarction from microthrombi leading, in turn, to increased mortality. 18 19 Despite the development of two validated scoring systems for the diagnosis of DIC in adults, diagnostic criteria in both adults and children lack consensus. 20 21 22 Recognizing these limitations, a recent adult study sought to develop a simplified set of criteria for the diagnosis of sepsis-associated coagulopathy (SAC) using only the platelet count and international normalized ratio (INR) value. The INR was developed to monitor vitamin-K antagonist therapy. In this study, it was used as a surrogate measure for the degree of coagulopathy. Using this scheme, they showed that SAC severity was an independent predictor of in-hospital mortality. 23 There are no similar studies in the pediatric septic shock population.
We aimed to develop and retrospectively apply a similar SAC classification scheme to children admitted to our pediatric intensive care unit (PICU) with septic shock. Our first objective was to evaluate the prevalence of SAC in children with a diagnosis of septic shock. Our second objective was to explore for possible correlations between SAC severity and selected clinical factors as well as outcome measures. If correlations exist, then SAC severity may have a role in identifying patients with sepsis who are at higher risk of poorer outcomes and might benefit from closer monitoring, earlier initiation of bundled care, and earlier transfer to an intensive care unit (ICU).
Materials and Methods
This was an unmatched, retrospective cohort study of children admitted to a single, 24-bed, tertiary care, academic PICU with the diagnosis of septic shock between January 1, 2012 and December 31, 2017. This was the time period for which data was available in our electronic medical record. Children admitted with the diagnosis of septic shock were identified from the Virtual PICU systems, LLC (VPS) database at our site. The VPS database is a quality improvement based, pediatric critical care registry of over a million PICU cases from over 130 participating hospitals systems. VPS is co-owned by the Children's Hospital Association and Children's Hospital of Los Angeles. Two critical care physicians then reviewed the electronic medical records of all patients identified by this data query.
Included patients were ≤18 years old with the diagnosis of septic shock. The diagnosis of septic shock generated from the VPS query was confirmed through chart review by the physician reviewers. The operational definition of septic shock for this study was attending physician documentation that the patient had septic shock. We did not consider any other clinical or treatment parameters for this definition. All attending dictations for a patient's hospitalization were reviewed to identify cases where the initial diagnosis of septic shock was disproven. Exclusion criteria were any order for limitation in care (e.g., do not intubate or do not resuscitate) or transfer to another ICU (e.g., Neonatal Intensive Care Unit) or health care facility. The study protocol was submitted and approved by our Institutional Review Board and the need for informed consent was waived.
The exposure variable was SAC severity. SAC categories were developed a priori with adaptations from those previously published—the mild and moderate categories were merged into a new nonsevere group. 23 The classification scheme is shown in Table 1 . The categories were: No SAC, Nonsevere SAC, Severe SAC, and Indeterminate SAC. Patients in whom multiple values were obtained, the highest INR value and lowest platelet count obtained in the first 48 hours (starting at 12 am on the day of PICU admission) were used for classification purposes. Patients for whom an INR and/or platelet count were not available from the first 48 hours of PICU admission were classified as having “Indeterminate SAC.” Within the SAC classification scheme, patients were not further subcategorized as medical or surgical due to the limited sample size.
Table 1. Sepsis-associated coagulopathy classification scheme.
| SAC category | Criteria |
|---|---|
| No SAC | INR <1.2 AND platelet count >150 × 10 3 /μL |
| Nonsevere SAC | INR 1.2–1.5 AND/OR platelet count 81–150 × 10 3 /μL |
| Severe SAC | INR ≥1.6 AND/OR platelet count ≤80 × 10 3 /μL |
Abbreviations: INR, international normalized ratio; SAC, sepsis-associated coagulopathy.
Demographic data were collected for each patient including age, gender, race, and co-morbidities. Clinical data collected included pediatric index of morality 2 (PIM-2) scores, blood culture results, and primary infection source. Potential confounding variables were age, PIM-2 score, and presence of a hematologic/oncologic comorbidity. Exploratory outcome variables included: requirement and duration of mechanical ventilation; requirement, maximum number concurrently administered, and duration of vasopressors and/or inotropes; need for renal replacement therapy; PICU length of stay; PICU mortality; and in-hospital mortality.
Comorbidities included chronic diagnoses present at admission (e.g., leukemia) and were classified according the primary organ system impacted. These were obtained from the admission history and physical note. Positive blood culture results were grouped as follows: gram positive, gram negative, fungal, or mixed. The primary source of infection was determined by the physician reviewers utilizing clinical data (e.g., culture data, polymerase chain reaction testing, etc.) and the attending or fellow documentation in the electronic medical record. The source was classified by the primary organ system affected, central line associated, or not specified.
Patients on chronic mechanical ventilation were excluded from the mechanical ventilation outcome analysis. Mechanical ventilation duration was obtained from the respiratory flowsheet while vasopressor/inotrope and renal replacement therapy requirement data were obtained from the intake/output flowsheets in the medical record. For vasopressor/inotropes, we included any continuous infusion provided for hemodynamic support including epinephrine, norepinephrine, vasopressin, phenylephrine, dopamine, and milrinone. We collected the number of vasopressors administered concurrently as well and the total number of hours on vasopressors. We did not collect data regarding the exact number of hours of exposure to each vasopressor. Length of stay and mortality data were reported in the VPS data query and confirmed during chart review.
Statistical Methods
Descriptive statistics were presented using means, medians, standard deviations and ranges where appropriate for continuous variables while using counts and percentages for categorical variables. To compare the characteristics and outcomes between severe and nonsevere SAC, we utilized the Kruskal–Wallis test for continuous variables and chi-square (or Fisher's exact test for small samples) for categorical variables. We utilized the generalized linear regression to model the continuous and binary outcomes adjusting for the confounding variables of age and PIM-2 score. For the continuous outcomes where normality assumption of the distribution was violated, we applied an appropriate Box-Cox transformation. p -Values <0.05 were considered statistically significant. No adjustments for multiple testing were performed as these analyses were exploratory and hypothesis generating. These methods were utilized for the primary data analysis as well as a post hoc analysis that excluded patients with hematologic/oncologic co-morbidities. Data were analyzed utilizing SAS v 9.4 (Cary; North Carolina, United States). As this was an exploratory study, we did not perform a calculation of required sample size to detect differences in outcome variables.
Sources and Mitigation of Bias
There are two types of bias that are inherent to a retrospective cohort study—information bias and selection bias. We acknowledge that these sources of bias may exist, and we have tried to mitigate them where possible. During the chart review, careful attention was made to avoid any missing data that would worsen the amount of information bias present in our results. One such measure included reviewing all attending physician documentation rather than the admission and discharge note only. Original omission of data in the medical record could not be mitigated or quantified. Selection bias could be less reliably mitigated in the absence of a prospective cohort study design. Given the exploratory nature of our study and the small sample size, multivariate analysis was not performed other than adjusting for the potential confounding variables of age and PIM-2 score. Another attempt to limit selection bias was the post-hoc data analysis that excluded the patients with a hematologic/oncologic comorbidity.
Results
The VPS query yielded 119 patient encounters with a diagnosis of septic shock. Of those, 11 encounters were excluded. The STROBE flow chart for this study is shown in Fig. 1 . Excluding 31 patients with indeterminate SAC, SAC was present in 93.5% of the patients with septic shock in our cohort. Of those with complete data for SAC categorization, 61% were severe and 39% were nonsevere.
Fig. 1.
Patient selection flowchart and sepsis-associated coagulopathy (SAC) classification.
The descriptive characteristics of the severe and nonsevere SAC cohorts are presented in Table 2 . Based on our a priori SAC definitions, there was an expected and significant difference in the mean platelet count and INR between the nonsevere and severe SAC groups. In addition, significantly more children with severe SAC had a positive blood culture and a line-associated source. Exploratory outcome variables are presented in Table 3 . There were significant differences between children with nonsevere and severe SAC for mechanical ventilation duration. Two patients in the severe SAC group were removed from this outcome measure due to chronic mechanical ventilation support. The significant differences between severe and nonsevere groups in aforementioned variables were maintained even after adjusting for confounding variables of age and PIM-2 Score. There was no statistically significant difference between the nonsevere and severe SAC cohorts for mechanical ventilation requirement, vasopressor requirement, and renal replacement therapy requirement. A post-hoc analysis of the cohort was performed excluding the ten patients with an underlying oncologic co-morbidity. There was no change in statistically significant outcome variables previously described for the nonsevere and severe SAC groups ( Table 4 ). None of the included patients in this study were on extracorporeal membrane oxygenation support or anticoagulation therapy during the first 48 hours of PICU admission.
Table 2. Characteristics of patients with sepsis-associated coagulopathy (SAC).
| Nonsevere SAC | Severe SAC | p -Value | |
|---|---|---|---|
| Patients (%) | 25 (34.7) | 47 (65.3) | |
| Male (%) | 10 (40) | 22 (46) | 0.6258 |
| Mean age in months (SD) | 106.3 (84.2) | 107.4 (75.9) | 0.8084 |
| Mean PIM-2 risk of mortality score (SD) | 3.87 (4.25) | 6.66 (7.49) | 0.0942 |
| Race | |||
| Caucasian (%) | 17 (68) | 32 (68) | 0.7431 |
| African American (%) | 6 (24) | 13 (27.7) | |
| Other (%) | 2 (8) | 2 (7.4) | |
| Co-morbidities | |||
| None (%) | 13 (52) | 10 (21.3) | 0.1695 |
| Oncologic (%) | 1 (4) | 9 (19.1) | |
| Neurologic (%) | 4 (16) | 9 (19.1) | |
| Pulmonary (%) | 2 (8) | 5 (10.6) | |
| Other (%) | 5 (20) | 14 (29.8) | |
| Mean platelet count (10 3 ; SD) | 206.7 (100.2) | 78.2 (94.2) | < 0.0001 |
| Mean INR (SD) | 1.3 (0.17) | 2.0 (0.84) | < 0.0001 |
| Infectious source | |||
| Central line associated (%) | 0 (0) | 10 (21.3) | 0.0389 |
| Pulmonary (%) | 6 (24) | 10 (21.3) | |
| Central nervous system (%) | 2 (8) | 3 (6.4) | |
| Genitourinary (%) | 4 (16) | 4 (8.5) | |
| Abdominal (%) | 2 (8) | 4 (8.5) | |
| Skin/soft tissue (%) | 4 (16) | 2 (4.3) | |
| Ear, nose, throat (%) | 2 (8) | 0 (0) | |
| Not specified (%) | 5 (20) | 14 (29.8) | |
| Blood culture result | |||
| Positive (%) | 6 (24) | 27 (57.5) | 0.0122 |
| Negative (%) | 19 (76) | 20 (42.6) | |
| Organism isolated (% of positive cultures) | |||
| Gram positive | 4 (66.7) | 11 (40.7) | 0.1466 |
| Gram negative | 1 (16.7) | 13 (48.2) | |
| Mixed gram positive/negative | 1 (16.7) | 0 (0) | |
| Fungal | 0 (0) | 3 (11.1) | |
Abbreviations: INR, international normalized ratio; PIM, pediatric index of morality; SAC, sepsis-associated coagulopathy; SD, standard deviation.
Table 3. Exploratory outcomes by sepsis-associated coagulopathy (SAC) category.
| Nonsevere SAC | Severe SAC | p -Value | |
|---|---|---|---|
| Median hours mechanical ventilation duration (Range, N ) | 108.8 (10–614.3, 25) | 198.5 (12.5–316.5, 45) | 0.0115 |
| Median maximum number of concurrent vasopressors (Range, N ) | 1 (0–3, 25) | 2 (0–4, 47) | 0.1034 |
| Median hours vasopressor duration (Range, N ) | 35.3 (1–75, 19) | 44.2 (3–1,392, 36) | 0.0796 |
| In-hospital mortality, N (%) | 0 (0) | 6 (12.8) | 0.0858 |
| ICU mortality, N (%) | 0 (0) | 5 (10.6) | 0.1559 |
| Median PICU length of stay in days (Range, N ) | 4.5 (0.3–6.6, 25) | 8.4 (0.5–12.3, 47) | 0.1130 |
Abbreviations: ICU, intensive care unit; PICU, pediatric intensive care unit; SAC, sepsis-associated coagulopathy.
Table 4. Selected outcomes by sepsis-associated coagulopathy (SAC) category—excluding patients with oncologic co-morbidities.
| Nonsevere SAC | Severe SAC | p -Value | |
|---|---|---|---|
| Median hours mechanical ventilation duration (range, N ) | 111 (29–140.6, 24) | 228.5 (12.5–1,464, 36) | 0.016 |
| Median maximum number of concurrent vasopressors (range) | 1 (0–3, 24) | 2 (0–4, 36) | 0.130 |
| Median hours vasopressor duration (range, N ) | 35.5 (1–35.5, 24) | 107.1 (3–1,392, 34) | 0.058 |
| In-hospital mortality, N (%) | 0 (0) | 6 (12.8) | 0.073 |
| ICU mortality, N (%) | 0 (0) | 5 (10.6) | 0.147 |
| Median PICU length of stay in days (range, N ) | 4.8 (0.3–31.9, 24) | 9.9 (0.5–61.5, 36) | 0.092 |
Abbreviations: ICU, intensive care unit; PICU, pediatric intensive care unit.
All of the observed mortalities occurred in the severe SAC group with the exception of two patients in the indeterminate SAC group. Both patients in the indeterminate group died prior to ICU discharge—one after a PICU length of stay of 51 days and another after approximately 4 hours. Neither patient had an INR obtained in the first 48 hours or a positive blood culture. Their lowest platelet counts in the first 48 hours of PICU admission were 283,000 and 30,000, respectively. Both patients had a pulmonary source of infection and required mechanical ventilation as well as vasopressor support.
Discussion
The results of our study suggest that SAC is highly prevalent in pediatric septic shock. Our findings also suggest that SAC severity may be correlated to bacteremia and certain outcomes starting early in the PICU course. Hemodynamic decompensation is a late finding in children with septic shock due to their ability to increase systemic vascular resistance and augment cardiac output by increasing their heart rate. 24 Therefore, it is essential to identify patients early in the development of severe sepsis and septic shock before clinical deterioration occurs. We propose that the platelet count and INR may help identify those children with sepsis who are at high risk for poorer outcomes including, but not limited to mortality.
Patients with severe SAC had longer average mechanical ventilation duration than those with nonsevere SAC. Acute respiratory distress syndrome and DIC frequently coexist, which may explain this relationship. 25 The difference in mechanical ventilation duration between the two SAC severity groups was marked at 3.74 days (nonsevere SAC—4.53 days vs. severe SAC—8.27 days). With prolonged mechanical ventilation comes risks such as nosocomial infections, ventilator-induced lung injury, sedative medication dependence, and neuromuscular weakness. 26 SAC categorization may allow the PICU team to plan management strategies that anticipate and mitigate these risks as well as manage family and patient expectations.
The majority (82%) of patients with a positive blood culture had severe SAC and this difference was statistically significant between the severe and nonsevere groups. This suggests that the presence of bacteremia may correlate with the development of SAC. This is supported by presentations of some infections such as meningococcemia which is associated with one of the most severe manifestations of DIC, purpura fulminans. 27 In this series, the majority of patients with gram-negative bacteremia had severe SAC although the numbers are too small to draw any conclusions from this. The endotoxins produced by many gram-negative bacteria are known to play an important role in the initiation of thrombin generation, a central step to DIC development. 28 The difference in blood culture result category between the two groups did not reach statistical significance, but there was a trend toward significance.
While the difference in the number of concurrently administered vasopressors and vasopressor duration did not reach statistical significance, there was still a clinically relevant difference. In our cohort, patients with nonsevere SAC required only one vasopressor at any given time for a median of 35.3 hours. However, in those with severe SAC, the median number of concurrent vasopressors was two for a median of 44.2 hours. With multiple vasopressors, a patient is more likely to have a central line and/or arterial line placed. This not only exposes them to the immediate risk of an invasive procedure, but also to the long-term risks of health care-acquired conditions such as thrombosis and central line-associated blood stream infections. Prolonged duration and increased number of vasopressors is also likely to prolong the time to initiation of enteral feeding at some centers. Lastly, children on multiple vasopressors are often managed with continuous neuromuscular blockade, increasing the risk of critical illness myopathy.
Mortality is often regarded as the most important outcome measure. We found that there was no statistically significant difference for both in-hospital and PICU mortality. However, all observed mortalities occurred in the severe SAC group with the exception of two patients who died in the indeterminate SAC group. No patients died with nonsevere SAC or no SAC. One prior study of 62 children with DIC did not detect a correlation between mortality and the severity of many laboratory values used to diagnose DIC. 25 However, this study did not include the INR. Furthermore, that study, much like ours, was limited by a small sample size. It is often difficult to demonstrate a mortality difference in pediatric studies due to the intrinsically low mortality rate. In the setting of a small sample size, a low p -value (0.0858) for a correlation between SAC severity and in-hospital mortality suggests that a larger sample size could reveal a significant result. Assuming a power of 85%, to detect the 11% difference in mortality rate between the severe SAC group and the nonsevere SAC group suggested by our findings, a sample size of 211 in each group would be needed.
Strengths and Limitations
One of the strengths of this study is the simplicity of the SAC classification system. It is an easily available screening tool for patients with septic shock. If future investigations confirm that it can be used as a prognostic tool, it can be easily applied in the clinical arena as a part of bundled care. An additional strength is the post-hoc analysis removing patients with oncologic co-morbidities, an important confounding variable.
The primary limitations of this study are its retrospective design and sample size. As previously discussed, the study design introduces the possibility of selection and information bias. It would have been helpful also to know what blood products were administered and for what clinical indications. A retrospective study does not allow us to obtain that information reliably. Second, it is possible that the prevalence of SAC was overestimated in our study due to the large number of patients with indeterminate SAC ( N = 31, 28.7%). Another source of selection bias may have existed with the sickest patients being more likely to have platelet counts and INR assessed, leading to an overestimation of SAC incidence. Conversely, it is possible that the incidence of SAC was underestimated as 76% of all patients with SAC received a blood product transfusion. An additional limitation is that we did not collect data regarding the indication for transfusions. This could have altered the most abnormal INR and platelet count obtained in the first 48 hours. Finally, the external validity of our findings is likely limited to similar tertiary care centers. The prevalence of SAC and its severity are likely to be impacted by the average illness severity and underlying co-morbidities of the cohort cared for at that center. A prospective, multicenter study designed to capture all patients admitted to the ICU with sepsis will allow us to obtain details that are more granular with larger number of patients.
Future Directions
Our findings should be considered hypothesis generating. Prospective, multicenter studies are needed to confirm the prevalence of SAC in children with septic shock as well as the correlation of SAC severity with outcomes. If SAC severity can be shown to correlate with outcomes, prospective evaluation of its utility in stratifying patients by severity may be beneficial. The platelet count and INR change throughout the development and resolution of septic shock. It would be valuable to determine whether changes in the platelet count and INR over time have any prognostic value. Lastly, there is a need to evaluate the performance of SAC classification scheme separately in medical and surgical PICU patients.
Conclusion
A simple scheme utilizing the platelet count and INR to classify SAC severity for PICU patients within 48 hours of admission may predict important outcomes such as blood culture positivity and mechanical ventilation duration. Additional studies are needed to confirm its prognostic utility for these outcomes and for other significant outcomes, primarily mortality.
Funding Statement
Funding None.
Conflict of Interest None declared.
Note
This study was presented as an oral abstract presentation at the 2018 Society of Critical Care Medicine Congress and published in electronic abstract form only following that meeting.
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