Pediatric Sepsis Biomarker Risk Model Biomarkers and Estimation of Myocardial Dysfunction in Pediatric Septic Shock

Diagnostic Validation of the Updated Pediatric Sepsis Biomarker Risk II for Acute Kidney Injury Prediction Model in Pediatric Septic Shock

OBJECTIVES

We previously derived the updated Pediatric Sepsis Biomarker Risk for Acute Kidney Injury (PERSEVERE-II AKI) prediction model, which had robust diagnostic test characteristics for severe AKI on day 3 (D3 severe AKI) of septic shock. We now sought to validate this model in an independent cohort of children to the one in which the model was developed.

DESIGN

A secondary analysis of a multicenter, prospective, observational study carried out from January 2019 to December 2022.

SETTING

Ten PICUs in the United States.

PATIENTS

Children with septic shock 1 week to 18 years old admitted to the PICU.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Seventy-nine of 363 patients (22%) had D3 severe AKI, defined as Kidney Disease Improving Global Outcomes stage 2 or higher. Patients were assigned a probability of D3 severe AKI using the PERSEVERE-II AKI model. The model predicted D3 severe AKI with an area under the receiver operating characteristic curve of 0.89 (95% CI, 0.85-0.93), sensitivity of 77% (95% CI, 66-86%), specificity of 88% (95% CI, 84-92%), positive predictive value of 65% (95% CI, 54-74%), and negative predictive value of 93% (95% CI, 89-96%). These data represent an increase in post-test probability of D3 severe AKI with a positive test from 22% to 65%, and a prevalence threshold of 28%. On multivariable regression, the PERSEVERE-II AKI prediction model demonstrated greater adjusted odds ratio (aOR) for D3 severe AKI (aOR, 11.2; 95% CI, 4.9-25.3) and lesser aOR for failure of D3 renal recovery from early AKI (aOR, 0.31; 95% CI, 0.13-0.69).

CONCLUSIONS

The PERSEVERE-II AKI model demonstrates consistently robust performance for prediction of new or persistent D3 severe AKI in children with septic shock. A major limitation is that actual D3 severe AKI prevalence is below the prevalence threshold for the test, and thus future work should focus on evaluating use in enriched populations.

Characteristics and Risk Factors for Pediatric Sepsis

OBJECTIVE

Sepsis is considered a major cause of health loss in children and had high mortality and morbidity. Currently, there is no reliable model for predicting the prognosis of pediatric patients with sepsis. This study aimed to analyze the clinical characteristics of sepsis in children and assess the risk factors associated with poor prognosis in pediatric sepsis patients to identify timely interventions and improve their outcomes.

METHODS

This study analyzed the clinical indicators and laboratory results of septic patients hospitalized in the Pediatric Intensive Care Unit of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China, from January 1, 2019, to December 31, 2021. Risk factors for sepsis were identified by logistic regression analyses.

RESULTS

A total of 355 children with sepsis were enrolled, with 333 children (93.8%) in the good prognosis group, and 22 children (6.2%) in the poor prognosis group. Among them, there were 255 patients (71.8%) in the sepsis group, and 100 patients (28.2%) in the severe sepsis group. The length of hospital stay in the poor prognosis group was longer than that in the good prognosis group (P<0.01). The levels of interleukin 1β (IL-1β) in the poor prognosis group were higher than those in the good prognosis group (P>0.05), and the platelet (PLT), albumin (ALB), and hemoglobin (Hb) levels were lower in the poor prognosis group (P<0.01). The IL-8 levels in the severe sepsis group were higher than those in the sepsis group (P<0.05). Multiple logistic regression analysis suggested that lower Hb levels, ALB levels, peak PLT counts, and higher IL-1β levels were independent risk factors for poor prognosis in children with sepsis.

CONCLUSION

Lower Hb, ALB, and PLT counts and elevated IL-1β are independent risk factors for poor prognosis in children with sepsis.

Multilevel omics for the discovery of biomarkers in pediatric sepsis

Severe sepsis causes organ dysfunction and continues to be the leading reason for pediatric death worldwide. Early recognition of sepsis could substantially promote precision treatment and reduce the risk of pediatric death. The host cellular response to infection during sepsis between adults and pediatrics could be significantly different. A growing body of studies focused on finding markers in pediatric sepsis in recent years using multi-omics approaches. This narrative review summarized the progress in studying pediatric sepsis biomarkers from genome, transcript, protein, and metabolite levels according to the omics technique that has been applied for biomarker screening. It is most likely not a single biomarker could work for precision diagnosis of sepsis, but a panel of markers and probably a combination of markers detected at multi-levels. Importantly, we emphasize the importance of group distinction of infectious agents in sepsis patients for biomarker identification, because the host response to infection of bacteria, virus, or fungus could be substantially different and thus the results of biomarker screening. Further studies on the investigation of sepsis biomarkers that were caused by a specific group of infectious agents should be encouraged in the future, which will better improve the clinical execution of personalized medicine for pediatric sepsis.

Integrated PERSEVERE and endothelial biomarker risk model predicts death and persistent MODS in pediatric septic shock: a secondary analysis of a prospective observational study

Background

Multiple organ dysfunction syndrome (MODS) is a critical driver of sepsis morbidity and mortality in children. Early identification of those at risk of death and persistent organ dysfunctions is necessary to enrich patients for future trials of sepsis therapeutics. Here, we sought to integrate endothelial and PERSEVERE biomarkers to estimate the composite risk of death or organ dysfunctions on day 7 of septic shock.

Methods

We measured endothelial dysfunction markers from day 1 serum among those with existing PERSEVERE data. TreeNet® classification model was derived incorporating 22 clinical and biological variables to estimate risk. Based on relative variable importance, a simplified 6-biomarker model was developed thereafter.

Results

Among 502 patients, 49 patients died before day 7 and 124 patients had persistence of MODS on day 7 of septic shock. Area under the receiver operator characteristic curve (AUROC) for the newly derived PERSEVEREnce model to predict death or day 7 MODS was 0.93 (0.91–0.95) with a summary AUROC of 0.80 (0.76–0.84) upon tenfold cross-validation. The simplified model, based on IL-8, HSP70, ICAM-1, Angpt2/Tie2, Angpt2/Angpt1, and Thrombomodulin, performed similarly. Interaction between variables—ICAM-1 with IL-8 and Thrombomodulin with Angpt2/Angpt1—contributed to the models’ predictive capabilities. Model performance varied when estimating risk of individual organ dysfunctions with AUROCS ranging from 0.91 to 0.97 and 0.68 to 0.89 in training and test sets, respectively.

Conclusions

The newly derived PERSEVEREnce biomarker model reliably estimates risk of death or persistent organ dysfunctions on day 7 of septic shock. If validated, this tool can be used for prognostic enrichment in future pediatric trials of sepsis therapeutics.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04070-5.