Children with malignancies and septic shock - an attempt to understand the risk factors

Abstract Objectives: To explain the high mortality of septic shock in children with cancer. Methods: A retrospective cohort from 2016 to 2020, of children aged 0 to 18 years, and septic shock. Results: The authors included 139 patients. Acute lymphocytic leukemia was the most frequent diagnosis (16.5%), and Gram-negative bacteria were the most frequent blood culture isolates (22.3%). There were 57 deaths in ICU (41%), 10 in the first 24 hours of shock (early death). A LASSO model with variables: neutropenia (coefficient 0.215), respiratory (0.81), hematological (1.41), and neurological (0.72) dysfunctions, age (-0.002) and solid tumor recurrence (0.34) generated AUC = 0.79 for the early death outcome. Survivors had significant differences in the PRISM-IV score (mean ± SD 10.9 ± 6.2 in the survivors, 14.1 ± 6.5 in the deceased, p = 0.004), and in the mean number of organ dysfunctions (3.2 ± 1.1 in the survivors, 3.8 ± 6.5 in the deceased, p < 0.001). A positive fluid balance in the first 24 hours of sepsis between 2% and 6% of body weight showed a reduction effect on the probability of death in ICU (hazard ratio 0.47, 95% CI 0.24-0.92, p = 0.027). The recurrence of any cancer was a predictor of in-hospital death, regardless of severity. Conclusions: Recurrence of any cancer is an important risk of sepsis-related death. A positive fluid balance between 20 and 60 mL/kg or 2% and 6% of body weight in the first 24 hours after the onset of sepsis is related to lower mortality.

Children with malignancies and septic shock - an attempt to understand the risk factors.

OBJECTIVES: To explain the high mortality of septic shock in children with cancer. METHODS: A retrospective cohort from 2016 to 2020, of children aged 0 to 18 years, and septic shock. RESULTS: The authors included 139 patients. Acute lymphocytic leukemia was the most frequent diagnosis (16.5%), and Gram-negative bacteria were the most frequent blood culture isolates (22.3%). There were 57 deaths in ICU (41%), 10 in the first 24 hours of shock (early death). A LASSO model with variables: neutropenia (coefficient 0.215), respiratory (0.81), hematological (1.41), and neurological (0.72) dysfunctions, age (-0.002) and solid tumor recurrence (0.34) generated AUC = 0.79 for the early death outcome. Survivors had significant differences in the PRISM-IV score (mean ± SD 10.9 ± 6.2 in the survivors, 14.1 ± 6.5 in the deceased, p = 0.004), and in the mean number of organ dysfunctions (3.2 ± 1.1 in the survivors, 3.8 ± 6.5 in the deceased, p < 0.001). A positive fluid balance in the first 24 hours of sepsis between 2% and 6% of body weight showed a reduction effect on the probability of death in ICU (hazard ratio 0.47, 95% CI 0.24-0.92, p = 0.027). The recurrence of any cancer was a predictor of in-hospital death, regardless of severity. CONCLUSIONS: Recurrence of any cancer is an important risk of sepsis-related death. A positive fluid balance between 20 and 60 mL/kg or 2% and 6% of body weight in the first 24 hours after the onset of sepsis is related to lower mortality.

PRISM 4-C: An Adapted PRISM IV Algorithm for Children With Cancer.

We evaluated the performance of PRISM IV for pediatric cancer patients, and adapted and calibrated the algorithm to calculate mortality probabilities for these patients. An ambidirectional cohort was used, and data were collected from March 2017 prospectively to April 2019, and retrospectively to November 2014. The derivation set for model building contained 500 patients, and a validation set of 503 patients. Risk variables for hospital death were tested in logistic regression models encompassing PRISM IV components. There were 128 deaths (12.7%), being 65 deaths in the validation set. In the validation set, the PRISM IV algorithm had an area under the receiver operating characteristic curve of 0.89, with P=0.13 by Hosmer-Lemeshow test, and predicted 33 of the 65 deaths for a standardized mortality rate of 1.8 (95% confidence interval, 1.4-2.9; P<0.001 by Mid-P test). Our modified algorithm had an area under the receiver operating characteristic curve of 0.93, with P=0.3 by Hosmer-Lemeshow test and an standardized mortality rate of 1.02 (95% confidence interval, 0.79-1.19). The modified algorithm predicted 63.7 of 65 deaths. The PRISM IV algorithm was a poor predictor of mortality in children with cancer. The modified algorithm improved the predictive performance.

Vancomycin Therapeutic Targets and Nephrotoxicity in Critically Ill Children With Cancer.

To obtain pharmacokinetic and pharmacodynamic data for vancomycin in a cohort of critically ill pediatric oncology patients, we analyzed 256 measurements of vancomycin concentrations in 94 patients. Variables were tested as possible risk factors for vancomycin-related nephrotoxicity or death for 28 days. We found the following: mean vancomycin trough serum concentration, 15.6 ± 12.4 µg/mL; mean vancomycin clearance, 0.16 ± 0.098 L/h/kg; and mean vancomycin distribution volume, 1.04 ± 0.11 L/kg. Only 13.6% of serum trough level measurements were between 15 and 20 µg/mL. The trough levels showed a strong correlation with the AUC (area under the curve of serum concentrations vs. time over 24 h to the minimum inhibitory concentration ratio), with a 94% positive predictive value for AUC/MIC ≥ 400, but only for MIC=1. The doses that are currently used (60 mg/kg/d) attained the therapeutic target (AUC/MIC ≥ 400) in only 56% of measurements, considering MIC=1. A serum trough level of ≥ 20 µg/mL was an independent risk for nephrotoxicity (P = 0.0008; odds ratio = 17.83). Vancomycin-related nephrotoxicity was a predictor of death for up to 28 days (P = 0.003, odds ratio = 7.68). Currently administered doses of vancomycin do not reach the therapeutic target for critical cancer patients, particularly if staphylococci isolates have a MIC>1.

Adverse drug events in a paediatric intensive care unit: a prospective cohort.

OBJECTIVES: To describe adverse drug events (ADEs) in children under intensive care, identify risk factors and tools that can detect ADEs early, and the impact on length of stay (LOS). DESIGN: A prospective observational study. SETTING: Paediatric intensive care unit of a tertiary care teaching hospital. PATIENTS: 239 patients with a mean age of 67.5 months representing 1818 days of hospitalisation in intensive care unit. INTERVENTIONS: Active search of charts and electronic patient records using triggers. The statistical analysis involved linear and logistic regression. MEASUREMENTS AND MAIN RESULTS: The average LOS was 7.6 days. There were 110 proven, probable and possible ADEs in 84 patients (35.1%). We observed 138 instances of triggers. The major classes of drugs associated with events were: antibiotics (n=41), diuretics (n=24), antiseizures (n=23), sedatives and analgesics (n=17) and steroids (n=18). The number of drugs administered was most related to the occurrence of ADEs and also to the LOS (p<0.001). The occurrence of an ADE may result in an increase in the LOS by 1.5 days per event, but this was not statistically significant in this sample. Patients aged less than 48 months also proved to be at a significant risk for ADEs, with an OR of 1.84 (95% CI 1.07 to 3.15, p=0.025). The number of drugs administered also correlated with the number of ADEs (p<0.0001). The chance of having at least one ADE increased linearly as the patient was administered more drugs. CONCLUSIONS: The use of multiple drugs as well as lower patient age favours the occurrence of ADEs. The active search described here provides a systematic approach to this problem.