Characteristics of pediatric recurrent acute mastoiditis: A case-control study.

BACKGROUND: Data on pediatric recurrent acute mastoiditis are lacking, despite its morbidity and clinical significance. Our aim was to describe the incidence, characteristics, and associated factors of recurrent mastoiditis in hospitalized children. METHODS: Using a case-control design, analyzing electronic data of hospitalized children with acute mastoiditis between June 2011 and December 2018, children with recurrent mastoiditis were compared to children with a single episode at the time of hospitalization. Recurrent episodes of mastoiditis were compared to the first episodes. Recurrent acute mastoiditis was defined as recurring mastoiditis ≥4-weeks after a completely resolved event. RESULTS: Of 347 children hospitalized with acute mastoiditis, 22 (6.3%) had recurrent mastoiditis; the median interval between episodes was 3 months (range: 1-36). The mean ± SD age was 2.3 ± 2.25 years. A comparison of first episodes in recurring cases to single episodes by univariate and multivariate analysis, showed no differences in the pre-admission management or in the isolated pathogens; however, a history of atopic dermatitis and percutaneous abscess drainage were more frequent in first episodes of recurring cases (27.3% vs. 1.2%, p < 0.001, and 27.3% vs. 10.0%, p = 0.026, respectively). The second episode of acute mastoiditis was characterized by a milder clinical course and shorter durations from symptoms to hospitalization, intravenous antibiotic therapy, and length of hospital stay. Linear regression showed that an increased interval from symptoms to hospitalization significantly increased length of hospital stay (regression coefficient of 0.215 [95% CI: 0.114-0.317], p < 0.001). CONCLUSIONS: Recurrent episodes of mastoiditis were clinically milder, with shorter length of hospital stay compared to first episodes, possibly because of early admission.

Hyperlactatemia in children following brain tumor resection: prevalence, associated factors, and clinical significance.

PURPOSE: Hyperlactatemia is associated with worse outcome among critically ill patients. The prevalence of hyperlactatemia in children following craniotomy for intracranial tumor resection is unknown. This study was designed to assess the prevalence, associated factors, and significance of postoperative hyperlactatemia in this context. METHODS: A retrospective study was conducted at an intensive care unit of a tertiary, pediatric medical center. Children younger than 18 years admitted following craniotomy for brain tumor resection between October 2004 and November 2019 were included. RESULTS: Overall, 222 elective craniotomies performed in 178 patients were analyzed. The mean age ± SD was 8.5 ± 5.5 years. All but two patients survived to discharge. All were hemodynamically stable. Early hyperlactatemia, defined as at least one blood lactate level ≥ 2.0 mmol/L during the first 24 h into admission, presented following 74% of the craniotomies; lactate normalized within a mean ± SD of 11 ± 6.1 h. The fluid balance per body weight at 12 h and 24 h into the intensive care unit admission was similar in children with and without hyperlactatemia [7.0 ± 17.6 vs 3.5 ± 16.4 ml/kg, p = 0.23 and 4.0 ± 27.2 vs 4.6 ± 29.4 ml/kg, p = 0.96; respectively]. Hyperlactatemia was associated with higher maximal blood glucose, older age, and a pathological diagnosis of glioma. Intensive care unit length of stay was similar following craniotomies with and without hyperlactatemia (p = 0.57). CONCLUSIONS: Hyperlactatemia was common in children following craniotomy for brain tumor resection. It was not associated with hemodynamic impairment or with a longer length of stay.

Fusobacterium necrophorum as an Emerging Pathogen of Acute Mastoiditis.

BACKGROUND: Recent reports have reported an increase in the incidence of acute mastoiditis because of Fusobacterium necrophorum. However, the crude incidence and the specific clinical and laboratory characteristics of F. necrophorum mastoiditis in children have not been described. Our aim was to describe these features to identify high-risk patients. METHODS: The electronic medical records of all children with acute mastoiditis at a tertiary medical center between July 2011 and December 2015 were analyzed. Using a stepwise logistic regression to identify independent risk factors for F. necrophorum, we formulated a predictive model. RESULTS: F. necrophorum was identified in 13% (19/149) of mastoiditis cases with an identifiable agent. Its incidence increased 7-fold from 2.8% in 2012 to 20.4% in 2015 (P = 0.02). F. necrophorum infection had unique clinical, laboratory and prognostic features. The vast majority had complications and underwent surgical intervention. The predictive model used 4 parameters to define high-risk patients for F. necrophorum infection at admission: females, winter/spring season, prior antibiotic treatment and a C-reactive protein value >20 mg/dL (area under receiver operating characteristic curve 0.929). CONCLUSIONS: Clinicians should be aware of the increasing incidence of F. necrophorum mastoiditis and consider anaerobic cultures and specific anaerobic coverage in high-risk patients.

Prediction of Maximal Heart Rate in Children and Adolescents.

OBJECTIVE: To identify a method to predict the maximal heart rate (MHR) in children and adolescents, as available prediction equations developed for adults have a low accuracy in children. We hypothesized that MHR may be influenced by resting heart rate, anthropometric factors, or fitness level. DESIGN: Cross-sectional study. SETTING: Sports medicine center in primary care. PARTICIPANTS: Data from 627 treadmill maximal exercise tests performed by 433 pediatric athletes (age 13.7 ± 2.1 years, 70% males) were analyzed. INDEPENDENT VARIABLES: Age, sex, sport type, stature, body mass, BMI, body fat, fitness level, resting, and MHR were recorded. MAIN OUTCOME MEASURES: To develop a prediction equation for MHR in youth, using stepwise multivariate linear regression and linear mixed model. To determine correlations between existing prediction equations and pediatric MHR. RESULTS: Observed MHR was 197 ± 8.6 b·min. Regression analysis revealed that resting heart rate, fitness, body mass, and fat percent were predictors of MHR (R = 0.25, P < 0.001), whereas age was not. Resting heart rate explained 15.6% of MHR variance, body mass added 5.7%, fat percent added 2.4%, and fitness added 1.2%. Existing adult equations had low correlations with observed MHR in children and adolescents (r = -0.03-0.34). CONCLUSIONS: A new equation to predict MHR in children and adolescents was developed, but was found to have low predictive ability, a finding similar to adult equations applied to children. CLINICAL RELEVANCE: Considering the narrow range of MHR in youth, we propose using 197 b·min as the mean MHR in children and adolescents, with 180 b·min the minimal threshold value (-2 standard deviations).