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Retrospective study of prognostic factors in pediatric invasive pneumococcal disease.

ABSTRACT: Streptococcus pneumoniae remains the leading causative pathogen in pediatric pneumonia and bacteremia throughout the world. The invasive pneumococcal disease (IPD) is known as isolation of S. pneumoniae from a normally sterile site (e.g., blood, cerebrospinal fluid, synovial fluid, pericardial fluid, pleural fluid, or peritoneal fluid). The aim of this study is to survey the clinical manifestations and laboratory results of IPD and identify the prognostic factors of mortality. From January 2001 to December 2006, a retrospective review of chart was performed in a teaching hospital in Taipei. The hospitalized pediatric patients with the diagnosis of pneumonia, arthritis, infectious endocarditis, meningitis or sepsis were recruited. Among them, 50 patients were pneumococcal infections proved by positive culture results or antigen tests. Clinical manifestations, laboratory data and hospitalization courses were analyzed. The median age was 3.5-year-old and there were 30 male patients (60%). Eight patients (16%) had underlying disease such as leukemia or congenital heart disease. Hemolytic uremic syndrome (HUS) was observed in ten patients and extracorporeal membrane oxygenation (ECMO) was performed in three patients. Leukocytosis, elevated C-reactive protein and AST level were noted in most of the patients. The overall mortality rate was 10%. We found that leukopenia, thrombocytopenia and high CRP level were significant predictors for mortality. In conclusion, S. pneumoniae remains an important health threat worldwide and IPD is life-threatening with high mortality rate. We found leukopenia, thrombocytopenia, and high CRP levels to be associated with mortality in pediatric IPD, and these factors are worthy of special attention at admission. Although we failed to identify a statistically significant prognostic factor in multivariate analysis due to relatively small sample size, we suggest an aggressive antibiotic treatment in patients with these factors at admission. Further large-scale studies are warranted.

SUBMITTER: Chiu NC

PROVIDER: S-EPMC5270593 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Retrospective study of prognostic factors in pediatric invasive pneumococcal disease.

Chiu Nan-Chang NC Chi Hsin H Peng Chun-Chih CC Chang Hung-Yang HY Huang Daniel Tsung-Ning DT Chang Lung L Lei Wei-Te WT Lin Chien-Yu CY

PeerJ 20170125

<i>Streptococcus pneumoniae</i> remains the leading causative pathogen in pediatric pneumonia and bacteremia throughout the world. The invasive pneumococcal disease (IPD) is known as isolation of <i>S. pneumoniae</i> from a normally sterile site (e.g., blood, cerebrospinal fluid, synovial fluid, pericardial fluid, pleural fluid, or peritoneal fluid). The aim of this study is to survey the clinical manifestations and laboratory results of IPD and identify the prognostic factors of mortality. From ...[more]

PMID: 28149700

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Project description:BackgroundInvasive candidiasis is a common cancer-related complication with a high fatality rate. If patients with a high risk of dying in the hospital are identified early and accurately, physicians can make better clinical judgments. However, epidemiological analyses and mortality prediction models of cancer patients with invasive candidiasis remain limited.MethodA set of 40 potential risk factors was acquired in a sample of 258 patients with both invasive candidiasis and cancer. To begin, risk factors for Candida albicans vs. non-Candida albicans infections and persistent vs. nonpersistent Candida infections were analysed using classic statistical methods. Then, we applied three machine learning models (random forest, logistic regression, and support vector machine) to identify prognostic indicators related to mortality. Prediction performance of different models was assessed by precision, recall, F1 score, accuracy, and AUC.ResultsOf the 258 patients both with invasive candidiasis and cancer included in the analysis. The median age of patients was 62 years, and 95 (36.82%) patients were older than 65 years, of which 178 (66.28%) were male. And 186 (72.1%) patients underwent surgery 2 weeks before data collection, 100 (39.1%) patients stayed in ICU during hospitalisation, 99 (38.4%) patients had bacterial blood infection, 85 (32.9%) patients had persistent invasive candidiasis, and 41 (15.9%) patients died within 30 days. The usage of drainage catheter and prolonged length of hospitalisation are the dominant risk factors for non-Candida albicans infections and persistent Candida infections, respectively. Risk factors, such as septic shock, history of surgery within the past 2 weeks, usage of drainage tubes, length of stay in ICU, total parenteral nutrition, serum creatinine level, fungal antigen, stay in ICU during hospitalisation, and total bilirubin level, were significant predictors of death. The RF model outperformed the LR and SVM models. Precision, recall, F1 score, accuracy, and AUC for RF were 64.29%, 75.63%, 69.23%, 89.61%, and 91.28%.ConclusionsIn this study, the machine learning-based models accurately predicted the prognosis of cancer and invasive candidiasis patients. The algorithm could be used to help clinicians in high-risk patients' early intervention.

Dataset Information

Retrospective study of prognostic factors in pediatric invasive pneumococcal disease.

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Retrospective study of prognostic factors in pediatric invasive pneumococcal disease.

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