Project description:BACKGROUND:Health-workers in developing countries rely on clinical algorithms, such as the Integrated Management of Childhood Illnesses (IMCI), for the management of patients, including diagnosis of serious bacterial infections (SBI). The diagnostic accuracy of IMCI in detecting children with SBI is unknown. Prediction rules and guidelines for SBI from well-resourced countries at outpatient level may help to improve current guidelines; however, their diagnostic performance has not been evaluated in resource-limited countries, where clinical conditions, access to care, and diagnostic capacity differ. The aim of this study was to estimate the diagnostic accuracy of existing prediction rules and clinical guidelines in identifying children with SBI in a cohort of febrile children attending outpatient health facilities in Tanzania. METHODS:Structured literature review to identify available prediction rules and guidelines aimed at detecting SBI and retrospective, external validation on a dataset containing 1005 febrile Tanzanian children with acute infections. The reference standard, SBI, was established based on rigorous clinical and microbiological criteria. RESULTS:Four prediction rules and five guidelines, including IMCI, could be validated. All examined rules and guidelines had insufficient diagnostic accuracy for ruling-in or ruling-out SBI with positive and negative likelihood ratios ranging from 1.04-1.87 to 0.47-0.92, respectively. IMCI had a sensitivity of 36.7% (95% CI 29.4-44.6%) at a specificity of 70.3% (67.1-73.4%). Rules that use a combination of clinical and laboratory testing had better performance compared to rules and guidelines using only clinical and or laboratory elements. CONCLUSIONS:Currently applied guidelines for managing children with febrile illness have insufficient diagnostic accuracy in detecting children with SBI. Revised clinical algorithms including simple point-of-care tests with improved accuracy for detecting SBI targeting in tropical resource-poor settings are needed. They should undergo careful external validation against clinical outcome before implementation, given the inherent limitations of gold standards for SBI.

Project description:Viral infections are among the most common causes for fever without an apparent source (FWS) in young children; however, many febrile children are treated with antibiotics despite the absence of bacterial infection. Adenovirus, human herpesvirus 6 (HHV-6) and enterovirus are detected in children with FWS more often than other viral species. Virus and bacteria interact with pattern recognition receptors in circulating blood leukocytes and trigger specific host transcriptional programs that mediate immune response, and unique transcriptional signatures may be ascertained to discriminate between viral and bacterial causes for children with FWS. Microarray analyses were conducted on peripheral blood samples obtained from 51 pediatric patients with confirmed adenovirus, human herpesvirus 6 (HHV-6), enterovirus or bacterial infection. Whole blood transcriptional profiles could clearly distinguish febrile children from healthy controls, and febrile children with viral infections from afebrile children carrying the same virus. Molecular pathways regulating host immune response were the most affected in febrile children with infection. Pattern recognition programs were prominently activated in all febrile children with infection, while differential activation of transcriptional programs was observed among viral species. Interferon signaling pathway was uniquely activated in children with febrile viral infection, while a different set of pathways was uniquely activated in children with bacterial infection. Transcriptional signatures were identified and classified febrile children with viral or bacterial infection with 87% overall accuracy, an improvement from the current clinical practice of deducing from white blood cell (WBC) count status. Similar degree of accuracy was observed when we validated the signature probes on data sets from an independent study with different microarray platforms. The current study confirms the clinical utility of blood transcriptional analysis, suggests the composition of transcriptional signatures which can be used to ascertain the infectious etiology of febrile young children without an apparent source, thus limit the overuse of antibiotics on febrile children presenting with this common clinical complaint.

Project description:Viral infections are among the most common causes for fever without an apparent source (FWS) in young children; however, many febrile children are treated with antibiotics despite the absence of bacterial infection. Adenovirus, human herpesvirus 6 (HHV-6) and enterovirus are detected in children with FWS more often than other viral species. Virus and bacteria interact with pattern recognition receptors in circulating blood leukocytes and trigger specific host transcriptional programs that mediate immune response, and unique transcriptional signatures may be ascertained to discriminate between viral and bacterial causes for children with FWS. Microarray analyses were conducted on peripheral blood samples obtained from 51 pediatric patients with confirmed adenovirus, human herpesvirus 6 (HHV-6), enterovirus or bacterial infection. Whole blood transcriptional profiles could clearly distinguish febrile children from healthy controls, and febrile children with viral infections from afebrile children carrying the same virus. Molecular pathways regulating host immune response were the most affected in febrile children with infection. Pattern recognition programs were prominently activated in all febrile children with infection, while differential activation of transcriptional programs was observed among viral species. Interferon signaling pathway was uniquely activated in children with febrile viral infection, while a different set of pathways was uniquely activated in children with bacterial infection. Transcriptional signatures were identified and classified febrile children with viral or bacterial infection with 87% overall accuracy, an improvement from the current clinical practice of deducing from white blood cell (WBC) count status. Similar degree of accuracy was observed when we validated the signature probes on data sets from an independent study with different microarray platforms. The current study confirms the clinical utility of blood transcriptional analysis, suggests the composition of transcriptional signatures which can be used to ascertain the infectious etiology of febrile young children without an apparent source, thus limit the overuse of antibiotics on febrile children presenting with this common clinical complaint. Total RNA samples extracted from whole blood of young children were processed for hybridization onto Illumina Human-HT12 version 4 beadchips, and differential expression of the transcripts was analyzed between sick children with either viral or bacterial infection and healthy children.

Project description:ImportanceDelirium at admission is associated with increased hospital morbidity and mortality, but it may be missed in up to 70% of cases. Use of a predictive algorithm in an electronic medical record (EMR) system could provide critical information to target assessment of those with delirium at admission.ObjectivesTo develop and assess a prediction rule for delirium using 2 populations of veterans and compare this rule with previously confirmed rules.Design, setting, and participantsIn a diagnostic study, randomly selected EMRs of hospitalized veterans from the Veterans Affairs (VA) External Peer Review Program at 118 VA medical centers with inpatient facilities were reviewed for delirium risk factors associated with the National Institute for Health and Clinical Excellence (NICE) delirium rule in a derivation cohort (October 1, 2012, to September 30, 2013) and a confirmation cohort (October 1, 2013, to March 31, 2014). Delirium within 24 hours of admission was identified using key word terms. A total of 39 377 veterans 65 years or older who were admitted to a VA medical center for congestive heart failure, acute coronary syndrome, community-acquired pneumonia, and chronic obstructive pulmonary disease were included in the study.ExposureThe EMR calculated delirium risk.Main outcomes and measuresDelirium at admission as identified by trained nurse reviewers was the main outcome measure. Random forest methods were used to identify accurate risk factors for prevalent delirium. A prediction rule for prevalent delirium was developed, and its diagnostic accuracy was tested in the confirmation cohort. This consolidated NICE rule was compared with previously confirmed scoring algorithms (electronic NICE and Pendlebury NICE).ResultsA total of 27?625 patients were included in the derivation cohort (28 118 [92.2%] male; mean [SD] age, 75.95 [8.61] years) and 11 752 in the confirmation cohort (11 536 [98.2%] male; mean [SD] age, 75.43 [8.55] years). Delirium at admission was identified in 2343 patients (8.5%) in the derivation cohort and 882 patients (7.0%) in the confirmation cohort. Modeling techniques identified cognitive impairment, infection, sodium level, and age of 80 years or older as the dominant risk factors. The consolidated NICE rule (area under the receiver operating characteristic [AUROC] curve, 0.91; 95% CI, 0.91-0.92; P?<?.001) had significantly higher discriminatory function than the eNICE rule (AUROC curve, 0.81; 95% CI, 0.80-0.82; P?<?.001) or Pendlebury NICE rule (AUROC curve, 0.87; 95% CI, 0.86-0.88; P?<?.001). These findings were confirmed in the confirmation cohort.Conclusions and relevanceThis analysis identified preexisting cognitive impairment, infection, sodium level, and age of 80 years or older as delirium screening targets. Use of this algorithm in an EMR system could direct clinical assessment efforts to patients with delirium at admission.

Project description:BackgroundLeft ventricular hypertrophy (LVH) is the main marker of HMOD in children and young people (CYP). We aimed to assess the prevalence of LVH and its determinants in CYP with primary hypertension (PH).MethodsA meta-analysis of prevalence was performed. A literature search of articles reporting LVH in CYP with PH was conducted in Medline, Embase, and Cochrane databases. Studies with a primary focus on CYP (up to 21 years) with PH were included. Meta-regression was used to analyze factors explaining observed heterogeneity.ResultsThe search yielded a total of 2,200 articles, 153 of those underwent full-text review, and 47 reports were included. The reports evaluated 51 study cohorts including 5,622 individuals, 73% male subjects, and a mean age of 13.6 years. LVH was defined as left ventricle mass index (LVMI) ≥ 95th percentile in 22 (47%), fixed cut-off ≥38.6 g/m2.7 in eight (17%), sex-specific fixed cut-off values in six (13%), and miscellaneously in others. The overall prevalence of LVH was 30.5% (95% CI 27.2-33.9), while heterogeneity was high (I 2 = 84%). Subgroup analysis including 1,393 individuals (76% male subjects, mean age 14.7 years) from pediatric hypertension specialty clinics and LVH defined as LVMI ≥95th percentile only (19 study cohorts from 18 studies), reported prevalence of LVH at 29.9% (95% CI 23.9 to 36.3), and high heterogeneity (I 2 = 84%). Two studies involving patients identified through community screening (n = 1,234) reported lower LVH prevalence (21.5%). In the meta-regression, only body mass index (BMI) z-score was significantly associated with LVH prevalence (estimate 0.23, 95% CI 0.08-0.39, p = 0.004) and accounted for 41% of observed heterogeneity, but not age, male percentage, BMI, or waist circumference z-score. The predominant LVH phenotype was eccentric LVH in patients from specialty clinics (prevalence of 22% in seven studies with 779 participants) and one community screening study reported the predominance of concentric LVH (12%).ConclusionLeft ventricular hypertrophy is evident in at least one-fifth of children and young adults with PH and in nearly a third of those referred to specialty clinics with a predominant eccentric LVH pattern in the latter. Increased BMI is the most significant risk association for LVH in hypertensive youth.

Dataset Information

Systematic review and meta-analysis of the discriminatory performance of risk prediction rules in febrile neutropaenic episodes in children and young people.

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Systematic review and meta-analysis of the discriminatory performance of risk prediction rules in febrile neutropaenic episodes in children and young people.

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