Dataset Information

A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections.

ABSTRACT:

Importance

In young febrile infants, serious bacterial infections (SBIs), including urinary tract infections, bacteremia, and meningitis, may lead to dangerous complications. However, lumbar punctures and hospitalizations involve risks and costs. Clinical prediction rules using biomarkers beyond the white blood cell count (WBC) may accurately identify febrile infants at low risk for SBIs.

Objective

To derive and validate a prediction rule to identify febrile infants 60 days and younger at low risk for SBIs.

Design, setting, and participants

Prospective, observational study between March 2011 and May 2013 at 26 emergency departments. Convenience sample of previously healthy febrile infants 60 days and younger who were evaluated for SBIs. Data were analyzed between April 2014 and April 2018.

Exposures

Clinical and laboratory data (blood and urine) including patient demographics, fever height and duration, clinical appearance, WBC, absolute neutrophil count (ANC), serum procalcitonin, and urinalysis. We derived and validated a prediction rule based on these variables using binary recursive partitioning analysis.

Main outcomes and measures

Serious bacterial infection, defined as urinary tract infection, bacteremia, or bacterial meningitis.

Results

We derived the prediction rule on a random sample of 908 infants and validated it on 913 infants (mean age was 36 days, 765 were girls [42%], 781 were white and non-Hispanic [43%], 366 were black [20%], and 535 were Hispanic [29%]). Serious bacterial infections were present in 170 of 1821 infants (9.3%), including 26 (1.4%) with bacteremia, 151 (8.3%) with urinary tract infections, and 10 (0.5%) with bacterial meningitis; 16 (0.9%) had concurrent SBIs. The prediction rule identified infants at low risk of SBI using a negative urinalysis result, an ANC of 4090/µL or less (to convert to ×109 per liter, multiply by 0.001), and serum procalcitonin of 1.71 ng/mL or less. In the validation cohort, the rule sensitivity was 97.7% (95% CI, 91.3-99.6), specificity was 60.0% (95% CI, 56.6-63.3), negative predictive value was 99.6% (95% CI, 98.4-99.9), and negative likelihood ratio was 0.04 (95% CI, 0.01-0.15). One infant with bacteremia and 2 infants with urinary tract infections were misclassified. No patients with bacterial meningitis were missed by the rule. The rule performance was nearly identical when the outcome was restricted to bacteremia and/or bacterial meningitis, missing the same infant with bacteremia.

Conclusions and relevance

We derived and validated an accurate prediction rule to identify febrile infants 60 days and younger at low risk for SBIs using the urinalysis, ANC, and procalcitonin levels. Once further validated on an independent cohort, clinical application of the rule has the potential to decrease unnecessary lumbar punctures, antibiotic administration, and hospitalizations.

SUBMITTER: Kuppermann N

PROVIDER: S-EPMC6450281 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections.

Kuppermann Nathan N Dayan Peter S PS Levine Deborah A DA Vitale Melissa M Tzimenatos Leah L Tunik Michael G MG Saunders Mary M Ruddy Richard M RM Roosevelt Genie G Rogers Alexander J AJ Powell Elizabeth C EC Nigrovic Lise E LE Muenzer Jared J Linakis James G JG Grisanti Kathleen K Jaffe David M DM Hoyle John D JD Greenberg Richard R Gattu Rajender R Cruz Andrea T AT Crain Ellen F EF Cohen Daniel M DM Brayer Anne A Borgialli Dominic D Bonsu Bema B Browne Lorin L Blumberg Stephen S Bennett Jonathan E JE Atabaki Shireen M SM Anders Jennifer J Alpern Elizabeth R ER Miller Benjamin B Casper T Charles TC Dean J Michael JM Ramilo Octavio O Mahajan Prashant P

JAMA pediatrics 20190401 4

<h4>Importance</h4>In young febrile infants, serious bacterial infections (SBIs), including urinary tract infections, bacteremia, and meningitis, may lead to dangerous complications. However, lumbar punctures and hospitalizations involve risks and costs. Clinical prediction rules using biomarkers beyond the white blood cell count (WBC) may accurately identify febrile infants at low risk for SBIs.<h4>Objective</h4>To derive and validate a prediction rule to identify febrile infants 60 days and yo ...[more]

PMID: 30776077

Similar Datasets

Project description:ImportanceClinicians often risk stratify young febrile infants for invasive bacterial infections (IBIs), defined as bacteremia and/or bacterial meningitis, using complete blood cell count parameters.ObjectiveTo estimate the accuracy of individual complete blood cell count parameters to identify febrile infants with IBIs.Design, setting, and participantsPlanned secondary analysis of a prospective observational cohort study comprising 26 emergency departments in the Pediatric Emergency Care Applied Research Network from 2008 to 2013. We included febrile (≥38°C), previously healthy, full-term infants younger than 60 days for whom blood cultures were obtained. All infants had either cerebrospinal fluid cultures or 7-day follow-up.Main outcomes and measuresWe tested the accuracy of the white blood cell count, absolute neutrophil count, and platelet count at commonly used thresholds for IBIs. We determined optimal thresholds using receiver operating characteristic curves.ResultsOf 4313 enrolled infants, 1340 (31%; 95% CI, 30% to 32%) were aged 0 to 28 days, 2412 were boys (56%), and 2471 were white (57%). Ninety-seven (2.2%; 95% CI, 1.8% to 2.7%) had IBIs. Sensitivities were low for common complete blood cell count parameter thresholds: white blood cell count less than 5000/µL, 10% (95% CI, 4% to 16%) (to convert to 109 per liter, multiply by 0.001); white blood cell count ≥15 000/µL, 27% (95% CI, 18% to 36%); absolute neutrophil count ≥10 000/µL, 18% (95% CI, 10% to 25%) (to convert to × 109 per liter, multiply by 0.001); and platelets <100 × 103/µL, 7% (95% CI, 2% to 12%) (to convert to × 109 per liter, multiply by 1). Optimal thresholds for white blood cell count (11 600/µL), absolute neutrophil count (4100/µL), and platelet count (362 × 103/µL) were identified in models that had areas under the receiver operating characteristic curves of 0.57 (95% CI, 0.50-0.63), 0.70 (95% CI, 0.64-0.76), and 0.61 (95% CI, 0.55-0.67), respectively.Conclusions and relevanceNo complete blood cell count parameter at commonly used or optimal thresholds identified febrile infants 60 days or younger with IBIs with high accuracy. Better diagnostic tools are needed to risk stratify young febrile infants for IBIs.

Project description:Young febrile infants are at substantial risk of serious bacterial infections; however, the current culture-based diagnosis has limitations. Analysis of host expression patterns ("RNA biosignatures") in response to infections may provide an alternative diagnostic approach.To assess whether RNA biosignatures can distinguish febrile infants aged 60 days or younger with and without serious bacterial infections.Prospective observational study involving a convenience sample of febrile infants 60 days or younger evaluated for fever (temperature >38° C) in 22 emergency departments from December 2008 to December 2010 who underwent laboratory evaluations including blood cultures. A random sample of infants with and without bacterial infections was selected for RNA biosignature analysis. Afebrile healthy infants served as controls. Blood samples were collected for cultures and RNA biosignatures. Bioinformatics tools were applied to define RNA biosignatures to classify febrile infants by infection type.RNA biosignatures compared with cultures for discriminating febrile infants with and without bacterial infections and infants with bacteremia from those without bacterial infections.Bacterial infection confirmed by culture. Performance of RNA biosignatures was compared with routine laboratory screening tests and Yale Observation Scale (YOS) scores.Of 1883 febrile infants (median age, 37 days; 55.7% boys), RNA biosignatures were measured in 279 randomly selected infants (89 with bacterial infections-including 32 with bacteremia and 15 with urinary tract infections-and 190 without bacterial infections), and 19 afebrile healthy infants. Sixty-six classifier genes were identified that distinguished infants with and without bacterial infections in the test set with 87% (95% CI, 73%-95%) sensitivity and 89% (95% CI, 81%-93%) specificity. Ten classifier genes distinguished infants with bacteremia from those without bacterial infections in the test set with 94% (95% CI, 70%-100%) sensitivity and 95% (95% CI, 88%-98%) specificity. The incremental C statistic for the RNA biosignatures over the YOS score was 0.37 (95% CI, 0.30-0.43).In this preliminary study, RNA biosignatures were defined to distinguish febrile infants aged 60 days or younger with vs without bacterial infections. Further research with larger populations is needed to refine and validate the estimates of test accuracy and to assess the clinical utility of RNA biosignatures in practice.

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:ImportanceFever in the first months of life remains one of the most common pediatric problems. Urinary tract infections are the most frequent serious bacterial infections in this population. All published guidelines and quality initiatives for febrile young infants recommend lumbar puncture (LP) and cerebrospinal fluid (CSF) testing on the basis of a positive urinalysis result to exclude bacterial meningitis as a cause. For well infants older than 28 days with an abnormal urinalysis result, LP remains controversial.ObjectiveTo assess the prevalence of bacterial meningitis among febrile infants 29 to 60 days of age with a positive urinalysis result to evaluate whether LP is routinely required.Data sourcesMEDLINE and Embase were searched for articles published from January 1, 2000, to July 25, 2018, with deliberate limitation to recent studies. Before analysis, the search was repeated (October 6, 2019) to ensure that new studies were included.Study selectionStudies that reported on healthy, full-term, well-appearing febrile infants 29 to 60 days of age for whom patient-level data could be ascertained for urinalysis results and meningitis status were included.Data extraction and synthesisData were extracted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and used the Newcastle-Ottawa Scale to assess bias. Pooled prevalences and odds ratios (ORs) were estimated using random-effect models.Main outcomes and measuresThe primary outcome was the prevalence of culture-proven bacterial meningitis among infants with positive urinalysis results. The secondary outcome was the prevalence of bacterial meningitis, defined by CSF testing or suggestive history at clinical follow-up.ResultsThe parent search yielded 3227 records; 48 studies were included (17 distinct data sets of 25 374 infants). The prevalence of culture-proven meningitis was 0.44% (95% CI, 0.25%-0.78%) among 2703 infants with positive urinalysis results compared with 0.50% (95% CI, 0.33%-0.76%) among 10 032 infants with negative urinalysis results (OR, 0.74; 95% CI, 0.39-1.38). The prevalence of bacterial meningitis was 0.25% (95% CI, 0.14%-0.45%) among 4737 infants with meningitis status ascertained by CSF testing or clinical follow-up and 0.28% (95% CI, 0.21%-0.36%) among 20 637 infants with positive and negative urinalysis results (OR, 0.89; 95% CI, 0.48-1.68).Conclusions and relevanceIn this systematic review and meta-analysis, the prevalence of bacterial meningitis in well-appearing febrile infants 29 to 60 days of age with positive urinalysis results ranged from 0.25% to 0.44% and was not higher than that in infants with negative urinalysis results. These results suggest that for these infants, the decision to use LP should not be guided by urinalysis results alone.

Project description:ObjectiveTo derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department.DesignProspective observational diagnostic study.SettingThree paediatric emergency care units: two in the Netherlands and one in the United Kingdom.ParticipantsChildren with fever, aged 1 month to 15 years, at three paediatric emergency care units: Rotterdam (n=1750) and the Hague (n=967), the Netherlands, and Coventry (n=487), United Kingdom. A prediction model was constructed using multivariable polytomous logistic regression analysis and included the predefined predictor variables age, duration of fever, tachycardia, temperature, tachypnoea, ill appearance, chest wall retractions, prolonged capillary refill time (>3 seconds), oxygen saturation <94%, and C reactive protein.Main outcome measuresPneumonia, other serious bacterial infections (SBIs, including septicaemia/meningitis, urinary tract infections, and others), and no SBIs.ResultsOxygen saturation <94% and presence of tachypnoea were important predictors of pneumonia. A raised C reactive protein level predicted the presence of both pneumonia and other SBIs, whereas chest wall retractions and oxygen saturation <94% were useful to rule out the presence of other SBIs. Discriminative ability (C statistic) to predict pneumonia was 0.81 (95% confidence interval 0.73 to 0.88); for other SBIs this was even better: 0.86 (0.79 to 0.92). Risk thresholds of 10% or more were useful to identify children with serious bacterial infections; risk thresholds less than 2.5% were useful to rule out the presence of serious bacterial infections. External validation showed good discrimination for the prediction of pneumonia (0.81, 0.69 to 0.93); discriminative ability for the prediction of other SBIs was lower (0.69, 0.53 to 0.86).ConclusionA validated prediction model, including clinical signs, symptoms, and C reactive protein level, was useful for estimating the likelihood of pneumonia and other SBIs in children with fever, such as septicaemia/meningitis and urinary tract infections.

Dataset Information

A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Conclusions and relevance

Publications

A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections.

Similar Datasets

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