In Search of an Ideal Protocol to Distinguish Risk for Serious Bacterial Infection in Febrile Young Infants.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

2 citing papers in PubMed.

1. Adding heart rate n-variability (HRnV) to clinical assessment potentially improves prediction of serious bacterial infections in young febrile infants at the emergency department: a prospective observational study.Annals of translational medicine · 2023
   Article
2. Using Machine Learning to Predict Invasive Bacterial Infections in Young Febrile Infants Visiting the Emergency Department.Journal of clinical medicine · 2021
   Article

Corrections and comments

• Comment on
  Declines in the Number of Lumbar Punctures Performed at United States Children's Hospitals, 2009-2019.2021
• Comment on
  Cost Analysis of Emergency Department Criteria for Evaluation of Febrile Infants Ages 29 to 90 Days.2021

Authors and funding

1 author.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

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