Use of Simple Heuristics to Target Macrolide Prescription in Children With Community-Acquired Pneumonia

Abstract

In children with CAP, simple clinical decision rules identify patients at risk for M pneumoniae infection. At present US macrolide resistance rates among invasive S pneumoniae isolates, both rules increase the chance of prescribing effective first-line antibiotics compared with general macrolide administration.

Mycoplasma pneumoniae and Streptococcus pneumoniae caused different microbial structure and correlation network in lung microbiota

“…Besides Lactococcus and Granulicatella mediated network, D2 group enriched Staphylococcus, Propionibacterium and Massilia indicated to construct a complex positive interaction with Acinetobacter, Raoultella and Limnohabitans. However, Mycoplasma seemed to be outside of these relationships, possibly attributable to lack of antagonistic relationship between M. pneumoniae with other airway pathogens, and low immunity of pneumonia children in D2 group caused by M. pneumoniae indued severe symptoms (19). And S. aureus was proved to be the airway pathogen, interacting with S. pneumoniae, H. influenza and P. aeruginosa negatively (2), which could promote colonization of S. aureus at BALF of children infected with M. pneumoniae.…”

“Better” clinical decisions do not necessarily require more time to make

“…Strategies could be based on fast-and-frugal heuristics paradigms, which involve rapid processing of relatively little information to make a decision [2]. Indeed, researchers have developed such strategies to assist clinicians in decision-making which compare favourably with more complex decision support tools [3]. Strategies which enable GPs to make the best use of their limited time may therefore be an important contribution to interventions to improve quality of care.…”

A million answers to twenty questions: Choosing by checklist

“…So the choice function indeed maximizes the we have defined. 8 For the 'if' half of Theorem 2, suppose we are given a choice function c that maximizes a preference relation . We can then build an extended checklist from a familiar item, the weaklybetter-than sets of the preference relation : for each x ∈ X, set a property P x equal to {y ∈ X: y x}, ignoring the duplicates that arise when x ∼ x .…”

“…The term 'non-compensatory choice models' is used in these fields to underscore the lack of 'tradeoffs' between earlier and later properties. 3 See for example [8].…”