Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Genomic Analysis Reveals Novel Diversity among the 1976 Philadelphia Legionnaires’ Disease Outbreak Isolates and Additional ST36 Strains

<div><p><i>Legionella pneumophila</i> was first recognized as a cause of severe and potentially fatal pneumonia during a large-scale outbreak of Legionnaires’ disease (LD) at a Pennsylvania veterans’ convention in Philadelphia, 1976. The ensuing investigation and recovery of four clinical isolates launched the fields of <i>Legionella</i> epidemiology and scientific research. Only one of the original isolates, “Philadelphia-1”, has been widely distributed or extensively studied. Here we describe the whole-genome sequencing (WGS), complete assembly, and comparative analysis of all Philadelphia LD strains recovered from that investigation, along with <i>L</i>. <i>pneumophila</i> isolates sharing the Philadelphia sequence type (ST36). Analyses revealed that the 1976 outbreak was due to multiple serogroup 1 strains within the same genetic lineage, differentiated by an actively mobilized, self-replicating episome that is shared with <i>L</i>. <i>pneumophila</i> str. Paris, and two large, horizontally-transferred genomic loci, among other polymorphisms. We also found a completely unassociated ST36 strain that displayed remarkable genetic similarity to the historical Philadelphia isolates. This similar strain implies the presence of a potential clonal population, and suggests important implications may exist for considering epidemiological context when interpreting phylogenetic relationships among outbreak-associated isolates. Additional extensive archival research identified the Philadelphia isolate associated with a non-Legionnaire case of “Broad Street pneumonia”, and provided new historical and genetic insights into the 1976 epidemic. This retrospective analysis has underscored the utility of fully-assembled WGS data for <i>Legionella</i> outbreak investigations, highlighting the increased resolution that comes from long-read sequencing and a sequence type-matched genomic data set.</p></div

Nucleotide polymorphisms unique to the CDC Philadelphia strains relative to the NCBI Philadelphia-1 reference sequence.

<p>Nucleotide polymorphisms unique to the CDC Philadelphia strains relative to the NCBI Philadelphia-1 reference sequence.</p

Nucleotide polymorphisms shared by strains CDC Philadelphia-2, -3, -4, and ATCC Philadelphia-1 relative to the NCBI Philadelphia-1 reference sequence.

<p>Nucleotide polymorphisms shared by strains CDC Philadelphia-2, -3, -4, and ATCC Philadelphia-1 relative to the NCBI Philadelphia-1 reference sequence.</p

Description of cases from whom <i>Legionella</i> was isolated during the 1976 Legionnaires' disease outbreak in Philadelphia.

<p>Description of cases from whom <i>Legionella</i> was isolated during the 1976 Legionnaires' disease outbreak in Philadelphia.</p

Nucleotide polymorphisms shared by all CDC Philadelphia strains relative to the NCBI Philadelphia-1 reference sequence.

<p>Nucleotide polymorphisms shared by all CDC Philadelphia strains relative to the NCBI Philadelphia-1 reference sequence.</p

Mauve whole-genome alignment of <i>L</i>. <i>pneumophila</i> strains within the Philadelphia clade.

<p>ProgressiveMauve was used to compare the fully assembled sequences of the Philadelphia historical <i>Legionella</i> strains as well as isolate E1-P. The minimum weight for pairwise LCBs (locally collinear blocks), which share common colors across genomes, was set to 100, otherwise, the program was run using default parameters as described in the Methods. The general clade organization, as well as the identity and location of the ~40-kb pP36-Ph and the ~45-kb pLP45 elements are shown. The general, expanded Philadelphia clade organization from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164074#pone.0164074.g001" target="_blank">Fig 1</a> is shown, therefore the phylogenetic distances are not to scale.</p

Gubbins-based recombinational analysis and phylogenetic tree reconstruction.

<p>Regions of elevated SNP density, representing potential horizontal gene transfer events, were identified by the Gubbins algorithm and software package, masked in the original multiple sequence alignment, and then core SNPs were identified with kSNP v3, as detailed in the Methods. The maximum-likelihood tree shown was constructed using RAxML v8 and 307 core, non-recombinant SNPs with 1000 bootstrappings. Red blocks represent regions of elevated SNP density conserved in multiple strains and blue blocks represent elevated SNP density only found in a single strain. <i>L</i>. <i>pneumophila</i> str. Philadelphia-4 was used as the reference/outgroup, and VGR-1 and -2 are labeled. Gubbins was run with default parameters. A Gubbins-generated tree with 480 non-recombining SNPs also exhibited similar topology.</p