Bovine mastitis is a polymicrobial disease requiring a polydiagnostic approach

peer-reviewedBovine mastitis, an inflammation of the udder, is associated with increases in milk somatic cell count usually resulting from bacterial infection. We analysed 50 mastitic milk samples via cultivation, 16S rRNA sequencing and a combination of the two (culturomics) to define the complete microbial content of the milk. Most samples contained over 10,000 cfu mL-1 total bacterial counts including isolates that were haemolysin positive (n = 36). Among colonies isolated from blood agar plates, Streptococcus uberis was dominant (11/50) followed by Streptococcus dysgalactiae (6/50), Pseudomonas (6/50), Enterococcus faecalis (6/50), Escherichia coli (6/50), Staphylococcus argenteus (4/50), Bacillus (4/50) and Staphylococcus aureus (2/50). 16S rRNA profiling revealed that amplicons were dominated by Rhodococcus, Staphylococcus, Streptococcus and Pseudomonas. A higher inter-sample diversity was noted in the 16S rRNA readouts, which was not always reflected in the plating results. The combination of the two methods highlights the polymicrobial complexity of bovine mastitis

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society