COMPARATIVE STUDY OF THE ANTIBIOGRAM OF SOME BACTERIA ISOLATED FROM AUTOMATED TELLER MACHINE (ATM) KEYPADS FROM ABAKALIKI AND AFIKPO IN EBONYI STATE

Automated Teller Machine (ATM) is used by millions of people each day and it is likely to be contaminated with different microorganisms. The ATM keypads were examined to assess them as a potential source of bacterial contamination and to provide the antibiogram of the isolated bacteria. The study lasted from April, 2016 to June, 2016. The procedures involved culturing and identifying swabs from the keypads of 20 ATMs using biochemical tests and Kirby Bauer disc diffusion method for the antibiotic sensitivity tests. The result indicated contamination of the keypads with Staphylococcus aureus 15 (44 %), Escherichia coli 8 (24 %), Klebsiella species 10 (29 %) and Enterobacter species 1 (3 %). There was no significant difference among the bacteria isolated (p > 0.05). The result of the antibiogram showed variation in the susceptibility pattern of the isolates to the antibiotics. Stapphylococcus was 92% resistance to penicillin, followed by ampiclox 85 %, erythromycin 77 % and augmentine 62 %, and while 62 %, 46 % were susceptible to levofloxacine and streptomycine respectively. Escherichia coli was 100% resistance to norfloxacine, followed by penicillin and amoxyl 86%, while 71% of E. coli was susceptible to levofloxacine, followed by ciprofloxacine 57 % and gentamycine 43 %. Klebsiella species were 80 % resistance to penicillin and erythromycin, followed by ampiclox and nalidixic acid 60 %, but 80 % susceptible to levofloxacine, and 60 % susceptible to augmentine, ciprofloxacin and chloramphenicol. The variation of the isolates to the antibiotics demands the need for periodic screening of common bacterial pathogen. Keywords: Antibiogram, Bacteria, Automated teller machine (ATM), Abakaliki and Afikpo

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