6 research outputs found
Use of Netilmicin Once or Twice Daily in Preterm Newborns: Evaluation of Nephrotoxicity by Urinary α1-Microglobulin and Retinol Binding Protein
Searches for Dark Matter annihilation signatures in the Segue 1 satellite galaxy with the MAGIC-I telescope
We report the results of the observation of the nearby satellite galaxy Segue
1 performed by the MAGIC-I ground-based gamma-ray telescope between November
2008 and March 2009 for a total of 43.2 hours. No significant gamma-ray
emission was found above the background. Differential upper limits on the
gamma-ray flux are derived assuming various power-law slopes for the possible
emission spectrum. Integral upper limits are also calculated for several
power-law spectra and for different energy thresholds. The values are of the
order of 10^{-11} ph cm^{-2}$ s^{-1} above 100 GeV and 10^{-12} ph cm^{-2}
s^{-1} above 200 GeV. Segue 1 is currently considered one of the most
interesting targets for indirect dark matter searches. In these terms, the
upper limits have been also interpreted in the context of annihilating dark
matter particles. For such purpose, we performed a grid scan over a reasonable
portion of the parameter space for the minimal SuperGravity model and computed
the flux upper limit for each point separately, taking fully into account the
peculiar spectral features of each model. We found that in order to match the
experimental upper limits with the model predictions, a minimum flux boost of
10^{3} is required, and that the upper limits are quite dependent on the shape
of the gamma-ray energy spectrum predicted by each specific model. Finally we
compared the upper limits with the predictions of some dark matter models able
to explain the PAMELA rise in the positron ratio, finding that Segue 1 data are
in tension with the dark matter explanation of the PAMELA spectrum in the case
of a dark matter candidate annihilating into tau+tau-. A complete exclusion
however is not possible due to the uncertainties in the Segue 1 astrophysical
factor.Comment: 26 pages, 10 figures. Matched to published versio
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