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

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

Death following pulmonary complications of surgery before and during the SARS-CoV-2 pandemic

Abstract Background This study aimed to determine the impact of pulmonary complications on death after surgery both before and during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Methods This was a patient-level, comparative analysis of two, international prospective cohort studies: one before the pandemic (January–October 2019) and the second during the SARS-CoV-2 pandemic (local emergence of COVID-19 up to 19 April 2020). Both included patients undergoing elective resection of an intra-abdominal cancer with curative intent across five surgical oncology disciplines. Patient selection and rates of 30-day postoperative pulmonary complications were compared. The primary outcome was 30-day postoperative mortality. Mediation analysis using a natural-effects model was used to estimate the proportion of deaths during the pandemic attributable to SARS-CoV-2 infection. Results This study included 7402 patients from 50 countries; 3031 (40.9 per cent) underwent surgery before and 4371 (59.1 per cent) during the pandemic. Overall, 4.3 per cent (187 of 4371) developed postoperative SARS-CoV-2 in the pandemic cohort. The pulmonary complication rate was similar (7.1 per cent (216 of 3031) versus 6.3 per cent (274 of 4371); P = 0.158) but the mortality rate was significantly higher (0.7 per cent (20 of 3031) versus 2.0 per cent (87 of 4371); P &amp;lt; 0.001) among patients who had surgery during the pandemic. The adjusted odds of death were higher during than before the pandemic (odds ratio (OR) 2.72, 95 per cent c.i. 1.58 to 4.67; P &amp;lt; 0.001). In mediation analysis, 54.8 per cent of excess postoperative deaths during the pandemic were estimated to be attributable to SARS-CoV-2 (OR 1.73, 1.40 to 2.13; P &amp;lt; 0.001). Conclusion Although providers may have selected patients with a lower risk profile for surgery during the pandemic, this did not mitigate the likelihood of death through SARS-CoV-2 infection. Care providers must act urgently to protect surgical patients from SARS-CoV-2 infection. </jats:sec