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- Masterson, Siobhán, et al.
(författare)
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Out-of-hospital cardiac arrest survival in international airports.
- 2018
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 127, s. 58-62
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The highest achievable survival rate following out-of-hospital cardiac arrest is unknown. Data from airports serving international destinations (international airports) provide the opportunity to evaluate the success of pre-hospital resuscitation in a relatively controlled but real-life environment.METHODS: This retrospective cohort study included all cases of out-of-hospital cardiac arrest at international airports with resuscitation attempted between January 1st, 2013 and December 31st, 2015. Crude incidence, patient, event characteristics and survival to hospital discharge/survival to 30 days (survival) were calculated. Mixed effect logistic regression analyses were performed to identify predictors of survival. Variability in survival between airports/countries was quantified using the median odds ratio.RESULTS: There were 800 cases identified, with an average of 40 per airport. Incidence was 0.024/100,000 passengers per year. Percentage survival for all patients was 32%, and 58% for patients with an initial shockable heart rhythm. In adjusted analyses, initial shockable heart rhythm was the strongest predictor of survival (odds ratio, 36.7; 95% confidence interval [CI], 15.5-87.0). In the bystander-witnessed subgroup, delivery of a defibrillation shock by a bystander was a strong predictor of survival (odds ratio 4.8; 95% CI, 3.0-7.8). Grouping of cases was significant at country level and survival varied between countries.CONCLUSIONS: In international airports, 32% of patients survived an out-of-hospital cardiac arrest, substantially more than in the general population. Our analysis suggested similarity between airports within countries, but differences between countries. Systematic data collection and reporting are essential to ensure international airports continually maximise activities to increase survival.
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| 2. |
- Pemberton, Hugh G., et al.
(författare)
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Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment
- 2023
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Ingår i: EJNMMI Research. - 2191-219X. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. Methods: Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. Results: Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r 2 = 0.98). Conclusion: Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
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