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- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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- Ademuyiwa, Adesoji O., et al.
(författare)
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Determinants of morbidity and mortality following emergency abdominal surgery in children in low-income and middle-income countries
- 2016
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Ingår i: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 1:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: Child health is a key priority on the global health agenda, yet the provision of essential and emergency surgery in children is patchy in resource-poor regions. This study was aimed to determine the mortality risk for emergency abdominal paediatric surgery in low-income countries globally.Methods: Multicentre, international, prospective, cohort study. Self-selected surgical units performing emergency abdominal surgery submitted prespecified data for consecutive children aged <16 years during a 2-week period between July and December 2014. The United Nation's Human Development Index (HDI) was used to stratify countries. The main outcome measure was 30-day postoperative mortality, analysed by multilevel logistic regression.Results: This study included 1409 patients from 253 centres in 43 countries; 282 children were under 2 years of age. Among them, 265 (18.8%) were from low-HDI, 450 (31.9%) from middle-HDI and 694 (49.3%) from high-HDI countries. The most common operations performed were appendectomy, small bowel resection, pyloromyotomy and correction of intussusception. After adjustment for patient and hospital risk factors, child mortality at 30 days was significantly higher in low-HDI (adjusted OR 7.14 (95% CI 2.52 to 20.23), p<0.001) and middle-HDI (4.42 (1.44 to 13.56), p=0.009) countries compared with high-HDI countries, translating to 40 excess deaths per 1000 procedures performed.Conclusions: Adjusted mortality in children following emergency abdominal surgery may be as high as 7 times greater in low-HDI and middle-HDI countries compared with high-HDI countries. Effective provision of emergency essential surgery should be a key priority for global child health agendas.
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| 9. |
- Tahir, M. J., et al.
(författare)
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Internet addiction and sleep quality among medical students during the COVID-19 pandemic : A multinational cross-sectional survey
- 2021
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 16:11 November
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Tidskriftsartikel (refereegranskat)abstract
- Background The emergence of the COVID-19 pandemic has affected the lives of many people, including medical students. The present study explored internet addiction and changes in sleep patterns among medical students during the pandemic and assessed the relationship between them. Methods A cross-sectional study was carried out in seven countries, the Dominican Republic, Egypt, Guyana, India, Mexico, Pakistan, and Sudan, using a convenience sampling technique, an online survey comprising demographic details, information regarding COVID-19, the Pittsburgh Sleep Quality Index (PSQI), and the Internet Addiction Test (IAT). Results In total, 2749 participants completed the questionnaire. Of the total, 67.6% scored above 30 in the IAT, suggesting the presence of an Internet addiction, and 73.5% scored equal and above 5 in the PSQI, suggesting poor sleep quality. Internet addiction was found to be significant predictors of poor sleep quality, causing 13.2% of the variance in poor sleep quality. Participants who reported COVID-19 related symptoms had disturbed sleep and higher internet addiction levels when compared with those who did not. Participants who reported a diagnosis of COVID-19 reported poor sleep quality. Those living with a COVID-19 diagnosed patient reported higher internet addiction and worse sleep quality compared with those who did not have any COVID-19 patients in their surroundings. Conclusion The results of this study suggest that internet addiction and poor sleep quality are two issues that require addressing amongst medical students. Medical training institutions should do their best to minimize their negative impact, particularly during the current COVID-19 pandemic.
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- Akhtar, Malik N., et al.
(författare)
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Accurate Assignment of Significance to Neuropeptide Identifications Using Monte Carlo K-Permuted Decoy Databases
- 2014
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:10, s. e111112-
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Tidskriftsartikel (refereegranskat)abstract
- In support of accurate neuropeptide identification in mass spectrometry experiments, novel Monte Carlo permutation testing was used to compute significance values. Testing was based on k-permuted decoy databases, where k denotes the number of permutations. These databases were integrated with a range of peptide identification indicators from three popular open-source database search software (OMSSA, Crux, and X! Tandem) to assess the statistical significance of neuropeptide spectra matches. Significance p-values were computed as the fraction of the sequences in the database with match indicator value better than or equal to the true target spectra. When applied to a test-bed of all known manually annotated mouse neuropeptides, permutation tests with k-permuted decoy databases identified up to 100% of the neuropeptides at p-value < 10(-5). The permutation test p-values using hyperscore (X! Tandem), E-value (OMSSA) and Sp score (Crux) match indicators outperformed all other match indicators. The robust performance to detect peptides of the intuitive indicator "number of matched ions between the experimental and theoretical spectra" highlights the importance of considering this indicator when the p-value was borderline significant. Our findings suggest permutation decoy databases of size 1x10(5) are adequate to accurately detect neuropeptides and this can be exploited to increase the speed of the search. The straightforward Monte Carlo permutation testing (comparable to a zero order Markov model) can be easily combined with existing peptide identification software to enable accurate and effective neuropeptide detection. The source code is available at http://stagbeetle.animal.uiuc.edu/pepshop/MSMSpermutationtesting.
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