| 11. |
- Bentham, James, et al.
(author)
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A century of trends in adult human height
- 2016
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In: eLIFE. - 2050-084X. ; 5
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Journal article (peer-reviewed)abstract
- Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.522.7) and 16.5 cm (13.319.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries.
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| 12. |
- Bentham, James, et al.
(author)
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A century of trends in adult human height
- 2016
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In: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 5
-
Journal article (peer-reviewed)abstract
- Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5–22.7) and 16.5 cm (13.3– 19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8– 144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries.
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| 13. |
- Berg, Johanna, et al.
(author)
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Perceived usefulness of trauma audit filters in urban India: a mixed-methods multicentre Delphi study comparing filters from the WHO and low and middle-income countries
- 2022
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In: Bmj Open. - : BMJ. - 2044-6055. ; 12:6
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Journal article (peer-reviewed)abstract
- Objective To compare experts' perceived usefulness of audit filters from Ghana, Cameroon, WHO and those locally developed; generate context-appropriate audit filters for trauma care in selected hospitals in urban India; and explore characteristics of audit filters that correlate to perceived usefulness. Design A mixed-methods approach using a multicentre online Delphi technique. Setting Two large tertiary hospitals in urban India. Methods Filters were rated on a scale from 1 to 10 in terms of perceived usefulness, with the option to add new filters and comments. The filters were categorised into three groups depending on their origin: low and middle-income countries (LMIC), WHO and New (locally developed), and their scores compared. Significance was determined using Kruskal-Wallis test followed by Wilcoxon rank-sum test. We performed a content analysis of the comments. Results 26 predefined and 15 new filter suggestions were evaluated. The filters had high usefulness scores (mean overall score 9.01 of 10), with the LMIC filters having significantly higher scores compared with those from WHO and those newly added. Three themes were identified in the content analysis relating to medical relevance, feasibility and specificity. Conclusions Audit filters from other LMICs were deemed highly useful in the urban India context. This may indicate that the transferability of defined trauma audit filters between similar contexts is high and that these can provide a starting point when implemented as part of trauma quality improvement programmes in low-resource settings.
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| 14. |
- Björk, Jonas, et al.
(author)
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A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department
- 2006
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In: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 6:28
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Journal article (peer-reviewed)abstract
- Background Several models for prediction of acute coronary syndrome (ACS) among chest pain patients in the emergency department (ED) have been presented, but many models predict only the likelihood of acute myocardial infarction, or include a large number of variables, which make them less than optimal for implementation at a busy ED. We report here a simple statistical model for ACS prediction that could be used in routine care at a busy ED. Methods Multivariable analysis and logistic regression were used on data from 634 ED visits for chest pain. Only data immediately available at patient presentation were used. To make ACS prediction stable and the model useful for personnel inexperienced in electrocardiogram (ECG) reading, simple ECG data suitable for computerized reading were included. Results Besides ECG, eight variables were found to be important for ACS prediction, and included in the model: age, chest discomfort at presentation, symptom duration and previous hypertension, angina pectoris, AMI, congestive heart failure or PCI/CABG. At an ACS prevalence of 21% and a set sensitivity of 95%, the negative predictive value of the model was 96%. Conclusions The present prediction model, combined with the clinical judgment of ED personnel, could be useful for the early discharge of chest pain patients in populations with a low prevalence of ACS.
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| 15. |
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| 16. |
- Björk, Jonas, et al.
(author)
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Risk predictions for individual patients from logistic regression were visualized with bar-line charts.
- 2012
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In: Journal of Clinical Epidemiology. - : Elsevier BV. - 1878-5921 .- 0895-4356. ; 65, s. 335-342
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Journal article (peer-reviewed)abstract
- OBJECTIVE: The interface of a computerized decision support system is crucial for its acceptance among end users. We demonstrate how combined bar-line charts can be used to visualize predictions for individual patients from logistic regression models. STUDY DESIGN AND SETTING: Data from a previous diagnostic study aiming at predicting the immediate risk of acute coronary syndrome (ACS) among 634 patients presenting to an emergency department with chest pain were used. Risk predictions from the logistic regression model were presented for four hypothetical patients in bar-line charts with bars representing empirical Bayes adjusted likelihood ratios (LRs) and the line representing the estimated probability of ACS, sequentially updated from left to right after assessment of each risk factor. RESULTS: Two patients had similar low risk for ACS but quite different risk profiles according to the bar-line charts. Such differences in risk profiles could not be detected from the estimated ACS risk alone. The bar-line charts also highlighted important but counteracted risk factors in cases where the overall LR was less informative (close to one). CONCLUSION: The proposed graphical technique conveys additional information from the logistic model that can be important for correct diagnosis and classification of patients and appropriate medical management.
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| 17. |
- Björkelund, Anders, et al.
(author)
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Machine learning compared with rule‐in/rule‐out algorithms and logistic regression to predict acute myocardial infarction based on troponin T concentrations
- 2021
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In: Journal of the American College of Emergency Physicians Open. - Hoboken, NJ : John Wiley & Sons. - 2688-1152. ; 2:2
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Journal article (peer-reviewed)abstract
- AbstractObjectiveComputerized decision-support tools may improve diagnosis of acute myocardial infarction (AMI) among patients presenting with chest pain at the emergency department (ED). The primary aim was to assess the predictive accuracy of machine learning algorithms based on paired high-sensitivity cardiac troponin T (hs-cTnT) concentrations with varying sampling times, age, and sex in order to rule in or out AMI.MethodsIn this register-based, cross-sectional diagnostic study conducted retrospectively based on 5695 chest pain patients at 2 hospitals in Sweden 2013–2014 we used 5-fold cross-validation 200 times in order to compare the performance of an artificial neural network (ANN) with European guideline-recommended 0/1- and 0/3-hour algorithms for hs-cTnT and with logistic regression without interaction terms. Primary outcome was the size of the intermediate risk group where AMI could not be ruled in or out, while holding the sensitivity (rule-out) and specificity (rule-in) constant across models.ResultsANN and logistic regression had similar (95%) areas under the receiver operating characteristics curve. In patients (n = 4171) where the timing requirements (0/1 or 0/3 hour) for the sampling were met, using ANN led to a relative decrease of 9.2% (95% confidence interval 4.4% to 13.8%; from 24.5% to 22.2% of all tested patients) in the size of the intermediate group compared to the recommended algorithms. By contrast, using logistic regression did not substantially decrease the size of the intermediate group.ConclusionMachine learning algorithms allow for flexibility in sampling and have the potential to improve risk assessment among chest pain patients at the ED.
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| 18. |
- Blodgett, Joanna M., et al.
(author)
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Device-measured physical activity and cardiometabolic health : the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium
- 2023
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In: European Heart Journal. - 0195-668X .- 1522-9645.
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Journal article (peer-reviewed)abstract
- Background and Aims: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.Methods: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.Results: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with −0.63 (95% confidence interval −0.48, −0.79), −0.43 (−0.25, −0.59), −0.40 (−0.25, −0.56), and −0.15 (0.05, −0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day.Conclusions: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.
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| 19. |
- Bodetoft, Stefan, et al.
(author)
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Effects of oxygen inhalation on cardiac output, coronary blood flow and oxygen delivery in healthy individuals, assessed with MRI.
- 2011
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In: European Journal of Emergency Medicine. - 0969-9546. ; 18, s. 25-30
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Journal article (peer-reviewed)abstract
- OBJECTIVES: Oxygen (O2) is a cornerstone in the treatment of critically ill patients, and the guidelines prescribe 10-15 l of O2/min even to those who are initially normoxic. Studies using indirect or invasive methods suggest, however, that supplemental O2 may have negative cardiovascular effects. The aim of this study was to test the hypothesis, using noninvasive cardiac magnetic resonance imaging, that inhaled supplemental O2 decreases cardiac output (CO) and coronary blood flow in healthy individuals. METHODS: Sixteen healthy individuals inhaled O2 at 1, 8 and 15 l/min through a standard reservoir bag mask. A 1.5 T magnetic resonance imaging scanner was used to measure stroke volume, CO and coronary sinus blood flow. Left ventricular (LV) perfusion was calculated as coronary sinus blood flow/LV mass. RESULTS: The O2 response was dose-dependent. At 15 l of O2/min, blood partial pressure of O2 increased from an average 11.7 to 51.0 kPa with no significant changes in blood partial pressure of CO2 or arterial blood pressure. At the same dose, LV perfusion decreased by 23% (P=0.005) and CO decreased by 10% (P=0.003) owing to a decrease in heart rate (by 9%, P<0.002), with no significant changes in stroke volume or LV dimensions. Owing to the decreased CO and LV perfusion, systemic and coronary O2 delivery fell by 4 and 11% at 8 l of O2/min, despite the increased blood oxygen content. CONCLUSION: Our data indicate that O2 administration decreases CO, LV perfusion and systemic and coronary O2 delivery in healthy individuals. Further research should address the effects of O2 therapy in normoxic patients.
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| 20. |
- Borna, Catharina, et al.
(author)
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The objective CORE score allows early rule out in acute chest pain patients
- 2018
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In: Scandinavian Cardiovascular Journal. - : Informa UK Limited. - 1401-7431 .- 1651-2006. ; 52:6, s. 308-314
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Journal article (peer-reviewed)abstract
- Objectives. Chest pain is a common complaint in the emergency department (ED), and it is a challenge to identify low-risk chest pain patients eligible for early discharge. We aimed to develop a simple objective decision rule to exclude 30-day major adverse cardiac events (MACE) in ED chest pain patients. Design. We analyzed prospectively included patients presenting with chest pain. Low risk patients were identified with the clinical objective rule-out evaluation (CORE). CORE was based on high sensitivity cardiac troponin T (hs-cTnT) tests at ED presentation (0 h) and 2 h later together with a simplified risk score consisting of four objective variables: age ≥65 years and a history of arterial disease, hypertension or diabetes. For the patient to be classified as low risk in the CORE rule, hs-cTnT had to be ≤14 ng/L both at 0 and 2 h, and the sum of the risk score had to be 0. The primary outcome was MACE within 30 days. Results. Among the 751 patients in the final analysis, 90 (11.9%) had a MACE. CORE identified 248 (33%) of patients as low risk with a sensitivity of 98.9% (CI 93.1–99.9) and a negative predictive value of 99.6% (95% CI 97.4–100) for 30-day MACE. Adding the ED physician’s interpretation of the ECG to CORE did not improve diagnostic performance. Conclusion. A simple objective decision rule (CORE) identified one-third of all patients as having a very low 30-day risk of MACE. These patients may potentially be discharged without additional investigations for acute coronary syndrome.
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