| 1. |
- Nordberg, Marika, et al.
(författare)
-
Aetiology of tick-borne infections in an adult swedish population-are co-infections with multiple agents common
- 2014
-
Ingår i: Open Journal of Clinical Diagnostics. - Scientific Research : Scientific Research Publishing, Inc.. - 2162-5816 .- 2162-5824. ; 4:1, s. 31-40
-
Tidskriftsartikel (refereegranskat)abstract
- In Scandinavia, tick-borne infections affecting humans include Lyme borreliosis (LB), tick-borne encephalitis (TBE) and human granulocytic anaplasmosis (HGA). Each of these infections can present with unspecific symptoms. In this prospective clinical study, we recruited patients based on two independent inclusion criteria; 1) patients with unspecific symptoms, i.e. fever (≥38.0˚C) or a history of feverishness and/or any combination of headache, myalgia or arthralgia and 2) patients with erythema migrans (EM), following an observed tick bite or tick exposure within one month prior to onset of symptoms. A total of 206 patients fulfilled the study. Among these, we could identify 186 cases of LB (174 with EM), 18 confirmed and two probable cases of HGA and two cases of TBE. Thirteen of the HGA cases presented without fever. Furthermore, 22 of the EM patients had a sub-clinical co-infection with Anaplasma phagocytophilum, based on serology. Both TBE cases had co-infections, one with Borrelia burgdorferi and one with Anaplasma phagocytophilum. We conclude that it is important to consider several causative agents and possible co-infections in the clinical management of infectious diseases where ticks may be suspected as vectors.
|
|
| 2. |
- Javeed, Ashir, 1989-, et al.
(författare)
-
Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning
- 2023
-
Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:8
-
Tidskriftsartikel (refereegranskat)abstract
- Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clinical decision support system for predicting mortality in cardiac patients to address this problem. The dataset collected for the experimental purposes of the proposed model consisted of 55 features with a total of 368 samples. We found that the classes in the dataset were highly imbalanced. To avoid the problem of bias in the machine learning model, we used the synthetic minority oversampling technique (SMOTE). After balancing the classes in the dataset, the newly proposed system employed a (Formula presented.) statistical model to rank the features from the dataset. The highest-ranked features were fed into an optimized random forest (RF) model for classification. The hyperparameters of the RF classifier were optimized using a grid search algorithm. The performance of the newly proposed model ((Formula presented.) _RF) was validated using several evaluation measures, including accuracy, sensitivity, specificity, F1 score, and a receiver operating characteristic (ROC) curve. With only 10 features from the dataset, the proposed model (Formula presented.) _RF achieved the highest accuracy of 94.59%. The proposed model (Formula presented.) _RF improved the performance of the standard RF model by 5.5%. Moreover, the proposed model (Formula presented.) _RF was compared with other state-of-the-art machine learning models. The experimental results show that the newly proposed decision support system outperforms the other machine learning systems using the same feature selection module ((Formula presented.)).
|
|
| 3. |
- Berner, Jessica, et al.
(författare)
-
Factors influencing Internet usage in older adults (65 years and above) living in rural and urban Sweden
- 2015
-
Ingår i: Health Informatics Journal. - : Sage Publications. - 1460-4582 .- 1741-2811. ; 21:3, s. 237-249
-
Tidskriftsartikel (refereegranskat)abstract
- Older adults living in rural and urban areas have shown to distinguish themselves in technology adoption; a clearer profile of their Internet use is important in order to provide better technological and health-care solutions. Older adults' Internet use was investigated across large to midsize cities and rural Sweden. The sample consisted of 7181 older adults ranging from 59 to 100 years old. Internet use was investigated with age, education, gender, household economy, cognition, living alone/or with someone and rural/urban living. Logistic regression was used. Those living in rural areas used the Internet less than their urban counterparts. Being younger and higher educated influenced Internet use; for older urban adults, these factors as well as living with someone and having good cognitive functioning were influential. Solutions are needed to avoid the exclusion of some older adults by a society that is today being shaped by the Internet.
|
|
| 4. |
- Stridsman, Caroline, et al.
(författare)
-
Creating a balance between breathing and viability : Experiences of well-being when living with chronic obstructive pulmonary disease
- 2015
-
Ingår i: Primary Health Care Research and Development. - 1463-4236 .- 1477-1128. ; 16:1, s. 42-52
-
Tidskriftsartikel (refereegranskat)abstract
- Aim To describe experiences of well-being among people with moderate to very severe chronic obstructive pulmonary disease (COPD). BACKGROUND: Living with COPD is related to a complex life situation, and quality of life (QOL) is shown to decrease because of respiratory symptoms and fatigue. However, studies describing well-being in COPD as a subjective description of QOL are rare. METHODS: Ten participants with moderate to very severe COPD from the Obstructive Lung Disease in Northern Sweden (OLIN) COPD study were interviewed about their experiences of well-being. A latent qualitative content analysis was used to analyse the data. Findings To achieve well-being despite breathlessness, the participants had to adapt to their limitations and live towards the future. They created a balance between breathing and viability by adjusting to a lifelong limitation, handling variations in illness, relying on self-capacity and accessibility to a trustful care. The participants adjusted to lifelong limitations through acceptance and replacement of former activities. They handled variations in illness by taking advantage of the good days and using emotional adaptation strategies. The participants relied on their own self-capacity, feeling that smoking cessation, physical activity and breathing fresh air increased their well-being. They requested accessibility to a trustful care and highlighted the need for continuous care relationships and access to medications. These findings can enhance health-care professionals' understanding of the possibilities for increased well-being for people living with COPD.
|
|
| 5. |
- Rennemark, Mikael, 1951-, et al.
(författare)
-
Relationships between frequency of moderate physical activity and longevity : an 11-year follow-up study
- 2018
-
Ingår i: Gerontology and geriatric medicine. - : Sage Publications. - 2333-7214. ; 4, s. 1-8
-
Tidskriftsartikel (refereegranskat)abstract
- Objectives: Moderate physical activity gains survival. There are, however, several variables that may affect this relationship. In this study, the relationship between moderate physical activity and longevity was investigated, taking into account age, gender, smoking habits, cohabitation status, body mass index, leg strength and balance, education level and cognitive function. Method: A sample of 8,456 individuals aged 60 to 96 years, representative of the Swedish population, was included. Participants were followed from 2004 to 2015. Cox regression analyses were used to investigate the predictive value of physical activity on longevity. Results: Participants still alive in the follow-up measure were more physically active on a moderate level. Being active 2 to 3 times a week or more was related to a 28% lower risk of not being alive at the follow-up measure. Discussion: The low frequency of physical activity, necessary for survival benefits should be considered in public health programs.
|
|
| 6. |
- Lagergren, Mårten, et al.
(författare)
-
Horizontal and vertical targeting : a population-based comparison of public eldercare services in urban and rural areas of Sweden
- 2016
-
Ingår i: Aging Clinical and Experimental Research. - : Springer Science and Business Media LLC. - 1594-0667 .- 1720-8319. ; 28:1, s. 147-158
-
Tidskriftsartikel (refereegranskat)abstract
- The concepts of target efficiency can be used to assess the extent to which service provision is in line with the needs of the population. Horizontal target efficiency denotes the extent to which those deemed to need a service receive it and vertical target efficiency is the corresponding extent to which those who receive services actually need them. The aim of this study was to assess the target efficiency of the Swedish eldercare system and to establish whether target efficiencies differ in different geographical areas such as large urban, midsize urban and rural areas. Vertical efficiency was measured by studying those people who received eldercare services and was expressed as a percentage of those who received services who were functionally dependent. To measure horizontal target efficiency, data collected at baseline in the longitudinal population study SNAC (Swedish National study on Aging and Care) during the years 2001-2004 were used. The horizontal efficiency was calculated as the percentage of functionally dependent persons who received services. Functional dependency was measured as having difficulty with instrumental activities of daily living (IADL) and/or personal activities of daily living (PADL). Services included long-term municipal eldercare services (LTC). Horizontal target efficiency for the public LTC system was reasonably high in all three geographical areas, when using dependency in PADL as the measure of need (70-90 %), but efficiency was lower when the less restrictive measure of IADL dependency was used (40-50 %). In both cases, the target efficiency was markedly higher in the large urban and the rural areas than in the midsize urban areas. Vertical target efficiency showed the same pattern-it was almost 100 % in all areas for IADL dependency, but only 50-60 % for PADL dependency. Household composition differed in the areas studied as did the way public long-term care was provided to people living alone as compared to those co-habiting.
|
|
| 7. |
- Kvist, Ola, et al.
(författare)
-
A cross-sectional magnetic resonance imaging study of factors influencing growth plate closure in adolescents and young adults
- 2021
-
Ingår i: Acta Paediatrica. - : John Wiley & Sons. - 0803-5253 .- 1651-2227. ; 110:4, s. 1249-1256
-
Tidskriftsartikel (refereegranskat)abstract
- Aim To assess growth plate fusion by magnetic resonance imaging (MRI) and evaluate the correlation with sex, age, pubertal development, physical activity and BMI. Methods Wrist, knee and ankle of 958 healthy subjects aged 14.0-21.5 years old were examined using MRI and graded by two radiologists. Correlations of growth plate fusion score with age, pubertal development, physical activity and BMI were assessed. Results Complete growth plate fusion occurred in 75%, 85%, 97%, 98%, 98% and 90%, 97%, 95%, 97%, 98% (radius, femur, proximal- and distal tibia and calcaneus) in 17-year-old females and 19-year-old males, respectively. Complete fusion occurs approximately 2 years earlier in girls than in boys. Pubertal development correlated with growth plate fusion score (rho = 0.514-0.598 for the different growth plate sites) but regular physical activity did not. BMI also correlated with growth plate fusion (rho = 0.186-0.384). Stratified logistic regression showed increased odds ratio (OR F: 2.65-8.71; M: 1.71-4.03) for growth plate fusion of obese or overweight subects versus normal-weight subjects. Inter-observer agreement was high (Kappa = 0.87-0.94). Conclusion Growth plate fusion can be assessed by MRI; occurs in an ascending order, from the foot to the wrist; and is significantly influenced by sex, pubertal development and BMI, but not by physical activity.
|
|
| 8. |
- Lundberg, Jenny, 1976-, et al.
(författare)
-
Early Signs of Diabetes Explored from an Engineering Perspective
- 2019
-
Ingår i: Smart Industry & Smart Education. - Cham : Springer. - 9783319956787 - 9783319956770 ; , s. 22-31
-
Konferensbidrag (refereegranskat)abstract
- Undetected diabetes is a global issue, estimated to over 200 million persons affected. Engineering opportunities in capturing early signs of diabetes has a potential due to the complexity to interpret early signs and link it to diabetes. Persons with untreated diabetes are doubled in risk of getting cardiovascular diseases and may also suffer other consequent diseases. In Sweden, approximately 450 thousand have diabetes where 80-90% are of type 2 with 1/4 unaware of it, i.e. approx. 100 thousand. Screening approaches, searching specifically for diabetes in persons not showing symptoms has been initiated with positive results. However, some general drawbacks of screening such as false sense of security are an issue. In this publication, we focus upon in home measurements and empowering of the individual in identifying early signs of diabetes. The methods in this publication are to gather data, evaluate and give suggestion if clinical test to confirm or reject diabetes. In home measurements, education process with companies for innovation possibilities.
|
|
| 9. |
- Lindberg, Terese, et al.
(författare)
-
Prevalence and Incidence of Atrial Fibrillation and Other Arrhythmias in the General Older Population : Findings From the Swedish National Study on Aging and Care
- 2019
-
Ingår i: Gerontology and geriatric medicine. - : SAGE PUBLICATIONS INC. - 2333-7214. ; 5
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: To study the prevalence and cumulative incidence of arrhythmias in the general population of adults aged 60 and older over a 6-year period. Study Design and Setting: Data were taken from the Swedish National Study on Aging and Care (SNAC), a national, longitudinal, multidisciplinary study of the general elderly population (defined as 60 years of age or older). A 12-lead resting electrocardiography (ECG) was performed at baseline and 6-year follow-up. Results: The baseline prevalence of atrial fibrillation (AF) was 4.9% (95% confidence interval [CI] = [4.5%, 5.5%]), and other arrhythmias including ventricular premature complexes (VPCs), supraventricular tachycardia (SVT), and supraventricular extrasystole (SVES) were seen in 8.4% (7.7%, 9.0%) of the population. A first- or second-degree atrioventricular (AV) block was found in 7.1% of the population (95% CI = [6.5%, 7.7%]), and there were no significant differences between men and women in baseline arrhythmia prevalence. The 6-year cumulative incidence of AF was 4.1% (95% CI = [3.5%, 4.9%]), or 6.9/1,000 person-years (py; 95% CI = [5.7, 8.0]). The incidence of AF, other arrhythmias, AV block, and pacemaker-induced rhythm was significantly higher in men in all cohorts except for the oldest. Conclusion: Our data highlight the prevalence and incidence of arrhythmias, which rapidly increase with advancing age in the general population.
|
|
| 10. |
- Javeed, Ashir, 1989-, et al.
(författare)
-
Predicting Dementia Risk Factors Based on Feature Selection and Neural Networks
- 2023
-
Ingår i: Computers, Materials and Continua. - : Tech Science Press. - 1546-2218 .- 1546-2226. ; 75:2, s. 2491-2508
-
Tidskriftsartikel (refereegranskat)abstract
- Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity, mortality, and disabilities. Since there is a consensus that dementia is a multifactorial disorder, which portrays changes in the brain of the affected individual as early as 15 years before its onset, prediction models that aim at its early detection and risk identification should consider these characteristics. This study aims at presenting a novel method for ten years prediction of dementia using on multifactorial data, which comprised 75 variables. There are two automated diagnostic systems developed that use genetic algorithms for feature selection, while artificial neural network and deep neural network are used for dementia classification. The proposed model based on genetic algorithm and deep neural network had achieved the best accuracy of 93.36%, sensitivity of 93.15%, specificity of 91.59%, MCC of 0.4788, and performed superior to other 11 machine learning techniques which were presented in the past for dementia prediction. The identified best predictors were: age, past smoking habit, history of infarct, depression, hip fracture, single leg standing test with right leg, score in the physical component summary and history of TIA/RIND. The identification of risk factors is imperative in the dementia research as an effort to prevent or delay its onset.
|
|
