| 1. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Abodayeh, Kamaleldin, et al.
(författare)
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Stochastic Numerical Analysis for Impact of Heavy Alcohol Consumption on Transmission Dynamics of Gonorrhoea Epidemic
- 2020
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Ingår i: Computers, Materials and Continua. - : TECH SCIENCE PRESS. - 1546-2218 .- 1546-2226. ; 62:3, s. 1125-1142
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to perform a comparison of deterministic and stochastic models. The stochastic modelling is a more realistic way to study the dynamics of gonorrhoea infection as compared to its corresponding deterministic model. Also, the deterministic solution is itself mean of the stochastic solution of the model. For numerical analysis, first, we developed some explicit stochastic methods, but unfortunately, they do not remain consistent in certain situations. Then we proposed an implicitly driven explicit method for stochastic heavy alcohol epidemic model. The proposed method is independent of the choice of parameters and behaves well in all scenarios. So, some theorems and simulations are presented in support of the article.
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| 3. |
- Shatanawi, Wasfi, et al.
(författare)
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Essential Features Preserving Dynamics of Stochastic Dengue Model
- 2021
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Ingår i: CMES - Computer Modeling in Engineering & Sciences. - : TECH SCIENCE PRESS. - 1526-1492 .- 1526-1506. ; 126:1, s. 201-215
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Tidskriftsartikel (refereegranskat)abstract
- Nonlinear stochastic modelling plays an important character in the different fields of sciences such as environmental, material, engineering, chemistry, physics, biomedical engineering, and many more. In the current study, we studied the computational dynamics of the stochastic dengue model with the real material of the model. Positivity, boundedness, and dynamical consistency are essential features of stochastic modelling. Our focus is to design the computational method which preserves essential features of the model. The stochastic non-standard finite difference technique is most efficient as compared to other techniques used in literature. Analysis and comparison were explored in favour of convergence. Also, we address the comparison between the stochastic and deterministic models.
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| 4. |
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| 5. |
- Aziz, Maria, et al.
(författare)
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Efficient Removal of Lead and Chromium From Aqueous Media Using Selenium Based Nanocomposite Supported by Orange Peel
- 2022
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Ingår i: Frontiers in Environmental Science. - : Frontiers Media S.A.. - 2296-665X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- This study presents the synthesis of activated orange peel, derived from bio-waste (orange peel) and its doping with selenium nano-particles to enhance the adsorption capacity. The synthesized nanocomposite orange peel/Selenium (OP/Se) was applied as adsorbents for the removal of Lead (Pb) and Chromium (Cr) from synthetic waste water as an economical water cleaning technology. Orange peel/Selenium nanocomposite was characterized by X-Ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and Scanning electron microscopy (SEM). Scanning electron microscopy results showed the porous structure of OP/Se nanocomposite and distinct peaks observed in XRD and FTIR spectra depicted the successful synthesis of nanocomposite. Batch experiments were conducted to figure out the effect of different parameters on adsorption of Pb and Cr by using Atomic Absorption Spectroscopy. The maximum adsorption capacity of 99.9% was achieved for both lead and chromium at acidic pH. While at temperature of 60°C the maximum adsorption of 98.3 and 95.9% was found for Pb and Cr respectively. Furthermore the experimental data was examined with Pseudo-first order, first-order and Pseudo-second order kinetic model, as well as Morris Intraparticle diffusion model where the pseudo second order was best fitted which indicated the chemisorption mechanism in adsorption process. The adsorption process followed the Langmuir isotherm model verified that OP/Se nanocomposite was found to be favorable for the process of adsorption. The adsorption thermodynamics indicate that adsorption of heavy metals ions is spontaneous (ΔG° < 0) and the adsorption increases with increase in temperature which means that reaction was endothermic in nature. This study revealed that the synthesized bio-activated nanocomposite was an efficient adsorbent material for the removal of heavy metals from waste water.
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| 6. |
- Jibran, Muhammad Ali, et al.
(författare)
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Position prediction for routing in software defined internet of vehicles
- 2020
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Ingår i: Journal of Communications. - : Engineering and Technology Publishing. - 1796-2021 .- 2374-4367. ; 15:2, s. 157-163
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Tidskriftsartikel (refereegranskat)abstract
- By the prediction of future location for a vehicle in Internet of Vehicles (IoV), data forwarding schemes can be further improved. Major parameters for vehicle position prediction includes traffic density, motion, road conditions, and vehicle current position. In this paper, therefore, our proposed system enforces the accurate prediction with the help of real-time traffic from the vehicles. In addition, the proposed Neural Network Model assists Edge Controller and centralized controller to compute and predict vehicle future position inside and outside of the vicinity, respectively. Last but not least, in order to get real-time data, and to maintain a quality of experience, the edge controller is explored with Software Defined Internet of Vehicles. In order to evaluate our framework, SUMO simulator with Open Street map is considered and the results prove the importance of vehicle position prediction for vehicular networks.
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| 7. |
- Rafiq, Shazia, et al.
(författare)
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Comparison of neural mobilization and conservative treatment on pain, range of motion, and disability in cervical radiculopathy : A randomized controlled trial
- 2022
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17:12
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The objective of the study was to compare the effectiveness of neural mobilization technique with conservative treatment on pain intensity, cervical range of motion, and disability.Methods: It was a randomized clinical trial; data was collected from Mayo Hospital, Lahore. Eighty-eight patients fulfilling the sample selection criteria were randomly assigned into group 1 (neural mobilization) and group 2 (conventional treatment). Pain intensity was measured on a numeric pain rating scale, range of motion with an inclinometer, and functional status with neck disability index (NDI). Data were analyzed using SPSS, repeated measure ANOVA for cervical ranges and the Friedman test for NPRS and NDI were used for within-group analysis. Independent samples t-test for cervical ranges and Mann-Whitney U test for NPRS and NDI were used for between-group comparisons.Results: There was a significant improvement in pain, disability, and cervical range of motion after the treatment in both groups compared to the pre-treatment status (p < 0.001), and when both groups were compared neural mobilization was more effective than conventional treatment in reducing pain and neck disability (p < 0.001), but there was no significant difference present in the mean score of cervical range of motion between both groups. (p>0.05).Conclusions: The present study concluded that both neural mobilization and conservative treatment were effective as an exercise program for patients with cervical radiculopathy, however, neural mobilization was more effective in reducing pain and neck disability in cervical radiculopathy.
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| 8. |
- Rafiq, Shazia, et al.
(författare)
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Effects of neurodynamic mobilization on health-related quality of life and cervical deep flexors endurance in patients of cervical radiculopathy : A randomized trial
- 2022
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Ingår i: BioMed Research International. - : Hindawi Publishing Corporation. - 2314-6133 .- 2314-6141. ; 2022
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Cervical radiculopathy is disorder of cervical spinal nerve root affecting large number of population. Previously many studies are conducted to design suitable protocol for management of this disorder, but they lack in quality. The purpose of this study was to compare the effects of neural mobilization and cervical isometrics on health-related quality of life and deep flexors endurance in cervical radiculopathy.Methods: A double-blinded randomized clinical trial was conducted at Mayo Hospital, Lahore, Pakistan. Eighty-eight patients within the age range of 35-50 years were included in the study after taking their consent. In the experimental group (n = 44), median nerve mobilization was applied along with cervical isometric exercises. The control group (n = 44) performed cervical isometric exercises alone. Muscle endurance was measured by craniocervical flexion test and quality of life on 36 items short form health survey SF-36 scale. Measurements were taken at baseline, at 2nd week, and at 4th week. For missing data, intention-to-treat analysis was used.Results: Within-group comparison with Friedman test showed a significant difference between pre, mid, and posttreatment scores on craniocervical flexion test and in all domains of SF 36 in both groups. While between-group comparison with Mann-Whitney U test showed all variables were similar at baseline but after 4 weeks there was a statistically significant improvement in craniocervical flexion test scores and all domains of SF 36 in the experimental group. But domain of pain showed mean rank of 49.43 after 4 weeks in the experimental group and 39.57 in the control group with p = 0.065 and d = 0.579, while for all the other 7 domains values were p < .05 and d > 0.25.Conclusion: Neural mobilization combined with cervical isometrics shows significant effects in improving quality of life and deep flexors endurance in patients with cervical radiculopathy than cervical isometrics alone.
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| 9. |
- Usman, Ali, et al.
(författare)
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Machine Learning Computational Fluid Dynamics
- 2021
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Ingår i: 2021 Swedish Artificial Intelligence Society Workshop (SAIS). - : IEEE. ; , s. 46-49
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Konferensbidrag (refereegranskat)abstract
- Numerical simulation of fluid flow is a significant research concern during the design process of a machine component that experiences fluid-structure interaction (FSI). State-of-the-art in traditional computational fluid dynamics (CFD) has made CFD reach a relative perfection level during the last couple of decades. However, the accuracy of CFD is highly dependent on mesh size; therefore, the computational cost depends on resolving the minor feature. The computational complexity grows even further when there are multiple physics and scales involved making the approach time-consuming. In contrast, machine learning (ML) has shown a highly encouraging capacity to forecast solutions for partial differential equations. A trained neural network has offered to make accurate approximations instantaneously compared with conventional simulation procedures. This study presents transient fluid flow prediction past a fully immersed body as an integral part of the ML-CFD project. MLCFD is a hybrid approach that involves initialising the CFD simulation domain with a solution forecasted by an ML model to achieve fast convergence in traditional CDF. Initial results are highly encouraging, and the entire time-based series of fluid patterns past the immersed structure is forecasted using a deep learning algorithm. Prepared results show a strong agreement compared with fluid flow simulation performed utilising CFD.
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| 10. |
- Batool, S S., et al.
(författare)
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Comparative Analysis of Ti, Ni, and Au Electrodes on Characteristics of TiO2 Nanofibers for Humidity Sensor Application
- 2013
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Ingår i: Journal of Materials Science & Technology. - : Elsevier. - 1005-0302. ; 29:5, s. 411-414
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Tidskriftsartikel (refereegranskat)abstract
- The effect of metal (Ti, Ni, and Au) electrodes on humidity sensing properties of electrospun TiO2 nanofibers was investigated in this work. The devices were fabricated by evaporating metal contacts on SiO2 layer thermally grown on silicon substrate. The separation between the electrodes was 90 mm for all sensors. The sensors were tested from 40% to 90% relative humidity (RH) by AC electrical characterization at room temperature. When sensors are switched between 40% and 90% RH, the corresponding response and recovery time are 3 s and 5 s for Ti-electrode sensor, 4 s and 7 s for Ni-electrode sensor, and 7 s and 13 s for Au-electrode sensor. The hysteresis was 3%, 5% and 15% for Ti-, Ni-, and Au-electrode sensor, respectively. The sensitivity of Ti, Ni, and Au-electrode sensors are 7.53 M Omega/% RH, 5.29 MU/% RH and 4.01 M Omega/% RH respectively at 100 Hz. Therefore Ti-electrode sensor is found to have linear response, fast response and recovery time and higher sensitivity as compared with those of Ni- and Au-electrode sensors. Comparison of humidity sensing properties of sensors with different electrode material may propose a compelling route for designing and optimizing humidity sensors.
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| 11. |
- Batool, S S, et al.
(författare)
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Silica nanofibers based impedance type humidity detector prepared on glass substrate
- 2013
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Ingår i: Vacuum. - : Elsevier. - 0042-207X .- 1879-2715. ; 87, s. 1-6
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Tidskriftsartikel (refereegranskat)abstract
- Impedance type relative humidity detector is fabricated by depositing electrospun silica nanofibers on glass substrate. The silica nanofibers with an average diameter similar to 150 nm and length similar to 100 mu m were used. Thermogravimetric and differential scanning calorimetric analysis confirm that the accurate annealing temperature is 500 degrees C for complete removal of PVP. Humidity detecting devices were fabricated by defining titanium electrodes on top of the silica nanofibers. The performance of silica nanofibers humidity detectors was tested by AC electrical measurements at 40-90% relative humidity. The response and the recovery times were 5 s and 3 s, respectively, between 40% and 90% relative humidity. Contribution of dipoles, space charge polarization, relaxation of these dipoles and low frequency dispersion phenomenon were observed during impedance measurements.
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| 12. |
- Bueno, Moises, et al.
(författare)
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Modification of asphalt mixtures for cold regions using microencapsulated phase change materials
- 2019
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Phase change materials (PCMs) may be used to regulate the temperature of road surfaces to avoid low-temperature damages when asphalt materials become brittle and prone to cracking. With this in mind, different asphalt mixtures were modified with microencapsulated phase change materials (i.e. tetradecane) to assess their thermal benefits during the phase change process. Likewise, the effect on the mechanical performance of PCMs as a replacement of mineral filler was assessed. Special attention was paid to dry and wet modification processes for incorporating the PCMs into the mixtures. The results showed that PCM modifications are indeed able to slow down cooling and affect temperatures below zero. Approximately, a maximum of 2.5 °C offset was achieved under the tested cooling conditions compared to the unmodified reference specimens. Regarding the mechanical response at 0 °C and 10 °C, the results indicated that the PCM modification significantly reduces the stiffness of the material in comparison with the values obtained for the reference mixture.
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| 13. |
- Imran, Z., et al.
(författare)
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Excellent humidity sensing properties of cadmium titanate nanofibers
- 2013
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Ingår i: Ceramics International. - : Elsevier. - 0272-8842 .- 1873-3956. ; 39:1, s. 457-462
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Tidskriftsartikel (refereegranskat)abstract
- We report humidity sensing characteristics of CdTiO3 nanofibers prepared by electrospinning. The nanofibers were porous having an average diameter and length of similar to 50-200 nm and similar to 100 mu m, respectively. The nanofiber humidity sensor was fabricated by defining aluminum electrodes using photolithography on top of the nanofibers deposited on glass substrate. The performance of the CdTiO3 nanofiber humidity sensor was evaluated by AC electrical characterization from 40% to 90% relative humidity at 25 degrees C. The frequency of the AC signal was varied from 10(-1) to 10(6) Hz. Fast response time and recovery time of 4 s and 6 s were observed, respectively. The sensor was highly sensitive and exhibited a reversible response with small hysteresis of less than 7%. Long term stability of the sensor was confirmed during 30 day test. The excellent sensing characteristics prove that the CdTiO3 nanofibers are potential candidate for use in high performance humidity sensors.
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| 14. |
- Jamil, Hira, et al.
(författare)
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Electrospun titanium dioxide nanofiber humidity sensors with high sensitivity
- 2012
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Ingår i: Ceramics International. - : Elsevier. - 0272-8842 .- 1873-3956. ; 38:3, s. 2437-2441
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Tidskriftsartikel (refereegranskat)abstract
- Titanium dioxide nanofibers were synthesized using electrospinning technique. The nanofibers were porous with an average diameter and length of similar to 150 nm and 200 p,m, respectively. Humidity-sensing devices were fabricated by lithographically defined aluminum electrodes on top of the nanofibers deposited on silicon dioxide grown thermally on a silicon substrate. The performance of a TiO2 nanofiber humidity sensor was tested by AC and DC electrical measurements at 40-90% relative humidity. The response and the recovery time were 1 s and 4 s, respectively, between 40% and 90% relative humidity. The sensitivity of the TiO2 humidity sensor in the range of 40-90% RH was 150 M Omega/%RH and 20 M Omega/%RH at 10 Hz and 100 Hz, respectively. The excellent sensing characteristics are attributed to the porous nature and the small diameter of the nanofibers.
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| 15. |
- Keel, George, et al.
(författare)
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Time-driven activity-based costing for patients with multiple chronic conditions : a mixed-method study to cost care in a multidisciplinary and integrated care delivery centre at a university-affiliated tertiary teaching hospital in Stockholm, Sweden
- 2020
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Ingår i: BMJ Open. - London : BMJ Publishing Group Ltd. - 2044-6055. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: This study can be applied to cost the complex non-standardised processes used to treat patients with multiple chronic conditions. DESIGN: A mixed-method approach to cost analysis, following a modified healthcare-specific version of the seven-step Time-Driven Activity-Based Costing (TDABC) approach. SETTING: A multidisciplinary integrated and person-centred care delivery centre at a university-affiliated tertiary teaching hospital in Stockholm, Sweden, designed to improve care coordination for patients with multiple chronic conditions, specifically diabetes, cardiovascular disease and kidney disease. PARTICIPANTS: 314 patients (248 men and 66 women) fit inclusion criteria. Average age was 80 years. RESULTS: This modified TDABC analysis costed outpatient care for patients with multiple chronic conditions. The approach accounted for the difficulty of conceptualising care cycles. The estimated total cost, stratified by resources, can be reviewed together with existing managerial accounting statements to inform management decisions regarding the multidisciplinary centre. CONCLUSIONS: This article demonstrates that the healthcare-specific seven-step approach to TDABC can be applied to cost care for patients with multiple chronic conditions, where pathways are not yet discernable. It became clear that there was a need for slight methodological adaptations for this particular patient group to make it possible to cost these pathways, stratified by activity and resource. The value of this approach can be discerned from the way management incorporated the results of this analysis into the development of their hospital strategy. In the absence of integrated data infrastructures that can link patients and resources across financial, clinical and process data sets, the scalability of this method will be difficult. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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| 16. |
- Pais, Jorge C., et al.
(författare)
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Crumb Rubber Modified Binders
- 2023
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Ingår i: RILEM State-of-the-Art Reports. - : Springer Nature. ; , s. 37-67
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- RILEM Technical Committee 279 WMR is dedicated to the Valorization of Waste and Secondary Materials for Roads. Its Task Group 2 investigated Crumb Rubber (CR) as an additive to enhance the performance of bitumen. CR recycled from end-of-life tires (ELTs) was chosen for this investigation because crumb rubber modified bitumen (CRMB) has been used to improve bituminous mixtures performance for fatigue and reflective cracking. The success of these mixtures is due to the CRMB viscosity that allows the use of an increased amount of bitumen compared to conventional mixtures. Because the viscosity of the CRMB is a function of the CR surface, and presently various types of CRs are produced, it is crucial to verify how these materials perform as a bitumen modifier. Interlaboratory experiments were performed on four types of CR, obtained from mechanical grinding, cryogenic process, waterjet pulverization and reacted and activated rubber. Three base, 35/50, 50/70 and 70/100, bitumen were used for the modification. Mechanical and chemical properties of CRMB were investigated. Despite some differences in the non-mechanical tests, i.e., penetration, softening point and viscosity, the results of the mechanical tests (complex shear modulus) suggest that the bitumen penetration grade ultimately dictates CRMB response.
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| 17. |
- Pang, Andy W., et al.
(författare)
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Towards a comprehensive structural variation map of an individual human genome
- 2010
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-7596 .- 1465-6906. ; 11:5, s. R52-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Several genomes have now been sequenced, with millions of genetic variants annotated. While significant progress has been made in mapping single nucleotide polymorphisms (SNPs) and small (< 10 bp) insertion/deletions (indels), the annotation of larger structural variants has been less comprehensive. It is still unclear to what extent a typical genome differs from the reference assembly, and the analysis of the genomes sequenced to date have shown varying results for copy number variation (CNV) and inversions. Results: We have combined computational re-analysis of existing whole genome sequence data with novel microarray-based analysis, and detect 12,178 structural variants covering 40.6 Mb that were not reported in the initial sequencing of the first published personal genome. We estimate a total non-SNP variation content of 48.8 Mb in a single genome. Our results indicate that this genome differs from the consensus reference sequence by approximately 1.2% when considering indels/CNVs, 0.1% by SNPs and approximately 0.3% by inversions. The structural variants impact 4,867 genes, and >24% of structural variants would not be imputed by SNP-association. Conclusions: Our results indicate that a large number of structural variants have been unreported in the individual genomes published to date. This significant extent and complexity of structural variants, as well as the growing recognition of their medical relevance, necessitate they be actively studied in health-related analyses of personal genomes. The new catalogue of structural variants generated for this genome provides a crucial resource for future comparison studies.
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| 18. |
- Rafiq, Muhammad
(författare)
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Eliminating guesswork : an exploration of the role of predictive modelling in care management for patients with multimorbidities
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Patients with multiple chronic conditions of diabetes, cardiovascular and kidney diseases are one of the most complex group of patients and high consumers of care. Multidisciplinary integrated care delivery models such as Integrated Practice Units have been introduced to improve patient care and reduce health care utilization through offering comprehensive and coordinated care. In addition to the traditional approaches of improving care around patients with multiple chronic conditions, innovative approaches such as developing predictive technologies using machine learning and artificial intelligence are needed to reduce costs and improve care delivery processes of patients with multiple chronic conditions. Multidisciplinary integrated care units are an ideal setting for development and application of predictive technologies using artificial intelligence and machine learning. Aim: The aim of this thesis is to develop and explore how a predictive decision support model for physicians can be used to improve the management of clinical processes applied to individual patients with multiple chronic conditions of diabetes, cardiovascular and kidney diseases (HND patients). Method: This thesis consists of four studies. Study I used descriptive statistics from a randomized controlled trial CareHND (NCT03362983) to describe and compare HND patients’ care utilization patterns between traditional care and multidisciplinary integrated care. Study II implemented two different types of Recurrent Neural Networks to learn about vectors representations of HND patients to demonstrate how ICD codes and clinical procedures contribute towards predicting 30-day hospital readmission using electronic health records data. Study III was a mixed-methods study employing an experience-based co-design model to explore the needs and preferences of physician managers regarding the role of predictive analytics in decision support for patients with multiple chronic conditions, and inputs in the design and development of hospital readmission prediction model. Study IV employed supervised machine learning models to improve and validate a hospital readmission prediction model using electronic health records data and compared their performance. Findings: Study I found that HND patients consumed large amounts of healthcare resources including high hospitalization rates, emergency department visits and frequent encounters with the healthcare professionals. This finding implies that innovative methods like machine learning models should be used to explore the impact of integrated care interventions on care utilization. Study II found that three distinct sub-types of HND patients could be identified using patients’ vectors representation and clustering approach, and deep learning models were able to identify and quantify key contributors to hospital readmission. Study III found that healthcare professionals’ involvement in the design of predictive technologies right from the outset can facilitate a smoother implementation and adoption and enhance their predictive performance. Study IV found that hospital readmission prediction models perform better at the patient sub-group level, and target patients should be clustered based on most similar characteristics before development of predictive modeling. Discussion: This thesis demonstrates how predictive analytics can be applied to cluster patients with multiple chronic conditions into sub-groups having clinically distinct characteristics and develop hospital readmission prediction models. More broadly, this thesis demonstrates how to conceptualize, design, and develop predictive technologies in complex patients with multiple chronic conditions using electronic health records data. This thesis establishes a groundwork for improving management of clinical processes of patients with multiple chronic conditions using machine learning models, and has implications for the wider development, implementation, and adoption of predictive technologies in healthcare. The healthcare management implications of the thesis are centered around the potential improvement of healthcare management practices through patient segmentation and hospital readmission predictions. The thesis also has implications for how opportunities can be created around the design and development of predictive technologies through co-design approaches by actively involving healthcare professionals. Conclusion: This thesis demonstrates that involving healthcare professionals in the design and development of predictive technologies for patients with multiple chronic conditions in a multidisciplinary care setting can produce better results in predicting hospital readmissions and identify clinically distinct patient sub-types. For a wider implementation and adoption of predictive technologies in healthcare, knowledge and competence development of clinicians and managers on the use of such technologies is important. Efforts should be made to actively involve healthcare professionals in the conceptualization, design, development, implementation, and adoption of predictive technologies that may also help reduce healthcare professionals’ unfounded anxieties and concerns about the role of predictive technologies in their daily practices. The difficulty to operationalize the large quantity of available healthcare data should be overcome by ensuring seamless access to healthcare data that can facilitate a smoother design, development, adoption, and implementation of predictive technologies in healthcare. Building proper data structures around the EHRs such that the healthcare data can be collected and easily utilized in the development of predictive technologies is important.
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| 19. |
- Rafiq, Muhammad, et al.
(författare)
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Extreme Consumers of Health Care: Patterns of Care Utilization in Patients with Multiple Chronic Conditions Admitted to a Novel Integrated Clinic
- 2019
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Ingår i: Journal of Multidisciplinary Healthcare. - Macclesfield : Dove Medical Press Ltd.. - 1178-2390. ; 12, s. 1075-1083
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Patients with multiple chronic conditions (MCC) of diabetes, cardiovascular and kidney diseases; hereafter referred to as HND (heart/cardiac-, nephrology-, diabetes mellitus-) patients, are high utilizers of health care. However, the care received is often insufficiently coordinated between different specialties and health-care providers. This study aims to describe the characteristics of HND patients and to explore the initial effects of a multidisciplinary and person-centered care on total care utilization.Patients and Methods: We conducted a sub-study of HND patients recruited in an ongoing randomized trial CareHND (NCT03362983). Descriptive statistics of patient characteristics, including diagnostic data and Charlson Comorbidity Index scores, informed a comparison of care utilization patterns between HND patient care and traditional care. Diagnostic and care utilization data were collected from a regional database. Wilcoxon signed ranked sum tests were performed to compare care utilization frequencies between the two groups.Results: Patients included in the study were care-intensive with several diagnoses and experienced a high level of variation in care utilization and diagnoses profiles. HND patients were sicker than their counterparts in the control group. Utilization indicators were similar between the two arms. There was some indication that the HND center is beginning to perform as expected, but no results were statistically significant.Conclusion: This study sits among many studies reporting difficulties obtaining statistically significant findings for MCC patients. However, previous research has shown that the key components of this intervention, such as integrated, multidisciplinary, inter-professional collaboration within patient-centered care have had a positive effect on health-care outcomes. More innovative methods beyond the RCT, such as machine learning should be explored to evaluate the impact of integrated care interventions on care utilization.
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| 20. |
- Rafiq, Muhammad, et al.
(författare)
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Predictive analytics support for complex chronic medical conditions : An experience-based co-design study of physician managers’ needs and preferences
- 2024
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Ingår i: International Journal of Medical Informatics. - Shannon : Elsevier. - 1386-5056 .- 1872-8243. ; 187, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The literature suggests predictive technology applications in health care would benefit from physician and manager input during design and development. The aim was to explore the needs and preferences of physician managers regarding the role of predictive analytics in decision support for patients with the highly complex yet common combination of multiple chronic conditions of cardiovascular (Heart) and kidney (Nephrology) diseases and diabetes (HND). Methods: This qualitative study employed an experience-based co-design model comprised of three data gathering phases: 1. Patient mapping through non-participant observations informed by process mining of electronic health records data, 2. Semi-structured experience-based interviews, and 3. A co-design workshop. Data collection was conducted with physician managers working at or collaborating with the HND center, Danderyd University Hospital (DSAB), in Stockholm, Sweden. HND center is an integrated practice unit offering comprehensive person-centered multidisciplinary care to stabilize disease progression, reduce visits, and develop treatment strategies that enables a transition to primary care. Results: Interview and workshop data described a complex challenge due to the interaction of underlying pathophysiologies and the subsequent need for multiple care givers that hindered care continuity. The HND center partly met this challenge by coordinating care through multiple interprofessional and interdisciplinary shared decision-making interfaces. The large patient datasets were difficult to operationalize in daily practice due to data entry and retrieval issues. Predictive analytics was seen as a potentially effective approach to support decision-making, calculate risks, and improve resource utilization, especially in the context of complex chronic care, and the HND center a good place for pilot testing and development. Simplicity of visual interfaces, a better understanding of the algorithms by the health care professionals, and the need to address professional concerns, were identified as key factors to increase adoption and facilitate implementation. Conclusions: The HND center serves as a comprehensive integrated practice unit that integrates different medical disciplinary perspectives in a person-centered care process to address the needs of patients with multiple complex comorbidities. Therefore, piloting predictive technologies at the same time with a high potential for improving care represents an extreme, demanding, and complex case. The study findings show that health care professionals’ involvement in the design of predictive technologies right from the outset can facilitate the implementation and adoption of such technologies, as well as enhance their predictive effectiveness and performance. Simplicity in the design of predictive technologies and better understanding of the concept and interpretation of the algorithms may result in implementation of predictive technologies in health care. Institutional efforts are needed to enhance collaboration among the health care professionals and IT professionals for effective development, implementation, and adoption of predictive analytics in health care. © 2024 The Author(s)
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| 21. |
- Roberts, Jason D., et al.
(författare)
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Ankyrin-B dysfunction predisposes to arrhythmogenic cardiomyopathy and is amenable to therapy
- 2019
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Ingår i: Journal of Clinical Investigation. - : AMER SOC CLINICAL INVESTIGATION INC. - 0021-9738 .- 1558-8238. ; 129:8, s. 3171-3184
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Tidskriftsartikel (refereegranskat)abstract
- Arrhythmogenic cardiomyopathy (ACM) is an inherited arrhythmia syndrome characterized by severe structural and electrical cardiac phenotypes, including myocardial fibrofatty replacement and sudden cardiac death. Clinical management of ACM is largely palliative, owing to an absence of therapies that target its underlying pathophysiology, which stems partially from our limited insight into the condition. Following identification of deceased ACM probands possessing ANK2 rare variants and evidence of ankyrin-B loss of function on cardiac tissue analysis, an ANK2 mouse model was found to develop dramatic structural abnormalities reflective of human ACM, including biventricular dilation, reduced ejection fraction, cardiac fibrosis, and premature death. Desmosomal structure and function appeared preserved in diseased human and murine specimens in the presence of markedly abnormal beta-catenin expression and patterning, leading to identification of a previously unknown interaction between ankyrin-B and beta-catenin. A pharmacological activator of the WNT/beta-catenin pathway, SB-216763, successfully prevented and partially reversed the murine ACM phenotypes. Our findings introduce what we believe to be a new pathway for ACM, a role of ankyrin-B in cardiac structure and signaling, a molecular link between ankyrin-B and beta-catenin, and evidence for targeted activation of the WNT/beta-catenin pathway as a potential treatment for this disease.
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| 22. |
- Saeed, Sumbul, et al.
(författare)
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Realization of Peptone Biosensor Based on Newly Prepared NiO Nanostructures
- 2017
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Ingår i: Sensor Letters. - : American Scientific Publishers. - 1546-198X .- 1546-1971. ; 15:10, s. 822-826
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Tidskriftsartikel (refereegranskat)abstract
- The present study authenticates the fabrication of nickel oxide porous shaped nanostructure by hydrothermal method. The novel and functionalized nickel oxide nanomaterial were visualized by using scanning electron microscopy (SEM) and X-ray diffraction techniques (XRD). NiO nanomaterial advertised sensitive, selective and attracted morphology for the development of peptone biosensor. Phenylalanine displays a soft template and growth directing agent for the developing of nickel oxide low dimension nanostructures. The nickel oxide nanomaterial together with protease possesses tremendous role towards the oxidation potential phenomena and transfer of anodic electro-catalytic current for the peptone. The generation of low potential electrochemical signals exhibited the determination of peptone by utilizing different electrochemical techniques for the given concentration ranging from 0.1 mM to 2.5 mM with the measured limit of detection about 0.002 mM with a sensitivity of 107200 μA/mMCm2. The well-defined and highly developed sensor system provides the standard platform for the fabrication and functioning of new devices that are helpful for the determination of many biological macromolecules. The presented peptone biosensor is highly selective, sensitive, and reproducible that could also be useful for the determination of peptone from various milk samples.
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