27 research outputs found
Yoğun bakım hastalarında diyabetes mellitus malnütrisyonla ilişkili midir? Diyabet ve malnütrisyon
No full textAmaç: Hastalık türleri ve tedavi yöntemleri yetersiz beslenmenin alevlenmesine yol açabilir. Bu çalışmada, üçüncü basamak bir hastanenin yoğun bakım ünitesinde (YBÜ) diyabetes mellituslu hastaların beslenme durumunun araştırılması amaçlandı.Yöntem: Yüz doksan iki hasta çalışmaya dahil edildi ve iki gruba ayrıldı. Çalışma grubuna tip 2 diyabetli 77 hasta, kontrol grubuna ise diyabeti olmayan 115 hasta alındı. Beslenme durumu ve riski NRS (Nutritional Risk Screening) 2002, Nutric skoru, MNA (Mini-Nutritional Assessment) ve MUST (Malnutrition Universal Screening Tool) testleri ile değerlendirildi.Bulgular: Gruplar NRS 2002 (3.37 ± 1.84 vs. 3.93 ± 1.72, p = 0.075), Nutric skoru (4.61 ± 1.85 vs. 4.56 ± 1.85, p = 0.869), MNA (8.0 ± 3.1 vs. 7.1 ± 3.2, p = 0.068) ve MUST skoruna (1.62 ± 1.46 vs. 1.81 ± 1.59, p = 0.456) göre benzer bulundu.Sonuç: Bu çalışmada, malnütrisyon riski her iki grupta benzer bulundu. Bu sonuç malnütrisyonun diyabete ek olarak eşlik eden diğer hastalıklarla da ilişkili olduğunu düşündürmektedir.Aim: Types of diseases and treatment modalities can also lead to the exacerbation of malnutrition. The aim of this study was to investigate nutritional status of patients with diabetes mellitus in the intensive care unit of a tertiary hospital.Materials and methods: One hundred and ninety-two patients were enrolled and divided into two groups. The study group comprised of 77 patients with type 2 diabetes and the control group comprised of 115 patients without diabetes. The nutritional risk assessment was tested with NRS (Nutritional Risk Screening) 2002, Nutric score, MNA (Mini-Nutritional Assessment) and MUST (Malnutrition Universal Screening Tool). Results: The groups were comparable according to the NRS 2002 (3.37 ± 1.84 vs. 3.93 ± 1.72, p = 0.075), Nutric score (4.61 ± 1.85 vs. 4.56 ± 1.85, p = 0.869), MNA (8.0 ± 3.1 vs. 7.1 ± 3.2, p = 0.068) and MUST score (1.62 ± 1.46 vs. 1.81 ± 1.59, p = 0.456). Conclusion: In this study, the risk of malnutrition is comparable in both groups. This result may suggest that malnutrition is also related to co-morbidities in addition to diabetes
D-Dimer/Fibrinogen Ratio as a Prominent Predictor of Mortality in COVID-19 Patients Admitted To the Intensive Care Unit
No full textPurpose: In this retrospective cohort study, evaluating the role of the D-dimer/fibrinogen ratio in predicting the in-hospital mortality rate of COVID-19 regardless of the presence of comorbidities was aimed.
Materials and Methods: This retrospective cohort study included patients admitted to the intensive care unit. The demographic data of the patients (sex, age, body mass index, comorbidities), their prognostic clinical scores, laboratory results, and need for and duration of invasive mechanical ventilation (IMV) were recorded.
Results: The rates of chronic renal diseases, acute renal failure, cardiac diseases, and severe sepsis were significantly higher in the exitus group. It was found that lower levels of lymphocytes were associated with increased mortality. Furthermore, neutrophil counts and the neutrophil to lymphocyte ratio (NLR) were associated with increased mortality. A higher D-dimer/fibrinogen ratio (DDFR) was a predictor of mortality but not a predictor of the duration of hospitalization in the ICU.
Conclusion: DDFR has a potential impact in anticipating mortality rates in COVID-19 patients
A New Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications
No full text<p>This database is proposed by the Realistic 3D research group at Mid Sweden University, Sundsvall, Sweden. The database details are explained thoroughly in a submission to QoMEX 2024, and the database has been reviewed as part of the submission. <strong>This work will be presented at QoMEX 2024 at Karlshamn, Sweden</strong>.</p>
<p>The database README file will be slightly updated to reflect the citation information as given below, after the QoMEX 2024 conference. You can use this database in your work, provided that you cite the database as below:</p>
<blockquote>
<p>Zerman, E., Gond, M., Takhtardeshir, S., Olsson, R., & Sjöström, M. (2024). A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications. <em>The 16th International Conference on Quality of Multimedia Experience (QoMEX)</em>. IEEE. (<strong>Accepted - to be presented</strong>)</p>
</blockquote>
<p>BibTeX:</p>
<blockquote>
<p>@inproceedings{zerman2024spherical,<br> title = {A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications},<br> author = {Zerman, Emin and Gond, Manu and Takhtardeshir, Soheib and Olsson, Roger and Sj{\"o}str{\"o}m, M{\aa}rten},<br> booktitle = {The 16th International Conference on Quality of Multimedia Experience (QoMEX)},<br> year = {2024},<br> organization = {IEEE},<br> note = {(Accepted - to be presented)}<br>}</p>
</blockquote>
<p>This database contains 20 spherical light fields of 1 x 60 views, captured with a consumer-grade 360-degree camera: Insta360 X3. The capture is done using a dolly to ensure the separation between consecutive views is exactly 1 cm. In addition to the original captures, this database also provides outputs for two different use cases: compression and view synthesis. Several parameters, features, and objective quality metric values are also included.</p>
Noninvasive auto-titrating ventilation (AVAPS-AE) versus average volume-assured pressure support (AVAPS) ventilation in hypercapnic respiratory failure patients: reply
No full textNoninvasive auto-titrating ventilation (AVAPS-AE) versus average volume-assured pressure support (AVAPS) ventilation in hypercapnic respiratory failure patients: reply
No full textBASICS DATASET: Broad Quality Assessment of Static Point Clouds in a Compression Scenario
No full text<p>Point clouds have become increasingly prevalent in representing 3D scenes within virtual environments, alongside 3D meshes. Their ease of capture has facilitated a wide array of applications on mobile devices, including smartphones and other microcontrollers. Notably, point cloud compression has reached an advanced stage and being standardized. However, the availability of quality assessment datasets, which are essential for the development of improved objective quality metrics, remains limited.<br>We introduce BASICS, a large-scale quality assessment dataset tailored for static point clouds. The BASICS dataset comprises 75 unique point clouds, each compressed with four different algorithms, resulting in the evaluation of nearly 1500 point clouds by 3500 unique participants.</p>
<div>For a detailed explanation of the dataset and the analysis done, please refer to the related publication:</div>
<div> </div>
<div>@ARTICLE{10403987,<br> author={Ak, Ali and Zerman, Emin and Quach, Maurice and Chetouani, Aladine and Smolic, Aljosa and Valenzise, Giuseppe and Le Callet, Patrick},<br> journal={IEEE Transactions on Multimedia}, <br> title={BASICS: Broad Quality Assessment of Static Point Clouds in a Compression Scenario}, <br> year={2024},<br> pages={1-13},<br> doi={10.1109/TMM.2024.3355642}}</div>
<div> </div>
<div>BASICS paper is accepted to be published in IEEE TMM. The above article will be updated later on with the correct DOI.</div>
<p><br>The BASICS dataset was previously used for the ICIP 2023 ICIP PCQVA Grand Challenge. Since the challenge is over, we are making it public for the community to build upon! Check the link below for the ICIP 2023 PCQVA Challenge Page:<br>https://sites.google.com/view/icip2023-pcvqa-grand-challenge/</p>
<p> </p>
Knowledge and Attitudes Toward Organ Donation and Brain Death Among Medical Staff of Intensive Care Units
No full textMiX-LFQDB: MIUN-Xidian Light Field Quality Database for Compressed Light Field Images using Learning-based vs. Conventional Methods
No full textThis database was created by a joint effort from the Realistic 3D research group at Mid Sweden University (Sundsvall, Sweden) and the School of Telecommunications Engineering in Xidian University (Xi'an, China). The database details are explained thoroughly in the publication, which is accepted (and to appear in the proceedings of) the 27th IEEE International Workshop on Multimedia Signal Processing (MMSP) in 2025.
You can use this database in your work under the Creative Commons Attribution 4.0 International (CC-BY 4.0) licence, provided that you cite the database as below:
Zerman, E., Takhtardeshir, S., Trioux, A., Qin, J., Wu, W., Olsson, R., & Sjöström, M. (2025). Subjective Visual Quality Assessment of Compressed Light Field Images: Learning-based vs. Conventional Methods. The 27th IEEE International Workshop on Multimedia Signal Processing (MMSP).DOI: (To be updated after publication)
BibTeX:
@inproceedings{zerman2025subjective title = {Subjective Visual Quality Assessment of Compressed Light Field Images: Learning-based vs. Conventional Methods}, author = {Zerman, Emin and Takhtardeshir, Soheib and Trioux, Anthony and Qin, Jianlong and Wu, Wenjie and Olsson, Roger and Sj{\"o}str{\"o}m, M{\aa}rten}, booktitle = {The 27th IEEE International Workshop on Multimedia Signal Processing (MMSP)}, year = {2025}, organization = {IEEE}}
This database contains 85 light field stimuli, rendered as pseudo-video sequences with a spiral trajectory, and the subjective quality scores collected by 40 people in two different countries (19 in Mid Sweden University, Sweden; and 21 in Xidian University, China). The 85 LF stimuli were generated from 5 source LFs using 4 different LF compression methods, comprising two conventional methods (H.265/HEVC and JPEG Pleno) and two learning-based methods (RLVC and EF-VAE)
A New Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications
No full textThis database is created by the Realistic 3D research group at Mid Sweden University, Sundsvall, Sweden. The database details are explained thoroughly in the publication which was published at the 16th International Conference on Quality of Multimedia Experience (QoMEX) in 2024. This database was also reviewed as part of the submission and publication process.
You can use this database in your work under the Creative Commons Attribution 4.0 International (CC-BY 4.0) licence, provided that you cite the database as below:
Zerman, E., Gond, M., Takhtardeshir, S., Olsson, R., & Sjöström, M. (2024). A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications. The 16th International Conference on Quality of Multimedia Experience (QoMEX). IEEE. DOI: 10.1109/QoMEX61742.2024.10598264
BibTeX:
@inproceedings{zerman2024spherical, title = {A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications}, author = {Zerman, Emin and Gond, Manu and Takhtardeshir, Soheib and Olsson, Roger and Sj{\"o}str{\"o}m, M{\aa}rten}, booktitle = {The 16th International Conference on Quality of Multimedia Experience (QoMEX)}, year = {2024}, organization = {IEEE}, doi = {10.1109/QoMEX61742.2024.10598264}}
This database contains 20 spherical light fields of 1 x 60 views, captured with a consumer-grade 360-degree camera: Insta360 X3. The capture was done using a dolly to ensure the separation between consecutive views is exactly 1 cm. In addition to the original captures, this database also provides outputs for two different use cases: compression and view synthesis. Several parameters, features, and objective quality metric values are also included.
N.B. Only the README file and this description have been updated after the initial submission on 2024-02-09
Noninvasive auto-titrating ventilation (AVAPS-AE) versus average volume-assured pressure support (AVAPS) ventilation in hypercapnic respiratory failure patients.
No full textAuto-titrating noninvasive ventilation (NIV) has been developed as a new mode applying variable expiratory-positive airway pressure (EPAP) in addition to variable inspiratory pressures (IPAP), both to deliver targeted tidal volume (VT) and to eliminate upper airway resistance. The purpose of this study is to evaluate whether NIV with auto-titrating mode will decrease more PaCO2 within a shorter time compared to volume-assured mode in hypercapnic intensive care unit (ICU) patients. The hypercapnic respiratory failure patients treated with average volume assured pressure support- automated EPAP mode (group1) were compared with those treated with average volume-assured pressure support mode (group2). Two groups were matched with each other according to baseline diagnoses, demographic characteristics, arterial blood gas values, target VT settings and daily NIV usage times. Built-in software was used to gather the ventilatory parameters. Twenty-eight patients were included in group 1, and 22 in group 2. The decrease in PaCO2 had been achieved within a shorter time period in group 1 (p < 0.05). This response was more pronounced within the first 6 h (mean reduction in PaCO2 was 7 +/- 7 mmHg in group 1 and 2 +/- 5 mmHg in group 2, p = 0.025), and significantly greater reductions in PaCO2 (18 +/- 11 mmHg in group 1 and 9 +/- 8 mmHg in group 2, p = 0.008) and plasma HCO3 levels (from 32 to 30 mEq and from 35 to 35 mEq, p = 0.007) took place within first 4 days. While mean IPAP was similar in both groups, maximum EPAP, mean VT and leak were significantly higher in group 1 than in group 2 (p < 0.05). Results of this preliminary study suggest that, this new auto-titrating NIV mode may provide additional benefit on volume-assured mode in decreasing PaCO2 more efficiently and rapidly in hypercapnic ICU patients
