Tag: pubmed

J Long Term Eff Med Implants. 2022;32(1):65-71. doi: 10.1615/JLongTermEffMedImplants.2021039884.

ABSTRACT

The aim of this retrospective study was to evaluate the long-term predictability of treatment using implants with hydrophobic and hydrophilic surfaces, according to clinical parameters and survival rates. Records from all patients who received dental implants between January 2013 and December 2014 at ILAPEO College were fully evaluated by two graduate dentists. Records with incomplete or unclear data were excluded from the study. The variables evaluated were demographic data, design of implants and prosthetic components, type of loading, data related to the patients’ general health, and survival of implants and prostheses. The final retrospective sample comprised 776 patients with 2707 implants, with up to 5 years of follow-up. Survival rates of implants and prostheses were 97.93% and 98.77%, respectively. Implants with hydrophobic (97.87%) and hydrophilic (98.34%) surfaces exhibited similar survival rates. Considering the different types of loading, there was no statistically significant difference between loading protocols regarding implant survival rates. Unsuitable healing capacity, uncooperative and not motivated patient, loss of prosthesis, and peri-implant bone loss were confirmed statistically to be factors that may contribute to implant loss, according to hazard ratio and odds ratio. The present study showed similar and high overall survival rates for implant with both types of surfaces, in the long term. The surface treatment, implant model and loading protocol had no significant influence on implant loss. Therefore, the evaluated implant systems were able to offer a high predictability for both hydrophobic and hydrophilic implants.

PMID:35377995 | DOI:10.1615/JLongTermEffMedImplants.2021039884

J Long Term Eff Med Implants. 2022;32(1):25-32. doi: 10.1615/JLongTermEffMedImplants.2021038617.

ABSTRACT

Implant therapy is a treatment option to ensure prosthesis survival rate and it is also done as a fixed dental prosthesis for replacing single and multiunit gaps. Posterior maxilla often has insufficient bone quality and quantity; for this reason it makes implant placement challenging in the site. Posterior edentulous maxilla presents special challenges to implant surgeons that are unique to this region compared to other regions of the maxilla. Thus, the aim of this study is to determine the common implant dimensions used in posterior maxilla. Completed case sheets were collected from a private dental hospital software system. Case sheets were taken from June 2019 to March 2020. Data was retrieved and evaluated by two reviewers. The parameters taken were patients, age groups, gender, teeth indicated for implants (maxillary premolars and molars), implant height, and implant width. Two-hundred fifty-four implants have been placed on the posterior maxilla of which 139 were premolars and 115 were molars. There was no statistical significance between the implants placed in both males and females (p value: 0.274). Between the age groups, the highest number of implants was seen in 41-60 years (n = 146) followed by 17-40 years (n = 78) and finally > 61 years (n = 30). The p value was 0.000, which was statistically significant. Various implant sizes for posterior maxilla have been introduced due to its challenging site. Thus in our study, we can see there is a difference in sizes for premolars and molars. Implant dimensions with increased height are used in the premolars compared to the molars. Implant dimensions with increased width are used in the molars compared to the premolars. In general, implant width and implant height can range from 3.6 to 4.5 mm and implant height ranging from 9.50 to 12.00 mm.

PMID:35377991 | DOI:10.1615/JLongTermEffMedImplants.2021038617

J Long Term Eff Med Implants. 2022;32(1):7-18. doi: 10.1615/JLongTermEffMedImplants.2021038874.

ABSTRACT

INTRODUCTION: Mini-implant assisted rapid palatal expansion (MARPE) is gradually becoming the treatment of choice to correct the transverse dimension, exceeding the limitations of conventional RME devices. One of the key factors for orthodontic diagnosis and treatment planning apart from a stable occlusion is a balanced and aesthetic facial profile that is influenced by maxillary expansion. Similarly, it also affects the anatomy and physiology of the nasal cavity since nasal airflow is a continuous stimulus for lowering of the palate and for lateral maxillary growth. Hence, there is a need to conduct further research on the effects of MARPE on the facial soft tissues as well as the airway, enabling the orthodontist to reach a more accurate diagnosis as well as aid in the treatment planning process.

AIMS AND OBJECTIVES: This retrospective three-dimensional study was planned and designed with the objective of measuring facial soft tissue and airway changes in individuals treated with mini-implant assisted rapid palatal expansion (MARPE) using CBCT.

MATERIALS AND METHODS: This study was carried out on CBCT records of 10 patients in the age group of 18-30 years. These records were then imported into Romexis software and calibrated. The facial soft tissue and airway parameters were measured for each individual at selected landmarks and compared before and after expansion.

RESULT: Statistically significant differences in the soft tissue parameters were observed, which included an increased H-angle, increased soft tissue subnasal to H-line and a decreased soft palate surface area after MARPE.

PMID:35377989 | DOI:10.1615/JLongTermEffMedImplants.2021038874

PLoS One. 2022 Apr 4;17(4):e0266489. doi: 10.1371/journal.pone.0266489. eCollection 2022.

ABSTRACT

Existing lane-changing models generally neglect the detailed modeling of lane-changing actions and model lane-changing only as an instantaneous event. In this study, an intertunnel weaving section was taken as the background, the lane-changing duration and distance in the lane-changing process were taken as the main research objects. The detailed modeling of a lane-changing action was emphasized. Aerial videos of intertunnel weaving sections were collected, and accurate vehicle trajectory data were extracted. Basic data analysis shows that the lane-changing duration has a lognormal distribution and the lane-changing distance has a normal distribution. To analyze the difference of the lane-changing behavior characteristics in different lane-changing environments, based on the lead spacing and lag spacing in the target lane, a hierarchical clustering algorithm was applied to classify the lane-changing environment into six different types. Then, a deep neural network regression model was applied to model the lane-changing process for each environment type. The results show that the horizontal distribution, vertical distribution and statistical characteristics of the lane changing points under different lane-changing environments are significantly different. The prediction accuracy of the lane-changing distance after classification is improved by at least 61%, and the prediction accuracy of the lane-changing duration after classification is improved by at least 57%. It is also found that lane-changing behavior characteristics with large or small lag spacing are easier to predict, while in the other cases, the randomness of the lane-changing behavior characteristics is more obvious. The research results can be incorporated into lane-changing decision assistance systems and micro traffic simulation models to make the assistance system safer and more effective, and the simulation outputs should be more realistic and accurate.

PMID:35377917 | DOI:10.1371/journal.pone.0266489

PLoS One. 2022 Apr 4;17(4):e0265381. doi: 10.1371/journal.pone.0265381. eCollection 2022.

ABSTRACT

Article-level measures of publication impact (alternative metrics or altmetrics) can help authors and other stakeholders assess engagement with their research and the success of their communication efforts. The wide variety of altmetrics can make interpretation and comparative assessment difficult; available summary tools are either narrowly focused or do not reflect the differing values of metrics from a stakeholder perspective. We created the EMPIRE (EMpirical Publication Impact and Reach Evaluation) Index, a value-based, multi-component metric framework for medical publications. Metric weighting and grouping were informed by a statistical analysis of 2891 Phase III clinical trial publications and by a panel of stakeholders who provided value assessments. The EMPIRE Index comprises three component scores (social, scholarly, and societal impact), each incorporating related altmetrics indicating a different aspect of engagement with the publication. These are averaged to provide a total impact score and benchmarked so that a score of 100 equals the mean scores of Phase III clinical trial publications in the New England Journal of Medicine (NEJM) in 2016. Predictor metrics are defined to estimate likely long-term impact. The social impact component correlated strongly with the Altmetric Attention Score and the scholarly impact component correlated modestly with CiteScore, with the societal impact component providing unique insights. Analysis of fresh metrics collected 1 year after the initial dataset, including an independent sample, showed that scholarly and societal impact scores continued to increase, whereas social impact scores did not. Analysis of NEJM ‘notable articles’ showed that observational studies had the highest total impact and component scores, except for societal impact, for which surgical studies had the highest score. The EMPIRE Index provides a richer assessment of publication value than standalone traditional and alternative metrics and may enable medical researchers to assess the impact of publications easily and to understand what characterizes impactful research.

PMID:35377894 | DOI:10.1371/journal.pone.0265381

PLoS One. 2022 Apr 4;17(4):e0266570. doi: 10.1371/journal.pone.0266570. eCollection 2022.

ABSTRACT

BACKGROUND: Healthcare workers, including residents, are prone to various mental health disorders especially given the context of the COVID-19 pandemic. Residents, particularly, are already under undue stress due to their respective training program demands.

METHODS: This cross-sectional, online survey-based study from August to November 2020 collected demographic and mental health measurements from all residents at the Aga Khan University Hospital, Nairobi. The questionnaire investigated demographic variables, information regarding direct care of COVID-19 patients, prior history of mental health and mental health outcomes using the Patient Health Questionnaire, Generalized Anxiety Disorder scale, Insomnia Severity Index, Impact of Event Scale-Revised Questionnaire and Stanford Professional Fulfillment Index Questionnaire.

RESULTS: A total of 100 residents completed the survey (participation rate 77.5%). Participants were about equal in gender (women [53%]), with a median age of 31.28 years, and majority were single (66.7%). A total of 66 participants (66%) were directly engaged in COVID-19 care. Depression: 64.3%, anxiety: 51.5%, insomnia: 40.5%, distress: 35.4%, and burnout: 51.0% were reported in all participants. Statistical significance was found in median depression, professional fulfillment and interpersonal disengagement when comparing frontline resident directly involved in care of COVID-19 patient versus second line residents.

CONCLUSION: Residents directly involved with caring for COVID-19 patients had statistically higher incidences of depression and interpersonal disengagement and lower professional fulfillment compared to second line residents. Keeping in mind the limited resources in sub-Saharan Africa, urgent and geographically specific strategies are needed to help combat mental health disorders in this specific population.

PMID:35377909 | DOI:10.1371/journal.pone.0266570

PLoS Negl Trop Dis. 2022 Apr 4;16(4):e0010297. doi: 10.1371/journal.pntd.0010297. eCollection 2022 Apr.

ABSTRACT

Dengue, a mosquito transmitted febrile viral disease, is a serious public health concern in Bangladesh. Despite significant number of incidences and reported deaths each year, there are inadequate number of studies relating the temporal trends of the clinical parameters as well as socio-demographic factors with the clinical course of the disease. Therefore, this study aims to associate the clinical parameters, demographic and behavioral factors of the dengue patients admitted in a tertiary care hospital in Dhaka, Bangladesh during the 2019 outbreak of dengue with the clinical course of the disease. Data were collected from the 336 confirmed dengue in-patients and analyzed using SPSS 26.0 software. Majority of the patients were male (2.2 times higher than female) who required longer time to recover compared to females (p < 0.01), urban resident (54.35%) and belonged to the age group of 18-40 years (73.33%). Dengue fever (90.77%) and dengue hemorrhagic fever (5.95%) were reported in most of the dengue patients while fever (98%) was the most frequently observed symptom. A significantly positive association was found between patient’s age and number of manifested symptoms (p = 0.013). Average duration of stay in the hospital was 4.9 days (SD = 1.652) and patient’s recovery time was positively correlated with delayed hospitalization (p < 0.01). Additionally, recovery time was negatively correlated with initial blood pressure (both systolic (p = 0.001, and diastolic (p = 0.023)) and platelet count (p = 0.003) of the patients recorded on the first day of hospitalization. Finally, a statistical model was developed which predicted that, hospital stay could be positively associated with an increasing trend of temperature, systolic blood pressure and reduced platelets count. Findings of this study may be beneficial to better understand the clinical course of the disease, identify the potential risk factors and ensure improved patient management during future dengue outbreaks.

PMID:35377886 | DOI:10.1371/journal.pntd.0010297

PLoS Comput Biol. 2022 Apr 4;18(4):e1009309. doi: 10.1371/journal.pcbi.1009309. Online ahead of print.

ABSTRACT

For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance.

PMID:35377867 | DOI:10.1371/journal.pcbi.1009309

PLoS One. 2022 Apr 4;17(4):e0262204. doi: 10.1371/journal.pone.0262204. eCollection 2022.

ABSTRACT

BACKGROUND: Washington, DC, and sub-Saharan Africa are both affected by generalized HIV epidemics. However, care for persons living with HIV (PLWH) and clinical outcomes may differ in these geographically and culturally diverse areas. We compared patient and clinical site characteristics among adult persons living with HIV (PLWH) enrolled in two longitudinal HIV cohort studies-the African Cohort Study (AFRICOS) and the DC Cohort.

METHODS: The DC Cohort is a clinic-based city-wide longitudinal cohort comprised of PLWH attending 15 HIV clinics in Washington, DC. Patients’ socio-demographic characteristics, clinical evaluations, and laboratory data are retrospectively collected from electronic medical records and limited manual chart abstraction. AFRICOS is a prospective observational cohort of PLWH and uninfected volunteers attending 12 select HIV care and treatment facilities in Nigeria, Kenya, Uganda and Tanzania. AFRICOS study participants are a subset of clinic patients who complete protocol-specific visits every 6 months with history and physical examination, questionnaire administration, and blood/sputum collection for ascertainment of HIV outcomes and comorbidities, and neurocognitive and functional assessments. Among participants aged ≥ 18 years, we generated descriptive statistics for demographic and clinical characteristics at enrollment and follow up and compared them using bivariable analyses.

RESULTS: The study sample included 2,774 AFRICOS and 8,420 DC Cohort participants who enrolled from January 2013 (AFRICOS)/January 2011 (DC Cohort) through March 2018. AFRICOS participants were significantly more likely to be women (58.8% vs 27.1%) and younger (83.3% vs 61.1% aged < 50 years old) and significantly less likely to be MSM (only 0.1% of AFRICOS population reported MSM risk factor) than DC Cohort. Similar rates of current viral suppression (about 75% of both samples), hypertension, hepatitis B coinfection and alcohol use were observed. However, AFRICOS participants had significantly higher rates of CD4<200 and tuberculosis and significantly lower rates of obesity, DM, hepatitis C coinfection and syphilis.

CONCLUSIONS: With similar viral suppression outcomes, but many differences between our cohorts noted, the combined sample provides unique opportunities to assess and compare HIV care and treatment outcomes in the U.S. and sub-Saharan Africa. Comparing these two cohorts may inform care and treatment practices and may pave the way for future pathophysiologic analyses.

PMID:35377881 | DOI:10.1371/journal.pone.0262204

IEEE J Biomed Health Inform. 2022 Apr 4;PP. doi: 10.1109/JBHI.2022.3164570. Online ahead of print.

ABSTRACT

Positron Emission Tomography (PET) has become a preferred imaging modality for cancer diagnosis, radiotherapy planning, and treatment responses monitoring. Accurate and automatic tumor segmentation is the fundamental requirement for these clinical applications. Deep convolutional neural networks have become the state-of-the-art in PET tumor segmentation. The normalization process is one of the key components for accelerating network training and improving the performance of the network. However, existing normalization methods either introduce batch noise into the instance PET image by calculating statistics on batch level or introduce background noise into every single pixel by sharing the same learnable parameters spatially. In this paper, we proposed an attentive transformation (AT)-based normalization method for PET tumor segmentation. We exploit the distinguishability of breast tumor in PET images and dynamically generate dedicated and pixel-dependent learnable parameters in normalization via the transformation on a combination of channel-wise and spatial-wise attentive responses. The attentive learnable parameters allow to re-calibrate features pixel-by-pixel to focus on the high-uptake area while attenuating the background noise of PET images. Our experimental results on two real clinical datasets show that the AT-based normalization method improves breast tumor segmentation performance when compared with the existing normalization methods.

PMID:35377850 | DOI:10.1109/JBHI.2022.3164570