scholarly journals Early Tooth Loss after Periodontal Diagnosis: Development and Validation of a Clinical Decision Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1363
Author(s):  
Francisco Santos ◽  
Frederico Beato ◽  
Vanessa Machado ◽  
Luís Proença ◽  
José João Mendes ◽  
...  
Keyword(s):  
Tooth Loss ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Clinical Attachment Loss ◽  
Dental Hospital ◽  
Total Variability ◽  
Tooth Type ◽  
The University ◽  
Development And Validation ◽  
Early Tooth Loss

The aim of this study was to develop and validate a predictive early tooth loss multivariable model for periodontitis patients before periodontal treatment. A total of 544 patients seeking periodontal care at the university dental hospital were enrolled in the study. Teeth extracted after periodontal diagnosis and due to periodontal reasons were recorded. Clinical and sociodemographic variables were analyzed, considering the risk of short-term tooth loss. This study followed the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines for development and validation, with two cohorts considered as follows: 455 patients in the development phase and 99 in the validation phase. As a result, it was possible to compute a predictive model based on tooth type and clinical attachment loss. The model explained 25.3% of the total variability and correctly ranked 98.9% of the cases. The final reduced model area under the curve (AUC) was 0.809 (95% confidence interval (95% CI): 0.629–0.989) for the validation sample and 0.920 (95% CI: 0.891–0.950) for the development cohort. The established model presented adequate prediction potential of early tooth loss due to periodontitis. This model may have clinical and epidemiologic relevance towards the prediction of tooth loss burden.

scholarly journals Early Tooth Loss after Periodontal Diagnosis: Development and Validation of a Clinical Decision Model

2021 ◽  
Author(s):  
Francisco Santos ◽  
Frederico Beato ◽  
Vanessa Machado ◽  
Luís Proença ◽  
José João Mendes ◽  
...  
Keyword(s):  
Tooth Loss ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Short Term ◽  
Clinical Attachment Loss ◽  
Dental Hospital ◽  
Total Variability ◽  
Tooth Type ◽  
Development And Validation ◽  
Early Tooth Loss

The aim of this study was to develop and validate a predictive early tooth loss multivariable model for periodontitis patients before periodontal treatment. A total of 544 patients seeking periodontal care at a university dental hospital were enrolled in the study. Teeth extracted after periodontal diagnosis and due to periodontal reasons were recorded. Clinical and sociodemographic variables were analyzed, considering the risk of short-term tooth loss. This study followed the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines for development and validation, with two cohorts considered as follows: 455 patients in the development phase and 99 in the validation phase. As a result, it was possible to compute a predictive model based on tooth type and clinical attachment loss. The model explained 25.3% of the total variability and correctly ranked 98.9% of the cases. The final reduced model area under the curve (AUC) was 0.809 (95% Confidence Interval (95% CI): 0.629 - 0.989) for the validation sample and 0.920 (95% CI: 0.891 - 0.950) for the development cohort. The established model presented adequate prediction potential of early tooth loss due to periodontitis. This model may have clinical and epidemiologic relevance towards the prediction of tooth loss burden.

Integrating Legacy Laboratory Information Systems into a Client-Server World: The University of Minnesota Clinical Workstation (CWS) Project

1995 ◽  
Vol 34 (03) ◽  
pp. 289-296 ◽  
Author(s):  
B. H. Sielaff ◽  
D. P. Connelly ◽  
K. E. Willard
Keyword(s):  
Information Systems ◽  
Clinical Decision ◽  
Database Management System ◽  
University Of Minnesota ◽  
Client Server ◽  
Clinical Workstation ◽  
Future Hospital ◽  
The Cost ◽  
The University ◽  
Laboratory Information Systems

Abstract:The development of an innovative clinical decision-support project such as the University of Minnesota’s Clinical Workstation initiative mandates the use of modern client-server network architectures. Preexisting conventional laboratory information systems (LIS) cannot be quickly replaced with client-server equivalents because of the cost and relative unavailability of such systems. Thus, embedding strategies that effectively integrate legacy information systems are needed. Our strategy led to the adoption of a multi-layered connection architecture that provides a data feed from our existing LIS to a new network-based relational database management system. By careful design, we maximize the use of open standards in our layered connection structure to provide data, requisition, or event messaging in several formats. Each layer is optimized to provide needed services to existing hospital clients and is well positioned to support future hospital network clients.

Development and Validation of Spectrophotometric and Liquid Chromatographic Methods for Estimation of Tigecycline in Injections

2020 ◽  
Vol 13 (5) ◽  
pp. 5148-5154
Author(s):  
Sagar Suman Panda ◽  
Ravi Kumar B.V.V.
Keyword(s):  
Area Under The Curve ◽  
Reversed Phase ◽  
Equal Concentration ◽  
Pharmaceutical Dosage Form ◽  
Liquid Chromatographic Method ◽  
Array Detection ◽  
The Difference ◽  
The One ◽  
Development And Validation ◽  
Liquid Chromatographic

Three new analytical methods were optimized and validated for the estimation of tigecycline (TGN) in its injection formulation. A difference UV spectroscopic, an area under the curve (AUC), and an ultrafast liquid chromatographic (UFLC) method were optimized for this purpose. The difference spectrophotometric method relied on the measurement of amplitude when equal concentration solutions of TGN in HCl are scanned against TGN in NaOH as reference. The measurements were done at 340 nm (maxima) and 410nm (minima). Further, the AUC under both the maxima and minima were measured at 335-345nm and 405-415nm, respectively. The liquid chromatographic method utilized a reversed-phase column (150mm×4.6mm, 5µm) with a mobile phase of methanol: 0.01M KH2PO4 buffer pH 3.5 (using orthophosphoric acid) in the ratio 80:20 %, v/v. The flow rate was 1.0ml/min, and diode array detection was done at 349nm. TGN eluted at 1.656min. All the methods were validated for linearity, precision, accuracy, stability, and robustness. The developed methods produced validation results within the satisfactory limits of ICH guidance. Further, these methods were applied to estimate the amount of TGN present in commercial lyophilized injection formulations, and the results were compared using the One-Way ANOVA test. Overall, the methods are rapid, simple, and reliable for routine quality control of TGN in the bulk and pharmaceutical dosage form. 

scholarly journals Blood Pressure and Tooth Loss: A Large Cross-Sectional Study with Age Mediation Analysis

2021 ◽  
Vol 18 (1) ◽  
pp. 285
Author(s):  
José João Mendes ◽  
João Viana ◽  
Filipe Cruz ◽  
Dinis Pereira ◽  
Sílvia Ferreira ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Tooth Loss ◽  
Cross Sectional Study ◽  
Mediation Effect ◽  
Sectional Study ◽  
Cross Sectional ◽  
Undiagnosed Hypertension ◽  
Dental Hospital ◽  
Continuous Measures ◽  
Effect Of Age

We aimed to investigate the association between blood pressure (BP) and tooth loss and the mediation effect of age. A cross-sectional study from a reference dental hospital was conducted from September 2017 to July 2020. Single measures of BP were taken via an automated sphygmomanometer device. Tooth loss was assessed through oral examination and confirmed radiographically. Severe tooth loss was defined as 10 or more teeth lost. Additional study covariates were collected via sociodemographic and medical questionnaires. A total of 10,576 patients were included. Hypertension was more prevalent in severe tooth loss patients than nonsevere tooth lost (56.1% vs. 39.3%, p < 0.001). The frequency of likely undiagnosed hypertension was 43.4%. The adjusted logistic model for sex, smoking habits and body mass index confirmed the association between continuous measures of high BP and continuous measures of tooth loss (odds ratio (OR) = 1.05, 95% CI: 1.03–1.06, p < 0.001). Age mediated 80.0% and 87.5% of the association between periodontitis with both systolic BP (p < 0.001) and diastolic BP (p < 0.001), respectively. Therefore, hypertension and tooth loss are associated, with a consistent mediation effect of age. Frequency of undiagnosed hypertension was elevated. Age, gender, active smoking, and BMI were independently associated with raised BP.

scholarly journals Dental Education during the COVID-19 Pandemic in a German Dental Hospital

2021 ◽  
Vol 18 (13) ◽  
pp. 6905
Author(s):  
Julia Winter ◽  
Roland Frankenberger ◽  
Frank Günther ◽  
Matthias Johannes Roggendorf
Keyword(s):  
Undergraduate Students ◽  
Dental Treatment ◽  
Dental Education ◽  
Full Recovery ◽  
Patient Treatment ◽  
Mouth Rinse ◽  
Rubber Dam ◽  
Dental Hospital ◽  
The University ◽  
Student Assistants

Due to the SARS-CoV-2 pandemic, dental treatment performed by undergraduate students at the University of Marburg/Germany was immediately stopped in spring 2020 and stepwise reinstalled under a new hygiene concept until full recovery in winter 2020/21. Patient treatment in the student courses was evaluated based on three aspects: (1) Testing of patients with a SARS-CoV-2 Rapid Antigen (SCRA) Test applied by student assistants (SA); (2) Improved hygiene regimen, with separated treatment units, cross-ventilation, pre-operative mouth rinse and rubber dam application wherever possible; (3) Recruitment of patients: 735 patients were pre-registered for the two courses; 384 patients were treated and a total of 699 tests with the SCRA test were performed by SAs. While half of the patients treated in the course were healthy, over 40% of the patients that were pre-registered but not treated in the course revealed a disease being relevant to COVID (p < 0.001). 46 patients had concerns to visit the dental hospital due to the increase of COVID incidence levels, 14 persons refused to be tested. The presented concept was suitable to enable patient treatment in the student course during the SARS-CoV-2 pandemic.

scholarly journals A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 169
Author(s):  
Sergi Gómez-Quintana ◽  
Christoph E. Schwarz ◽  
Ihor Shelevytsky ◽  
Victoriya Shelevytska ◽  
Oksana Semenova ◽  
...  
Keyword(s):  
Patent Ductus Arteriosus ◽  
Heart Defects ◽  
Ductus Arteriosus ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Heart Sounds ◽  
Decision Tree Classifier ◽  
Support Tool ◽  
Tree Classifier ◽  
Patent Ductus

The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.

scholarly journals Predicting drowning from sea and weather forecasts: development and validation of a model on surf beaches of southwestern France

2021 ◽  
pp. injuryprev-2020-044092
Author(s):  
Éric Tellier ◽  
Bruno Simonnet ◽  
Cédric Gil-Jardiné ◽  
Marion Lerouge-Bailhache ◽  
Bruno Castelle ◽  
...  
Keyword(s):  
Regression Models ◽  
Area Under The Curve ◽  
Temperature Wave ◽  
Medical Emergency ◽  
Emergency Center ◽  
Logistic Regression Models ◽  
Weather Forecasts ◽  
Step Model ◽  
Daily Risk ◽  
Development And Validation

ObjectiveTo predict the coast-wide risk of drowning along the surf beaches of Gironde, southwestern France.MethodsData on rescues and drownings were collected from the Medical Emergency Center of Gironde (SAMU 33). Seasonality, holidays, weekends, weather and metocean conditions were considered potentially predictive. Logistic regression models were fitted with data from 2011 to 2013 and used to predict 2015–2017 events employing weather and ocean forecasts.ResultsAir temperature, wave parameters, seasonality and holidays were associated with drownings. Prospective validation was performed on 617 days, covering 232 events (rescues and drownings) reported on 104 different days. The area under the curve (AUC) of the daily risk prediction model (combined with 3-day forecasts) was 0.82 (95% CI 0.79 to 0.86). The AUC of the 3-hour step model was 0.85 (95% CI 0.81 to 0.88).ConclusionsDrowning events along the Gironde surf coast can be anticipated up to 3 days in advance. Preventative messages and rescue preparations could be increased as the forecast risk increased, especially during the off-peak season, when the number of available rescuers is low.

Pseudogenized Amelogenin Reveals Early Tooth Loss in True Toads (Anura: Bufonidae)

2021 ◽  
Author(s):  
John Shaheen ◽  
Austin B Mudd ◽  
Thomas G H Diekwisch ◽  
John Abramyan
Keyword(s):  
Tooth Loss ◽  
Tooth Enamel ◽  
Synonymous Substitution ◽  
Bufo Bufo ◽  
Molecular Dating ◽  
Bufo Gargarizans ◽  
The Family ◽  
Synonymous Substitution Rates ◽  
Mandibular Teeth ◽  
Early Tooth Loss

Abstract Extant anurans (frogs and toads) exhibit reduced dentition, ranging from a lack of mandibular teeth to complete edentulation, as observed in the true toads of the family Bufonidae. The evolutionary timeline of these reductions remains vague due to a poor fossil record. Previous studies have demonstrated an association between the lack of teeth in edentulous vertebrates and the pseudogenization of the major tooth enamel gene amelogenin (AMEL) through accumulation of deleterious mutations and the disruption of its coding sequence. In the present study we have harnessed the pseudogenization of AMEL as a molecular dating tool to correlate loss of dentition with genomic mutation patterns during the rise of the family Bufonidae. Specifically, we have utilized AMEL pseudogenes in three members of the family as a tool to estimate the putative date of edentulation in true toads. Comparison of AMEL sequences from Rhinella marina, Bufo gargarizans and Bufo bufo, with nine extant, dentulous frogs, revealed mutations confirming AMEL inactivation in Bufonidae. AMEL pseudogenes in modern bufonids also exhibited remarkably high 86–93% sequence identity among each other, with only a slight increase in substitution rate and relaxation of selective pressure, in comparison to functional copies in other anurans. Moreover, using selection intensity estimates and synonymous substitution rates, analysis of functional and pseudogenized AMEL resulted in an estimated inactivation window of 46-60 MYA in the lineage leading to modern true toads, a timeline that coincides with the rise of the family Bufonidae.

scholarly journals Impact of Grade Groups on Prostate Cancer-Specific and Other-Cause Mortality: Competing Risk Analysis from a Large Single Institution Series

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1963
Author(s):  
Daimantas Milonas ◽  
Tomas Ruzgas ◽  
Zilvinas Venclovas ◽  
Mindaugas Jievaltas ◽  
Steven Joniau
Keyword(s):  
Clinical Decision Making ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Competing Risk ◽  
Grade Group ◽  
Tertiary Center ◽  
Stable Performance ◽  
Cancer Specific Mortality ◽  
Risk Of Cancer

Objective: To assess the risk of cancer-specific mortality (CSM) and other-cause mortality (OCM) using post-operative International Society of Urological Pathology Grade Group (GG) model in patients after radical prostatectomy (RP). Patients and Methods: Overall 1921 consecutive men who underwent RP during 2001 to 2017 in a single tertiary center were included in the study. Multivariate competing risk regression analysis was used to identify significant predictors and quantify cumulative incidence of CSM and OCM. Time-depending area under the curve (AUC) depicted the performance of GG model on prediction of CSM. Results: Over a median follow-up of 7.9-year (IQR 4.4-11.7) after RP, 235 (12.2%) deaths were registered, and 52 (2.7%) of them were related to PCa. GG model showed high and stable performance (time-dependent AUC 0.88) on prediction of CSM. Cumulative 10-year CSM in GGs 1 to 5 was 0.9%, 2.3%, 7.6%, 14.7%, and 48.6%, respectively; 10-year OCM in GGs was 15.5%, 16.1%, 12.6%, 17.7% and 6.5%, respectively. The ratio between 10-year CSM/OCM in GGs 1 to 5 was 1:17, 1:7, 1:2, 1:1, and 7:1, respectively. Conclusions: Cancer-specific and other-cause mortality differed widely between GGs. Presented findings could aid in personalized clinical decision making for active treatment.

Drug Alert Experience and Salience during Medical Residency at Two Healthcare Institutions

2021 ◽  
Vol 12 (02) ◽  
pp. 355-361
Author(s):  
Kinjal Gadhiya ◽  
Edgar Zamora ◽  
Salim M. Saiyed ◽  
David Friedlander ◽  
David C. Kaelber
Keyword(s):  
Internal Medicine ◽  
Residency Training ◽  
Medical Center ◽  
Internal Medicine Resident ◽  
Clinical Decision ◽  
University Of Pennsylvania ◽  
Teaching Hospitals ◽  
Medicine Resident ◽  
Internal Medicine Residents ◽  
The University

Abstract Background Drug alerts are clinical decision support tools intended to prevent medication misadministration. In teaching hospitals, residents encounter the majority of the drug alerts while learning under variable workloads and responsibilities that may have an impact on drug-alert response rates. Objectives This study was aimed to explore drug-alert experience and salience among postgraduate year 1 (PGY-1), postgraduate year 2 (PGY-2), and postgraduate year 3 (PGY-3) internal medicine resident physicians at two different institutions. Methods Drug-alert information was queried from the electronic health record (EHR) for 47 internal medicine residents at the University of Pennsylvania Medical Center (UPMC) Pinnacle in Pennsylvania, and 79 internal medicine residents at the MetroHealth System (MHS) in Ohio from December 2018 through February 2019. Salience was defined as the percentage of drug alerts resulting in removal or modification of the triggering order. Comparisons were made across institutions, residency training year, and alert burden. Results A total of 126 residents were exposed to 52,624 alerts over a 3-month period. UPMC Pinnacle had 15,574 alerts with 47 residents and MHS had 37,050 alerts with 79 residents. At MHS, salience was 8.6% which was lower than UPMC Pinnacle with 15%. The relatively lower salience (42% lower) at MHS corresponded to a greater number of alerts-per-resident (41% higher) compared with UPMC Pinnacle. Overall, salience was 11.6% for PGY-1, 10.5% for PGY-2, and 8.9% for PGY-3 residents. Conclusion Our results are suggestive of long-term drug-alert desensitization during progressive residency training. A higher number of alerts-per-resident correlating with a lower salience suggests alert fatigue; however, other factors should also be considered including differences in workload and culture.

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