The insecure airway: a comparison of knots and commercial devices for securing endotracheal tubes

BACKGROUND: Endotracheal Tubes (ETTs) are commonly secured using adhesive tape, cloth tape, or commercial devices. The objectives of the study were (1) To compare degrees of movement of ETTs secured with 6 different commercial devices and (2) To compare movement of ETTs secured with cloth tape tied with 3 different knots (hitches). METHODS: A 17 cm diameter PVC tube with 14 mm "mouth" hole in the side served as a mannequin. ETTs were subjected to repeated jerks, using a cable and pulley system. Measurements: (1) Total movement of ETTs relative to "mouth" (measure used for devices) (2) Slippage of ETT through securing knot (measure used for knots). RESULTS: Among commercial devices, the Dale(® )showed less movement than other devices, although some differences between devices did not reach significance. Among knots, Magnus and Clove Hitches produced less slippage than the Cow Hitch, but these differences did not reach statistical significance. CONCLUSION: Among devices tested, the Dale(® )was most secure. Within the scope offered by the small sample sizes, there were no statistically significant differences between the knots in this study

Machine-learned multi-system surrogate models for materials prediction

AbstractSurrogate machine-learning models are transforming computational materials science by predicting properties of materials with the accuracy of ab initio methods at a fraction of the computational cost. We demonstrate surrogate models that simultaneously interpolate energies of different materials on a dataset of 10 binary alloys (AgCu, AlFe, AlMg, AlNi, AlTi, CoNi, CuFe, CuNi, FeV, and NbNi) with 10 different species and all possible fcc, bcc, and hcp structures up to eight atoms in the unit cell, 15,950 structures in total. We find that the deviation of prediction errors when increasing the number of simultaneously modeled alloys is &lt;1 meV/atom. Several state-of-the-art materials representations and learning algorithms were found to qualitatively agree on the prediction errors of formation enthalpy with relative errors of &lt;2.5% for all systems.</jats:p

Machine-learned multi-system surrogate models for materials prediction

Surrogate machine-learning models are transforming computational materials science by predicting properties of materials with the accuracy of ab initio methods at a fraction of the computational cost. We demonstrate surrogate models that simultaneously interpolate energies of different materials on a dataset of 10 binary alloys (AgCu, AlFe, AlMg, AlNi, AlTi, CoNi, CuFe, CuNi, FeV, NbNi) with 10 different species and all possible fcc, bcc and hcp structures up to 8 atoms in the unit cell, 15\,950 structures in total. We find that the deviation of prediction errors when increasing the number of simultaneously modeled alloys is less than 1\,meV/atom. Several state-of-the-art materials representations and learning algorithms were found to qualitatively agree on the prediction errors of formation enthalpy with relative errors of $<$2.5\% for all systems

Estimating gestational age and its relation to the anthropometric status of newborns: a study comparing the Capurro and ultrasound methods with last menstrual period Estimativa da idade gestacional e sua relação com o estado antropométrico em recém-nascidos: uma comparação dos métodos Capurro e ultrassonográfico com a data da última menstruação

OBJECTIVE: to assess the accuracy of the Capurro somatic and ultrasound methods, taking date of last menstruation as a reference point, for evaluating gestational age and anthropometric classification of term newborns. METHODS: a prevalence study was carried out involving 309 pregnant women and their term newborns, 92 of whom were small for gestational age and 217 appropriate sized for gestational age, at two public maternity hospitals in the Brazilian city of Salvador. The evaluation of the differences between the median gestational age according to the two methods was carried out using the non-parametric "Wilcoxon Signed-Rank Test." The accuracy of the methods for evaluating gestational age for the small for gestational age newborns was estimated by calculating the sensitivity, specificity, positive predictive value, negative predictive value and ROC (Receiver Operating Characteristic) curve. RESULTS: compared to ultrasound, the Capurro method overestimated the gestational age in newbornsof less than 39 weeks and underestimated it in older newborns. Ultrasound underestimated gestational agein newborns with more than 37 weeks. CONCLUSION: ultrasound was found to have greater sensitivity for prediction of small for age newborns (96.6%), while the Capurro method presented greater specificity (75.5%). The highest accuracy was obtained using ultrasound in the 41st gestational week (ROC=77.0%).<br>OBJETIVOS: avaliar a acurácia dos métodos físico de Capurro e da ultrassonografia (USG), tomandocomo referência o método da data da última menstruação (DUM), na avaliação da idade gestacional e classificação antropométrica de recém-nascidos (RN) a termo. MÉTODOS: estudo de prevalência, envolvendo 309 puérperas e seus recém-nascidos a termo, sendo 92 pequenos para idade gestacional (PIG) e 217 adequados para idade gestacional (AIG), de duas maternidades públicas de Salvador. A avaliação das diferenças entre as medianas da idade gestacional segundo os métodos foi realizada utilizando-se o teste não paramétrico "Wilcoxon Signed-Rank Test." A acurácia dos métodos na avaliação da idade gestacional para o diagnóstico de RN PIG foi verificada através do cálculo da sensibilidade, especificidade, valor preditivo positivo, valor preditivo negativo e curva ROC (Receiver Operating Characteristic). RESULTADOS: comparado à ultrassonografia, o método de Capurro superestimou a idade gestacional em recém-natos menores de 39 semanas e substimou a naqueles acima deste patamar. A USG substimou aidade gestacional em recém-nascidos com mais de 37 semanas. CONCLUSÕES: na predição de RN PIG, maior sensibilidade foi observada para a USG (96,6%) e maior especificidade para o Capurro (75,5%). Melhor acurácia foi observada para a USG na 41ª semana gestacional (ROC=77,0%)

Regional Variation in Late Preterm Births in North Carolina

OBJECTIVE: Late preterm (LPT) neonates (34 0/7th to 36 6/7th weeks' gestation) account for 70% of all premature births in the United States. LPT neonates have a higher morbidity and mortality risk than term neonates. LPT birth rates vary across geographic regions. Unwarranted variation is variation in medical care that cannot be explained by sociodemographic or medical risk factors; it represents differences in health system performance, including provider practice variation. The purpose of this study is to identify regional variation in LPT births in North Carolina that cannot be explained by sociodemographic or medical/obstetric risk factors. METHODS: We searched the NC State Center for Health Statistics linked birth-death certificate database for all singleton term and LPT neonates born between 1999 and 2006. We used multivariable logistic regression analysis to control for socio-demographic and medical/obstetric risk factors. The main outcome was the percent of late preterm birth in each of the six perinatal regions in North Carolina. RESULTS: We identified 884,304 neonates; 66,218 (7.5%) were LPT. After multivariable logistic regression, regions 2 (7.0%) and 6 (6.6%) had the highest adjusted percent of LPT birth. CONCLUSIONS: Analysis of a statewide birth cohort demonstrates regional variation in the incidence of LPT births among NC's perinatal regions after adjustment for sociodemographic and medical risk factors. We speculate that provider practice variation might explain some of the remaining difference. This is an area where policy changes and quality improvement efforts can help reduce variation, and potentially decrease LPT births