Assessing Risk of Severe Complications after Endoscopic Transnasal Transsphenoidal Surgery: A Comparison of Frailty, American Society of Anesthesiologists, and Comorbidity Scores

Objective This study aimed to improve age-independent risk stratification for patients undergoing endoscopic transnasal transsphenoidal (TNTS) approach to pituitary mass resection by investigating the associations between frailty, American Society of Anesthesiologists (ASA), and comorbidity scores with severe complications following TNTS. Design This study is a retrospective review. Setting This review was conducted utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database. Participants A total of 680 cases of TNTS identified from 2010 to 2013 were included in this study. Main Outcome Measures The modified frailty index (mFI) was calculated to quantify frailty. ASA and Charlson's comorbidity index (CCI) scores were obtained as physiologic status and comorbidity-based prognostic markers. Severe complications were separated into intensive care unit (ICU)-level complications, defined by Clavien–Dindo grade IV (CDIV) criteria, and mortality. Results Overall, 24 CDIV complications (3.5%) and 6 deaths (0.9%) were recorded. Scores for mFI (p = 0.01, R 2 = 0.97) and ASA (p = 0.04., R 2 = 0.87) were significantly correlated with CDIV complications. ASA scores were significantly correlated with mortality (p = 0.03, R 2 = 0.87), as well as independently associated with CDIV complication by multivariable regression models (odds ratio [OR] = 2.96, 95% confidence interval [CI]: 1.35–6.83, p < 0.01), while mFI was not. CCI was not significantly associated with CDIV complications or mortality. A multivariable regression model incorporating ASA had a lower Akaike's Information Criteria (AIC; 188.55) than a model incorporating mFI (195.99). Conclusion Frailty and physiologic status, as measured by mFI and ASA scores respectively, both correlate with ICU-level complications after TNTS. ASA scores demonstrate greater clinical utility than mFI scores; however, as they are more easily generated, uniquely correlated with mortality and independently associated with ICU-level complication risk on multivariable regression analysis.

Comparative Analysis of Basic and Extended Power Models of Boreholes Expansion Dependence on Explosive Charge in Blasting in Clay Soil

Spherical cavities made by explosive charge activation in a clay soils differ in size and shape. The mass of explosive charge lowered on the bottom of the borehole in a one-time blasting is typically relatively small and is calculated by a desired and planned performace. The effect of smaller explosive charge for spherical cavities is in principle different than continuously filled borehole in mining and blasting operations. Detonation of smaller explosive charge crushes the material in proximity of activated explosive charge. With the increase of distance from the explosive charge, the released energy in not enough for crushing of the materials, but instead compacts it. This paper is an extension of the previous research, which resulted in a smallest error of estimated in a model shown as the sum of square residuals (SS), largest value of determination coefficient (R2) and smallest loss of information through Akaike’s Information Criteria (AIC and AICc). This paper presents an extended power model of dependence of spherical cavity volume expansion on explosive charge. Extended model is a basic model with an additional parameter to ensure more precise mathematical description and further decrease of error of estimate for all efficiency indicators and for both types of explosive used.

Two-Hour Post-Load Plasma Glucose, a Biomarker to Improve the GRACE Score in Patients without Known Diabetes

Objective: To assess improvement in predictive performance of Global Registry of Acute Coronary Events risk score (GRS) by addition of a glucose matrix. Methods: 1,056 acute coronary syndrome (ACS) survivors without known diabetes had pre-discharge fasting (FPG) and 2-h post-load plasma glucose (2h-PG) measured. GRS was calculated. Major adverse cardiac events (MACE; death and non-fatal myocardial infarction) were recorded during follow-up. Cox proportional hazard regression predicted event-free survival. Likelihood ratio test, Akaike’s information criteria, continuous net reclassification index (NRI>0), and integrated discrimination improvement (IDI) were used to test the additional prognostic value of glycaemic indices over GRS. Results: During a median follow-up of 36.5 months, 211 MACEs (20.0%), 96 deaths (9.1%), and 115 non-fatal re-infarctions (10.9%), occurred. 2h-PG, but not FPG, independently predicted MACE-free survival at all time points (HR 1.08, 95% CI 1.03–1.13, p = 0.002, at 3 years). Risk of MACE increased by 8–11% with every 1 mmol/L rise in 2h-PG. 2h-PG significantly improved the prognostic models containing GRS. Models containing GRS and 2h-PG yielded lowest corrected Akaike’s information criteria compared to that with only GRS. 2h-PG, but not FPG, improved NRI>0 (NRI>0 0.169, p = 0.028 at 3 years) and IDI (IDI of 0.66%, p = 0.018 at 3 years) significantly at all time points during the follow-up. Conclusions: 2h-PG, but not FPG, improves performance of GRS-containing models in predicting post-ACS prognosis in the short to medium term.

Validation of the five-tier Taiwan Triage and Acuity Scale for prehospital use by Emergency Medical Technicians

ObjectivesThis study aimed to determine the inter-rater reliability of the five-level Taiwan Triage and Acuity Scale (TTAS) when used by emergency medical technicians (EMTs) and triage registered nurses (TRNs). Furthermore, it sought to validate the prehospital TTAS scores according to ED hospitalisation rates and medical resource consumption.MethodsThis was a prospective observational study. After training in five-level triage, EMTs triaged patients arriving to the ED and agreement with the nurse triage (TRN) was assessed. Subsequently, these trained research EMTs rode along on ambulance calls and assigned TTAS scores for each patient at the scene, while the on-duty EMTs applied their standard two-tier prehospital triage scale and followed standard practice, blinded to the TTAS scores. The accuracy of the TTAS scores in the field for prediction of hospitalisation and medical resource consumption were analysed using logistic regression and a linear model, respectively, and compared with the accuracy of the current two-tier prehospital triage scale.ResultsAfter EMT’s underwent initial training in five-level TTAS, inter-rater agreement between EMTs and TRNs for triage of ED patients was very good (κw=0.825, CI 0.750 to 0.900). For the outcome of hospitalisation, TTAS five-level system (Akaike’s Information Criteria (AIC)=486, area under the curve (AUC)=0.75) showed better discrimination compared with TPTS two-level system (AIC=508, AUC=0.66). Triage assignments by the EMTs using the the five-level TTAS was linearly associated with hospitalisation and medical resource consumption.ConclusionsA five-level prehospital triage scale shows good inter-rater reliability and superior discrimination compared with the two-level system for prediction of hospitalisation and medical resource requirements.

Prediction of Bridge Component Ratings Using Ordinal Logistic Regression Model

Prediction of bridge component condition is fundamental for well-informed decisions regarding the maintenance, repair, and rehabilitation (MRR) of highway bridges. The National Bridge Inventory (NBI) condition rating is a major source of bridge condition data in the United States. In this study, a type of generalized linear model (GLM), the ordinal logistic statistical model, is presented and compared with the traditional regression model. The proposed model is evaluated in terms of reliability (the ability of a model to accurately predict bridge component ratings or the agreement between predictions and actual observations) and model fitness. Five criteria were used for evaluation and comparison: prediction error, bias, accuracy, out-of-range forecasts, Akaike’s Information Criteria (AIC), and log likelihood (LL). In this study, an external validation procedure was developed to quantitatively compare the forecasting power of the models for highway bridge component deterioration. The GLM method described in this study allows modeling ordinal and categorical dependent variable and shows slightly but significantly better model fitness and prediction performance than traditional regression model.

Analysis of lactation feed intakes for sows with extended lactation lengths

The objectives of this research were to quantify and model daily feed intakes to 28 d of lactation in modern sows. A total of 4,512 daily feed intake (DFI) records were collected for 156 Hypor sows from February 2015 to March 2016. The mean lactation length was 27.9 ± 2.0 d. The data included 9 parity 1, 33 parity 2 and 114 parity 3+ sows. Data were collected using a computerized feeding system (Gestal Solo, JYGA Technologies, Quebec, Canada). The feeding system was used to set an upper limit to DFI for the first 7 d of lactation. Overall, the least-squares means of a model including the random effect of sow indicated that DFI's continued to slowly increase to 28 d of lactation. The DFI data were fitted to Generalized Michaelis-Menten (GMM) and polynomial functions of day of lactation (t). The GMM function [DFIi,t (kg/d) = DFI0 + (DFIA − DFI0)(t/K)C/[1 + (t/K)C]] was fitted with 2 random effects for DFI (dfiAi) and intercept (dfi0i) using the NLMIXED procedure in SAS®. The polynomial function DFIi,t (kg/d) = [B0 + B1 t + B2 t2 + B3 t3 + B4 t4] was fitted with three random effects for B0, B1, and B2 using the MIXED procedure in SAS®. Fixed effects models of the two functions had similar Akaike's Information Criteria (AIC) values and mean predicted DFI's. The polynomial function with 3 random effects provided a better fit to the data based on R2 30 (0.81 versus 0.79), AIC (14,709 versus 15,158) and RSD (1.204 versus 1.321) values than the GMM function with two random effects. The random effect for B2 in the polynomial function allowed for the fitting of the function to lactation records that had decreased DFI after 15 d of lactation. The random effects for the polynomial function were used to sort the lactation records into three groups based on the derivative of the function at 21 d of lactation. Lactation records of the three groups had similar DFI the first two weeks of lactation (P &gt; 0.40). The three groups of sows had substantially different DFI's after 18 d of lactation (P &lt; 0.028). The differences in both actual and predicted DFI's between the three groups increased with each day of lactation to day 28 (P &lt; 0.001). Mixed model polynomial functions can be used to identify sows with different patterns of DFI after 15 d of lactation.

Birds and Land Classes in Young Forested Landscapes

In the Mississippi Coastal Plain of the southeastern United States, we explored relationships among bird species and vegetation types and landscape characteristics at four different scales. We modeled abundance of priority avian species from Breeding Bird Surveys using land class metrics at 0.24, 1, 3, and 5-km extents. Our modeling method was logistic regression and model selection was based on Akaike’s Information Criteria and validation with reserved data. Northern bobwhite (Colinus virginianus), red-headed woodpecker (Melanerpes erythrocephalus), northern parula (Parula americana), Swainson’s warbler (Limnothlypis swainsonii), prairie warbler (Dendroica discolor), hooded warbler (Wilsonia citrina), and brown-headed cowbird (Molothrus ater) had models containing positive area or core area variables. White-eyed vireo (Vireo griseus) and gray catbird (Dumetella carolinensis) had models with a combination of area and edge associations at different scales. Acadian flycatcher (Empidonax virescens), red-bellied woodpecker (Melanerpes carolinus), wood thrush (Hylocichla mustelina), and yellow-breasted chat (Icteria virens) had positive edge density models. Modeling at different scales produced more complete habitat associations for most species and landscape variables were more influential at larger extents than the smallest extent. Although Mississippi is heavily forested, the landscape is unexpectedly fragmented, with small areal extents of vegetation types. Managers should seek to provide large extents of a variety of habitats, including historically representative vegetation types such as low density pine, to support persistence of a complete suite of avian species.

Maturity and growth characteristics of a commercially exploited stingray, Dasyatis dipterura

Maturity and growth characteristics were estimated for Dasyatis dipterura from western Mexico, where it is a common component of artisanal elasmobranch fisheries. Median disc width at maturity was estimated as 57.3 cm for females (n = 126) and 46.5 cm for males (n = 55) respectively. Age estimates were obtained from 304 fishery-derived specimens (169 female, 135 male). An annual pattern of band-pair deposition was validated through modified centrum edge and marginal increment analyses. Gompertz, polynomial and von Bertalanffy growth models were fit to disc width and weight-at-age data. Resulting models were evaluated based on biological rationale, standard error of model estimates, and Akaike’s information criteria. Growth characteristics differed significantly between females and males. Maximum age estimates were 28 years for females and 19 years for males. Three-parameter von Bertalanffy growth models of disc width-at-age data generated the most appropriate fits and produced relatively low estimates of instantaneous growth rates for females (DW∞ = 92.4 cm, k = 0.05, t0 = –7.61, DW0 = 31.4 cm) and males (DW∞ = 62.2 cm, k = 0.10, t0 = –6.80, DW0 = 31.3 cm). These values are the lowest reported for myliobatiform stingrays and indicate slow growth rates in comparison with elasmobranchs in general.