Citations

Motivated by the paucity of high‐quality stillbirth surveillance data and the spatial analysis of such data, we describe the pattern of stillbirth events as a step toward increased understanding of risk factors which can better guide future measures to mitigate these events. A challenge in such an analysis is that some mothers experience stillbirth events from independent pregnancies within a defined study period. To account for these dependencies, we parameterize our model to include a maternal contextual effect and broaden the appeal of Bayesian Poisson point process modeling to quantify excess stillbirth risk while considering a form of a log‐Gaussian Cox process. In the presence of extra unobserved spatial variation in risk, we demonstrate a pragmatic methodologic strategy to model the risk surface in relation to covariates and that there is a variance‐bias trade‐off associated with the use of a maternal contextual effect. We applied our strategy to the spatial distribution of stillbirth in Iowa during the years 2005–2011 using data obtained from an active, statewide public health surveillance program. We identified areas of excess risk for further investigation based on model components that captured important features of the data.

Objectives Local anesthetic injection into the interspace between the popliteal artery and the posterior capsule of the knee (IPACK) has the potential to provide motor‐sparing analgesia to the posterior knee after total knee arthroplasty. The primary objective of this cadaveric study was to evaluate injectate spread to relevant anatomic structures with IPACK injection. Methods After receipt of Institutional Review Board Biospecimen Subcommittee approval, IPACK injection was performed on fresh‐frozen cadavers. The popliteal fossa in each specimen was dissected and examined for injectate spread. Results Ten fresh‐frozen cadaver knees were included in the study. Injectate was observed to spread in the popliteal fossa at a mean ± SD of 6.1 ± 0.7 cm in the medial‐lateral dimension and 10.1 ± 3.2 cm in the proximal‐distal dimension. No injectate was noted to be in contact with the proximal segment of the sciatic nerve, but 3 specimens showed injectate spread to the tibial nerve. In 3 specimens, the injectate showed possible contact with the common peroneal nerve. The middle genicular artery was consistently surrounded by injectate. Conclusions This cadaver study of IPACK injection demonstrated spread throughout the popliteal fossa without proximal sciatic involvement. However, the potential for injectate to spread to the tibial or common peroneal nerve was demonstrated. Consistent surrounding of the middle genicular artery with injectate suggests a potential mechanism of analgesia for the IPACK block, due to the predictable relationship between articular sensory nerves and this artery. Further study is needed to determine the ideal site of IPACK injection.

Abstract Jagim, AR, Camic, CL, Askow, A, Luedke, J, Erickson, J, Kerksick, CM, Jones, MT, and Oliver, JM. Sex differences in resting metabolic rate among athletes. J Strength Cond Res 33(11): 3008–3014, 2019—The purpose of this study was to compare differences in resting metabolic rate (RMR) between sexes in Division III National Collegiate Athletic Association (NCAA) collegiate athletes and to identify predictors of RMR. Sixty-eight male (M) (age: 20.1 ± 1.5 years; height: 181.8 ± 5.9 cm; body mass (BM): 93.7 ± 16.3 kg; and body fat%: 16.3 ± 8.6%) and 48 female (F) athletes (age: 19.4 ± 1.3 years; height: 166.5 ± 6.0 cm; BM: 63.4 ± 12.7 kg; and body fat%: 21.5 ± 6.3%) participated in a single day of testing, which included determination of RMR using indirect calorimetry and air displacement plethysmography to measure fat mass and fat-free mass (FFM). An independent-samples t -test was used to compare differences in body composition and RMR between sexes, and regression analysis was used to identify predictors of RMR. Men had a significantly higher absolute RMR (M: 2,481 ± 209 vs. F: 1,553 ± 193 kcals·d −1 ; p < 0.001), but when adjusted for BM (M: 25.6 ± 8.3 vs. F: 25.9 ± 2.5 kcals·kg −1 BM per day; p = 0.82) and FFM (M: 31.1 ± 10.6 vs. F: 33.6 ± 3.8 kcals·kg −1 FFM per day; p = 0.12), these differences became nonsignificant. Regression analysis indicated that BM in both men (β = 0.73) and women (β = 0.88) was the strongest predictor of RMR. The results of the current study indicate minimal differences in RMR between sexes among athletic populations when adjusted for BM and FFM. In the current group of athletes, BM seems to account for the largest variability in RMR.