Multidisciplinary management of patients presenting with Lyme disease suspicion

Objective

The teaching hospital of Nancy, France, implemented a specific multidisciplinary care pathway (French acronym AMDPL) to improve the management of patients presenting with Lyme borreliosis (LB) suspicion. We aimed to assess the first year of activity of this care pathway.

Motion‐compensated b‐tensor encoding for in vivo cardiac diffusion‐weighted imaging

Motion is a major confound in diffusion‐weighted imaging (DWI) in the body, and it is a common cause of image artefacts. The effects are particularly severe in cardiac applications, due to the nonrigid cyclical deformation of the myocardium. Spin echo‐based DWI commonly employs gradient moment‐nulling techniques to desensitise the acquisition to velocity and acceleration, ie, nulling gradient moments up to the 2nd order (M2‐nulled). However, current M2‐nulled DWI scans are limited to encode diffusion along a single direction at a time. We propose a method for designing b‐tensors of arbitrary shapes, including planar, spherical, prolate and oblate tensors, while nulling gradient moments up to the 2nd order and beyond. The design strategy comprises initialising the diffusion encoding gradients in two encoding blocks about the refocusing pulse, followed by appropriate scaling and rotation, which further enables nulling undesired effects of concomitant gradients. Proof‐of‐concept assessment of in vivo mean diffusivity (MD) was performed using linear and spherical tensor encoding (LTE and STE, respectively) in the hearts of five healthy volunteers. The results of the M2‐nulled STE showed that (a) the sequence was robust to cardiac motion, and (b) MD was higher than that acquired using standard M2‐nulled LTE, where diffusion‐weighting was applied in three orthogonal directions, which may be attributed to the presence of restricted diffusion and microscopic diffusion anisotropy. Provided adequate signal‐to‐noise ratio, STE could significantly shorten estimation of MD compared with the conventional LTE approach. Importantly, our theoretical analysis and the proposed gradient waveform design may be useful in microstructure imaging beyond diffusion tensor imaging where the effects of motion must be suppressed.     

Prevalence and Correlates of Mental Health Problems in Norwegian Peacekeepers 18–38 Years Postdeployment

Peacekeeping missions involve experiences that may impact the mental health of participating soldiers. However, research on the long-term mental health consequences of peacekeeping is sparse. The present study aimed to find the prevalence of mental health problems (MHPs), possible MHP predictors, and associations between predictors and MHPs in Norwegian peacekeepers 18–38 years after deployment to a United Nations peacekeeping mission. We used data from a cross-sectional, postdeployment survey of Norwegian peacekeepers who served in Lebanon between 1978 and 1998 (N = 10,605). Participants were assessed for posttraumatic stress disorder (PTSD); anxiety; depression; insomnia; alcohol misuse; drug misuse; and exposure to pre-, peri-, and postdeployment stressors. Logistic regressions were executed to explore key variables associated with MHPs. Total MHP prevalence was 15.1%, 95% CI [14.4, 15.8]. The estimates for specific disorders were 0.1% for drug misuse, 3.4% for alcohol misuse, 4.0% for depression, 6.2% for PTSD, 6.4% for anxiety, and 9.3% for insomnia. Postdeployment stressors, OR = 1.91, 95% CI [1.79, 2.04]; employment status, OR = 1.41, 95% CI [1.33, 1.48]; and traumatic exposure during deployment, OR = 1.11, 95% CI [1.09, 1.12], were positively related to PTSD, χ2(17, N = 8,568) = 1,791.299, p < .001. Similar patterns were found for the other MHPs. Considering that most participants (84.9%) reported low symptom levels, our findings challenge the widespread public perception that most peacekeepers have MHPs. Moreover, our results indicate that future peacekeepers should be prepared for challenges they may face not only during deployment but also in the years following their homecoming.     

The development and validation of the Score for the Prediction of Postoperative Respiratory Complications (SPORC-2) to predict the requirement for early postoperative tracheal re-intubation: a hospital registry study

Postoperative pulmonary complications are associated with an increase in mortality, morbidity and healthcare utilisation. The Agency for Healthcare Research and Quality recommends risk assessment for postoperative respiratory complications in patients undergoing surgery. In this hospital registry study of adult patients undergoing non-cardiac surgery between 2005 and 2017 at two independent healthcare networks, a prediction instrument for early postoperative tracheal re-intubation was developed and externally validated. This was based on the development of the Score for Prediction Of Postoperative Respiratory Complications. For predictor selection, stepwise backward logistic regression and bootstrap resampling were applied. Development and validation cohorts were represented by 90,893 patients at Partners Healthcare and 67,046 patients at Beth Israel Deaconess Medical Center, of whom 699 (0.8%) and 587 (0.9%) patients, respectively, had their tracheas re-intubated. In addition to five pre-operative predictors identified in the Score for Prediction Of Postoperative Respiratory Complications, the final model included seven additional intra-operative predictors: early post-tracheal intubation desaturation; prolonged duration of surgery; high fraction of inspired oxygen; high vasopressor dose; blood transfusion; the absence of volatile anaesthetic use; and the absence of lung-protective ventilation. The area under the receiver operating characteristic curve for the new score was significantly greater than that of the original Score for Prediction Of Postoperative Respiratory Complications (0.84 [95%CI 0.82–0.85] vs. 0.76 [95%CI 0.75–0.78], respectively; p < 0.001). This may allow clinicians to develop and implement strategies to decrease the risk of early postoperative tracheal re-intubation.