Recovery Metrics Research Articles

Exploratory Analysis of Concussion Recovery Trajectories using Multi-modal Assessments and Serum Biomarkers.

Clinicians need better tools to assess severity, prognosis, and recovery from mild Traumatic Brain Injury (mTBI), which can cause long term impairment. To enable better mTBI outcome prediction, an initial step is to analyze the trajectory of recovery metrics over time. This study provides an assessment of recovery trajectories of mTBI while incorporating heterogeneity of individual responses. We analyze the trajectories over multiple discrete time points from baseline to 6 months post injury using a combination of neurocognitive and postural stability assessments and serum biomarkers. The data, obtained from FITBIR, consists of concussed subjects and a matched control group, to allow for comparison in prognostic assessment. Outcomes derived from this exploratory analysis will aid future studies in developing a mTBI recovery timeline model.Clinical relevance- This study further informs clinicians as to the recovery trajectory of clinical measures and biomarkers after mTBI to support return to play decisions. GFAP biomarker and measures related to balance, memory, orientation, and concentration were significantly different than controls early after mTBI.

Channel and vegetation recovery from dredging of a large river in the Gulf coastal plain, USA

AbstractAnthropogenic impacts in large rivers are widely studied, but studies of recovery once a disturbance has stopped are uncommon. This study examines the biogeomorphic recovery of a 40‐km river corridor on the mid‐Apalachicola River, Florida following the cessation of dredging, disposal, and snag removal in 2002. This failed navigation project resulted in vegetation losses (~166 ha between 1941 and 2004), river widening, and increased point bar areas. We used paired sets of imagery for a 10‐year period during the recovery process at two different flow levels to assess sand bar change, land cover change, and their spatial variations.Most large sand bars decreased significantly in area due to growth of pioneer species, typically from the bankside of the bar. Mean bar area shrank 0.17 and 0.20 ha for the 30th and 1st percentile flows, respectively. For the entire study area, both water‐level comparisons showed gains in vegetation (23.36 and 15.83 ha), compensated by losses in the extent of water (16.83 and 8.55 ha) and sand bar losses (6.53 and 7.28 ha). Overall, these gains during the 10‐year passive recovery period are equivalent to ~15% of the vegetation losses that resulted from the navigational dredging.As found in other studies, most of the pioneer vegetation grew approximately 2 m relative elevation above the low‐water surface. The initial length of the tree line and the area of herbaceous growth both had a significant and positive relationship with the area of new vegetation growth over the study interval. As parts of the river are healing, reduced channel capacity from narrowing and tree growth will benefit the floodplain. As elsewhere, understanding of a river's biogeomorphology, hydrology, and disturbance history can help in selecting appropriate recovery metrics to further advance the understanding and management of disturbed floodplains. © 2020 John Wiley & Sons, Ltd.

Abstract P244: Association Between Early Life Trauma and Change in HRV During Mental Stress Among Patients With Recent Myocardial Infarction

Background: Early-life traumatic experiences have been associated with increased cardiovascular disease risk. Little is known about how early-life traumatic experiences may affect changes in autonomic function during mental stress among young subjects post-MI. Objective: We hypothesized that those with high exposure to early-life trauma, compared to those with low exposure to early-life trauma, would have increased autonomic dysfunction at baseline, worse stress reactivity, and slower autonomic recovery. Methods: We evaluated 321 subjects with a history of recent myocardial infarction who underwent a laboratory-based mental stress speech task. HRV was measured at rest (T0), during mental stress (T1), and during recovery (T2) with ambulatory electrocardiographic monitoring. We evaluated low frequency (LF) HRV as the primary outcome because of its relationship with baroreflex sensitivity, psychological stress, and cardiovascular disease outcomes. Early life trauma was assessed using the Early Trauma Inventory Self Report - Short Form (ETI-SF) and a binary variable was calculated using one SD above the mean of the ETI-SF score, a previously validated cutpoint, to indicate high early-life trauma exposure and low otherwise. Sociodemographic factors, including race, highest education attained, age, and gender, were considered as potential confounders in multiple linear regression models. Differences amongst stress, rest, and recovery metrics were evaluated as outcomes in separate models. Results: Of 321 subjects with HRV data, 284 were included in the final analytic sample after excluding those with missing covariates. The mean age was 50.7 ± 6.7, 49% were female (139), and 64% were African-American (182); 260 (88.4%) reported experiencing high levels of early-life trauma. There were no associations between early-life trauma during baseline HRV (T0), reactivity to stress (T1 - T0), and prolonged reactivity (T2 - T0). However, those with high early-life trauma had reduced HRV during recovery from stress compared to those with low early-life trauma (T2 - T1; Beta (95% CI) = -0.37 (-0.73, -0.01)). Results were similar after adjustment for sociodemographic factors and did not vary by race/ethnicity or gender. Conclusion: Among subjects with recent MI, high exposure to early-life trauma is associated with prolonged stress-induced autonomic dysfunction during stress and recovery, while the low exposure subjects revert to baseline HRV levels during recovery. This may indicate greater stress-induced cardiotoxicity in those exposed to early life trauma.

Smartphone Use and Interest in a Spine Surgery Recovery Mobile Application Among Patients in a US Academic Neurosurgery Practice.

Mobile applications (apps) are serving an increasingly important role in healthcare for patients and providers alike. In addition to streamlining active communication of patient-reported outcomes regarding quality of life, pain, and opioid consumption, smartphones equipped with activity tracking afford the opportunity to passively and objectively measure mobility, a key metric of recovery in spine surgery. However, app development is a resource-intensive process. To survey adult neurosurgery patients regarding access to and interest in this platform. In June and July 2017, a paper-based anonymous survey was distributed to patients in the waiting room of the adult neurosurgery clinic of a large US academic medical center. Patients' smartphone use and interest in using a mobile app following spine surgery were the primary and secondary outcomes, respectively. Of 146 included responses, 102 patients (70%) regularly used a smartphone, and this number increased to 77% among patients with a history of spine surgery (n=66, 45% of respondents). Seventy-one percent of patients with previous spine surgery expressed an interest in using a postoperative monitoring and communication app, compared to 81% of patients without prior spine operations (n=80, 55%). Among neurosurgery patients, there is a high level of access to and interest in smartphone apps to aid postoperative recovery. These results are useful for other neurosurgeons considering mobile app development for this purpose.

Unilateral Versus Bilateral Facetectomy and its Effect on Segmental Lordosis and Disc Height in MIS TLIF

Background: Minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) techniques have allowed for improved recovery and other metrics compared to its open counterpart. Our expanding literature has increasingly demonstrated the importance of spinopelvic parameters. One of the concerns with MIS TLIF is that the limited exposure and existing technology make it difficult to restore lumbar lordosis at the degenerative level requiring surgery. We hypothesize that bilateral facetectomy with MIS techniques will allow for increased ability to restore segmental lumbar lordosis versus traditional unilateral facetectomy. Methods: This is a retrospective chart review of all patients who underwent single level MIS TLIF between 2017 and 2018. We collected baseline characteristics and reviewed operative records to determine whether unilateral or bilateral facetectomies were performed. We used intraoperative CT (O-Arm) sagittal reformatted images to measure segmental lordosis as well as anterior, middle, and posterior disc heights. Results: Forty patients were identified. Eighteen underwent bilateral facetectomy, and 22 had unilateral facetectomy. We found a significantly increased middle disc height in the bilateral facetectomy group of 3.6 mm vs 2.8 mm in the unilateral group (p=0.04). We also found increased lordosis (4.4 vs. 3.7, respectively) as well as anterior (4.5 vs 3.5) disc height in the bilateral facetectomy group but neither reached statistical significance. Conclusion: Bilateral facetectomy is a tool that can help achieve maximal lordosis and disc height restoration in MIS TLIF surgery. Benefits besides lordosis and disc height restoration include increased autograft for fusion. Across various papers there seems to be a trend toward greater lordosis and disc height restoration, however most papers including ours have been underpowered to find significance.

Landsat Time-Series for Estimating Forest Aboveground Biomass and Its Dynamics across Space and Time: A Review

The free open access data policy instituted for the Landsat archive since 2008 has revolutionised the use of Landsat data for forest monitoring, especially for estimating forest aboveground biomass (AGB). This paper provides a comprehensive review of recent approaches utilising Landsat time-series (LTS) for estimating AGB and its dynamics across space and time. In particular, we focus on reviewing: (1) how LTS has been utilised to improve the estimation of AGB (for both single-date and over time) and (2) recent LTS-based approaches used for estimating AGB and its dynamics across space and time. In contrast to using single-date images, the use of LTS can benefit forest AGB estimation in two broad areas. First, using LTS allows for the filling of spatial and temporal data gaps in AGB predictions, improving the quality of AGB products and enabling the estimation of AGB across large areas and long time-periods. Second, studies have demonstrated that spectral information extracted from LTS analysis, including forest disturbance and recovery metrics, can significantly improve the accuracy of AGB models. Throughout the last decade, many innovative LTS-based approaches for estimating forest AGB dynamics across space and time have been demonstrated. A general trend is that methods have evolved as demonstrated through recent studies, becoming more advanced and robust. However, most of these methods have been developed and tested in areas that are either supported by established forest inventory programs and/or can rely on Lidar data across large forest areas. Further investigations should focus on tropical forest areas where inventory data are often not systematically available and/or out-of-date.

Evaluating uncertainty in Landsat-derived postfire recovery metrics due to terrain, soil, and shrub type variations in southern California

ABSTRACT Temporal trajectories of apparent vegetation abundance based on the multi-decadal Landsat image series provide valuable information on the postfire recovery of chaparral shrublands, which tend to mature within one decade. Signals of change in fractional shrub cover (FSC) extracted from time-sequential Normalized Difference Vegetation Index (NDVI) data can be systematically biased due to spatial variation in shrub type, soil substrate, or illumination differences associated with topography. We evaluate the effects of these variables in Landsat-derived metrics of FSC and postfire recovery, based upon three chaparral sites in southern California which contain shrub community ecotones, complex terrain, and soil variations. Detailed validations of prefire and postfire FSC are based on high spatial resolution ortho-imagery; cross-stratified random sampling is used for variable control. We find that differences in the composition and structure of shrubs (inferred from ortho-imagery) can substantially influence FSC-NDVI relations and impact recovery metrics. Differences in soil type have a moderate effect on the FSC-NDVI relation in one of the study sites, while no substantial effects were observed due to variation of terrain illumination among the study sites. Arithmetic difference recovery metrics – based on NDVI values that were not normalized with unburned control plots – correlate in a moderate but significant manner with a change in FSC (R 2 values range 0.47–0.59 at two sites). Similar regression coefficients resulted from using Landsat visible reflectance data alone. The lowest correlations to FSC resulted from Soil-Adjusted Vegetation Index (SAVI) and are attributed to the effects of the soil-adjustment factor in sparsely vegetated areas. The Normalized Burn Ratio and Normalized Burn Ratio 2 showed a moderate correlation to FSC. This study confirms the utility of Landsat NDVI data for postfire recovery evaluation and implies a need for stratified analysis of postfire recovery in some chaparral landscapes.

316 Comparison of two cannulation methods on post-operative recovery in sheep

Abstract The objective of this study was to compare post-operative recovery of sheep undergoing one of two methods of cannulation. Twelve commercial wethers were assigned to a surgical treatments (1-step cannulation or 2-step cannulation) and monitored post-operatively. In the 1-step treatment a cannula was fitted during surgery; in the 2-step procedure, the rumen wall is externalized and clamped off for 7 days, after which the cannula is fitted. Surgeries were performed on 2 consecutive days by the same surgeon with treatments balanced across surgery day. Dry matter intake (DMI), body temperature (T), heart rate (HR), and respiration rate (RR) were monitored for 24 days post-surgery. Blood samples were collected daily for 14 days post-surgery and serum fibrinogen levels (F) were measured as an indication of inflammatory response. Initial and final body weights (BW) were taken to assess weight loss during the post-operative period. Data were analyzed using a mixed model with fixed effects of initial value, procedure, and day post-surgery. Day of surgery was used as a random effect and the interaction between procedure and day post-surgery was also evaluated. Cannulation method did not affect BW (P = 0.23), T (P = 0.11), HR (P = 0.96), RR (P = 0.16), or F (P = 0.80). After surgery, F (P = 0.0003) and T (P < 0.0001) increased to plateaus reached at d 5 and 11, respectively, post-surgery, irrespective of treatment. Sheep HR (P = 0.0019) increased steadily post-surgery. Although no treatment effects were observed for these recovery metrics, DMI for Treatment 2 was significantly lower (P < 0.0001) than for Treatment 1. Results indicate the cannulation methods elicit similar post-operative recovery responses but that animals may not come back onto feed as well after undergoing two-step cannulation.

Body size trends and recovery amongst bivalves following the end-Triassic mass extinction

Fossils in the immediate aftermath of mass extinctions are often of small size, a phenomenon attributed to the Lilliput Effect (temporary, size reduction of surviving species). There has been little attempt to study size trends during subsequent recovery intervals nor has the relationship between size, diversity and environmental controls been evaluated. Here we examine the recovery following the end-Triassic mass extinction amongst bivalves of the British Lower and Middle Lias. Three distinct phases of size change are seen that are independent of other recovery metrics: initially bivalves are small but the Lilliput Effect is a minor factor, the majority of small taxa belong to new species that undergo a later within-species size increase (the Brobdingnag Effect) throughout the subsequent Hettangian Stage. New species that appeared during the Hettangian were also progressively larger and Cope's Rule (size increase between successive species) is seen – notably amongst ammonites. The size increase was reversed during the Sinemurian Stage, when bivalves once again exhibited small body sizes. During the Pliensbachian Stage another phase of size increase occurred with further evidence of the Brobdingnag Effect. These three phases of size change are seen across all suspension feeding ecological guilds of bivalve but are not expressed among deposit feeders. Local environmental conditions explain some aspects of size patterns, but factors such as temperature, marine oxygenation and sea level, do not correlate with the long-term size trends. The Brobdingnag Effect may reflect increased availability/quality of food during the recovery interval: a factor that controlled bivalve size but not evolution.

Clinical Performance of Radiofrequency Ablation for Treatment of Uterine Fibroids: Systematic Review and Meta-Analysis of Prospective Studies.

Background: Radiofrequency ablation (RFA) has emerged as a safe and effective treatment option for women with symptomatic uterine fibroids and can be delivered by laparoscopic, transvaginal, or transcervical approaches. The evidence regarding typical patient outcomes with RFA has not previously been examined in a comprehensive fashion.Materials and Methods: We performed a systematic review of prospective studies for treatment of uterine fibroids with RFA. Main outcomes were procedure time, patient recovery metrics, change in fibroid volume, symptom severity score (SSS), health-related quality of life (HRQL), and reinterventions. Data were analyzed with random effects meta-analysis and metaregression.Results: We identified 32 articles of 1283 unique patients (median age: 42 years) treated with laparoscopic RFA (19 articles), transvaginal RFA (8 articles), or transcervical fibroid ablation (5 articles). Mean procedure time was 49 minutes, time to discharge was 8.2 hours, time to normal activities was 5.2 days, and time to return to work was 5.1 days. At 12 months follow-up, fibroid volume decreased by 66%, HRQL increased by 39 points, and SSS decreased by 42 points (all P < .001 versus baseline). The annual cumulative rate of reinterventions due to fibroid-related symptoms was 4.2%, 8.2%, and 11.5% through 3 years.Conclusions: RFA of uterine fibroids significantly reduces fibroid volume, provides significant durable improvements in fibroid-related quality of life, and is associated with favorable reintervention rates.

Optimizing the recovery of disrupted single-sourced multi-echelon assembly supply chain networks

We consider optimization problems related to the scheduling of Multi-Echelon Assembly Supply Chain (MEASC) networks that find application in the recovery from large-scale disruptive events. Each manufacturer within this network assembles a component from a series of sub-components received from other manufacturers and, due to high qualification standards, each sub-component of the manufacturer is single-sourced. Our motivating industries for this problem are defense aircraft and biopharmaceutical manufacturing. We develop scheduling decision rules that are applied locally at each manufacturer and are proven to optimize two industry-relevant global recovery metrics: (i) minimizing the maximum tardiness of any order of the final product of the MEASC network, and (ii) and minimizing the time to recover from the disruptive event. Our approaches are applied to a data set based on an industrial partner’s supply chain to show their applicability as well as their advantages over Integer Programming (IP) models. The developed decision rules are proven to be optimal, faster, and more robust than the equivalent IP formulations. In addition, they provide conditions under which local manufacturer decisions will lead to globally optimal recovery efforts. These decision rules can help managers to make better production and shipping decisions to optimize the recovery after disruptions and quantitatively test the impact of different pre-event mitigation strategies against potential disruptions. They can be further useful in MEASCs with or expecting a large amount of backorders.

Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery

Patient-generated health data captured from smartphone sensors have the potential to better quantify the physical outcomes of surgery. The ability of these data to discriminate between postoperative trends in physical activity remains unknown. To assess whether physical activity captured from smartphone accelerometer data can be used to describe postoperative recovery among patients undergoing cancer operations. This prospective observational cohort study was conducted from July 2017 to April 2019 in a single academic tertiary care hospital in the United States. Preoperatively, adults (age ≥18 years) who spoke English and were undergoing elective operations for skin, soft tissue, head, neck, and abdominal cancers were approached. Patients were excluded if they did not own a smartphone. Study participants downloaded an application that collected smartphone accelerometer data continuously for 1 week preoperatively and 6 months postoperatively. The primary end points were trends in daily exertional activity and the ability to achieve at least 60 minutes of daily exertional activity after surgery among patients with vs without a clinically significant postoperative event. Postoperative events were defined as complications, emergency department presentations, readmissions, reoperations, and mortality. A total of 139 individuals were approached. In the 62 enrolled patients, who were followed up for a median (interquartile range [IQR]) of 147 (77-179) days, there were no preprocedural differences between patients with vs without a postoperative event. Seventeen patients (27%) experienced a postoperative event. These patients had longer operations than those without a postoperative event (median [IQR], 225 [152-402] minutes vs 107 [68-174] minutes; P < .001), as well as greater blood loss (median [IQR], 200 [35-515] mL vs 25 [5-100] mL; P = .006) and more follow-up visits (median [IQR], 2 [2-4] visits vs 1 [1-2] visits; P = .002). Compared with mean baseline daily exertional activity, patients with a postoperative event had lower activity at week 1 (difference, -41.6 [95% CI, -75.1 to -8.0] minutes; P = .02), week 3 (difference, -40.0 [95% CI, -72.3 to -3.6] minutes; P = .03), week 5 (difference, -39.6 [95% CI, -69.1 to -10.1] minutes; P = .01), and week 6 (difference, -36.2 [95% CI, -64.5 to -7.8] minutes; P = .01) postoperatively. Fewer of these patients were able to achieve 60 minutes of daily exertional activity in the 6 weeks postoperatively (proportions: week 1, 0.40 [95% CI, 0.31-0.49]; P < .001; week 2, 0.49 [95% CI, 0.40-0.58]; P = .003; week 3, 0.39 [95% CI, 0.30-0.48]; P < .001; week 4, 0.47 [95% CI, 0.38-0.57]; P < .001; week 5, 0.51 [95% CI, 0.42-0.60]; P < .001; week 6, 0.73 [95% CI, 0.68-0.79] vs 0.43 [95% CI, 0.33-0.52]; P < .001). Smartphone accelerometer data can describe differences in postoperative physical activity among patients with vs without a postoperative event. These data help objectively quantify patient-centered surgical recovery, which have the potential to improve and promote shared decision-making, recovery monitoring, and patient engagement.

Evaluating Resilience-Centered Development Interventions with Remote Sensing

Natural disasters are projected to increase in number and severity, in part due to climate change. At the same time a growing number of disaster risk reduction (DRR) and climate change adaptation measures are being implemented by governmental and non-governmental organizations, and substantial post-disaster donations are frequently pledged. At the same time there has been increasing demand for transparency and accountability, and thus evidence of those measures having a positive effect. We hypothesized that resilience-enhancing interventions should result in less damage during a hazard event, or at least quicker recovery. In this study we assessed recovery over a 3 year period of seven municipalities in the central Philippines devastated by Typhoon Haiyan in 2013. We used very high resolution optical images (&lt;1 m), and created detailed land cover and land use maps for four epochs before and after the event, using a machine learning approach with extreme gradient boosting. The spatially and temporally highly variable recovery maps were then statistically related to detailed questionnaire data acquired by DEval in 2012 and 2016, whose principal aim was to assess the impact of a 10 year land-planning intervention program by the German agency for technical cooperation (GIZ). The survey data allowed very detailed insights into DRR-related perspectives, motivations and drivers of the affected population. To some extent they also helped to overcome the principal limitation of remote sensing, which can effectively describe but not explain the reasons for differential recovery. However, while a number of causal links between intervention parameters and reconstruction was found, the common notion that a resilient community should recover better and more quickly could not be confirmed. The study also revealed a number of methodological limitations, such as the high cost for commercial image data not matching the spatially extensive but also detailed scale of field evaluations, the remote sensing analysis likely overestimating damage and thus providing incorrect recovery metrics, and image data catalogues especially for more remote communities often being incomplete. Nevertheless, the study provides a valuable proof of concept for the synergies resulting from an integration of socio-economic survey data and remote sensing imagery for recovery assessment.

Forest resilience under global environmental change: Do we have the information we need? A systematic review.

The capacity of forests to recover after disturbance, i.e., their resilience, determines their ability to persist and function over time. Many variables, natural and managerial, affect forest resilience. Thus, understanding their effects is critical for the development of sound forest conservation and management strategies, especially in the context of ongoing global environmental changes. We conducted a representative review, meta-analysis, of the forest literature in this topic (search terms “forest AND resilience”). We aimed to identify natural conditions that promote or jeopardize resilience, assess the efficacy of post-disturbance management practices on forest recovery, and evaluate forest resilience under current environmental changes.We surveyed more than 2,500 articles and selected the 156 studies (724 observations) that compared and quantified forest recovery after disturbance under different contexts. Context of recovery included: resource gradients (moisture and fertility), post-disturbance biomass reduction treatments, species richness gradients, incidence of a second disturbance, and disturbance severity. Metrics of recovery varied from individual tree growth and reproduction, to population abundance, to species richness and cover. Analyses show management practices only favored recovery through increased reproduction (seed production) and abundance of recruitment stages. Higher moisture conditions favored recovery, particularly in dry temperate regions; and in boreal forests, this positive effect increased with regional humidity. Biomass reduction treatments were only effective in increasing resilience after a drought. Early recruiting plant stages benefited from increased severity, while disturbance severity was associated with lower recovery of remaining adult trees. This quantitative review provides insight into the natural conditions and management practices under which forest resilience is enhanced and highlights conditions that could jeopardize future resilience. We also identified important knowledge gaps, such as the role of diversity in determining forest resilience and the lack of data in many regions.

Contribution of individual psychological and psychosocial factors to symptom severity and time-to-recovery after naturally-occurring acute infective illness: The Dubbo Infection Outcomes Study (DIOS)

BackgroundSubstantial heterogeneity exists in both the severity of symptoms experienced as part of the sickness response to naturally-occurring infections, and the time taken for individuals to recover from these symptoms. Although contributing immunological and genetic factors have been previously been explored, less is known about the role of individual psychological and psychosocial factors, which may modulate the host immune response, or contribute independently, to symptom severity and duration. MethodsLongitudinally-collected data from 484 Caucasian participants (mean age: 33.5 years; 51% women) experiencing a naturally-occurring acute infective illness enrolled in the prospective Dubbo Infection Outcome Study (DIOS) were analysed. At intake and subsequent follow-up assessments, self-report questionnaires were used to ascertain individual psychological and psychosocial characteristics and symptom information. Principal component analysis was applied to symptom data to derive endophenotype severity scores representing discrete symptom domains (fatigue, mood, pain, neurocognitive difficulties) and an overall index of severity. The contribution of individual psychological (trait neuroticism, locus of control, and illness behaviours) and psychosocial factors (relative socioeconomic advantage) to endophenotype severity at baseline were examined using multivariable linear regression models; interval-censored flexible parametric proportional hazards survival models were used to explore time to recovery (defined using within-sample negative threshold values). ResultsAfter controlling for time since symptom onset, greater levels of trait neuroticism consistently predicted greater symptom severity across all symptom domains (all p’s < 0.015). Similarly, greater relative socioeconomic disadvantage was significantly associated with greater severity across all endophenotypes (p’s < 0.025) except neurocognitive disturbance. Locus of control and illness behaviours contributed differentially across endophenotypes. Reduced likelihood of recovery was significantly predicted by greater initial symptom severity for all endophenotypes (all p’s < 0.001), as well as higher levels of trait neuroticism. ConclusionsIndividual psychological and psychosocial factors contribute to the initial severity and to the prolonged course of symptoms after naturally-occurring infective illnesses. These factors may play an independent role, represent a bias in symptom reporting, or reflect increased stress responsivity and a heightened inflammatory response. Objective metrics for severity and recovery are required to further elucidate their roles.

Grizzly bear selection of recently harvested forests is dependent on forest recovery rate and landscape composition

Forests in the early stages of regeneration are valuable habitat for threatened grizzly bear (Ursus arctos) populations inhabiting the interior mountains of North America, with forest management affecting the timing, prevalence, and quality of such habitats. Forest harvesting can lead to early-seral habitat, however the quality and duration of post-harvest habitat compared to natural disturbances (e.g., wildfire), is not known. North American silvicultural practices are mandated to ensure tree regrowth following harvesting, and a rapid rate of growth in managed tree regeneration may lead to a shorter time window during which attractive early-seral habitat is available to bears compared to natural forest disturbances. The distribution of natural disturbances across forested landscapes may also be an important consideration in the response of bears to forest harvesting. In this study, we analyzed grizzly bear habitat selection for 160 collared grizzly bears across 118,000-km2 (68% of their known habitat) in Alberta, Canada, using metrics of forest disturbance and recovery derived from a 33-year satellite time series. We developed seasonal resource selection functions to evaluate (1) if selection of recently harvested forests was contingent upon the availability of natural disturbances, (2) how habitat selection within disturbed areas varied across disturbance types, and (3) how habitat suitability changed over time during the first 30 years of forest recovery following various disturbance types. Results showed that, compared to areas not recently disturbed, grizzly bears were up to three times more likely to select for harvested forests when natural disturbances were limited in their home range, while selection of harvested forests was neutral when natural disturbances were abundant. When available, grizzly bears were more likely to select for natural disturbances compared to harvested locations, especially during Hypophagia (spring) and Hyperphagia (fall). Selection of harvested locations was inversely related to forest recovery assessed by spectral analysis and decreased sharply 15–20 years post-harvest, at which point it tended to be lower than pre-disturbance. This study demonstrates the utility of vegetation, disturbance, and recovery metrics derived from satellite time series for enriching our understanding of wildlife habitat selection in dynamic landscapes. Our results also have implications for forest management in regions where grizzly bear habitat availability and selection patterns are important. While rapid forest recovery following harvest is desirable and beneficial for a multitude of ecological and economic objectives, it appears to minimize the period of attractive early-seral habitat for grizzly bears.

Optimising quantitative 90Y PET imaging: an investigation into the effects of scan length and Bayesian penalised likelihood reconstruction

BackgroundPositron emission tomography (PET) imaging of 90Y following selective internal radiation therapy (SIRT) is possible, but image quality is poor, and therefore, accurate quantification and dosimetry are challenging. This study aimed to quantitatively optimise 90Y PET imaging using a new Bayesian penalised likelihood (BPL) reconstruction algorithm (Q.Clear, GE Healthcare). The length of time per bed was also investigated to study its impact on quantification accuracy.MethodsA NEMA IQ phantom with an 8:1 sphere-to-background ratio was scanned overnight on a GE Discovery 710 PET/CT scanner. Datasets were rebinned into varying lengths of time (5–60 min); the 15-min rebins were reconstructed using BPL reconstruction with a range of noise penalisation weighting factors (beta values). The metrics of contrast recovery (CR), background variability (BV), and recovered activity percentage (RAP) were calculated in order to identify the optimum beta value. Reconstructions were then carried out on the rest of the timing datasets using the optimised beta value; the same metrics were used to assess the quantification accuracy of the reconstructed images.ResultsA beta value of 1000 produced the highest CR and RAP (76% and 73%, 37 mm sphere) without overly accentuating the noise (BV) in the image. There was no statistically significant increase (p < 0.05) in either the CR or RAP for scan times of > 15 min. For the 5-min acquisitions, there was a statistically significant decrease in RAP (28 mm sphere, p < 0.01) when compared to the 15-min acquisition.ConclusionOur results indicate that an acquisition length of 15 min and beta value of 1000 (when using Q.Clear reconstruction) are optimum for quantitative 90Y PET imaging. Increasing the acquisition time to more than 15 min reduces the image noise but has no significant impact on image quantification.

PSU36 SYSTEMATIC REVIEW OF SURGEON LEARNING CURVES IN ROBOT-ASSISTED SURGERY

To assess and summarize the impact surgeon learning curve effects could have on surgical metrics, clinical outcomes, and cost-benefit decisions in robot-assisted surgery across all surgical procedures. A systematic literature search of MEDLINE, MEDLINE In-Process, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and NHS Economic Evaluation Database were searched from 2012 to February 5, 2018. There were 2,316 total publications identified with potentially relevant information. From the systematic search, 68 studies were included in this review (49 in surgical setting; 19 in simulator/training setting). Of the 49 surgical studies, 80% were retrospective, 73% were single-arm, and all were observational in design. The number of surgeons per study was small; 67% of studies included fewer than five. The most frequent specialties were urology (n=20), general surgery (n=13), and gynecology (n=7). Time-based variables were the most commonly reported to assess learning curves (86% of studies), and the most reported individual metric was operative time (67% of studies). Other measures, including length of hospital stay, morbidity/mortality rates, and specialty-specific metrics, were less commonly reported. Of the major surgical, safety, and recovery metrics captured within this review, operative time (67%), complication rate (18%), and length of stay (10%) were reported most frequently, respectively. When evaluating the evidence base, the variability in results between studies and surgeons makes it challenging to synthesize a reliable estimate for length and burden of the learning curve for any one procedure. The literature lacks studies with high-quality designs assessing surgeon learning curves in robot-assisted surgery. In addition, the methods used to assess learning curves are poorly described and frequently inadequate. Opportunities remain to establish quantitative, evidence-based approaches to measuring and defining learning curves in robotic surgery, as well as estimating the clinical and economic burdens associated with surgeon learning.

Assessing spectral measures of post-harvest forest recovery with field plot data

Information regarding the nature and rate of forest recovery is required to inform forest management, monitoring, and reporting activities. Delayed establishment or return of forests has implications to harvest rotations and carbon uptake, among others, creating a need for spatially-explicit, large-area, characterizations of forest recovery. Landsat time series (LTS) has been demonstrated as a means to quantitatively relate forest recovery, noting that there are gaps in our understanding of the linkage between spectral measures of forest recovery and manifestations of forest structure and composition. Field plots provide a means to better understand the linkage between forest characteristics and spectral recovery indices. As such, from a large set of existing field plots, we considered the conditions present for the year in which the co-located pixel was considered spectrally recovered using the Years to Recovery (Y2R) metric. Y2R is a long-term metric of spectral recovery that indicates the number of years required for a pixel to return to 80% of its pre-disturbance Normalized Burn Ratio value. Absolute and relative metrics of recovery at 5 years post-disturbance were also considered. We used these three spectral recovery metrics to predict the stand development class assigned by the field crew for 284 seedling plots with an overall accuracy of 73.59%, with advanced seedling stands more accurately discriminated (omission error, OE = 15.74%) than young seedling stands (OE = 49.84%). We then used field-measured attributes (e.g. height, stem density, dominant species) from the seedling plots to classify the plots into three spectral recovery groups, which were defined using the Y2R metric: spectral recovery in (1) 1–5 years, (2) 6–10 years, or (3) 11–15 years. Overall accuracy for spectral recovery groups was 61.06%. Recovery groups 1 and 3 were discriminated with greater accuracy (producer’s and user’s accuracies > 66%) than recovery group 2 (< 50%). The top field-measured predictors of spectral recovery were mean height, dominant species, and percentage of stems in the plot that were deciduous. Variability in stand establishment and condition make it challenging to accurately discriminate among recovery rates within 10 years post-harvest. Our results indicate that the long-term metric Y2R relates to forest structure and composition attributes measured in the field and that spectral development post-disturbance corresponds with expectations of structural development, particularly height, for different species, site types, and deciduous abundance. These results confirm the utility of spectral recovery measures derived from LTS data to augment landscape-level assessments of post-disturbance recovery.

Long‐term plant community trajectories suggest divergent responses of native and non‐native perennials and annuals to vegetation removal and seeding treatments

Land managers frequently apply vegetation removal and seeding treatments to restore ecosystem function following woody plant encroachment, invasive species spread, and wildfire. However, the long‐term outcome of these treatments is unclear due to a lack of widespread monitoring. We quantified how vegetation removal (via wildfire or management) with or without seeding and environmental conditions related to plant community composition change over time in 491 sites across the intermountain western United States. Most community metrics took over 10 years to reach baseline conditions posttreatment, with the slowest recovery observed for native perennial cover. Total cover was initially higher in sites with seeding after vegetation removal than sites with vegetation removal alone, but increased faster in sites with vegetation removal only. Seeding after vegetation removal was associated with rapidly increasing non‐native perennial cover and decreasing non‐native annual cover. Native perennial cover increased in vegetation removal sites irrespective of seeding and was suppressed by increasing non‐native perennial cover. Seeding was associated with higher non‐native richness across the monitoring period as well as initially higher, then declining, total and native species richness. Several cover and richness recovery metrics were positively associated with mean annual precipitation and negatively associated with mean annual temperature, whereas relationships with weather extremes depended on the lag time and season. Our results suggest that key plant groups, such as native perennials and non‐native annuals, respond to restoration treatments at divergent timescales and with different sensitivities to climate and weather variation.