Scheduling and Vendor Consistency Improves Turnover Time Efficiency in Total Joint Arthroplasty.

BACKGROUND: Maximizing operative room (OR) efficiency is important for hospital efficiency, patient care, and positive surgeon and staff morale. Reducing turnover time (TOT) has become a popular focus to improve OR efficiency. The present study evaluated if TOT is influenced by changing case type, implant vendor, and/or laterality. METHODS: In total, 444 turnovers from January to July 2023 were retrospectively analyzed. All turnovers were same-surgeon turnovers between primary arthroplasty cases in dedicated, overlapping rooms. Single linear regression models tested the predictability of TOT based on case type, vendor, and laterality. A multivariate multiple regression and 1-way Analyses of Variance analyzed variables against each other. Independent sample t-tests evaluated TOTs when all variables were the same or different. RESULTS: Changing versus keeping the same case type increased TOT by 2.4 minutes (95% confidence interval [CI] = 0.7, 4.0; P = .004). Changing vendors increased TOT by 2.9 minutes (95% CI = 1.1, 4.7; P = .002). Laterality did not affect TOT, with a change of 0.9 minutes (95% CI = -0.6, 2.5; P = .229). Vendor (P = .030) independently predicted TOT when analyzed as a covariate with case type (P = .410). The TOT with same case type and vendor (mean 38.2 minutes; range, 22 to 62) was less than that of different case types and vendors (mean 41.4 minutes; range, 26 to 73) (P = .017). Mean TOT differed by 5.5 minutes when keeping all variables the same versus all different (P = .018). CONCLUSIONS: Maintaining a consistent case type, vendor, and laterality had a synergistic effect in reducing TOT in arthroplasty ORs with the same primary surgeon running 2 overlapping rooms. Changing vendor representatives was found to independently predict TOT increases, which is likely attributed to a disruption in workflow and collaboration of the multidisciplinary OR team. LEVEL OF EVIDENCE: Level III.

Molecular 14 C evidence for contrasting turnover and temperature sensitivity of soil organic matter components.

Climate projection requires an accurate understanding for soil organic carbon (SOC) decomposition and its response to warming. An emergent view considers that environmental constraints rather than chemical structure alone control SOC turnover and its temperature sensitivity (i.e., Q10 ), but direct long-term evidence is lacking. Here, using compound-specific radiocarbon analysis of soil profiles along a 3300-km grassland transect, we provide direct evidence for the rapid turnover of lignin-derived phenols compared with slower-cycling molecular components of SOC (i.e., long-chain lipids and black carbon). Furthermore, in contrast to the slow-cycling components whose turnover is strongly modulated by mineral association and exhibits low Q10 , lignin turnover is mainly regulated by temperature and has a high Q10 . Such contrasts resemble those between fast-cycling (i.e., light) and mineral-associated slow-cycling fractions from globally distributed soils. Collectively, our results suggest that warming may greatly accelerate the decomposition of lignin, especially in soils with relatively weak mineral associations.

How do endoscopic bladder tumor resection techniques affect pathology practice? EAU Section of Uro-Technology (ESUT) and Uropathology (ESUP) survey.

PURPOSE: We aimed to examine how different endoscopic bladder tumor resection techniques affect pathologists' clinical practice patterns. METHODS: An online survey including 28 questions clustered in four main sections was prepared by the ESUT ERBT Working Group and released to the pathologists working in the institutions of experts of the ESUT Board and the working groups and experts in the uropathology working group. A descriptive analysis was performed using the collected data. RESULTS: Sixty-eight pathologists from 23 countries responded to the survey. 37.3% of the participants stated that they always report the T1 sub-staging. Of those who gave sub-staging, 61.3% used T1a, b. 85.2% think that en bloc samples provide spatial orientation faster than piecemeal samples, and 60% think en bloc samples are timesaving during an inspection. 55.7% stated that whether the tissue sample is en bloc or piecemeal is essential. 57.4% think en bloc sample reduces turnaround time and is cost-effective for 44.1%. A large number of pathologists find that the pathology examination of piecemeal samples has a longer learning curve. CONCLUSION: The survey shows that pathologists think that they can diagnose faster, accurately, and cost-effectively with ERBT samples, but they do not often encounter them in practice. Moreover, en bloc samples may be a better choice in pathology resident training. Evidence from real-life observational pathology practice and clinical research can reveal the current situation more clearly and increase awareness on proper treatment in endoscopic management of bladder tumors.

High potential of stable carbon sequestration in phytoliths of China's grasslands.

Phytolith carbon (C) sequestration plays a key role in mitigating global climate change at a centennial to millennial time scale. However, previous estimates of phytolith-occluded carbon (PhytOC) storage and potential in China's grasslands have large uncertainties mainly due to multiple data sources. This contributes to the uncertainty in predicting long-term C sequestration in terrestrial ecosystems using Earth System Models. In this study, we carried out an intensive field investigation (79 sites, 237 soil profiles [0-100 cm], and 61 vegetation assessments) to quantify PhytOC storage in China's grasslands and to better explore the biogeographical patterns and influencing factors. Generally, PhytOC production flux and soil PhytOC density in both the Tibetan Plateau and the Inner Mongolian Plateau had a decreasing trend from the Northeast to the Southwest. The aboveground PhytOC production rate in China's grassland was 0.48 × 106 t CO2 a-1 , and the soil PhytOC storage was 383 × 106 t CO2 . About 45% of soil PhytOC was stored in the deep soil layers (50-100 cm), highlighting the importance of deep soil layers for C stock assessments. Importantly, the Tibetan Plateau had the greatest contribution (more than 70%) to the PhytOC storage in China's grasslands. The results of multiple regression analysis indicated that altitude and soil texture significantly influenced the spatial distribution of soil PhytOC, explaining 78.1% of the total variation. Soil phytolith turnover time in China's grasslands was mainly controlled by climatic conditions, with the turnover time on the Tibetan Plateau being significantly longer than that on the Inner Mongolian Plateau. Our results offer more accurate estimates of the potential for phytolith C sequestration from ecological restoration projects in degraded grassland ecosystems. These estimates are essential to parameterizing and validating global C models.

Observation-based global soil heterotrophic respiration indicates underestimated turnover and sequestration of soil carbon by terrestrial ecosystem models.

Soil heterotrophic respiration (Rh ) refers to the flux of CO2 released from soil to atmosphere as a result of organic matter decomposition by soil microbes and fauna. As one of the major fluxes in the global carbon cycle, large uncertainties still exist in the estimation of global Rh , which further limits our current understanding of carbon accumulation in soils. Here, we applied a Random Forest algorithm to create a global data set of soil Rh , by linking 761 field observations with both abiotic and biotic predictors. We estimated that global Rh was 48.8 ± 0.9 Pg C year-1 for 1982-2018, which was 16% less than the ensemble mean (58.6 ± 9.9 Pg C year-1 ) of 16 terrestrial ecosystem models. By integrating our observational Rh with independent soil carbon stock data sets, we obtained a global mean soil carbon turnover time of 38.3 ± 11 year. Using observation-based turnover times as a constraint, we found that terrestrial ecosystem models simulated faster carbon turnovers, leading to a 30% (74 Pg C) underestimation of terrestrial ecosystem carbon accumulation for the past century, which was especially pronounced at high latitudes. This underestimation is equivalent to 45% of the total carbon emissions (164 Pg C) caused by global land-use change at the same time. Our analyses highlight the need to constrain ecosystem models using observation-based and locally adapted Rh values to obtain reliable projections of the carbon sink capacity of terrestrial ecosystems.

Data-driven estimates of global litter production imply slower vegetation carbon turnover.

Accurate quantification of vegetation carbon turnover time (τveg ) is critical for reducing uncertainties in terrestrial vegetation response to future climate change. However, in the absence of global information of litter production, τveg could only be estimated based on net primary productivity under the steady-state assumption. Here, we applied a machine-learning approach to derive a global dataset of litter production by linking 2401 field observations and global environmental drivers. Results suggested that the observation-based estimate of global natural ecosystem litter production was 44.3 ± 0.4 Pg C year-1 . By contrast, land-surface models (LSMs) overestimated the global litter production by about 27%. With this new global litter production dataset, we estimated global τveg (mean value 10.3 ± 1.4 years) and its spatial distribution. Compared to our observation-based τveg , modelled τveg tended to underestimate τveg at high latitudes. Our empirically derived gridded datasets of litter production and τveg will help constrain global vegetation models and improve the prediction of global carbon cycle.

Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records.

The rate of change in atmospheric CO2 is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001-2016) in a 55 year old 30 km2 pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover ~18% of the global land area. The forest accumulated 145-160 g C m-2  year-1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m-2  year-1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m2 and 372 g N/m2 . Carbon accumulated mostly in the soil (~71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester ~0.4 Pg C/year over several decades.

Accelerated terrestrial ecosystem carbon turnover and its drivers.

The terrestrial carbon cycle has been strongly influenced by human-induced CO2 increase, climate change, and land use change since the industrial revolution. These changes alter the carbon balance of ecosystems through changes in vegetation productivity and ecosystem carbon turnover time (τeco ). Even though numerous studies have drawn an increasingly clear picture of global vegetation productivity changes, global changes in τeco are still unknown. In this study, we analyzed the changes of τeco between the 1860s and the 2000s and their drivers, based on theory of dynamic carbon cycle in non-steady state and process-based ecosystem model. Results indicate that τeco has been reduced (i.e., carbon turnover has accelerated) by 13.5% from the 1860s (74 years) to the 2000s (64 years), with reductions of 1 year of carbon residence times in vegetation (rveg ) and of 9 years in soil (rsoil ). Additionally, the acceleration of τeco was examined at biome scale and grid scale. Among different driving processes, land use change and climate change were found to be the major drivers of turnover acceleration. These findings imply that carbon fixed by plant photosynthesis is being lost from ecosystems to the atmosphere more quickly over time, with important implications for the climate-carbon cycle feedbacks.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long-term data assimilation.

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback.

Growth explains microbial carbon use efficiency across soils differing in land use and geology.

The ratio of carbon (C) that is invested into microbial growth to organic C taken up is known as microbial carbon use efficiency (CUE), which is influenced by environmental factors such as soil temperature and soil moisture. How microbes will physiologically react to short-term environmental changes is not well understood, primarily due to methodological restrictions. Here we report on two independent laboratory experiments to explore short-term temperature and soil moisture effects on soil microbial physiology (i.e. respiration, growth, CUE, and microbial biomass turnover): (i) a temperature experiment with 1-day pre-incubation at 5, 15 and 25 °C at 60% water holding capacity (WHC), and (ii) a soil moisture/oxygen (O2) experiment with 7-day pre-incubation at 20 °C at 30%, 60% WHC (both at 21% O2) and 90% WHC at 1% O2. Experiments were conducted with soils from arable, pasture and forest sites derived from both silicate and limestone bedrocks. We found that microbial CUE responded heterogeneously though overall positively to short-term temperature changes, and decreased significantly under high moisture level (90% WHC)/suboxic conditions due to strong decreases in microbial growth. Microbial biomass turnover time decreased dramatically with increasing temperature, and increased significantly at high moisture level (90% WHC)/suboxic conditions. Our findings reveal that the responses of microbial CUE and microbial biomass turnover to short-term temperature and moisture/O2 changes depended mainly on microbial growth responses and less on respiration responses to the environmental cues, which were consistent across soils differing in land use and geology.

Temperature sensitivity of soil organic carbon decomposition increased with mean carbon residence time: Field incubation and data assimilation.

Temperature sensitivity of soil organic carbon (SOC) decomposition is one of the major uncertainties in predicting climate-carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long-term field incubation experiment with deep soil collars (0-70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi-pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation (DA) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate.

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models.

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0-100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, temperature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temperature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. By providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about factors regulating the turnover of soil organic matter.

In vivo exfoliating efficacy of biodegradable beads and the correlation with user's satisfaction.

BACKGROUND/PURPOSE: By the end of 2017, non-biodegradable microbeads will be prohibited in USA, UK and Europe, due to their environmental issue. There are biodegradable beads available, but their effect on skin desquamation has not been evaluated yet. This study aimed to understand the skin renewal time, moisturizing effect and user's satisfaction of gel scrubs containing different exfoliating beads. METHODS: Gel scrubs, containing polyethylene, mannan or wax beads, were used in this study. The stratum corneum turnover time (SCTT) and skin hydration were evaluated by dansyl chloride staining technique and Corneometer® , respectively. The self-assessment was also performed after a 3-week home use trial. RESULTS: The SCTTs of three different gel scrubs were not significantly different. A numerical increase in the skin hydration level was found in all groups. Satisfaction scores for the appearance and usability attributes were similar, but scores for improvement in the skin hydration and skin smoothness were higher in the gel scrubs with mannan or wax beads. CONCLUSION: All three gel scrubs provided a similar effect on the SCTT and skin hydration, but gel scrubs with mannan or wax beads were more favorable. Thus, these two biodegradable exfoliating beads may be good substitutes in scrubbing products.

Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning.

OBJECTIVEFlow diverters (FDs) are designed to occlude intracranial aneurysms (IAs) while preserving flow to essential arteries. Incomplete occlusion exposes patients to risks of thromboembolic complications and rupture. A priori assessment of FD treatment outcome could enable treatment optimization leading to better outcomes. To that end, the authors applied image-based computational analysis to clinically FD-treated aneurysms to extract information regarding morphology, pre- and post-treatment hemodynamics, and FD-device characteristics and then used these parameters to train machine learning algorithms to predict 6-month clinical outcomes after FD treatment.METHODSData were retrospectively collected for 84 FD-treated sidewall aneurysms in 80 patients. Based on 6-month angiographic outcomes, IAs were classified as occluded (n = 63) or residual (incomplete occlusion, n = 21). For each case, the authors modeled FD deployment using a fast virtual stenting algorithm and hemodynamics using image-based computational fluid dynamics. Sixteen morphological, hemodynamic, and FD-based parameters were calculated for each aneurysm. Aneurysms were randomly assigned to a training or testing cohort in approximately a 3:1 ratio. The Student t-test and Mann-Whitney U-test were performed on data from the training cohort to identify significant parameters distinguishing the occluded from residual groups. Predictive models were trained using 4 types of supervised machine learning algorithms: logistic regression (LR), support vector machine (SVM; linear and Gaussian kernels), K-nearest neighbor, and neural network (NN). In the testing cohort, the authors compared outcome prediction by each model trained using all parameters versus only the significant parameters.RESULTSThe training cohort (n = 64) consisted of 48 occluded and 16 residual aneurysms and the testing cohort (n = 20) consisted of 15 occluded and 5 residual aneurysms. Significance tests yielded 2 morphological (ostium ratio and neck ratio) and 3 hemodynamic (pre-treatment inflow rate, post-treatment inflow rate, and post-treatment aneurysm averaged velocity) discriminants between the occluded (good-outcome) and the residual (bad-outcome) group. In both training and testing, all the models trained using all 16 parameters performed better than all the models trained using only the 5 significant parameters. Among the all-parameter models, NN (AUC = 0.967) performed the best during training, followed by LR and linear SVM (AUC = 0.941 and 0.914, respectively). During testing, NN and Gaussian-SVM models had the highest accuracy (90%) in predicting occlusion outcome.CONCLUSIONSNN and Gaussian-SVM models incorporating all 16 morphological, hemodynamic, and FD-related parameters predicted 6-month occlusion outcome of FD treatment with 90% accuracy. More robust models using the computational workflow and machine learning could be trained on larger patient databases toward clinical use in patient-specific treatment planning and optimization.

Effect of the Implementation of a New Electronic Health Record System on Surgical Case Turnover Time.

Many health care providers, hospitals, and hospital systems have adopted new electronic health records (EHR) to streamline patient care and comply with government mandates. Commercial EHR vendors advertise improved efficiency, but few studies have been performed to validate these claims. Therefore, this study was performed to evaluate the effect of deploying a new EHR system on operating room efficiency and surgical case turnover time (TOT) at our institution. Data on TOT were collected after implementation of a new EHR (Epic) from June 2015 to May 2016, which replaced a legacy system of both paper and electronic records. These TOTs were compared to data from the same months in the preceding year. Mean TOT and standard deviations were calculated. The two-sample t-test was used to compare means by month and the F-test was used to compare standard deviations. There was a significant increase in TOT (63.0 vs. 53.0 min, p < 0.001) in the first month after implementation. This improved by the second month (59.0 vs. 53.0 min, p < 0.001), but the relative increase persisted until the end of the fifth month after which it remained around the pre-implementation baseline until the end of the study. The standard deviation significantly decreased after the fourth month post-implementation and persisted throughout the studied period. We found that implementation of an EHR led to a significant decrease in efficiency that persisted for five months. While EHRs have the potential to improve hospital workflow, caution is advised in the case of operating room implementation. While the mean TOT did not improve beyond the pre-implementation baseline, the standard deviation was significantly improved after the first four months.

Analysis to Establish Differences in Efficiency Metrics Between Operating Room and Non-Operating Room Anesthesia Cases.

While a number of studies have examined efficiency metrics in the operating rooms (ORs), there are few studies addressing non-operating room anesthesia (NORA) metrics. The standards established in the realm of OR studies may not apply to ongoing investigations of NORA efficiency. We hypothesize that there are significant differences in these commonly used metrics. Using retrospective data from a single tertiary care hospital in the 2015 calendar year, we measured turnover times, cancellation rates, first case start delays, and scheduling error (actual time minus scheduled time) for the OR and NORA settings. On average, TOTs for NORA cases were approximately 50% shorter than OR cases (16.21 min vs. 37.18 min), but had a larger variation (11.02 min vs. 8.12 min). NORA cases were 64% as likely to be cancelled compared to OR cases. In contrast, NORA cases had an average first case start delay that was two times greater than that of OR cases (24.45 min vs. 10.58 min), along with over double the standard deviation (11.97 min vs. 5.90 min). Case times for NORA settings tended to be overestimated (-4.07 min versus -2.12 min), but showed less variation (8.61 min vs. 17.92 min). In short, there are significant differences in common efficiency metrics between OR and NORA cases. Future studies should elucidate and validate appropriate efficiency benchmarks for the NORA setting.

Potential for long-term transfer of dissolved organic carbon from riparian zones to streams in boreal catchments.

Boreal regions store most of the global terrestrial carbon, which can be transferred as dissolved organic carbon (DOC) to inland waters with implications for both aquatic ecology and carbon budgets. Headwater riparian zones (RZ) are important sources of DOC, and often just a narrow 'dominant source layer' (DSL) within the riparian profile is responsible for most of the DOC export. Two important questions arise: how long boreal RZ could sustain lateral DOC fluxes as the sole source of exported carbon and how its hydromorphological variability influences this role. We estimate theoretical turnover times by comparing carbon pools and lateral exports in the DSL of 13 riparian profiles distributed over a 69 km(2) catchment in northern Sweden. The thickness of the DSL was 36 ± 18 (average ± SD) cm. Thus, only about one-third of the 1-m-deep riparian profile contributed 90% of the lateral DOC flux. The 13 RZ exported 8.7 ± 6.5 g C m(-2) year(-1) , covering the whole range of boreal stream DOC exports. The variation could be explained by local hydromorphological characteristics including RZ width (R(2) = 0.90). The estimated theoretical turnover times were hundreds to a few thousands of years, that is there is a potential long-lasting supply of DOC. Estimates of net ecosystem production in the RZ suggest that lateral fluxes, including both organic and inorganic C, could be maintained without drawing down the riparian pools. This was supported by measurements of stream DO(14) C that indicated modern carbon as the predominant fraction exported, including streams disturbed by ditching. The transfer of DOC into boreal inland waters from new and old carbon sources has a major influence on surface water quality and global carbon balances. This study highlights the importance of local variations in RZ hydromorphology and DSL extent for future DOC fluxes under a changing climate.

Isotope turnover rates and diet-tissue discrimination in skin of ex situ bottlenose dolphins (Tursiops truncatus).

Diet-tissue discrimination factors (Δ(15)N or Δ(13)C) and turnover times are thought to be influenced by a wide range of variables including metabolic rate, age, dietary quality, tissue sampled and the taxon being investigated. In the present study, skin samples were collected from ex situ dolphins that had consumed diets of known isotopic composition for a minimum of 8 weeks. Adult dolphins consuming a diet of low fat (5-6%) and high δ(15)N value had significantly lower Δ(15)N values than animals consuming a diet with high fat (13.9%) and low δ(15)N value. Juvenile dolphins consuming a diet with low fat and an intermediate δ(15)N value had significantly higher Δ(15)N values than adults consuming the same diet. Calculated half-lives for δ(15)N ranged from 14 to 23 days (17.2 ± 1.3 days). Half-lives for δ(13)C ranged from 11 to 23 days with a significant difference between low fat (13.9 ± 4.8 days) and high fat diets (22.0 ± 0.5 days). Overall, our results indicate that while assuming a Δ(13)C value of 1‰ may be appropriate for cetaceans, Δ(15)N values may be closer to 1.5‰ rather than the commonly assumed 3‰. Our data also suggest that understanding seasonal variability in prey composition is another significant consideration when applying discrimination factors or turnover times to field studies focused on feeding habits. Isotope retention times of only a few weeks suggest that, in addition, these isotope data could play an important role in interpreting recent fine-scale habitat utilization and residency patterns.

Successful strategies for the reduction of operating room turnover times in a tertiary care academic medical center.

BACKGROUND: Turnover time (TOT) is one of the classic measures of operating room (OR) efficiency. There have been numerous efforts to reduce TOTs, sometimes through the employment of a process improvement framework. However, most examples of process improvement in the TOT focus primarily on operational changes to workflows and statistical significance. These examples of process improvement do not detail the complex organizational challenges associated with implementing, expanding, and sustaining change. METHODS: TOT data for general and gastrointestinal surgery were collected retrospectively over a 26-mo period at a large multispecialty academic institution. We calculated mean and median TOTs. TOTs were excluded if the sequence of cases was changed or cases were canceled. Data were retrieved from the perioperative nursing data entry system. RESULTS: Using performance improvement strategies, we determined how various events and organizational factors created an environment that was receptive to change. This ultimately led to a sustained decrease in the OR TOT both in the general and gastrointestinal surgery ORs that were the focus of the study (44.8 min versus 48.6 min; P < 0.0001) and other subspecialties (49.3 min versus 53.0 min; P < 0.0001), demonstrating that the effect traveled outside the study area. CONCLUSIONS: There are obstacles, such as organizational culture and institutional inertia, that OR leaders, managers, and change agents commonly face. Awareness of the numerous variables that may support or impede a particular change effort can inform effective change implementation strategies that are "organizationally compatible."

The efficiency of a dedicated staff on operating room turnover time in hand surgery.

PURPOSE: To evaluate the effect of orthopedic and nonorthopedic operating room (OR) staff on the efficiency of turnover time in a hand surgery practice. METHODS: A total of 621 sequential hand surgery cases were retrospectively reviewed. Turnover times for sequential cases were calculated and analyzed with regard to the characteristics of the OR staff being primarily orthopedic or nonorthopedic. RESULTS: A total of 227 turnover times were analyzed. The average turnover time with all nonorthopedic staff was 31 minutes, for having only an orthopedic surgical technician was 32 minutes, for having only an orthopedic circulator was 25 minutes, and for having both an orthopedic surgical technician and a circulator was 20 minutes. Statistical significance was seen when comparing only an orthopedic surgical technician versus both an orthopedic circulator and a surgical technician and when comparing both nonorthopedic staff versus both an orthopedic circulator and a surgical technician. CONCLUSIONS: OR efficiency is being increasingly evaluated for its effect on hospital revenue and OR staff costs. Reducing turnover time is one aspect of a multifaceted solution in increasing efficiency. Our study showed that, for hand surgery, orthopedic-specific staff can reduce turnover time. TYPE OF STUDY/LEVEL OF EVIDENCE: Economic/Decision Analysis III.