Prospective Evaluation of a Dynamic Acuity Score for Regularly Assessing a Critically Ill Patient's Risk of Mortality.

OBJECTIVE: Predictive models developed for use in ICUs have been based on retrospectively collected data, which does not take into account the challenges associated with live, clinical data. This study sought to determine if a previously constructed predictive model of ICU mortality (ViSIG) is robust when using data collected prospectively in near real-time. DESIGN: Prospectively collected data were aggregated and transformed to evaluate a previously developed rolling predictor of ICU mortality. SETTING: Five adult ICUs at Robert Wood Johnson-Barnabas University Hospital and one adult ICU at Stamford Hospital. PATIENTS: One thousand eight hundred and ten admissions from August to December 2020. MEASUREMENTS AND MAIN RESULTS: The ViSIG Score, comprised of severity weights for heart rate, respiratory rate, oxygen saturation, mean arterial pressure, mechanical ventilation, and values for OBS Medical's Visensia Index. This information was collected prospectively, whereas data on discharge disposition was collected retrospectively to measure the ViSIG Score's accuracy. The distribution of patients' maximum ViSIG Score was compared with ICU mortality rate, and cut points determined where changes in mortality probability were greatest. The ViSIG Score was validated on new admissions. The ViSIG Score was able to stratify patients into three groups: 0-37 (low risk), 38-58 (moderate risk), and 59-100 (high risk), with mortality of 1.7%, 12.0%, and 39.8%, respectively ( p < 0.001). The sensitivity and specificity of the model to predict mortality for the high-risk group were 51% and 91%. Performance on the validation dataset remained high. There were similar increases across risk groups for length of stay, estimated costs, and readmission. CONCLUSIONS: Using prospectively collected data, the ViSIG Score produced risk groups for mortality with good sensitivity and excellent specificity. A future study will evaluate making the ViSIG Score visible to clinicians to determine whether this metric can influence clinician behavior to reduce adverse outcomes.

Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation.

Wetlands provide essential ecosystem services, including nutrient cycling, flood protection, and biodiversity support, that are sensitive to changes in wetland hydrology. Wetland hydrological inputs come from precipitation, groundwater discharge, and surface run-off. Changes to these inputs via climate variation, groundwater extraction, and land development may alter the timing and magnitude of wetland inundation. Here, we use a long-term (14-year) comparative study of 152 depressional wetlands in west-central Florida to identify sources of variation in wetland inundation during two key time periods, 2005-2009 and 2010-2018. These time periods are separated by the enactment of water conservation policies in 2009, which included regional reductions in groundwater extraction. We investigated the response of wetland inundation to the interactive effects of precipitation, groundwater extraction, surrounding land development, basin geomorphology, and wetland vegetation class. Results show that water levels were lower and hydroperiods were shorter in wetlands of all vegetation classes during the first (2005-2009) time period, which corresponded with low rainfall conditions and high rates of groundwater extraction. Under water conservation policies enacted in the second (2010-2018) time period, median wetland water depths increased 1.35 m and median hydroperiods increased from 46 % to 83 %. Water-level variation was additionally less sensitive to groundwater extraction. The increase in inundation differed among vegetation classes with some wetlands not displaying signs of hydrological recovery. After accounting for effects of several explanatory factors, inundation still varied considerably among wetlands, suggesting a diversity of hydrological regimes, and thus ecological function, among individual wetlands across the landscape. Policies seeking to balance human water demand with the preservation of depressional wetlands would benefit by recognizing the heightened sensitivity of wetland inundation to groundwater extraction during periods of low precipitation.

Cannabis, a cause for anxiety? A critical appraisal of the anxiogenic and anxiolytic properties.

BACKGROUND: Cannabis has been documented for use in alleviating anxiety. However, certain research has also shown that it can produce feelings of anxiety, panic, paranoia and psychosis. In humans, Δ9-tetrahydrocannabinol (THC) has been associated with an anxiogenic response, while anxiolytic activity has been attributed mainly to cannabidiol (CBD). In animal studies, the effects of THC are highly dose-dependent, and biphasic effects of cannabinoids on anxiety-related responses have been extensively documented. A more precise assessment is required of both the anxiolytic and anxiogenic potentials of phytocannabinoids, with an aim towards the development of the 'holy grail' in cannabis research, a medicinally-active formulation which may assist in the treatment of anxiety or mood disorders without eliciting any anxiogenic effects. OBJECTIVES: To systematically review studies assessing cannabinoid interventions (e.g. THC or CBD or whole cannabis interventions) both in animals and humans, as well as recent epidemiological studies reporting on anxiolytic or anxiogenic effects from cannabis consumption. METHOD: The articles selected for this review were identified up to January 2020 through searches in the electronic databases OVID MEDLINE, Cochrane Central Register of Controlled Trials, PubMed, and PsycINFO. RESULTS: Acute doses of CBD were found to reduce anxiety both in animals and humans, without having an anxiogenic effect at higher doses. Epidemiological studies tend to support an anxiolytic effect from the consumption of either  CBD or THC, as well as whole plant cannabis. Conversely, the available human clinical studies demonstrate a common anxiogenic response to THC (especially at higher doses). CONCLUSION: Based on current data, cannabinoid therapies (containing primarily CBD) may provide a more suitable treatment for people with pre-existing anxiety or as a potential adjunctive role in managing anxiety or stress-related disorders. However, further research is needed to explore other cannabinoids and phytochemical constituents present in cannabis (e.g. terpenes) as anxiolytic interventions. Future clinical trials involving patients with anxiety disorders are warranted due to the small number of available human studies.

Elucidation of the microbial diversity in rivers in south-west Victoria, Australia impacted by rural agricultural contamination (dairy farming).

We assessed the water quality of south-west Victorian rivers impacted by the dairy industry using traditional water quality assessment together with culture-dependent (colilert/enterolert) and also culture-independent (next generation sequencing) microbial methods. The aim of the study was to identify relationships/associations between dairy farming intensity and water contamination. Water samples with high total and faecal coliforms (>1000 MPN cfu/100 ml), and with high nitrogen levels (TN) were observed in zones with a high proportion of dairy farming. Members of the genus Nitrospira, Rhodobacter and Rhodoplanes were predominant in such high cattle density zones. Samples from sites in zones with lower dairy farming activities registered faecal coliform numbers within the permissible limits (<1000 MPN cfu/100 ml) and showed the presence of a wide variety of microorganisms. However, no bacterial pathogens were found in the river waters regardless of the proportion of cattle. The data suggests that using the spatially weighted proportion of land used for dairy farming is a useful way to target at-risk sub-catchments across south west Victoria; further work is required to confirm that this approach is applicable in other regions.

Ebola cases and health system demand in Liberia.

In 2014, a major epidemic of human Ebola virus disease emerged in West Africa, where human-to-human transmission has now been sustained for greater than 12 months. In the summer of 2014, there was great uncertainty about the answers to several key policy questions concerning the path to containment. What is the relative importance of nosocomial transmission compared with community-acquired infection? How much must hospital capacity increase to provide care for the anticipated patient burden? To which interventions will Ebola transmission be most responsive? What must be done to achieve containment? In recent years, epidemic models have been used to guide public health interventions. But, model-based policy relies on high quality causal understanding of transmission, including the availability of appropriate dynamic transmission models and reliable reporting about the sequence of case incidence for model fitting, which were lacking for this epidemic. To investigate the range of potential transmission scenarios, we developed a multi-type branching process model that incorporates key heterogeneities and time-varying parameters to reflect changing human behavior and deliberate interventions in Liberia. Ensembles of this model were evaluated at a set of parameters that were both epidemiologically plausible and capable of reproducing the observed trajectory. Results of this model suggested that epidemic outcome would depend on both hospital capacity and individual behavior. Simulations suggested that if hospital capacity was not increased, then transmission might outpace the rate of isolation and the ability to provide care for the ill, infectious, and dying. Similarly, the model suggested that containment would require individuals to adopt behaviors that increase the rates of case identification and isolation and secure burial of the deceased. As of mid-October, it was unclear that this epidemic would be contained even by 99% hospitalization at the planned hospital capacity. A new version of the model, updated to reflect information collected during October and November 2014, predicts a significantly more constrained set of possible futures. This model suggests that epidemic outcome still depends very heavily on individual behavior. Particularly, if future patient hospitalization rates return to background levels (estimated to be around 70%), then transmission is predicted to remain just below the critical point around Reff = 1. At the higher hospitalization rate of 85%, this model predicts near complete elimination in March to June, 2015.

Density-dependent selection on mate search and evolution of Allee effects.

Sexually reproducing organisms require males and females to find each other. Increased difficulty of females finding mates as male density declines is the most frequently reported mechanism of Allee effects in animals. Evolving more effective mate search may alleviate Allee effects, but may depend on density regimes a population experiences. In particular, high-density populations may evolve mechanisms that induce Allee effects which become detrimental when populations are reduced and maintained at a low density. We develop an individual-based, eco-genetic model to study how mating systems and fitness trade-offs interact with changes in population density to drive evolution of the rate at which males or females search for mates. Finite mate search rate triggers Allee effects in our model and we explore how these Allee effects respond to such evolution. We allow a population to adapt to several population density regimes and examine whether high-density populations are likely to reverse adaptations attained at low densities. We find density-dependent selection in most of scenarios, leading to search rates that result in lower Allee thresholds in populations kept at lower densities. This mainly occurs when fecundity costs are imposed on mate search, and provides an explanation for why Allee effects are often observed in anthropogenically rare species. Optimizing selection, where the attained trait value minimizes the Allee threshold independent of population density, depended on the trade-off between search and survival, combined with monogamy when females were searching. Other scenarios led to runaway selection on the mate search rate, including evolutionary suicide. Trade-offs involved in mate search may thus be crucial to determining how density influences the evolution of Allee effects. Previous studies did not examine evolution of a trait related to the strength of Allee effects under density variation. We emphasize the crucial role that mating systems, fitness trade-offs and the evolving sex have in determining the density threshold for population persistence, in particular since evolution need not always take the Allee threshold to its minimum value.

Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover.

Because the natural reservoir of Ebola virus remains unclear and disease outbreaks in humans have occurred only sporadically over a large region, forecasting when and where Ebola spillovers are most likely to occur constitutes a continuing and urgent public health challenge. We developed a statistical modeling approach that associates 37 human or great ape Ebola spillovers since 1982 with spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over 3 decades across sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows that spillover intensity is highest during transitions between wet and dry seasons; overall, high seasonal intensity occurs over much of tropical Africa; and spillover intensity is greatest at high (>1,000/km2) and very low (<100/km2) human population densities compared with intermediate levels. These results suggest strong seasonality in Ebola spillover from wild reservoirs and indicate particular times and regions for targeted surveillance.

Validation of Intensive Care and Mechanical Ventilation Codes in Medicare Data.

OBJECTIVES: To assess the reliability of codes relevant to critically ill patients in administrative data. DESIGN: Retrospective cohort study linking data from Acute Physiology and Chronic Health Evaluation Outcomes, a clinical database of ICU patients with data from Medicare Provider Analysis and Review. We linked data based on matching for sex, date of birth, hospital, and date of admission to hospital. SETTING: Forty-six hospitals in the United States participating in Acute Physiology and Chronic Health Evaluation Outcomes. PATIENTS: All patients in Acute Physiology and Chronic Health Evaluation Outcomes greater than or equal to 65 years old who could be linked with hospitalization records in Medicare Provider Analysis and Review from January 1, 2009, through September 30, 2012. MEASUREMENTS AND MAIN RESULTS: Of 62,451 patients in the Acute Physiology and Chronic Health Evaluation Outcomes dataset, 80.1% were matched with data in Medicare Provider Analysis and Review. All but 2.7% of Acute Physiology and Chronic Health Evaluation Outcomes ICU patients had either an ICU or coronary care unit charge in Medicare Provider Analysis and Review. In Acute Physiology and Chronic Health Evaluation Outcomes, 37.0% received mechanical ventilation during the ICU stay versus 24.1% in Medicare Provider Analysis and Review. The Medicare Provider Analysis and Review procedure codes for mechanical ventilation had high specificity (96.0%; 95% CI, 95.8-96.2), but only moderate sensitivity (58.4%; 95% CI, 57.7-59.1), with a positive predictive value of 89.6% (95% CI, 89.1-90.1) and negative predictive value of 79.7% (95% CI, 79.4-80.1). For patients with mechanical ventilation codes, Medicare Provider Analysis and Review overestimated the percentage with a duration greater than 96 hours (36.6% vs 27.3% in Acute Physiology and Chronic Health Evaluation Outcomes). There was discordance in the hospital discharge status (alive or dead) for only 0.47% of all linked records (κ = 1.00). CONCLUSIONS: Medicare Provider Analysis and Review data contain robust information on hospital mortality for patients admitted to the ICU but have limited ability to identify all patients who received mechanical ventilation during a critical illness. Estimates of use of mechanical ventilation in the United States should likely be revised upward.

The Impact of Mortality on Total Costs Within the ICU.

OBJECTIVES: The high cost of critical care has engendered research into identifying influential factors. However, existing studies have not considered patient vital status at ICU discharge. This study sought to determine the effect of mortality upon the total cost of an ICU stay. DESIGN: Retrospective cohort study. SETTING: Twenty-six ICUs at 13 hospitals in the United States. PATIENTS: 58,344 admissions from January 1, 2012, to June 30, 2016, obtained from a commercial ICU database. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The median observed cost of a unit stay was $9,619 (mean = $16,353). A multivariable regression model was developed on the log of total costs for a unit stay, using severity of illness, unit admitting diagnosis, mortality in the unit, daily unit occupancy (occupying a bed at midnight), and length of mechanical ventilation. This model had an r of 0.67 and a median difference between observed and expected costs of $437. The first few days of care and the first day receiving mechanical ventilation had the largest effect on total costs. Patients dying before unit discharge had 12.4% greater costs than survivors (p < 0.01; 99% CI = 9.3-15.5%) after multivariable adjustment. This effect was most pronounced for patients with an extended ICU stay who were receiving mechanical ventilation. CONCLUSIONS: While the largest drivers of ICU costs at the patient level are day 1 room occupancy and day 1 mechanical ventilation, mortality before unit discharge is associated with substantially higher costs. The increase was most evident for patients with an extended ICU stay who were receiving mechanical ventilation. Studies evaluating costs among ICUs need to take mortality into account.

Cumulative Probability and Time to Reintubation in U.S. ICUs.

OBJECTIVE: Reintubation after liberation from mechanical ventilation is viewed as an adverse event in ICUs. We sought to describe the frequency of reintubations across U.S. ICUs and to propose a standard, appropriate time cutoff for reporting of reintubation events. DESIGN AND SETTING: We conducted a cohort study using data from the Project IMPACT database of 185 diverse ICUs in the United States. PATIENTS: We included patients who received mechanical ventilation and excluded patients who received a tracheostomy, had a do-not-resuscitate order placed, or died prior to first extubation. MEASUREMENTS AND MAIN RESULTS: We assessed the percentage of patients extubated who were reintubated; the cumulative probability of reintubation, with death and do-not-resuscitate orders after extubation modeled as competing risks, and time to reintubation. Among 98,367 patients who received mechanical ventilation without death or tracheostomy prior to extubation, 9,907 (10.1%) were reintubated, with a cumulative probability of 10.0%. Median time to reintubation was 15 hours (interquartile range, 2-45 hr). Of patients who required reintubation in the ICU, 90% did so within the first 96 hours after initial extubation; this was consistent across various patient subtypes (89.3% for electives surgical patients up to 94.8% for trauma patients) and ICU subtypes (88.6% for cardiothoracic ICUs to 93.5% for medical ICUs). CONCLUSIONS: The reintubation rate for ICU patients liberated from mechanical ventilation in U.S. ICUs is approximately 10%. We propose a time cutoff of 96 hours for reintubation definitions and benchmarking efforts, as it captures 90% of ICU reintubation events. Reintubation rates can be reported as simple percentages, without regard for deaths or changes in goals of care that might occur.

Existing and Future Educational Needs in Graduate and Postgraduate Education.

INTRODUCTION: This review was designed to make recommendations on future educational needs, principles of curricular development, and how the International Society for Sexual Medicine (ISSM) should address the need to enhance and promote human sexuality education around the world. AIM: To explore the ways in which graduate and postgraduate medical education in human sexuality has evolved and is currently delivered. METHODS: We reviewed existing literature concerning sexuality education, curriculum development, learning strategies, educational formats, evaluation of programs, evaluation of students, and faculty development. We reviewed literature relating to four main areas: (i) the current status of the international regulation of training in sexual medicine; (ii) the current delivery of education and training in sexual medicine; (iii) resident and postgraduate education in sexual medicine surgery; and (iv) education and training for allied health professionals. RESULTS: The main findings in these four areas are as follows. Sexual medicine has grown considerably as a specialty during the past 20 years, with many drivers being identified. However, the regulatory aspects of training, assessment, and certification are currently in the early stages of development and are in many ways lagging behind the scientific and clinical knowledge in the field. However, there are examples of the development of curricula with accompanying assessments that have attempted to set standards of education and training that might underlie the delivery of high-quality care to patients in sexual medicine. The development of competence assessment has been applied to surgical training in sexual medicine, and there is increasing interest in simulation as a means of enhancing technical skills training. Although the focus of curriculum development has largely been the medical profession, there is early interest in the development of standards for training and education of allied health professionals. CONCLUSION: Organizations of professionals in sexual health, such as the ISSM, have an opportunity, and indeed a responsibility, to provide and disseminate learning opportunities, curricula, and standards of training for doctors and allied health professionals in sexual medicine. Eardley I, Reisman Y, Goldstein S, et al. Existing and Future Educational Needs in Graduate and Postgraduate Education. J Sex Med 2017;14:475-485.

Variations in Case-Mix-Adjusted Duration of Mechanical Ventilation Among ICUs.

OBJECTIVES: To develop a model that predicts the duration of mechanical ventilation and then to use this model to compare observed versus expected duration of mechanical ventilation across ICUs. DESIGN: Retrospective cohort analysis. SETTING: Eighty-six eligible ICUs at 48 U.S. hospitals. PATIENTS: ICU patients receiving mechanical ventilation on day 1 (n = 56,336) admitted from January 2013 to September 2014. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We developed and validated a multivariable logistic regression model for predicting duration of mechanical ventilation using ICU day 1 patient characteristics. Mean observed minus expected duration of mechanical ventilation was then obtained across patients and for each ICU. The accuracy of the model was assessed using R. We defined better performing units as ICUs that had an observed minus expected duration of mechanical ventilation less than -0.5 days and a p value of less than 0.01; and poorer performing units as ICUs with an observed minus expected duration of mechanical ventilation greater than +0.5 days and a p value of less than 0.01. The factors accounting for the majority of the model's explanatory power were diagnosis (71%) and physiologic abnormalities (24%). For individual patients, the difference between observed and mean predicted duration of mechanical ventilation was 3.3 hours (95% CI, 2.8-3.9) with R equal to 21.6%. The mean observed minus expected duration of mechanical ventilation across ICUs was 3.8 hours (95% CI, 2.1-5.5), with R equal to 69.9%. Among the 86 ICUs, 66 (76.7%) had an observed mean mechanical ventilation duration that was within 0.5 days of predicted. Five ICUs had significantly (p < 0.01) poorer performance (observed minus expected duration of mechanical ventilation, > 0.5 d) and 14 ICUs significantly (p < 0.01) better performance (observed minus expected duration of mechanical ventilation, < -0.5 d). CONCLUSIONS: Comparison of observed and case-mix-adjusted predicted duration of mechanical ventilation can accurately assess and compare duration of mechanical ventilation across ICUs, but cannot accurately predict an individual patient's mechanical ventilation duration. There are substantial differences in duration of mechanical ventilation across ICU and their association with unit practices and processes of care warrants examination.

Comparing Time-Fixed Mortality Prediction Models and Their Effect on ICU Performance Metrics Using the Simplified Acute Physiology Score 3.

OBJECTIVES: To examine ICU performance based on the Simplified Acute Physiology Score 3 using 30-day, 90-day, or 180-day mortality as outcome measures and compare results with 30-day mortality as reference. DESIGN: Retrospective cohort study of ICU admissions from 2010 to 2014. SETTING: Sixty-three Swedish ICUs that submitted data to the Swedish Intensive Care Registry. PATIENTS: The development cohort was first admissions to ICU during 2011-2012 (n = 53,546), and the validation cohort was first admissions to ICU during 2013-2014 (n = 57,729). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Logistic regression was used to develop predictive models based on a first level recalibration of the original Simplified Acute Physiology Score 3 model but with 30-day, 90-day, or 180-day mortality as measures of outcome. Discrimination and calibration were excellent for the development dataset. Validation in the more recent 2013-2014 database showed good discrimination (C-statistic: 0.85, 0.84, and 0.83 for the 30-, 90-, and 180-d models, respectively), and good calibration (standardized mortality ratio: 0.99, 0.99, and 1.00; Hosmer-Lemeshow goodness of fit H-statistic: 66.4, 63.7, and 81.4 for the 30-, 90-, and 180-d models, respectively). There were modest changes in an ICU's standardized mortality ratio grouping (< 1.00, not significant, > 1.00) when follow-up was extended from 30 to 90 days and 180 days, respectively; about 11-13% of all ICUs. CONCLUSIONS: The recalibrated Simplified Acute Physiology Score 3 hospital outcome prediction model performed well on long-term outcomes. Evaluation of ICU performance using standardized mortality ratio was only modestly sensitive to the follow-up time. Our results suggest that 30-day mortality may be a good benchmark of ICU performance. However, the duration of follow-up must balance between what is most relevant for patients, most affected by ICU care, least affected by administrative policies and practically feasible for caregivers.

Low Childhood Socioeconomic Status Promotes Eating in the Absence of Energy Need.

Life-history theory predicts that exposure to conditions typical of low socioeconomic status (SES) during childhood will calibrate development in ways that promote survival in harsh and unpredictable ecologies. Guided by this insight, the current research tested the hypothesis that low childhood SES will predict eating in the absence of energy need. Across three studies, we measured (Study 1) or manipulated (Studies 2 and 3) participants' energy need and gave them the opportunity to eat provided snacks. Participants also reported their SES during childhood and their current SES. Results revealed that people who grew up in high-SES environments regulated their food intake on the basis of their immediate energy need; they ate more when their need was high than when their need was low. This relationship was not observed among people who grew up in low-SES environments. These individuals consumed comparably high amounts of food when their current energy need was high and when it was low. Childhood SES may have a lasting impact on food regulation.

Experimental demonstration of an Allee effect in microbial populations.

Microbial populations can be dispersal limited. However, microorganisms that successfully disperse into physiologically ideal environments are not guaranteed to establish. This observation contradicts the Baas-Becking tenet: 'Everything is everywhere, but the environment selects'. Allee effects, which manifest in the relationship between initial population density and probability of establishment, could explain this observation. Here, we experimentally demonstrate that small populations of Vibrio fischeri are subject to an intrinsic demographic Allee effect. Populations subjected to predation by the bacterivore Cafeteria roenbergensis display both intrinsic and extrinsic demographic Allee effects. The estimated critical threshold required to escape positive density-dependence is around 5, 20 or 90 cells ml(-1)under conditions of high carbon resources, low carbon resources or low carbon resources with predation, respectively. This work builds on the foundations of modern microbial ecology, demonstrating that mechanisms controlling macroorganisms apply to microorganisms, and provides a statistical method to detect Allee effects in data.

Nighttime intensivist staffing and mortality among critically ill patients.

BACKGROUND: Hospitals are increasingly adopting 24-hour intensivist physician staffing as a strategy to improve intensive care unit (ICU) outcomes. However, the degree to which nighttime intensivists are associated with improvements in the quality of ICU care is unknown. METHODS: We conducted a retrospective cohort study involving ICUs that participated in the Acute Physiology and Chronic Health Evaluation (APACHE) clinical information system from 2009 through 2010, linking a survey of ICU staffing practices with patient-level outcomes data from adult ICU admissions. Multivariate models were used to assess the relationship between nighttime intensivist staffing and in-hospital mortality among ICU patients, with adjustment for daytime intensivist staffing, severity of illness, and case mix. We conducted a confirmatory analysis in a second, population-based cohort of hospitals in Pennsylvania from which less detailed data were available. RESULTS: The analysis with the use of the APACHE database included 65,752 patients admitted to 49 ICUs in 25 hospitals. In ICUs with low-intensity daytime staffing, nighttime intensivist staffing was associated with a reduction in risk-adjusted in-hospital mortality (adjusted odds ratio for death, 0.62; P=0.04). Among ICUs with high-intensity daytime staffing, nighttime intensivist staffing conferred no benefit with respect to risk-adjusted in-hospital mortality (odds ratio, 1.08; P=0.78). In the verification cohort, there was a similar relationship among daytime staffing, nighttime staffing, and in-hospital mortality. The interaction between nighttime staffing and daytime staffing was not significant (P=0.18), yet the direction of the findings were similar to those in the APACHE cohort. CONCLUSIONS: The addition of nighttime intensivist staffing to a low-intensity daytime staffing model was associated with reduced mortality. However, a reduction in mortality was not seen in ICUs with high-intensity daytime staffing. (Funded by the National Heart, Lung, and Blood Institute.).