Effect of Nosocomial Vancomycin-Resistant Enterococcal Bacteremia on Mortality, Length of Stay, and Costs

2003 ◽  
Vol 24 (4) ◽  
pp. 251-256 ◽  
Author(s):  
Xiaoyan Song ◽  
Arjun Srinivasan ◽  
David Plaut ◽  
Trish M. Perl
Keyword(s):  
Mortality Rate ◽  
Length Of Stay ◽  
Severity Of Illness ◽  
Attributable Mortality ◽  
Crude Mortality Rate ◽  
Crude Mortality ◽  
Vancomycin Resistant ◽  
And Control ◽  
The Impact ◽  
Enterococcal Bacteremia

AbstractObjective:To determine the impact of vancomycin-resistant enterococcal bacteremia on patient outcomes and costs by assessing mortality, excess length of stay, and charges attributable to it.Design:A population-based, matched, historical cohort study.Setting:A 1,025-bed, university-based teaching facility and referral hospital.Patients:Two hundred seventy-seven vancomycin-resistant enterococcal bacteremia case-patients and 277 matched control-patients identified between 1993 and 2000.Results:The crude mortality rate was 50.2% and 19.9% for case-patients and control-patients, respectively, yielding a mortality rate of 30.3% attributable to vancomycin-resistant enterococcal bacteremia. The excess length of hospital stay attributable to vancomycin-resistant enterococcal bacteremia was 17 days, of which 12 days were spent in intensive care units. On average, $77,558 in extra charges was attributable to each vancomycin-resistant enterococcal bacteremia. To adjust for severity of illness, 159 pairs of case-patients and control-patients, who had the same severity of illness (All Patient Refined-Diagnosis Related Group complexity level), were further analyzed. When patients were stratified by severity of illness, the crude mortality rate was 50.3% among case-patients compared with 27.7% among control-patients, accounting for an attributable mortality rate of 22.6%. Attributable excess length of stay and charges were 17 days and $81,208, respectively.Conclusion:Vancomycin-resistant enterococcal bacteremia contributes significantly to excess mortality and economic loss, once severity of illness is considered. Efforts to prevent these infections will likely be cost-effective.

scholarly journals The Impact of Methicillin-Resistant Staphylococcus aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE) Flags on Hospital Operations

2016 ◽  
Vol 37 (7) ◽  
pp. 782-790 ◽  
Author(s):  
Erica S. Shenoy ◽  
Hang Lee ◽  
Taige Hou ◽  
Winston Ware ◽  
Erin E. Ryan ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Length Of Stay ◽  
Massachusetts General Hospital ◽  
Severity Of Illness ◽  
Vancomycin Resistant Enterococcus ◽  
Methicillin Resistant ◽  
Use Of Resources ◽  
Hospital Transfer ◽  
Vancomycin Resistant ◽  
The Impact

OBJECTIVETo determine the impact of methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus (MRSA/VRE) designations, or flags, on selected hospital operational outcomes.DESIGNRetrospective cohort study of inpatients admitted to the Massachusetts General Hospital during 2010–2011.METHODSOperational outcomes were time to bed arrival, acuity-unrelated within-hospital transfers, and length of stay. Covariates considered included demographic and clinical characteristics: age, gender, severity of illness on admission, admit day of week, residence prior to admission, hospitalization within the prior 30 days, clinical service, and discharge destination.RESULTSOverall, 81,288 admissions were included. After adjusting for covariates, patients with a MRSA/VRE flag at the time of admission experienced a mean delay in time to bed arrival of 1.03 hours (9.63 hours [95% CI, 9.39–9.88] vs 8.60 hours [95% CI, 8.47–8.73]). These patients had 1.19 times the odds of experiencing an acuity-unrelated within-hospital transfer [95% CI, 1.13–1.26] and a mean length of stay 1.76 days longer (7.03 days [95% CI, 6.82–7.24] vs 5.27 days [95% CI, 5.15–5.38]) than patients with no MRSA/VRE flag.CONCLUSIONSMRSA/VRE designation was associated with delays in time to bed arrival, increased likelihood of acuity-unrelated within-hospital transfers and extended length of stay. Efforts to identify patients who have cleared MRSA/VRE colonization are critically important to mitigate inefficient use of resources and to improve inpatient flow.Infect Control Hosp Epidemiol 2016;37:782–790

Attributable Mortality Rate for Carbapenem-Resistant Klebsiella pneumoniae Bacteremia

2009 ◽  
Vol 30 (10) ◽  
pp. 972-976 ◽  
Author(s):  
Abraham Borer ◽  
Lisa Saidel-Odes ◽  
Klaris Riesenberg ◽  
Seada Eskira ◽  
Nejama Peled ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Klebsiella Pneumoniae ◽  
Tertiary Care ◽  
Attributable Mortality ◽  
Historical Cohort ◽  
Control Subjects ◽  
Carbapenem Resistant ◽  
Crude Mortality Rate ◽  
Crude Mortality ◽  
Hospitalization Period

Objective.To determine the attributable (direct) mortality and morbidity caused by carbapenem-resistant Klebsiella pneumoniae bacteremia.Design.A matched retrospective, historical cohort design, using a stepwise procedure to stringendy match the best control subjects to the best case subjects.Setting.A 1,000-bed tertiary-care university teaching hospital.Patients.Case subjects were defined as adult patients with carbapenem-resistant K. pneumoniae bacteremia during the period from October 2005 through October 2008. Control subjects were defined as patients who were very similar to case subjects except that they did not have bacteremia.Methods.Matching potential control subjects to case subjects was performed at a 1:1 ratio using a computerized record system. The criteria used included same hospitalization period, similar Charlson comorbidity index, same underlying disease, same age within 10 years, and same sex. Demographic and clinical characteristics were collected from medical records.Results.During the study period, 319 patients developed an infection due to carbapenem-resistant K. pneumoniae. Of these 319 patients, 39 (12.2%) developed a bloodstream infection, for an overall rate of 0.59 episodes of carbapenem-resistant K. pneumoniae bacteremia per 10,000 patient-days. We excluded 7 patients from our study, leaving a total of 32 case subjects in our cohort. Case subjects were significandy more likely than control subjects (n = 32) to require care in an intensive care unit (12 case subjects [37.5%] vs 3 control subjects [9.4%]), ventilator support (17 case subjects [53.1%] vs 8 control subjects [25%]), and use of a central venous catheter (19 case subjects [59.4%] vs 9 control subjects [28.1%]). For case subjects, the crude mortality rate was 71.9% (ie, 23 of the 32 case subjects died); for control subjects, the crude mortality rate was 21.9% (ie, 7 of the 32 control subjects died) (P < .001. For case subjects, the attributable mortality was 50% (95% confidence interval [CI], 15.3%-98.6%). A mortality risk ratio of 3.3 (95% CI, 2.9-28.5) was found for case subjects with carbapenem-resistant K. pneumoniae bacteremia.Conclusions.Patients with carbapenem-resistant K. pneumoniae require more intensive and invasive care. We have shown that the crude and attributable mortality rates associated with carbapenem-resistant K. pneumoniae bacteremia were striking.

scholarly journals The Relationship Between Demographic, Socioeconomic, and Health-Related Parameters and the Impact of COVID-19 on 24 Regions in India: Exploratory Cross-Sectional Study (Preprint)

2020 ◽  
Author(s):  
Ravi Philip Rajkumar
Keyword(s):  
Mortality Rate ◽  
Sex Ratio ◽  
Multivariate Analyses ◽  
Case Fatality ◽  
Negatively Associated ◽  
Crude Mortality Rate ◽  
Crude Mortality ◽  
Health Related ◽  
The Impact ◽  
The Relationship

BACKGROUND The impact of the COVID-19 pandemic has varied widely across nations and even in different regions of the same nation. Some of this variability may be due to the interplay of pre-existing demographic, socioeconomic, and health-related factors in a given population. OBJECTIVE The aim of this study was to examine the statistical associations between the statewise prevalence, mortality rate, and case fatality rate of COVID-19 in 24 regions in India (23 states and Delhi), as well as key demographic, socioeconomic, and health-related indices. METHODS Data on disease prevalence, crude mortality, and case fatality were obtained from statistics provided by the Government of India for 24 regions, as of June 30, 2020. The relationship between these parameters and the demographic, socioeconomic, and health-related indices of the regions under study was examined using both bivariate and multivariate analyses. RESULTS COVID-19 prevalence was negatively associated with male-to-female sex ratio (defined as the number of females per 1000 male population) and positively associated with the presence of an international airport in a particular state. The crude mortality rate for COVID-19 was negatively associated with sex ratio and the statewise burden of diarrheal disease, and positively associated with the statewise burden of ischemic heart disease. Multivariate analyses demonstrated that the COVID-19 crude mortality rate was significantly and negatively associated with sex ratio. CONCLUSIONS These results suggest that the transmission and impact of COVID-19 in a given population may be influenced by a number of variables, with demographic factors showing the most consistent association.

scholarly journals The Relationship Between Demographic, Socioeconomic, and Health-Related Parameters and the Impact of COVID-19 on 24 Regions in India: Exploratory Cross-Sectional Study

10.2196/23083 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e23083
Author(s):  
Ravi Philip Rajkumar
Keyword(s):  
Mortality Rate ◽  
Sex Ratio ◽  
Multivariate Analyses ◽  
Case Fatality ◽  
Negatively Associated ◽  
Crude Mortality Rate ◽  
Crude Mortality ◽  
Health Related ◽  
The Impact ◽  
The Relationship

Background The impact of the COVID-19 pandemic has varied widely across nations and even in different regions of the same nation. Some of this variability may be due to the interplay of pre-existing demographic, socioeconomic, and health-related factors in a given population. Objective The aim of this study was to examine the statistical associations between the statewise prevalence, mortality rate, and case fatality rate of COVID-19 in 24 regions in India (23 states and Delhi), as well as key demographic, socioeconomic, and health-related indices. Methods Data on disease prevalence, crude mortality, and case fatality were obtained from statistics provided by the Government of India for 24 regions, as of June 30, 2020. The relationship between these parameters and the demographic, socioeconomic, and health-related indices of the regions under study was examined using both bivariate and multivariate analyses. Results COVID-19 prevalence was negatively associated with male-to-female sex ratio (defined as the number of females per 1000 male population) and positively associated with the presence of an international airport in a particular state. The crude mortality rate for COVID-19 was negatively associated with sex ratio and the statewise burden of diarrheal disease, and positively associated with the statewise burden of ischemic heart disease. Multivariate analyses demonstrated that the COVID-19 crude mortality rate was significantly and negatively associated with sex ratio. Conclusions These results suggest that the transmission and impact of COVID-19 in a given population may be influenced by a number of variables, with demographic factors showing the most consistent association.

Outcomes for and Risk Factors Associated With Vancomycin-ResistantEnterococcus faecalisand Vancomycin-ResistantEnterococcus faeciumBacteremia in Cancer Patients

2007 ◽  
Vol 28 (9) ◽  
pp. 1054-1059 ◽  
Author(s):  
G. Ghanem ◽  
R. Hachem ◽  
Y. Jiang ◽  
R. F. Chemaly ◽  
I. Raad
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Mortality Rate ◽  
Cancer Patients ◽  
Independent Risk Factor ◽  
Response To Therapy ◽  
Aminoglycoside Therapy ◽  
Significant Difference ◽  
Vancomycin Resistant ◽  
And Control

Objective.Vancomycin-resistant enterococci (VRE) are a major cause of nosocomial infection. We sought to compare vancomycin-resistant (VR)Enterococcus faecalisbacteremia and VREnterococcus faeciumbacteremia in cancer patients with respect to risk factors, clinical presentation, microbiological characteristics, antimicrobial therapy, and outcomes.Methods.We identified 210 cancer patients with VRE bacteremia who had been treated between January 1996 and December 2004; 16 of these 210 had VRE. faecalisbacteremia and were matched with 32 patients with VRE. faeciumbacteremia and 32 control patients. A retrospective review of medical records was conducted.Results.Logistic regression analysis showed that, compared with VRE. faecalisbacteremia, VRE. faeciumbacteremia was associated with a worse clinical response to therapy (odds ratio [OR], 0.3 [95% confidence interval (CI), 0.07-0.98];P= .046) and a higher overall mortality rate (OR, 8.3 [95% CI, 1.9-35.3];P= .004), but the VRE-related mortality rate did not show a statistically significant difference (OR, 6.8 [95% CI, 0.7-61.8];P= .09). Compared with control patients, patients with VRE. faecalisbacteremia were more likely to have received an aminoglycoside in the 30 days before the onset of bacteremia (OR, 5.8 [95% CI, 1.2-27.6];P= .03), whereas patients with VRE. faeciumbacteremia were more likely to have received a carbapenem in the 30 days before the onset of bacteremia (OR, 11.7 [95% CI, 3.6-38.6];P<.001). In a multivariate model that compared patients with VRE. faeciumbacteremia and control patients, predictors of mortality included acute renal failure on presentation (OR, 15.1 [95% CI, 2.3-99.2];P= .004) and VRE. faeciumbacteremia (OR, 11 [95% CI, 2.7-45.1];P<.001). No difference in outcomes was found between patients with VRE. faecalisbacteremia and control patients.Conclusions.VRE. faeciumbacteremia in cancer patients was associated with a poorer outcome than was VRE. faecalisbacteremia. Recent receipt of carbapenem therapy was an independent risk factor for VRE. faeciumbacteremia, and recent receipt of aminoglycoside therapy was independent risk factor forE. faecalisbacteremia.

scholarly journals Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Joshua J. Levy ◽  
Rebecca M. Lebeaux ◽  
Anne G. Hoen ◽  
Brock C. Christensen ◽  
Louis J. Vaickus ◽  
...  
Keyword(s):  
United States ◽  
Deep Learning ◽  
Mortality Rate ◽  
Satellite Images ◽  
The United States ◽  
Mortality Rates ◽  
Image Features ◽  
County Level ◽  
Crude Mortality Rate ◽  
Crude Mortality

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

scholarly journals Analysis of death causes of residents in poverty-stricken Areas in 2020: take Liangshan Yi Autonomous Prefecture in China as an example

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Rujun Liao ◽  
Lin Hu ◽  
Qiang Liao ◽  
Tianyu Zhu ◽  
Haiqun Yang ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Malignant Tumors ◽  
Heart Diseases ◽  
Health Policies ◽  
Years Of Life Lost ◽  
Crude Mortality Rate ◽  
Crude Mortality ◽  
Standardized Mortality Rate ◽  
Death Causes

Abstract Background Continuous surveillance of death can measure health status of the population, reflect social development of a region, thus promote health service development in the region and improve the health level of local residents. Liangshan Yi Autonomous Prefecture was a poverty-stricken region in Sichuan province, China. While at the end of 2020, as the announcement of its last seven former severely impoverished counties had shaken off poverty, Liangshan declared victory against poverty. Since it is well known that the mortality and cause of death structure will undergo some undesirable changes as the economy develops, this study aimed to reveal the distribution of deaths, as well as analyze the latest mortality and death causes distribution characteristics in Liangshan in 2020, so as to provide references for the decision-making on health policies and the distribution of health resources in global poverty-stricken areas. Methods Liangshan carried out the investigation on underreporting deaths among population in its 11 counties in 2018, and combined with the partially available data from underreporting deaths investigation data in 2020 and the field experience, we have estimated the underreporting rates of death in 2020 using capture-recapture (CRC) method. The crude mortality rate, age-standardized mortality rate, proportion and rank of the death causes, potential years of life lost (PYLL), average years of life lost (AYLL), potential years of life lost rate (PYLLR), standardized potential years of life lost (SPYLL), premature mortality from non-communicable diseases (premature NCD mortality), life expectancy and cause-eliminated life expectancy were estimated and corrected. Results In 2020, Liangshan reported a total of 16,850 deaths, with a crude mortality rate of 608.75/100,000 and an age-standardized mortality rate of 633.50/100,000. Male mortality was higher than female mortality, while 0-year-old mortality of men was lower than women’s. The former severely impoverished counties’ age-standardized mortality and 0-year-old mortality were higher than those of the non-impoverished counties. The main cause of death spectrum was noncommunicable diseases (NCDs), and the premature NCD mortality of four major NCDs were 14.26% for the overall population, 19.16% for men and 9.27% for women. In the overall population, the top five death causes were heart diseases (112.07/100,000), respiratory diseases (105.85/100,000), cerebrovascular diseases (87.03/100,000), malignant tumors (73.92/100,000) and injury (43.89/100,000). Injury (64,216.78 person years), malignant tumors (41,478.33 person years) and heart diseases (29,647.83 person years) had the greatest burden on residents in Liangshan, and at the same time, the burden of most death causes on men were greater than those on women. The life expectancy was 76.25 years for overall population, 72.92 years for men and 80.17 years for women, respectively, all higher than the global level (73.3, 70.8 and 75.9 years). Conclusions Taking Liangshan in China as an example, this study analyzed the latest death situation in poverty-stricken areas, and proposed suggestions on the formulation of health policies in other poverty-stricken areas both at home and abroad.

scholarly journals Length of stay, cost, and mortality of healthcare-acquired bloodstream infections in children and neonates: A systematic review and meta-analysis

2020 ◽  
Vol 41 (3) ◽  
pp. 342-354 ◽  
Author(s):  
Sofia Karagiannidou ◽  
Christos Triantafyllou ◽  
Theoklis E. Zaoutis ◽  
Vassiliki Papaevangelou ◽  
Nikolaos Maniadakis ◽  
...  
Keyword(s):  
Systematic Review ◽  
Mortality Rate ◽  
Length Of Stay ◽  
Healthcare Cost ◽  
Meta Analysis ◽  
Random Effect ◽  
Bloodstream Infections ◽  
Attributable Mortality ◽  
Study Selection ◽  
Critical Appraisal Skills

AbstractObjective:To estimate the attributable mortality, length of stay (LOS), and healthcare cost of pediatric and neonatal healthcare-acquired bloodstream infections (HA-BSIs).Design:A systematic review and meta-analysis.Methods:A systematic search (January 2000–September 2018) was conducted in PubMed, Cochrane, and CINAHL databases. Reference lists of selected articles were screened to identify additional studies. Case–control or cohort studies were eligible for inclusion when full text was available in English and data for at least 1 of the following criteria were provided: attributable or excess LOS, healthcare cost, or mortality rate due to HA-BSI. Study quality was evaluated using the Critical Appraisal Skills Programme Tool (CASP). Study selection and quality assessment were conducted by 2 independent researchers, and a third researcher was consulted to resolve any disagreements. Fixed- or random-effect models, as appropriate, were used to synthesize data. Heterogeneity and publication bias were evaluated.Results:In total, 21 studies were included in the systematic review and 13 studies were included in the meta-analysis. Attributable mean LOS ranged between 4 and 27.8 days; healthcare cost ranged between $1,642.16 and $160,804 (2019 USD) per patient with HA-BSI; and mortality rate ranged between 1.43% and 24%. The pooled mean attributable hospital LOS was 16.91 days (95% confidence interval [CI], 13.70–20.11) and the pooled attributable mortality rate was 8% (95% CI, 6–9). A meta-analysis was not conducted for cost due to lack of eligible studies.Conclusions:Pediatric HA-BSIs have a significant impact on mortality, LOS, and healthcare cost, further highlighting the need for implementation of HA-BSI prevention strategies.

The descriptive epidemiology of suicide in Tuscany, 1988-2002

2006 ◽  
Vol 15 (3) ◽  
pp. 202-210 ◽  
Author(s):  
Michele Arcangelo Martiello ◽  
Francesco Cipriani ◽  
Fabio Voller ◽  
Eva Buiatti ◽  
Mariano Giacchi
Keyword(s):  
Spatial Analysis ◽  
Rural Communities ◽  
Mortality Rate ◽  
Empirical Bayes ◽  
Mining District ◽  
Mine Closure ◽  
Descriptive Epidemiology ◽  
Bayes Estimates ◽  
Crude Mortality Rate ◽  
Crude Mortality

SUMMARYAims – To describe the epidemiology of Suicide in Tuscany according to the triad of time, place and person. Methods – The 4, 764 cases of suicide, defined according to categories E950-E959 of ICD-9 in Tuscany over the period 1988–2002, were obtained from the Tuscan Mortality Register. Mortality indicators were calculated and analyzed. The spatial analysis was carried out by deriving Empirical Bayes Estimates for the 287 municipalities. Results – The crude mortality rate in the 2000–2002 is 7.8 per 100000 population (male: 12.4; female: 3.5). The age-standardized rate in the 2000–2002 is 5.8 per 100, 000 population (male: 9.6; female: 2.6). The highest risk for suicide, especially in the case of males, are concentrated in the southern hinterland Tuscany, in a cluster of rural municipalities that represent the old mining district of Tuscany. The SMRs according to residential municipality (population per square kilometre), confirm a greater risk of suicide for males residing in rural communities. Conclusions – The cluster of excessive mortality from suicide in Southern Tuscany could be the consequence of social determinants, related to the urban and social crisis following agriculture decline and mine closure.Declaration of Interest: none.

scholarly journals Mortality among Guarani Indians in Southeastern and Southern Brazil

2011 ◽  
Vol 27 (suppl 2) ◽  
pp. s222-s236 ◽  
Author(s):  
Andrey Moreira Cardoso ◽  
Carlos E. A. Coimbra Jr. ◽  
Carla Tatiana Garcia Barreto ◽  
Guilherme Loureiro Werneck ◽  
Ricardo Ventura Santos
Keyword(s):  
Mortality Rate ◽  
Health Inequalities ◽  
Causes Of Death ◽  
Infant Mortality Rate ◽  
Indigenous Populations ◽  
Southeastern Brazil ◽  
Infant Deaths ◽  
Life Expectancy At Birth ◽  
Crude Mortality Rate ◽  
Crude Mortality

Worldwide, indigenous peoples display a high burden of disease, expressed by profound health inequalities in comparison to non-indigenous populations. This study describes mortality patterns among the Guarani in Southern and Southeastern Brazil, with a focus on health inequalities. The Guarani population structure is indicative of high birth and death rates, low median age and low life expectancy at birth. The crude mortality rate (crude MR = 5.0/1,000) was similar to the Brazilian national rate, but the under-five MR (44.5/1,000) and the infant mortality rate (29.6/1,000) were twice the corresponding MR in the South and Southeast of Brazil. The proportion of post-neonatal infant deaths was 83.3%, 2.4 times higher than general population. The proportions of ill-defined (15.8%) and preventable causes (51.6%) were high. The principal causes of death were respiratory (40.6%) and infectious and parasitic diseases (18.8%), suggesting precarious living conditions and deficient health services. There is a need for greater investment in primary care and interventions in social determinants of health in order to reduce the health inequalities.

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