Grotesque beauty

"My recent work explores the duality of beauty and the grotesque coexisting simultaneously within a singular sculptural form. I seek to make work that paradoxically seduces the viewer with the promise of beauty even as it repels in its cultivation of the unnatural and the perverse -- a sculptural elegance that takes its inspiration from the aversive feelings inspired by biological malformation. My work holds beauty and grotesqueness in uneasy balance."--Abstract from author supplied metadata

Delay-Independent Synchronization and Network Topology of Systems with Transmission Delay Couplings

We investigate the relationship between graph topology and delay-independent synchronization occuring in networks of the identical nonlinear systems with transmission delays. In this paper, we show that if networks contain a cycle subgraph of an odd number of nodes, partial synchronization corresponding to the equitable graph partition with the fewest cells occurs for a sufficiently large coupling strength regardless of the length of time-delay. The validity of the obtained results are examined through numerical simulations of Hindmarsh-Rose neuron systems networks

INTENSI UNTUK KELUAR PADA PERAWAT RUMAH SAKIT H DILIHAT DARI QWL, KEPUASAN KERJA DAN KELELAHAN EMOSI DENGAN MENGONTROL KEPUASAN PENGHASILAN

The amount of salary received by nurses was assumed to be the most influence the turnover intention form the hospital where they work.That is the main reason of this research to put pay satisfaction as control variable among a number of causes of quit. Former researces has reveal the causes of nurse turnover intention, such as job satisfaction, quality of work life dan emotional exhaustion of the nurse caused by thir workload. The hypothesis of this study is, by controlling pay satifaction, quality of work life, job satisfaction, and emotional exhaustion have impact on turnover intention. This study will use cluster random sampling technique. The data will be collected from questionnaire that will be given to nurse and then will be processed in quantitative way with hyrarchial regression analysis method.This research was held in a private hospital in Yogyakarta. The research conclude (n=79), by controlling pay satisfaction, there is R 2 increase of 0,198 (p < 0,01). By controlling pay satisfaction, QWL has the biggest significant impact to turnover intention signifikan (B = -0,070, p < 0,01) compariang the two other independent variable. This research suggest a practice of QWL to reduce nurse turnover intention to leave their organzation

Carbon monoxide poisoning surveillance in the Veterans Health Administration, 2010–2017

Abstract Background Exposure to carbon monoxide (CO), the odorless, colorless gas resulting from incomplete combustion of hydrocarbons, is preventable. Despite the significant risk of morbidity and mortality associated with CO poisoning, there currently exists no active national CO surveillance system in the United States (U.S.). Our study aims to use electronic health record data to describe the epidemiology of CO poisoning in the Veterans Health Administration healthcare population. Methods We identified unique inpatient and outpatient encounters coded with International Classification of Diseases (ICD) codes for CO poisoning and analyzed relevant demographic, laboratory, treatment, and death data from January 2010 through December 2017 for Veterans across all 50 U.S. states and Puerto Rico. Statistical methods used were 95% CI calculations and the two-tailed z test for proportions. Results We identified 5491 unique patients with CO poisoning, of which 1755 (32%) were confirmed/probable and 3736 (68%) were suspected. Unintentional poisoning was most common (72.9%) overall. Age less than 65 years, residence in Midwest U.S. Census region versus South or West, and winter seasonal trend were characteristics associated with confirmed/probable CO poisoning. Twenty-six deaths (1.5%) occurred within 30 days of confirmed/probable CO poisoning and were primarily caused by cardiovascular events (42%) or anoxic encephalopathy (15%). Conclusions Our findings support the use of ICD-coded data for targeted CO poisoning surveillance, however, improvements are needed in ICD coding to reduce the percentage of cases coded with unknown injury intent and/or CO poisoning source. Prevalence of CO poisoning among Veterans is consistent with other U.S. estimates. Since most cases are unintentional, opportunities exist for provider and patient education to reduce risk

Carbon Monoxide Poisoning in the Veterans Health Administration, 2010 - 2016

ObjectiveTo describe characteristics of Veterans Health Administration(VHA) patients with ICD 9/10 CM inpatient discharge and/oremergency department (ED)/urgent care outpatient encounter codesfor carbon monoxide (CO) poisoning.IntroductionIt is estimated that in the United States (US), unintentional non-firerelated CO poisoning causes an average of 439 deaths annually, and in2007 confirmed CO poisoning cases resulted in 21,304 ED visits and2,302 hospitalizations (71 per million and 8 per million population,respectively)1. Despite the significant risk of morbidity and mortalityassociated with CO poisoning, existing surveillance systems in theUnited States are limited. This study is the first to focus specificallyon CO poisoning trends within the VHA population.MethodsQueries were performed in VA PraedicoTMPublic HealthSurveillance System for inpatient discharges and emergency roomand urgent care outpatient visits with ICD 9/10 CM codes for COpoisoning from 1/1/2010 – 6/30/2016. A dataset of unique patientencounters with CO poisoning was compiled and further classified asaccidental, self-harm or unspecified. Patients with carboxyhemoglobin(COHb) blood level measurements≥10%2for the same timeframewere extracted and merged with the CO poisoning dataset.We analyzed for demographic, geographic and seasonal variables.Rates were calculated using total unique users of VHA care formatching time frame and geographic area as denominators.ResultsThere were a total of 671 unique VHA patients identified with COpoisoning. Of these, 298 (44%) were classified as accidental, 104(15%) self-harm, and 269 (40%) unspecified. A total of 6 patientsdied within 30 days of their coded diagnosis, however only 1 ofthese was directly attributable to CO poisoning. The overall rate ofCO poisoning over the study time frame was 18 per million uniqueusers of VHA care. CO poisoning diagnoses were obtained from396 (59%) outpatients, 216 (32%) inpatients, and 59 (9%) patientswith both and outpatient visit and inpatient admission. Patientswith self-harm classification were less likely to be seen in the ED(only 24 (6%) unique patients compared to 190 (48%) accidental and182 (46%) unspecified classifications). Of patients seen in the ED andsubsequently admitted, patients with the classification of accidentalpoisoning made up the largest percentage with 36 unique patients(61%). There were 71 (11%) females compared to 600 (89%) males.The highest represented age group was 45-64 with 342 unique patients(51%). Rates by US Census Region were highest in the Midwestand Northeast (27 and 23 per million unique users, respectively)compared to the West and South (15 and 13 per million uniqueusers, respectively) (Figure 1). Accidental CO poisonings showed aseasonal pattern with peaks occurring in late fall, winter, and earlyspring months (Figure 2). CO poisonings classified as unspecifiedhad a similar but less pronounced pattern, while those classified asself-harm were too few to observe any pattern over time. COHb bloodlevels≥10% were present in 111 (17%) of patients with CO poisoningcodes. Of patients with COHb measures≥10%, those with self-harmclassification were least represented with only 7 unique patients (6%).Accidental and unspecified classifications were equally representedwith 53 (48%) and 51 (46%) unique patients, respectively.ConclusionsThe impact of CO poisoning on the VHA patient population hasnot been well studied. The geographic distribution of the majorityof cases in the Midwest and Northeast, and the seasonal distributionof accidental cases in colder months seems to be appropriate withrespect to what is known of unintentional CO poisoning as oftenassociated with heat-generating sources3. Opportunities for furtherinvestigation include how potential CO poisoning cases are evaluatedin VHA given the low percentage of cases with COHb blood levelmeasurements

Carbon Monoxide Poisoning in the Veterans Health Administration, 2010 - 2016

ObjectiveTo describe characteristics of Veterans Health Administration(VHA) patients with ICD 9/10 CM inpatient discharge and/oremergency department (ED)/urgent care outpatient encounter codesfor carbon monoxide (CO) poisoning.IntroductionIt is estimated that in the United States (US), unintentional non-firerelated CO poisoning causes an average of 439 deaths annually, and in2007 confirmed CO poisoning cases resulted in 21,304 ED visits and2,302 hospitalizations (71 per million and 8 per million population,respectively)1. Despite the significant risk of morbidity and mortalityassociated with CO poisoning, existing surveillance systems in theUnited States are limited. This study is the first to focus specificallyon CO poisoning trends within the VHA population.MethodsQueries were performed in VA PraedicoTMPublic HealthSurveillance System for inpatient discharges and emergency roomand urgent care outpatient visits with ICD 9/10 CM codes for COpoisoning from 1/1/2010 – 6/30/2016. A dataset of unique patientencounters with CO poisoning was compiled and further classified asaccidental, self-harm or unspecified. Patients with carboxyhemoglobin(COHb) blood level measurements≥10%2for the same timeframewere extracted and merged with the CO poisoning dataset.We analyzed for demographic, geographic and seasonal variables.Rates were calculated using total unique users of VHA care formatching time frame and geographic area as denominators.ResultsThere were a total of 671 unique VHA patients identified with COpoisoning. Of these, 298 (44%) were classified as accidental, 104(15%) self-harm, and 269 (40%) unspecified. A total of 6 patientsdied within 30 days of their coded diagnosis, however only 1 ofthese was directly attributable to CO poisoning. The overall rate ofCO poisoning over the study time frame was 18 per million uniqueusers of VHA care. CO poisoning diagnoses were obtained from396 (59%) outpatients, 216 (32%) inpatients, and 59 (9%) patientswith both and outpatient visit and inpatient admission. Patientswith self-harm classification were less likely to be seen in the ED(only 24 (6%) unique patients compared to 190 (48%) accidental and182 (46%) unspecified classifications). Of patients seen in the ED andsubsequently admitted, patients with the classification of accidentalpoisoning made up the largest percentage with 36 unique patients(61%). There were 71 (11%) females compared to 600 (89%) males.The highest represented age group was 45-64 with 342 unique patients(51%). Rates by US Census Region were highest in the Midwestand Northeast (27 and 23 per million unique users, respectively)compared to the West and South (15 and 13 per million uniqueusers, respectively) (Figure 1). Accidental CO poisonings showed aseasonal pattern with peaks occurring in late fall, winter, and earlyspring months (Figure 2). CO poisonings classified as unspecifiedhad a similar but less pronounced pattern, while those classified asself-harm were too few to observe any pattern over time. COHb bloodlevels≥10% were present in 111 (17%) of patients with CO poisoningcodes. Of patients with COHb measures≥10%, those with self-harmclassification were least represented with only 7 unique patients (6%).Accidental and unspecified classifications were equally representedwith 53 (48%) and 51 (46%) unique patients, respectively.ConclusionsThe impact of CO poisoning on the VHA patient population hasnot been well studied. The geographic distribution of the majorityof cases in the Midwest and Northeast, and the seasonal distributionof accidental cases in colder months seems to be appropriate withrespect to what is known of unintentional CO poisoning as oftenassociated with heat-generating sources3. Opportunities for furtherinvestigation include how potential CO poisoning cases are evaluatedin VHA given the low percentage of cases with COHb blood levelmeasurements

Does Antimicrobial Prescription Data Improve Influenza Surveillance in VA?

INTRODUCTION: Antimicrobial prescriptions are a new data source available to the Veterans Health Administration (VHA) biosurveillance program. Little is known about whether antiviral or antibacterial prescription data correlates with influenza ICD-9-CM coded encounters. We therefore evaluated the utility and timeliness of antiviral and antibacterial utilization for influenza surveillance. METHODS: Antiviral (oseltamivir, zanamivir) and antibacterial (azithromycin) outpatient (OP) prescriptions and OP ESSENCE coded respiratory syndrome, influenza-like-illness (ILI) or influenza-specific ICD-9-CM coded visits were analyzed covering the 2010–2011 and 2011–2012 influenza seasons (July 1, 2010–July 31, 2012) for 152 VA medical centers and 971 outpatient clinics using VA Corporate Data Warehouse and ESSENCE biosurveillance tool. Correlation analysis and peak comparisons were performed. RESULTS: For this time period, there were 2,880,415 respiratory, 1,578,421 ILI, and 5,158 influenza-specific coded visits. For both influenza seasons, respiratory and ILI visits peaked at weeks 1–2 whereas influenza-specific visits had two peaks between weeks 37–40 and weeks 6–11 (See Figure 1 and 2). The total number of prescriptions was 631,272 azithromycin; 8,362 oseltamivir; and 88 zanamivir (See Figure 2). Spearman rank correlation coefficients for daily antiviral prescriptions and influenza-coded visits were (0.70); ILI visits (0.64), and respiratory illness visits (0.62), respectively; and for azithromycin prescriptions 0.77, 0.98, and 0.97 respectively. Oseltamivir and zanamivir prescriptions only increased in 2010–2011 starting with week 51 and peaking week 6 and in 2011–2012 starting with week 8 and peaking week 14. However, azithromycin prescriptions tracked better across the entire influenza season (peaking at weeks 1–2 for both influenza seasons). CONCLUSIONS: VA outpatient prescription data indicated that significantly more ILI and respiratory syndrome visits occurred compared to antiviral prescriptions dispensed with marginal temporal correlation between visits and antiviral prescriptions. Reasons for this finding require further investigation. Although we did not chart review the visit code and antimicrobial prescription in individual records, possible factors may be related to later presentation of cases, perceived lack of efficacy of antivirals, or insufficient coding of influenza. Thus, antiviral prescription data provided minimal additional information for influenza trend monitoring in VA although may still be useful a marker of more severe illness. Interestingly, azithromycin use tracked better with the onset and peaks of the influenza season. Further investigation is also needed to determine whether patients with influenza-specific coded encounters were also prescribed azithromycin and why relatively few encounters were coded with an influenza-specific code

Does Antimicrobial Prescription Data Improve Influenza Surveillance in VA?

Whether antiviral or antibacterial prescriptions correlate with influenza coded encounters is unknown. Oseltamivir, zanamivir and azithromycin outpatient prescriptions from VA Corporate Data Warehouse and respiratory syndrome, influenza-like-illness (ILI) and influenza-specific ICD-9-CM coded visits from outpatient ESSENCE were analyzed for the 2010-2012 influenza seasons in all VA medical centers and outpatient clinics. Significantly more ILI and respiratory syndrome encounters occurred compared to antiviral prescriptions dispensed with marginal temporal correlation between visits and antiviral prescriptions. Azithromycin prescriptions tracked closely with the onset and peaks of the influenza season. Surprisingly, antiviral prescription data provided minimal additional information for influenza trend monitoring in VA