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As antibiotic consumption rates between hospitals can vary depending on the characteristics of the patients treated, risk-adjustment that compensates for the patient-based variation is required to assess the impact of any stewardship measures. The aim of this study was to investigate the usefulness of patient-based administrative data variables for adjusting aggregate hospital antibiotic consumption rates. Data on total inpatient antibiotics and six broad subclasses were sourced from 34 acute hospitals from 2006 to 2014. Aggregate annual patient administration data were divided into explanatory variables, including major diagnostic categories, for each hospital. Multivariable regression models were used to identify factors affecting antibiotic consumption. Coefficient of variation of the root mean squared errors (CV-RMSE) for the total antibiotic usage model was very good (11%), however, the value for two of the models was poor (> 30%). The overall inpatient antibiotic consumption increased from 82.5 defined daily doses (DDD)/100 bed-days used in 2006 to 89.2 DDD/100 bed-days used in 2014; the increase was not significant after risk-adjustment. During the same period, consumption of carbapenems increased significantly, while usage of fluoroquinolones decreased. In conclusion, patient-based administrative data variables are useful for adjusting hospital antibiotic consumption rates, although additional variables should also be employed.
Assuntos
Antibacterianos/uso terapêutico , Uso de Medicamentos/estatística & dados numéricos , Hospitais Públicos , Pacientes Internados/estatística & dados numéricos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Bases de Dados como Assunto , Feminino , Humanos , Irlanda , Tempo de Internação , Masculino , Pessoa de Meia-Idade , Análise de Regressão , Estudos Retrospectivos , Risco Ajustado , Centros de Atenção Terciária , Adulto JovemRESUMO
BACKGROUND: This study aimed to investigate overall and sex-specific excess all-cause mortality since the inception of the COVID-19 pandemic until August 2020 among 22 countries. METHODS: Countries reported weekly or monthly all-cause mortality from January 2015 until the end of June or August 2020. Weekly or monthly COVID-19 deaths were reported for 2020. Excess mortality for 2020 was calculated by comparing weekly or monthly 2020 mortality (observed deaths) against a baseline mortality obtained from 2015-2019 data for the same week or month using two methods: (i) difference in observed mortality rates between 2020 and the 2015-2019 average and (ii) difference between observed and expected 2020 deaths. RESULTS: Brazil, France, Italy, Spain, Sweden, the UK (England, Wales, Northern Ireland and Scotland) and the USA demonstrated excess all-cause mortality, whereas Australia, Denmark and Georgia experienced a decrease in all-cause mortality. Israel, Ukraine and Ireland demonstrated sex-specific changes in all-cause mortality. CONCLUSIONS: All-cause mortality up to August 2020 was higher than in previous years in some, but not all, participating countries. Geographical location and seasonality of each country, as well as the prompt application of high-stringency control measures, may explain the observed variability in mortality changes.
Assuntos
COVID-19 , Feminino , França , Humanos , Itália , Masculino , Mortalidade , Pandemias , SARS-CoV-2RESUMO
BACKGROUND: To date, over 2 million people worldwide have died with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To describe the experience in Ireland, this study examined associations between underlying conditions and the following outcomes: mortality, admission to hospital or admission to the intensive care unit (ICU) among those infected with COVID-19. METHODS: This study used data from the Health Protection Surveillance Centre in Ireland and included confirmed cases of COVID-19 from the first wave of the pandemic between March and July 2020. Two cohorts were included: all cases (community and hospital) and hospital admissions only. For all cases, health outcome data included mortality and hospitalisation. For hospitalised cases, outcome data included mortality and ICU admission. Logistic regression was used to examine associations between underlying conditions and outcomes across both cohorts. Results are presented as adjusted odds ratios (OR) and 95% confidence intervals (CIs). FINDINGS: There were 19,789 cases included in analysis, which encompassed 1,476 (7.5%) deaths, 2,811 (14.2%) hospitalisations, and 438 (2.2%) ICU admissions of whom 90 (20.5%) died. Significantly higher risk of mortality, hospitalisation and ICU admission was associated with having chronic heart disease, a BMI ≥40kg/m2 and male sex. Additionally, diagnosis of a chronic neurological condition (OR 1.41; 95%CI:1.17, 1.69), chronic kidney disease (OR 1.74; 95%CI:1.35, 2.24) and cancer (OR 2.77; 95%CI:2.21, 3.47) were significantly associated with higher risk of mortality among all cases, with similar patterns of association observed for mortality among hospitalised cases. INTERPRETATION: The identification of underlying conditions among COVID-19 cases may help identify those at highest risk of the worst health outcomes and inform preventive strategies to improve outcomes. FUNDING: This study was supported by the Health Service Executive, Health Protection Surveillance Centre. KEB and MM are funded by the Health Research Board (RL-15-1579 and EIA-2019-012 respectively).
RESUMO
OBJECTIVE: To describe the incidence, clinical characteristics and outcomes of critically ill patients in Ireland with pandemic (H1N1) 2009 infection, and to provide a dynamic assessment of the burden of such cases on Irish intensive care units. DESIGN, SETTING AND PARTICIPANTS: Multicentre prospective observational study of all adult patients admitted to any of the 30 ICUs in the Republic of Ireland between 15 July 2009 and 30 May 2010. MAIN OUTCOME MEASURES: Patient demographics, clinical characteristics and ICU mortality; ICU admissions, bed-days, bed occupancy rates and distribution. RESULTS: Seventy-seven adult patients with pandemic (H1N1) 2009 infection were admitted to 27 of 30 Irish ICUs. The median age was 43 years (IQR, 30-56 years); 67 patients (88%) were aged under 65; 39 (51%) were male. Sixty-two patients (82%) had comorbid conditions, including obesity (36%), respiratory disease (34%) and malignancy or immunosuppression (20%). Eight (11%) were pregnant, and 27 (36%) were smokers. Sixty-seven patients were mechanically ventilated, 24 (32%) required renal replacement therapy, 39 (51%) received vasopressors and four (5%) received extracorporeal membrane oxygenation. Of 14 patients (18%) who died in the ICU, two had no pre-existing comorbidities. The ICU admission rate of patients with pandemic (H1N1) 2009 infection was 22.5/million population. A total of 1882 ICU bed-days (557.5 bed-days/million adult population) were consumed, equating to a 3.9% bed occupancy rate, with a peak of 14.0% in October 2009. Median length of stay was 12 days (IQR, 7-34 days). CONCLUSION: The 2009 influenza A (H1N1) pandemic was a significant burden on Irish ICUs, predominantly affecting the tertiary centres. The demographics and clinical characteristics were similar to those described in the southern hemisphere, suggesting such data may inform future resource planning for similar threats.