COVID-19 incidence and outcome by affluence/deprivation across three pandemic waves in Ireland: A retrospective cohort study using routinely collected data.

BACKGROUND: Since the pandemic onset, deprivation has been seen as a significant determinant of COVID-19 incidence and mortality. This study explores outcomes of COVID-19 in the context of material deprivation across three pandemic waves in Ireland. METHODS: Between 1st March 2020 and 13th May 2021, 252,637 PCR-confirmed COVID-19 cases were notified in Ireland. Cases were notified to the national Computerised Infectious Disease Reporting (CIDR) system. Each case was geo-referenced and assigned a deprivation category according to the Haase-Pratschke (HP) Deprivation Index. Regression modelling examined three outcomes: admission to hospital; admission to an intensive care unit (ICU) and death. RESULTS: Deprivation increased the likelihood of contracting COVID-19 in all age groups and across all pandemic waves, except for the 20-39 age group. Deprivation, age, comorbidity and male gender carried increased risk of hospital admission. Deprivation was not a factor in predicting ICU admission or death, and diagnosis in wave 2 was associated with the lowest risk of all three outcomes. CONCLUSIONS: Our study suggests that COVID-19 spreads easily through all strata of society and particularly in the more deprived population; however this was not a consistent finding. Ireland is ethnically more homogenous than other countries reporting a larger deprivation gradient, and in such societies, structural racial differences may contribute more to poor COVID outcomes than elements of deprivation.

Venous thromboembolism incidence in the Ireland east hospital group: a retrospective 22-month observational study.

OBJECTIVES: To determine the incidence of venous thromboembolism (VTE) and the incidence of hospital-acquired VTE (HA-VTE) arising within the population served by the Ireland East Hospital Group (IEHG). DESIGN: /home/user/Documents/Sathish Kumar G/RFO/June/21-06-2019/bmjopen_iss_9_7_20190621_1/ A retrospective observational study was conducted using hospital discharge data obtained from the hospital inpatient enquiry data reporting system. In this system, VTE events recorded as 'primary diagnosis' represented the reason for initial hospital admission, whereas VTE recorded as a 'secondary diagnosis' occurred following admission and were therefore used as an approximation of HA-VTE. These data were used to estimate the overall incidence of VTE and the proportion of these events which were hospital-acquired. SETTING: The IEHG is the largest hospital group in the Irish healthcare system and serves a population of over 1 million individuals. PARTICIPANTS: Data were generated from records pertaining to the 2727 patient admission episodes where a diagnosis of VTE was made during the 22-month study period. RESULTS: During the study period, 2727 VTE events were recorded within the IEHG (which serves a population of 1 036 279) corresponding to an incidence of 1.44 (95% CI 1.36 to 1.51) per 1000 per annum. 1273 (47%) of VTE events were recorded as secondary VTE. The incidence of VTE was highest among individuals over 85 years of age (16.03 per 1000;95% CI 12.81 to 19.26) and was more common following emergency hospital admission. CONCLUSION: These data suggest that HA-VTE accounts for at least 47% of all VTE events arising within a hospital group serving a population of over 1 million individuals within the Ireland. Given that HA-VTE is a well-recognised source of (potentially preventable) hospital deaths, these findings provide a compelling argument for prioritising strategies directed at reducing the risk of VTE among hospital patients served by the IEHG and within the Ireland as a whole.

Risk-adjusted antibiotic consumption in 34 public acute hospitals in Ireland, 2006 to 2014.

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.

The influence of socioeconomic status on patient survival on chronic dialysis.

Socioeconomic status (SES) has been linked to worse end-stage kidney disease survival. The effect of SES on survival on chronic dialysis, including the impact of transplantation, was examined. A retrospective, observational study investigated the association of SES with dialysis patient survival, with censoring at time of transplantation. Adult patients commencing dialysis from 1990 to 2009 in an Irish tertiary center received a spatial SES score using the 2011 Pobal Haase-Pratschke Deprivation Index and were compared by quartile. Cox proportional hazard models and Kaplan-Meier survival analysis examined any association of SES with survival. The 1794 patients included had a median follow-up of 3.8 years. Patients in the lowest SES area quartile were significantly younger than the highest, mean age 56.7 vs. 59 years, P = 0.006, respectively. There was no association between SES area score and survival in an unadjusted model (hazard ratio [HR] 1.00, 95% confidence interval [CI] 0.99-1.01). Survival in the highest SES area quartile was superior to the lowest SES in a multivariable adjusted model including age, gender, and dialysis modality (HR 0.83, 95% CI 0.70-0.99, P = 0.04). These results were only mildly attenuated by censoring at time of transplantation (highest SES area quartile deprived vs. lowest SES area quartile, HR 0.85, 95% CI 0.70-1.03, P = 0.09). Superior patient survival was identified in the highest SES areas compared with the lowest following age-adjusted analyses, despite the older population in the most affluent areas. Further research should focus on identifying modifiable targets for intervention that account for this socioeconomic-related survival advantage.

Influence of socioeconomic status on allograft and patient survival following kidney transplantation.

AIM: Whether socioeconomic status confers worse outcomes after kidney transplantation is unknown. Its influence on allograft and patient survival following kidney transplantation in Ireland was examined. METHODS: A retrospective, observational cohort study of adult deceased-donor first kidney transplant recipients from 1990 to 2009 was performed. Those with a valid Irish postal address were assigned a socioeconomic status score based on the Pobal Hasse-Pratschke deprivation index and compared in quartiles. Cox proportional hazards models and Kaplan-Meier survival analysis were used to investigate any significant association of socioeconomic status with patient and allograft outcomes. RESULTS: A total of 1944 eligible kidney transplant recipients were identified. The median follow-up time was 8.2 years (interquartile range 4.4-13.3 years). Socioeconomic status was not associated with uncensored or death-censored allograft survival (hazard ratio (HR) 1.0, 95% confidence interval (CI) 0.99-1.00, P = 0.33 and HR 1.0, 95% CI 0.99-1.00, P = 0.37, respectively). Patient survival was not associated with socioeconomic status quartile (HR 1.0, 95% CI 0.93-1.08, P = 0.88). There was no significant difference among quartiles for uncensored or death-censored allograft survival at 5 and 10 years. CONCLUSION: There was no socioeconomic disparity in allograft or patient outcomes following kidney transplantation, which may be partly attributable to the Irish healthcare model. This may give further impetus to calls in other jurisdictions for universal healthcare and medication coverage for kidney transplant recipients.