Associations between COVID-19 and hospitalisation with respiratory and non-respiratory conditions: a record linkage study.

OBJECTIVES: To assess associations between SARS-CoV-2 infection and the incidence of hospitalisation with selected respiratory and non-respiratory conditions in a largely SARS-CoV-2 vaccine-naïve population . DESIGN, SETTING, PARTICIPANTS: Self-control case series; analysis of population-wide surveillance and administrative data for all laboratory-confirmed COVID-19 cases notified to the Victorian Department of Health (onset, 23 January 2020 - 31 May 2021; ie, prior to widespread vaccination rollout) and linked hospital admissions data (admission dates to 30 September 2021). MAIN OUTCOME MEASURES: Hospitalisation of people with acute COVID-19; incidence rate ratios (IRRs) comparing incidence of hospitalisations with defined conditions (including cardiac, cerebrovascular, venous thrombo-embolic, coagulative, and renal disorders) from three days before to within 89 days of onset of COVID-19 with incidence during baseline period (60-365 days prior to COVID-19 onset). RESULTS: A total of 20 594 COVID-19 cases were notified; 2992 people (14.5%) were hospitalised with COVID-19. The incidence of hospitalisation within 89 days of onset of COVID-19 was higher than during the baseline period for several conditions, including myocarditis and pericarditis (IRR, 14.8; 95% CI, 3.2-68.3), thrombocytopenia (IRR, 7.4; 95% CI, 4.4-12.5), pulmonary embolism (IRR, 6.4; 95% CI, 3.6-11.4), acute myocardial infarction (IRR, 3.9; 95% CI, 2.6-5.8), and cerebral infarction (IRR, 2.3; 95% CI, 1.4-3.9). CONCLUSION: SARS-CoV-2 infection is associated with higher incidence of hospitalisation with several respiratory and non-respiratory conditions. Our findings reinforce the value of COVID-19 mitigation measures such as vaccination, and awareness of these associations should assist the clinical management of people with histories of SARS-CoV-2 infection.

Excess mortality among people with communicable diseases over a 30-year period, Victoria, Australia: a whole of population cohort study.

Background: Understanding mortality burden associated with communicable diseases is key to informing resource allocation, disease prevention and control efforts, and evaluating public health interventions. We quantified excess mortality among people notified with communicable diseases in Victoria, Australia. Methods: Cases of communicable disease notified in Victoria between 1 January 1991 and 31 December 2021 were linked to the death registry. Informational gain obtained through linkage and 30-day case fatality rates were calculated for each disease. Standardised mortality ratios (SMR) and 95% confidence intervals were calculated up to a year following illness onset. Findings: There were 1,032,619 cases and 5985 (0.58%) died ≤30 days of illness onset. Following linkage, the 30-day case fatality rate increased more than 2-fold. Diseases with high 7-day SMR signifying excess mortality included invasive pneumococcal disease (167.7, 95% CI 153.4-182.7); listeriosis (166.2, 95% CI 121.2-218.3); invasive meningococcal disease (145.9, 95% CI 116.7-178.3); legionellosis (43.3, 95% CI 28.0-62.0); and COVID-19 (21.9, 95% CI 19.7-24.3). Most diseases exhibited a strong negative gradient, with high SMRs in the first 7-days of illness onset that reduced over time. Interpretation: We demonstrated that the rate of death in Victoria's notifiable disease surveillance dataset is underestimated. Further, compared to a general population, there is evidence of elevated all-cause mortality among people notified with communicable diseases often up to one year following illness onset. Not all elevated risk is likely directly attributable to the communicable diseases of interest, rather, it may reflect underlying comorbidities or behaviours in these individuals. Regardless of attribution, infection with communicable diseases may represent a marker of mortality. Key to preventing deaths may be through timely and appropriate transition to primary and preventive healthcare following diagnosis. Funding: No funding was provided for this study.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study.

BACKGROUND: Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables. METHODS: A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review. RESULTS: Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%. CONCLUSIONS: High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.

Factors involved in intensive care unit mortality following medical retrieval: identifying differences between intensive care unit survivors and non-survivors.

OBJECTIVE: The study aimed to determine factors related to ICU mortality in critically ill patients transferred by Adult Retrieval Victoria (ARV) medical staff. Patients who died in ICU after interhospital transfer were compared against those who survived. METHODS: This was a retrospective cohort study of ARV cases between 1 January 2009 and 30 June 2010. Retrieval data were linked with data from the ANZICS CORE APD (Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database). Victoria Data Linkage (VDL) performed linkage of data. Data included demographic and clinical data obtained during transfer and clinical data recorded in ICU. RESULTS: Of the 601 cases transferred by ARV during the study period, 549 cases were eligible for linkage to 25 543 ANZICS APD case records for the same period. VDL matched 460 of these cases (83.8%). Mortality rate in the matched sample was 13.9%. Variables associated with mortality were: advanced age (odds ratios [OR] 1.02, 95% confidence interval [CI] 1.00-1.04, P = 0.02), principal referral problem cardiac (OR 1.84, 95%CI 1.02-3.32, P = 0.04), lower mean arterial blood pressure (OR 0.97, 95% CI 0.95-0.99, P = 0.005) and tachycardia (OR 1.02, 95% CI 1.00-1.03, P = 0.008) on arrival at destination hospital. CONCLUSIONS: Advanced age, lower mean arterial blood pressure and tachycardia towards the completion of transfer were associated with increased ICU mortality in this population. Clinicians should be aware of the additional risk for cardiac patients.