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You are here: Home > Clinical Informatics and Big Data > Study reveals trends in incidence of spontaneous pneumothorax

Study reveals trends in incidence of spontaneous pneumothorax

10 October 2018 · Listed under Clinical Informatics and Big Data, Respiratory

Oxford researchers supported by the NIHR Oxford Biomedical Research Centre have published research that show how the rates of incidence and recurrence of spontaneous pneumothorax have changed over time.

The research, published on 9 October in the Journal of the American Medical Association, involved teams from the Oxford BRC’s Respiratory and Clinical Informatics themes, using almost 50 years of data held by the Unit of Healthcare Epidemiology in the University of Oxford’s Big Data Institute.

Spontaneous pneumothorax is a common disease known to have an unusual epidemiological profile, but there are limited contemporary population-based data.

Previous attempts to measure the incidence of this condition were based on studies that were often small, many years old and from single centres, or on two national databases that covered limited periods.

Looking at data from 1968 to 2016, the researchers found that the annual hospital admission rate for spontaneous pneumothorax in England increased from 9.1 to 14.1 per 100 000 population, with differences by sex and by age.

Between these dates, there were 170 929 hospital admissions for spontaneous pneumothorax, with the majority (73 per cent) being men.

Of patients with spontaneous pneumothorax, 60.8% had chronic lung disease.

Record-linkage analysis showed that the overall increase in admissions over time could be due in part to an increase in repeat admissions, but there were also significant increases in the annual rate of first-known spontaneous pneumothorax admissions in some population subgroups, for example women aged 65 and older.

The study found that the probability of recurrence within five years was similar by sex, but there were variations according to age group and the presence of chronic lung disease.

Read more about the findings.

← Oxford team use DNA sequencing and patient data to halt infection outbreak
Genetic changes associated with physical activity emerge thanks to machine learning pioneers →

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