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Unprecedented rates of PPH: a prospective observational cohort study of blood loss in childbirth (the stop study)
  1. A Briley1,
  2. PT Seed1,
  3. H Ballard2,
  4. G Tydeman3,
  5. M Waterstone2,
  6. R Tribe1,
  7. J Sandall1,
  8. S Bewley1
  1. 1Women's Health Academic Centre KHP, London, United Kingdom
  2. 2Dartford and Gravesham NHS Trust, Dartford, United Kingdom
  3. 3NHS Fife, Kirkcaldy, United Kingdom

Abstract

Background Postpartum haemorrhage (PPH >500mls) is common, easily treatable and remains a major cause of morbidity, with UK Confidential Enquiries and Scottish Severe Morbidity Audits demonstrating high rates of substandard care.

Aim To investigate the incidence, prediction and management of PPH.

Methods Minimal anonymised data were prospectively imported into a secure internet based data management system from NHS electronic records from 10,213 women delivering in two units (one teaching, one district) between 1/8/08-31/7/09. A weighted sampling strategy provided a representative sample set to assess haemorrhage; 1,851 notes were reviewed. Multiple logistic regression with hierarchical ordering of variables was used to predict PPH and progression onto severe PPH (>1500mls). Severe PPH incidence was compared with an earlier case-control study from the same geographical population (COSMO 1997-8).

Results The contemporaneous data showed a PPH rate of 34% (main risk factors: pyrexia, instrumental, caesarean, retained placenta). The main risk factors for progression to severe PPH were BMI, previous PPH, previous caesarean, praevia and syntometrine use. There was a 4.2-fold rise in numbers of severe PPHs since COSMO (93 vs 391) and 3.5-fold increased incidence (1.12% [95%CI 0.92, 1.38] vs 3.8% [95% CI 3.5, 4.2]).

Conclusions Although consistent with other time-trends, these are the highest reported PPH and severe PPH rates in the literature. This web-based audit and feedback tool could facilitate ongoing contemporaneous evaluation of incidence, management and innovation in treating PPH, filling the gap between national level data (CEMD, UKOSS, Scottish Audit) and local near-miss audits with their inherent limitations.

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