Chapter 17 Obstetric haemorrhage

Background: Peripartum hysterectomy is a life-saving procedure resorted to when conservative measures fail to control obstetric haemorrhage. Several predisposing factors, suboptimal care and lack of infrastructure may lead to this emergency procedure. We wanted to find out factors associated with peripartum hysterectomy and the adverse maternal outcomes at our centre.Methods: A retrospective case series analysis of 40 cases of peripartum hysterectomy performed over a period of 5 years from January 2010 to December 2014 at Government Medical College Hospital, Thrissur, Kerala was done.Results: The incidence of peripartum hysterectomy was 0.29%. The most common indication for peripartum hysterectomy was hysterectomy was uterine atony (50%). Thirty-five women (88%) were between 20 and 35 years. Most of the subjects were unbooked. There were two maternal deaths (case fatality rate of 5%) following peripartum hysterectomy during this period. All the subjects required blood transfusion.Conclusions: Prompt performance hysterectomy before the patient’s clinical condition deteriorates is the key to success. The incidence of adherent placenta is increasing, so every effort should be taken to reduce the caesarean section rates globally.

Download Full-text

P.85 Re-audit of the management of blood product administration for major obstetric haemorrhage

International Journal of Obstetric Anesthesia ◽

10.1016/j.ijoa.2021.103083 ◽

2021 ◽

Vol 46 ◽

pp. 103083

Author(s):

D Iyer ◽

J. Niewiarowski ◽

K. Kalopita ◽

R. Russell

Keyword(s):

Blood Product ◽

Obstetric Haemorrhage

Download Full-text

High mortality rate of obstetric critically ill women in Rwanda and its predictability

BMC Pregnancy and Childbirth ◽

10.1186/s12884-021-03882-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Alcade Rudakemwa ◽

Amyl Lucille Cassidy ◽

Théogène Twagirumugabe

Keyword(s):

Prediction Models ◽

Average Length ◽

Mortality Prediction ◽

Routine Practice ◽

Icu Mortality ◽

Resource Limited ◽

Obstetric Haemorrhage ◽

Tertiary Hospitals ◽

Mortality Prediction Models ◽

Qsofa Score

Abstract Background Reasons for admission to intensive care units (ICUs) for obstetric patients vary from one setting to another. Outcomes from ICU and prediction models are not well explored in Rwanda owing to lack of appropriate scores. This study aimed to assess reasons for admission and accuracy of prediction models for mortality of obstetric patients admitted to ICUs of two public tertiary hospitals in Rwanda. Methods We prospectively collected data from all obstetric patients admitted to the ICUs of the two public tertiary hospitals in Rwanda from March 2017 to February 2018 to identify reasons for admission, demographic and clinical characteristics, outcome including death and its predictability by both the Modified Early Obstetric Warning Score (MEOWS) and quick Sequential Organ Failure Assessment (qSOFA). We analysed the accuracy of mortality prediction models by MEOWS or qSOFA by using logistic regression adjusting for factors associated with mortality. Area under the Receiver Operating characteristic (AUROC) curves is used to show the predicting capacity for each individual tool. Results Obstetric patients (n = 94) represented 12.8 % of all 747 ICU admissions which is 1.8 % of all 4.999 admitted women for pregnancy or labor. Sepsis (n = 30; 31.9 %) and obstetric haemorrhage (n = 24; 25.5 %) were the two commonest reasons for ICU admission. Overall ICU mortality for obstetric patients was 54.3 % (n = 51) with average length of stay of 6.6 ± 7.525 days. MEOWS score was an independent predictor of mortality (adjusted (a)OR 1.25; 95 % CI 1.07–1.46) and so was qSOFA score (aOR 2.81; 95 % CI 1.25–6.30) with an adjusted AUROC of 0.773 (95 % CI 0.67–0.88) and 0.764 (95 % CI 0.65–0.87), indicating fair accuracy for ICU mortality prediction in these settings of both MEOWS and qSOFA scores. Conclusions Sepsis and obstetric haemorrhage were the commonest reasons for obstetric admissions to ICU in Rwanda. MEOWS and qSOFA scores could accurately predict ICU mortality of obstetric patients in resource-limited settings, but larger studies are needed before a recommendation for their use in routine practice in similar settings.

Download Full-text

Validation of anaemia, haemorrhage and blood disorder reporting in hospital data in New South Wales, Australia

BMC Research Notes ◽

10.1186/s13104-021-05584-x ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Heather J. Baldwin ◽

Tanya A. Nippita ◽

Siranda Torvaldsen ◽

Therese M. McGee ◽

Kristen Rickard ◽

...

Keyword(s):

Postpartum Haemorrhage ◽

New South ◽

New South Wales ◽

High Sensitivity ◽

Hospital Data ◽

Blood Disorders ◽

Blood Disorder ◽

South Wales ◽

Obstetric Haemorrhage ◽

Tertiary Hospitals

Abstract Objective Hospital data are a useful resource for studying pregnancy complications, including bleeding-related conditions, however, the reliability of these data is unclear. This study aims to examine reliability of reporting of bleeding-related conditions, including anaemia, obstetric haemorrhage and blood disorders, and procedures, such as blood transfusion and hysterectomy, in coded hospital records compared with obstetric data from two large tertiary hospitals in New South Wales. Results There were 36,051 births between 2011 and 2015 included in the analysis. Anaemia and blood disorders were poorly reported in the hospital data, with sensitivity ranging from 2.5% to 24.8% (positive predictive value (PPV) 12.0–82.6%). Reporting of postpartum haemorrhage, transfusion and hysterectomy showed high sensitivity (82.8–96.0%, PPV 78.0–89.6%) while moderate consistency with the obstetric data was observed for other types of obstetric haemorrhage (sensitivity: 41.9–65.1%, PPV: 50.0–56.8%) and placental complications (sensitivity: 68.2–81.3%, PPV: 20.3–72.3%). Our findings suggest that hospital data may be a reliable source of information on postpartum haemorrhage, transfusion and hysterectomy. However, they highlight the need for caution for studies of anaemia and blood disorders, given high rates of uncoded and ‘false’ cases, and suggest that other sources of data should be sought where possible.

Download Full-text