Evidence map›Paper›PMID 31502306›Full record

ArticlePaediatric and perinatal epidemiology2020

Monitoring severe acute maternal morbidity across Europe: A feasibility study.

Anne A Chantry, Sylvan Berrut, Serena Donati, Mika Gissler, Raphael Goldacre, Marian Knight, Alice Maraschini, Kirsten Monteath, Anna Morris, Cristina Teixeira and 3 more

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In one paragraph

Article in Paediatric and perinatal epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Anne A ChantryINSERM UMR 1153, Obstetrical, Perinatal and Paediatric Epidemiology Research Team (Epopé), Centre for Epidemiology and Statistics Sorbonne Paris Cité (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France.ORCID 0000-0001-8307-6462
Sylvan BerrutFederal Statistical Office, Neuchâtel, Switzerland.
Serena DonatiMaternal and Child Health Unit, National Centre for Disease Prevention and Health Promotion - Italian National Institute of Health, Rome, Italy.
Mika GisslerInformation Services Department, THL National Institute for Health and Welfare, Helsinki, Finland.
Raphael GoldacreUnit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
Marian KnightNational Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Alice MaraschiniMaternal and Child Health Unit, National Centre for Disease Prevention and Health Promotion - Italian National Institute of Health, Rome, Italy.
Kirsten MonteathInformation Services Division, NHS National Services Scotland, Edinburgh, UK.
Anna MorrisInformation Services Department, NHS Wales Informatics Service, Cardiff, UK.
Cristina TeixeiraEPI Unit Instituto de Saúde Pública da Universidade do Porto, Porto, Portugal.
Rachael WoodInformation Services Division, NHS National Services Scotland, Edinburgh, UK.
Jennifer ZeitlinINSERM UMR 1153, Obstetrical, Perinatal and Paediatric Epidemiology Research Team (Epopé), Centre for Epidemiology and Statistics Sorbonne Paris Cité (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France.
Catherine Deneux-TharauxINSERM UMR 1153, Obstetrical, Perinatal and Paediatric Epidemiology Research Team (Epopé), Centre for Epidemiology and Statistics Sorbonne Paris Cité (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France.ORCID 0000-0002-6561-3321

Funding

Department of Health
6 · The paper itself

Abstract

backgroundMonitoring severe acute maternal morbidity (SAMM) appears essential for optimising care and informing health care policies, especially given changes in obstetric practices and mother profiles. International comparisons can identify areas where improvement is needed, but the comparability of indicators must be evaluated.

objectiveTo assess the feasibility of monitoring SAMM using common definitions from hospital discharge databases across Europe.

methodsWe used hospital discharge data in eight countries (2 826 868 deliveries) to identify women with SAMM among all hospitalisations of women of reproductive age admitted for antenatal or delivery care. Five SAMM indicators were investigated: eclampsia, septicaemia, hysterectomy, hysterectomy associated with a diagnosis of obstetric haemorrhage, and red blood cell (RBC) transfusion associated with a diagnosis of obstetric haemorrhage. Between-country variation was described, by the ratio of the highest to lowest rates, while external validation was assessed by comparing with population-based studies on maternal morbidity.

resultsRatios for hysterectomy and red blood cell (RBC) transfusion in the context of obstetric haemorrhage were 1:2.1 and 1:3.5, respectively. High values of hysterectomy and low values of transfusion were both consistent with high maternal mortality from haemorrhage (France, Italy, Portugal). Ratios across countries were relatively low for eclampsia (1:3.4) but very high for septicaemia (1:22.5). Compared to population-based morbidity estimates, eclampsia was over-reported in hospital databases whereas the two indicators of severe haemorrhage had good external validity.

conclusionsIn association with diagnosis codes indicating obstetric haemorrhage, hysterectomy and RBC transfusion appear to be good candidates for surveillance of maternal morbidity in Europe.

Indexed as

Delivery, ObstetricPostpartum HemorrhagePregnancy ComplicationsAdultEpidemiological MonitoringErythrocyte TransfusionEuropeFeasibility StudiesFemaleHospital Information SystemsHumansHysterectomyOutcome Assessment, Health CarePatient DischargePregnancyQuality ImprovementEuropehospital discharge databasesmaternal health surveillanceobstetric complicationssevere acute maternal morbidity

Identifiers

PMID31502306

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.