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Introduction With a view to inform policy for improved postabortion care, we describe abortion-related near-miss and mortality by sociodemographic risk factors and management options by pregnancy trimester in Uganda. Methods This secondary data analysis used an adapted WHO near-miss methodology to collect cross-sectional maternal near-miss and abortion complications data at 43 health facilities in Central and Eastern Uganda in 2016-2017. We computed abortion severe morbidity, near-miss and mortality ratios per 100 000 live births, and described the proportion of cases that worsened to an abortion near-miss or death, stratified by geographical region and trimester. We tested for association between independent variables and abortion near-miss, and obtained prevalence ratios for association between second trimester near-miss and independent demographic and management indicators. We assessed health facility readiness for postabortion care provision in Central and Eastern regions. Results Of 3315 recorded severe abortion morbidity cases, 1507 were near-misses. Severe abortion morbidity, near-miss and mortality ratios were 2063, 938 and 23 per 100 000 live births, respectively. Abortion-related mortality ratios were 11 and 57 per 100 000 in Central and Eastern regions, respectively. Abortion near-miss cases were significantly associated with referral (p<0.001). Second trimester had greater abortion mortality than first trimester. Eastern region had greater abortion-related morbidity and mortality than Central region with facilities in the former characterised by inferior readiness to provide postabortion care. Conclusions Uganda has a major abortion near-miss morbidity and mortality; with mortality higher in the second trimester. Life-saving commodities are lacking especially in Eastern region compromising facility readiness for postabortion care provision.
We collected cross-sectional data on maternal near-miss as part of a cluster randomised two-arm trial to assess the impact of a 1 day competency-based training ‘Helping Mothers Survive: Bleeding after Birth’ on morbidity and mortality due to postpartum haemorrhage (PPH). The primary trial details are reported elsewhere.23 The study was conducted in 11, and 7 districts in Central and Eastern regions of Uganda, respectively, at 22 hospitals, and 21 high case load health centres; 9 were private not for profit (PNFP) and 34 public. In each district, taken as a cluster, we included all public hospitals and randomly sampled health centres and PNFP health facilities with more than 400 deliveries per year. Ministry of Health Uganda recommended the selected districts and all health facilities offer at least basic EmOC services. Data collection run from June 2016 to September 2017. We used the WHO near-miss form to collect data of all maternal near-miss events, and deaths which took place in the selected health facilities.24 The data collection form was amended and included severe abortion complications, see online supplemental appendix I, as a screening question to ensure that these events were captured consistently. Details of categories for organ dysfunction, critical interventions, and other data collected are reported elsewhere.23 bmjgh-2020-003274supp001.pdf At each health facility, two of the midwives, selected as data collectors received a 1-day training on near-miss methodology and the data collection process. We collected data prospectively from several service points at the health facilities including (1) antenatal, labour and postnatal ward, (2) female and surgical ward, (3) laboratory and (4) theatre to ensure that all cases of near-miss and maternal deaths were included. A standard protocol was used to abstract information from the patient’s clinical case notes and registries for admission, birth, theatre, laboratory and discharge. From the paper forms, the data collectors entered data onto a tablet-based application (Lenovo A3500-F) and uploaded onto the cloud server biweekly using Open Data Kit Collect software application. Data on the total number of live births in the facilities were collected through monthly telephone calls and verified during supervision visits. The data collectors were supported through biweekly supervision visits and regular telephone calls to ensure complete and correct abstraction of data. This paper uses only the data on maternal near-misses admitted as abortion-related complications. An abortion was defined as termination of a pregnancy less than 28 weeks gestation age. We extracted data for women coded as having abortion complications from those with severe maternal morbidity. Women with ectopic pregnancy or gestation age above 27 weeks were excluded, viability in Uganda begins at 28 weeks.19 Since PPH and abortion are both bleeding complications, we screened the PPH cases to identify the abortion cases that were miscoded as PPH using a gestation age less than 28 weeks. Cases that were coded as abortion cases but where the gestation age was missing were not excluded from the data set (see online supplemental appendix II). We assessed for PAC provision health facility readiness at the 43 health facilities from February to April 2016 using an adapted Uganda health facility assessment tool. Components therein are very similar to the WHO service availability and readiness assessment tool,25 however, we did not collect information on whether the abortion was spontaneous or induced, and provision of family planning services as these were not captured in the primary study tool. Key items measured that influence access and availability to PAC services at all the health facilities included: (1) uterotonics like misoprostol and oxytocin; (2) manual vacuum aspiration (MVA) sets; (3) intravenous fluids; (4) parenteral antibiotics; (5) ability to provide PAC services 24 hours a day, 7 days a week (24/7); (6) referral capability (motorised transport for referral, health provider accompanying a referral); (7) communication means; and for health facilities offering comprehensive EmOC; (8) blood transfusion services and (9) surgical/laparotomy capability. Service readiness components like equipment and commodities were verified by checking their presence on the wards, pharmacy, laboratory and the health facility stores. Health facilities’ ability to provide PAC services 24/7 was verified with checking duty schedules, ward and theatre registers for the previous 3 months. We inquired about the presence of motorised transport at the health facility, and whether the most recent referral to a higher facility had been accompanied by a health provider to check the referral capability. The main outcome, ANM, was defined using our adapted WHO near-miss criteria as a case of severe abortion complication with either organ dysfunction, severe sepsis, blood transfusion or laparotomy. Given the paucity of blood products in low to middle income countries, the threshold for massive blood transfusion was reduced to two units down from the five units recommended by WHO.14 26 27 Other outcomes were: Independent variables included background characteristics like gestation age based on weeks of amenorrhoea, patient’s age in completed years, number of pregnancies and timing of onset of complications. Reproductive and institutional factors like HIV status, referral status (referred into the facility), type of health facility and ownership. We also collected information on complications including infection, organ dysfunction and maternal death; as well as management options like types of uterine evacuation, uterotonics administered, and additional interventions, for example, blood transfusion, number of blood transfusion units administered and laparotomy, all abstracted from the patient’s clinical case notes. Statistical analysis was performed using Stata V.14. We present the number of women with severe abortion complications, ANM, abortion-related deaths; and SAMR, ANMR and AMR for all women in the study, then segregated by region. We also present the proportions of SAM that had ANM or abortion-related deaths by region and pregnancy trimester. The estimates were not weighted for region. We designated health facility as a primary sampling unit and assigned all health facilities the same weight using STATA command svyset (pw=wgt), psu(id3) singleunit (centred). Background characteristics and categorical outcomes were presented with descriptive statistics. Continuous variables were summarised using means (SD) or medians (IQR) and categorical variables using proportions (CIs). Pearson’s χ2 was used to test the difference between severe abortion complications cases and those that progressed to be ANM across different sociodemographic, reproductive and institutional characteristics. We computed 95% CIs and statistical significance established at p<0.05. We excluded women with missing data for gestation age and unrecorded HIV status in the statistical test computation for background and reproductive characteristics comparison among near-miss cases to avoid misinterpretation of findings. We then described the proportion of women with severe abortion complications or ANM that suffered complications such as infection, organ dysfunction, maternal death and the management options received including type of uterine evacuation, uterotonics administered, blood transfusion and when a laparotomy was performed. To examine the association between first and second trimester ANM and background characteristics, reproductive factors, institutional factors, types of complications and management options, we did multiple generalised linear models with binomial family and log link to obtain unadjusted prevalence ratios effect estimates. Regarding health facility readiness for PAC, we computed the percentage of facilities that fulfilled each readiness indicator, for all health facilities and for central and eastern region. Performed Pearson χ2 or Fischer’s exact tests to compare PAC health facility readiness between the central and eastern region. The funder had no role in study conceptualisation, data collection, analysis and manuscript writing. All authors had full access to the study data and the corresponding author had final responsibility for the decision to submit for publication.
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