This study had the main objective to assess the epidemiology including the profile and outcomes of critical illness among obstetric patients admitted in ICU in public referral hospitals in Rwanda and to evaluate the accuracy of affordable mortality prediction tools that can be used in resource-limited settings. In our findings, obstetric admissions to ICU in public referral hospitals in Rwanda account for 12.8% of all ICU admissions and 1.8% of all deliveries. These rates of ICU admission for obstetric patients are relatively higher compared with those reported in high income countries (0.22–0.76% [1,14,15]. They are rather similar to those found in middle income countries like Brazil (1%) and Turkey (1.27%) [1,14–17]. Our findings are also comparable to that in a study done in Nigeria where obstetric admissions to ICU represented 17.29% and 2.05% of all deliveries [18].
In this study, the rate of ICU admission to all deliveries was 1.8%. It might have been higher given the limited capacity of our ICUs representing only around 1.5% of hospital beds while the ideal number should be more than 10% as it is the case in high income countries [19,20]. This scarcity of ICU beds is shared with other sub-Saharan African countries showing that the number of obstetric patients admitted in ICU falls in a range of 0.24–0.97% [4,7,21]. However, one could argue that, if the number of ICU beds could allow, the number of obstetric patients admitted in ICU in Rwanda could have been increased as the profile of patients admitted in ICU and the severity of the diseases such as the need of ventilators in about 90% and vasopressors for 50% of patients among others. Indeed, the two leading causes of admission to ICU for obstetric patients in Rwanda were sepsis (31.9%) and obstetric haemorrhagic shock (25.5%). These reasons for admission substantially differ from those prevailing in high income countries to partly explain discrepancies in terms of mortality rates as sepsis and septic shock are generally associated with a high mortality in both high income countries like in United states [22] and low income countries including Rwanda[10]. The second commonest cause of admission is hemorrhagic shock and resulting coagulation disorders related to delays to achieve haemostasis, lack of readily available blood products and massive transfusion when these are available may also contribute to the high mortality in obstetric patients in low income countries. Similar findings for main reasons for admission in ICU have been reported in a study conducted in Kenya [4].
The mortality rate in our critically ill obstetric patients was as high as 53.4% but worse outcome has been seen in other sub-Saharan African countries like Burkina Faso where this mortality reached 60% [23]. This poor outcome of our patients may be attributable to the limited capacity of our ICUs on one hand, and to the severity of illness among those admitted in ICU as explained above on the other hand. In contrast to our findings, in the study conducted in Kenya, Githae et al report mortality of 33% of all obstetric admission in ICU and those requiring ventilation and inotropic support were 33% and 30% of obstetric admissions, respectively compared with 95.7% and 50% in our study [4]. The mortality for obstetric patients admitted in ICU from our study is comparable to one for general ICU patients in Rwanda where it was 48.7% [10]. Data from our study shows that sepsis was highly prevalent and results correlates with the a single centre study in Rwanda where sepsis was the most common causes of morbidity and mortality among obstetric patients admitted in tertiary hospital[24].
A number of mortality prediction tools have been developed for general patients admitted in ICU such as Acute Physiology and Chronic Health Evaluation (APACHE), Simplified Acute Physiology Score (SAPS) and Sequential Organ Failure Assessment (SOFA) however, generalisation to obstetric patients remains challenging [25]. Our study evaluated accuracy of MEOWS and qSOFA in predicting mortality for obstetric patients admitted to ICU and found as easy tools as their components are part of routine clinical assessment. Yet, these predictive tools have good discriminative power with an area under the curve showing their performance (AUROC: 0.773[0.666–0.880], p < 0.0001 for MEOWS and 0.764[0.654–0.873], p < 0.0001 for qSOFA). Similarly, in a study conducted in Australia among emergency patients with suspected sepsis, it was found that a positive qSOFA (≥ 2 points) identified those at high risk of in hospital mortality or longer ICU stay[26]. In the study done in India, the AUROC showed good discriminative power with qSOFA in predicting mortality (AUROC: 0.73; 95% CI, 0.69–0.77) among septic patients admitted, both in ICU and non-ICU[27]. Above findings have similarities with our study with regards to qSOFA as predictive model, though, our findings are applied in obstetric patients. Our study evaluated accuracy of MEOWS predictive model. Our findings are comparable to the findings in a research conducted in the United Kingdom which showed that MEOWS had high sensitivity and good specificity to early, detect morbidity among obstetric patients outside ICU[12]. Though different setting, MEOWS as a simple bed side model may be applied to obstetric patients at admission to ICU to predict their outcome.
Data for this study were prospectively collected from two tertiary hospitals which may give it strength to be generalizable to whole obstetric population. However, the study has its own limitations such as the small sample size to allow this extrapolation to the general population. To achieve, it would be necessary to collect data for a longer period given the limited number of ICU and ICU beds in the country[28]. Furthermore, it could have been interesting to follow up those patients after their discharge from ICU to also report the mortality at 28 and 90 days but many of them were discharged before those dates and could not be reached anymore.