Decision-to-delivery interval of emergency cesarean section in Uganda: a retrospective cohort study

Abstract

Background

In many low and medium human development index (LM-HDI) countries, the rate of maternal and neonatal morbidity and mortality is high^1,2. Preventing adverse perinatal outcomes is often critically time-dependent, however, demand can exceed capacity for prompt intervention in these settings³. Despite global initiatives for improvement, there remains considerable complexity in increasing obstetrics resource availability in LM-HDI settings^4,5. We considered whether improving patterns of service provision might provide an alternative strategy to reduce adverse perinatal outcomes in LM-HDI settings. Studies have shown that risk of adverse perinatal outcomes is associated with service provision factors such as obstetric staff working patterns^6,7. This has only, however, been studied extensively in well-resourced countries and so there is a need to investigate the modifiable patterns of service provision in low and medium human development index obstetric settings.

One aspect of service provision with the potential to influence perinatal outcome is the decision-to-delivery interval of emergency cesarean section⁸. National guidelines in the USA and UK suggest a target of 30 minutes after the decision to deliver by emergency cesarean section is established^9,10. Such guidelines, however, are not well-evidenced¹¹ and may not be feasible even in well-resourced obstetric settings¹². Furthermore, whilst globally it is generally accepted that the decision-to-delivery interval should be kept to the minimum time achievable¹³, there are currently no context-appropriate targets intended to minimise adverse outcomes in low and medium human development index countries.

Mulago National Referral Hospital is a government-run facility with over 2700 beds¹⁴ in Kampala, Uganda. The birth rate has been reported to exceed 39,000 per annum¹⁵ and a substantial proportion of the deliveries are by emergency cesarean section¹⁶. This high volume combined with the socio-economic challenges¹⁵, poor baseline health status^17,18, and lack of antenatal care¹⁹ experienced by mothers presenting to the hospital, has resulted in high rates of maternal and neonatal morbidity and mortality^20,21. Studies from this setting have shown that obstetric service provision is not uniform during a 24-hour shift cycle²². We therefore aimed to investigate whether the modifiable factor of decision-to-delivery interval is associated with adverse perinatal outcomes.

Methods

Mothers who delivered a singleton pregnancy, at viable gestational age (≥24 completed weeks), by emergency cesarean section during the period of June 2017 were included in the study. We analysed their full medical records for the entire delivery episode from admission to discharge. Data was collected contemporaneously in fully anonymised form and the data used for analysis is summarised in Table 1. Mothers who died following emergency cesarean section were excluded from the study (n ≤ 3), due to possession of their records by other investigatory authorities. Cases of intrauterine death in which the fetus was thought to have demised prior to presentation at the hospital were also excluded, as this outcome could not have been affected by decision-to-delivery interval.

Using binary logistic regression, we compared the characteristics of deliveries occurring during the day to those during the night and those during weekends to weekdays. Using univariate and multivariate Cox proportional hazard models, we assessed the relationship between both maternal risk factors and indications for each emergency cesarean section and the decision-to-delivery interval. These models accounted for time-at-risk of adverse outcomes. Using binomial regression models, we assessed the relationship between adverse perinatal outcomes and the decision-to-delivery interval. Using generalised additive models (in which all events were considered equivalent), we assessed the relationship between (i) time of decision, (ii) time of delivery, and (iii) decision-to-delivery interval, and adverse outcomes. The generalised additive models incorporated a nonlinear term for event time on the risk of each adverse outcome and this was estimated using cubic splines. We therefore avoided making any assumptions about the nature of the relationship between the time of an event and the risk of an adverse outcome.

All multivariate models were adjusted for covariates selected on the basis of clinical relevance and using Akaike Information Criterion (AIC) to optimise model fit. Statistical significance of the nonlinear effect of time of delivery was assessed using a likelihood-ratio test. To summarise our findings, Kaplan-Meier curves were constructed to represent the decision-to-delivery interval of the entire population and of relevant sub-cohorts. Our findings were considered statistically significant at an alpha level of 0.05. Power calculations were performed by Monte Carlo simulation.All analyses were conducted using the R statistical software package version 3.5.1.

Results

During the study period of June 2017, 412 mothers underwent an emergency cesarean section at Mulago Hospital. Of these, 396 delivered a singleton pregnancy at viable gestational age (≥24 completed weeks) and 349 of these records had complete information regarding the decision-to-delivery interval. 5 observations were removed from the time-dependent analysis on the basis that their status as an emergency was reversed prior to delivery. In these 5 cases, the neonate was delivered more than 4 days after the initial decision time. A delivery by emergency cesarean section occurred on average every 104 minutes (median 13.7 per day) throughout the entire study period. The median decision-to-delivery interval was 5.5 hours, with interquartile range 3.3–10.7 and range 0.5–92.3 hours (Figure 1).. 2% (7/344) of neonates were delivered within 1 hour of decision-making.

The average number of decisions made per hour varied significantly throughout the day (minimum: 0.03 decisions per hour 05:00–06:00, maximum: 1.1 decisions per hour between 12:00–13:00, p<0.001, Figure 2A).. The average number of deliveries also varied significantly (minimum 0.03 deliveries per hour 08:00–10:00, maximum 0.87 deliveries per hour between 19:00–20:00, p<0.001, Figure 2B).. The average length of decision-to-delivery interval also varied significantly throughout the day (minimum 3.3hrs 16:00–17:00, maximum 9.4hrs 01:00–02:00, p<0.01, Figure 3).. Specifically, mothers who delivered during the night (between 0:00 and 08:00) waited on average 2 hours longer for their emergency cesarean section compared to the rest of the cohort. There was a 5.6-hour difference in average length of interval between those delivering during the longest wait times (00:00 to 08.00) and shortest wait times (12:00 to 20.00) (Figure 3). There was no significant difference in the interval on any particular day of the week or at the weekend.

None of the risk factors known prior to birth, including preeclampsia, were significantly associated with shorter decision-to-delivery intervals using univariate analysis (Table 2).. Longer interval was associated only with preeclampsia (p<0.05) and premature rupture of the membranes / oligohydramnios (p<0.01) on univariate analysis. After adjustment for relevant covariates, both preeclampsia (HR 0.61; CI 0.38–0.97, p<0.05) and premature rupture of the membranes / oligohydramnios (HR 0.60; CI 0.37–0.96, p<0.05) retained significance.

We examined whether individual indications for emergency cesarean section were associated with the decision-to-delivery interval (Table 3) with univariate analysis. Fetal distress was associated with a shorter interval (p<0.05, Figure 4A) whilst preeclampsia was associated with a longer interval (p<0.05, Figure 4B).. After adjustment for relevant covariates in multivariate models, fetal distress (HR 1.63, CI 1.23–2.15; p<0.001), previous cesarean section (HR 1.66, CI 1.24–2.21; p<0.01), malpresentation (HR 1.78, CI 1.17–2.69; p<0.01), antepartum haemorrhage (HR 1.56, CI 1.00–2.43, P<0.05) and impending uterine rupture (HR 1.85, CI 1.24–2.78; p<0.05) were all significantly associated with shorter interval.

None of the maternal or fetal adverse outcomes measured showed a linear relationship with the decision-to-delivery interval (Table 4).. There was, however, a significant association between the timing of a decision or delivery and adverse perinatal outcomes. This included the outcomes of both perinatal (Figure 5A-B; p<0.05) and neonatal (Figure 5C-D; p<0.05) death. The risk of both perinatal death and neonatal death varied by >50% between the highest and lowest risk periods (Figure 5A-D). The lowest risk decision period was in the morning between 08:00 and noon (p<0.01), whereas the lowest risk delivery period was in the afternoon between noon and 20:00 (p<0.05). The highest risk decisions and deliveries both occurred between 22:00 and 04:00. The risk of both perinatal death (p<0.05) and neonatal death (p<0.05) showed significantly stronger association with the decision time than delivery time.

Discussion

In this obstetric setting, the average decision-to-delivery interval was 5.5 hours, with only 2% of babies delivered within an hour of decision-making. Women with certain indications were delivered more quickly once the decision for emergency Cesarean section was made. Fetal distress, malpresentation, antepartum haemorrhage, and previous Cesarean section (both with and without concern regarding impending uterine rupture) were prioritised over other indications. Whilst there was no association between the length of the decision-to-delivery interval and adverse perinatal outcomes, both the interval and risk of perinatal mortality showed significant diurnal variation. The time of decision-making was better correlated with the risk of adverse perinatal outcome that the time of delivery.

Accounting for the time taken to clean and restock the theatres between cases, we have observed a remarkable continuous rate of emergency surgery in this LM-HDI setting. The average decision-to-delivery interval was significantly longer than targets adopted in well-resourced obstetric settings¹⁰ as well as the average interval reported in other low resource contexts globally^13,23. However inconsistent categorisation of cases as ’emergencies’²⁴ and different obstetric populations complicate international comparisons.

There was significant diurnal variation in decision-to-delivery interval and risk of perinatal death, which may reflect the fluctuating availability of senior clinicians during a 24-hour period. As in many obstetric settings globally, the most experienced obstetricians at Mulago Hospital are available for ward rounds and decision-making during the day, however, not overnight. In line with this, the times of shortest interval occurred during normal working hours (12:00–20:00). The period with fewest decisions for emergency cesarean section were made (22:00–02:00) corresponded to the times of highest perinatal mortality, whilst the period when the rate of decision-making was increasing most rapidly (09:00–13:00) was associated with the lowest risk.

Reducing the average decision-to-delivery interval by 5 hours to be in keeping with the 30-minute targets set elsewhere^9,10 is unlikely to be feasible in our already under-resourced study setting. Moreover, existing guidelines are not well-evidenced¹¹ with little direct evidence of benefit even in well-resourced obstetric setting. We did not find evidence of a direct relationship between longer interval and adverse perinatal outcomes, therefore it is unlikely to be of benefit to focus scarce resources towards dramatically reducing absolute time to delivery. Rather, our data support the idea that clear, timely, and well-supported clinical decision-making may have more influence on perinatal outcomes. Normal working hours also correspond to the highest availability of non-medical services such as technicians, porters and laboratory clinicians. This may therefore also be an independent aspect for the hospital to consider when developing service design to improve perinatal outcomes. Whilst continuously performing emergency cesarean section has significant demands on resource utilisation and may be a non-modifiable limiting factor, it is rational to believe that clinical delays to treatment are modifiable even within resource constraints. A previous study, for example, demonstrated that the average time to complete obstetric triage reduced from 192 to 38 minutes when a midwife was allocated to this specific task²².

The high volume of deliveries and baseline incidence of adverse events at Mulago Hospital meant that, although temporally short, our study was sufficiently powered for the crucial outcomes of perinatal and neonatal mortality. Furthermore, since such a high volume of deliveries can complicate detailed medical record-keeping, our strategy of bespoke contemporaneous data collection by a dedicated researcher present in the institution increases our confidence in the accuracy of the timings presented. The study is also underpinned by a powerful and sophisticated statistical modelling strategy, in which non-parametric dynamic additive models were used to determine the risks of adverse perinatal outcomes relative to baseline risk, without making assumptions about the risk / time relationship.

A limitation of the current study is that our results relate only to delay in delivery after the decision for emergency Cesarean is made. Previous analysis from the study setting has found that the average triage time is longer for mothers who present overnight²². Delays besides the decision-to-delivery interval may therefore vary in a predictable diurnal cycle. We were also unable to explicitly model the influence of the experience of available obstetricians throughout the day. Whilst the periods during which the least experienced obstetricians are alone in the hospital correlate with the longest decision-to-delivery intervals and highest risk of perinatal mortality, we could not demonstrate a causal association here.

In this context, where many mothers present to hospital already in obstructed labour²⁵, a direction of future study would be to investigate delays in the total time to delivery besides the decision-to-delivery interval. Such delays may also vary diurnally, for example, due to traffic patterns in the surrounding urban area. Clinician experience can be associated with perinatal outcomes both indirectly, through increased decision-to-delivery interval and directly, through for example operative skill. Further analysis of the obstetricians available throughout the day is required to determine whether modifying the periods during which the those least experienced are alone in the hospital would result in reduced risk of perinatal mortality.

Conclusion

In this busy sub-Saharan Africa maternity setting, the average decision-to-delivery interval of emergency cesarean section is longer than target times adopted in well-resourced obstetric settings. There is no direct relationship between the interval and adverse perinatal outcomes, however, there is significant diurnal variation in the risk of perinatal and neonatal mortality. The rate of adverse perinatal outcomes is better correlated with time of decision-making than with length of decision-to-delivery interval or time of delivery. This suggests that focus on supporting safe clinical decision-making during high-risk periods may be a useful and feasible strategy for reducing neonatal morbidity and mortality.

Declarations

Ethics approval and consent to participate: Ethical approval for the study was granted by the Mulago Hospital Research and Ethics Committee (protocol number 1605). A waiver for the requirement of informed consent from the mothers whose records were analysed was granted by the Chair of the Committee on the grounds of being a minimal risk study.

Availability of data and materials: All data relevant to the study are included in the article.

Competing interests: The authors have no conflicts of interest to declare.

Funding: This work was supported by NURTURE fellowship to AN, grant number D43TW010132 and the DELTAS Africa Initiative (grant# 107743/Z/15/Z). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)‘s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (grant #107743/Z/15/Z) and the UK government. The views expressed in this publication are those of the author(s) and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government. We are also grateful for the financial contribution of the Addenbrooke’s Abroad Grant Scheme, provided by Addenbrooke’s Hospital Charitable Trust.

Author contributions: The project was conceived by NH and CA, with guidance from AN and AM. The research protocol for permission to use medical records was written by NH and IN and ethical approval was obtained by IN and MS from the Research and Ethics Committee of Mulago Hospital. Data was collected by NH, facilitated and supervised by MS at Mulago Hospital. Data analysis was conducted by CA and the manuscript was written by NH and CA. Intellectual input and approval of the manuscript was provided by IN, AN, MS, AM and CP.

References

1.WHO | International Classification of Diseases, 11th Revision (ICD–11). WHO (2019).

2.Alkema, L. et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. Lancet 387, 462–474 (2016).

3.Wall, S. N. et al. Reducing intrapartum-related neonatal deaths in low- and middle-income countries-what works? Semin. Perinatol. 34, 395–407 (2010).

4.Akseer, N. et al. Ending preventable newborn deaths in a generation. Int. J. Gynaecol. Obstet. 131 Suppl 1, S43–8 (2015).

5.Koblinsky, M. et al. Quality maternity care for every woman, everywhere: a call to action. Lancet (London, England) 388, 2307–2320 (2016).

6.Aiken, C. E., Aiken, A. R., Scott, J. G. & Brockelsby, J. C. The influence of hours worked prior to delivery on maternal and neonatal outcomes: a retrospective cohort study. Am. J. Obstet. Gynecol. 215, 634.e1–634.e7 (2016).

7.Reif, P. et al. Do time of birth, unit volume, and staff seniority affect neonatal outcome in deliveries at ≥34+0 weeks of gestation? BJOG 125, 884–891 (2018).

8.Tolcher, M. C., Johnson, R. L., El-Nashar, S. A. & West, C. P. Decision-to-incision time and neonatal outcomes: a systematic review and meta-analysis. Obstet. Gynecol. 123, 536–48 (2014).

9.CLASSIFICATION OF URGENCY OF CAESAREAN SECTION-A CONTINUUM OF RISK Purpose. (2010).

10.Kilpatrick, S. J., American Academy of Pediatrics & American College of Obstetricians and Gynecologists. Guidelines for perinatal care. (American Academy of Pediatrics, 2017).

11.Boehm, F. H. Decision to incision: time to reconsider. Am. J. Obstet. Gynecol. 206, 97–8 (2012).

12.MacKenzie, I. Z. & Cooke, I. What is a reasonable time from decision-to-delivery by caesarean section? Evidence from 415 deliveries. BJOG 109, 498–504 (2002).

13.Singh, R., Deo, S. & Pradeep, Y. The decision-to-delivery interval in emergency Caesarean sections and its correlation with perinatal outcome: evidence from 204 deliveries in a developing country. Trop. Doct. 42, 67–69 (2012).

14.Nolens, B. et al. Birthing experience and quality of life after vacuum delivery and second-stage caesarean section: a prospective cohort study in Uganda. Trop. Med. Int. Heal. 23, 914–922 (2018).

15.Ssempiira, J. et al. Geostatistical modelling of malaria indicator survey data to assess the effects of interventions on the geographical distribution of malaria prevalence in children less than 5 years in Uganda. PLoS One 12, e0174948 (2017).

16.Nakimuli, A. et al. Incidence and determinants of neonatal morbidity after elective caesarean section at the national referral hospital in Kampala, Uganda. BMC Res. Notes 8, 624 (2015).

17.Beaton, A. et al. Impact of heart disease on maternal, fetal and neonatal outcomes in a low-resource setting. Heart 105, 755–760 (2019).

18.Wanyama, R., Obai, G., Odongo, P., Kagawa, M. N. & Baingana, R. K. Are women in Uganda gaining adequate gestational weight? A prospective study in low income urban Kampala. Reprod. Health 15, 160 (2018).

19.Kisuule, I. et al. Timing and reasons for coming late for the first antenatal care visit by pregnant women at Mulago hospital, Kampala Uganda. BMC Pregnancy Childbirth 13, 121 (2013).

20.Roberts, D. A. et al. Benchmarking health system performance across regions in Uganda: a systematic analysis of levels and trends in key maternal and child health interventions, 1990–2011. BMC Med. 13, 285 (2015).

21.Abdallah, Y. et al. Is facility based neonatal care in low resource setting keeping pace? A glance at Uganda’s National Referral Hospital. Afr. Health Sci. 16, 347 (2016).

22.Forshaw, J. et al. Exploring the third delay: an audit evaluating obstetric triage at Mulago National Referral Hospital. BMC Pregnancy Childbirth 16, 300 (2016).

23.Hirani, B. A., Mchome, B. L., Mazuguni, N. S. & Mahande, M. J. The decision delivery interval in emergency caesarean section and its associated maternal and fetal outcomes at a referral hospital in northern Tanzania: a cross-sectional study. BMC Pregnancy Childbirth 17, 411 (2017).

24.Schauberger, C. W. & Chauhan, S. P. Emergency cesarean section and the 30-minute rule: definitions. Am. J. Perinatol. 26, 221–6 (2009).

25.Kayiga, H., Ajeani, J., Kiondo, P. & Kaye, D. K. Improving the quality of obstetric care for women with obstructed labour in the national referral hospital in Uganda: lessons learnt from criteria based audit. BMC Pregnancy Childbirth 16, 152 (2016).

Tables

Table 1: Summary of data extracted from contemporaneous medical notes.

Table 2: Factors known prior to delivery.

Numeric characteristics are shown as mean ± standard deviation. Categorical characteristics are shown as n (%). Impact on decision-to-delivery interval is represented by the hazard ratio and confidence intervals from a Cox proportional hazards model conditioned only on the characteristic of interest. Significance is the p value derived from the same model. *p<0.05, **p<0.01.

Table 3: Indications for emergency cesarean section.

The number of mothers with each indication for emergency cesarean section along with the percentage of the analytic cohort is shown. More than one indication was present in many cases. The median decision-to-delivery interval and IQR range are shown for each indication. The impact of each indication on decision-to-delivery interval is represented by the p-values from a Cox proportional hazards model conditioned only on the indication of interest. Significance is the p value derived from the same model. *p<0.05.

Table 4: Outcomes of delivery.

The number of mothers who experienced each adverse outcome is shown along with the percentage. For outcomes that can apply to all deliveries (perinatal death, stillbirth, adverse maternal outcomes) the total was n=344. For outcomes that apply only to live born infants, the total was n=330. More than one adverse outcome was present in some cases. The influence of decision-to-delivery interval is represented by p-values derived from logistic regression models, in which the risk of outcome is conditioned upon the length of the interval in hours. The influence of decision time and delivery time are the p-values derived from generalised additive models with a non-parametric effect for the time of day at decision and delivery respectively. All models were adjusted for the sex and gestational age-specific centile of the neonate’s birth weight. *p<0.05, **p<0.01.