Introduction
Most of the obstetric morbidities and mortalities occur in developing and under-privileged countries. These occur mostly during the peri-partum period, that is, around the time of delivery and in the immediate post-partum period. Thus, the peri-partum period becomes the most vital period for the pregnant woman.[1] There is a vast change in the physiology of the body during the peri-partum time, which makes it a crucial period to diagnose an emergency and so that enough time is there to enact upon it.
To further reduce the maternal mortality ratio, the focus has been shifted to the new indicators such as obstetric morbidity and severe maternal morbidity to mortality ratio which have been advised in obstetrics. Failures in the health delivery system will be understood well by these indicators.[2,3] Most of the adverse pregnancy outcomes have the following set of deteriorating events starting from healthy and normal pregnancy to morbidity to severe morbidity converting to near miss followed by mortality. In the obstetric population, it can be difficult to recognize the early signs and symptoms of a life-threatening disease because normally, pregnancy generates significant and foreseeable changes in maternal vital signs and symptoms;[4] therefore, the track and trigger system of these parameters on a chart will be useful in recognizing patients with imminent clinical deterioration, thus preventing the obstetric morbidity and mortality.[5,6]
The Confidential Enquiry into Maternal and Child Health (CEMACH) report, UK, recommended the use of the MEOWS chart (Modified Early Obstetric Warning System chart), which was designed to detect the patients suffering from illnesses that may lead to severe obstetric morbidity and mortality.[5,7] This chart includes periodic measurements of basic physiological parameters to trace and track the patient’s clinical condition over a period of time[8] in order to notify the risk awareness and evaluate the patient at an urgent basis, with timely diagnosis and treatment.
Very few studies have evaluated the MEOWS chart as a tool to predict obstetric morbidity.[9-12] Also, the results of these studies do not provide strong evidence to support the clinical usefulness of the MEOWS chart parameters to identify patients who are at high risk for severe morbidity or mortality.
With the present study, we aim to evaluate the predictive value of the MEOWS chart as a screening tool to identify patients likely to have morbidity in an obstetric care unit. The objectives of this study were to study and compare between obstetric morbidity in patients with normal (non-triggered) and abnormal (triggered) MEOWS chart findings and to study the sensitivity, specificity, predictive values, and accuracy of the MEOWS chart to predict obstetric morbidity.
It is of utmost importance for the primary care clinicians to be aware of the MEOWS chart as they are the primary pillar of the health care system which can strengthen the maternal care and help in providing better health services in remote and rural areas.
Materials and Methodology
This study was an observational study which was conducted in the Department of Obstetrics and Gynaecology of Acharya Vinoba Bhave Rural Hospital (AVBRH), Datta Meghe Institute of Medical Science (DMIMS) Sawangi (M), Wardha, over a span of 2 years from September 2017 till August 2019.
Ethical approval was obtained from the institutional ethical committee with the corresponding approval number as DMIMS (DU)/IEC/2017-18/6663. This study has been granted the grant from ICMR (Indian Council of Medical Research).
A total of 1000 ante-natal women beyond 28 weeks of gestation who were in labour were recruited as study subjects.
The sample size was obtained by using the following formula:
where n is the sample size
Z1(1-α/2) is the level of significance at 5%, that is, 95% confidence interval = 1.96%.
– pre-determined sensitivity from a pre-determined study
d2 – precision of estimate
Prevalence – morbidity prevalence
Hence, the minimum required sample size was 964, and a total of 1000 patients were enrolled into the study.
Cases in whom pregnancy continued and did not terminate in next 24 hours and patients who did not give consent were excluded from the study. The MEOWS chart recommended in the CEMACH report was used for this study.[5,7,13] The following parameters were recorded on the MEOWS chart of each patient as per the standard protocol, and the standard values of parameters as defined in the MEOWS chart were used to define the type of trigger zone as shown in Table 1. The parameters such as heart rate, respiratory rate, blood pressure, general condition, neural response, temperature, oxygen saturation, and proteinuria were recorded on the MEOWS chart at the time of admission and subsequently monitored and recorded. The monitoring was performed every 4 hourly till 24 hours post delivery. From day 2 of the delivery, charting was performed once daily till the time patient was discharged. There are two other parameters: Liquor was clinically observed at the time of rupture of membranes, either spontaneously or artificially ruptured. Lochia was clinically observed once the patient had delivered. On day 1, it was observed 4 hourly and followed by once daily till the patient got discharged.
In the MEOWS chart, trigger was defined as either one red zone (any one parameter that was markedly abnormal, with values in the red zone as shown in Table 1) or two yellow zones (when simultaneously any two parameters were moderately de-ranged with values in yellow zones as shown in Table 1). While monitoring, the patients were divided into two groups – triggered and non-triggered groups – according to the parameters as explained above. These triggered and non-triggered patients were further classified into category 1 (patients who did not have any obstetric morbidity during hospital stay) and category 2 (patients who had any obstetric morbidity during hospital stay) on the basis of maternal outcome and whether they were diagnosed with any obstetric morbidity during hospital stay. Table 2 shows the types and diagnostic criteria of disease entities leading to obstetric morbidity.
Statistical analysis
The data obtained were evaluated by using the descriptive and inferential statistics. The analysis was performed by using Chi square test and test statistics, that is, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and odds ratio. The pieces of software used in the analysis were SPSS 24.0 version and Pad Prism 7.0 version, and P < 0.05 was considered as the level of significance.
Observations and Results
The MEOWS chart of 1000 patients was analysed. As shown in Table 3, out of 1000 patients, 24.8% patients were categorised into the triggered group and 75.2% patients were categorised into the non-triggered group after admission.
Table 4 shows the comparison of socio-demographic characteristics amongst triggered and non-triggered groups. In both the triggered and non-triggered groups, the majority of the patients belonged to the same age group, that is, 20–30 years of age. Out of the total patients in the triggered group, 78.6% (195) patients were from the rural area, and out of the total patients in the non-triggered group, 71.8% (540) patients were from the rural area. The maximum number of patients in the triggered group belonged to the lower socio-economic class, that is 64.1% (159), whereas in the non-triggered group, the maximum number of patients were from the upper lower socio-economic class, that is, 48.3% (363). With respect to the ante-natal care, there were 60.10% (149) patients of the total triggered group and 89.50% (673) patients of the total non-triggered group who received ante-natal care.
In the total triggered group and non-triggered group, 33.5% (83) and 19.7% (148) patients, respectively, were in the gestational age from 28 to 37 weeks. Of the total triggered patients, 66.5% (165) patients were in the gestational age, and of the total non-triggered patients, 80.3% (604) patients were in the gestational age of more than 37 weeks.
Table 5 shows the comparison of the mode of delivery and obstetric intervention received amongst the triggered and non-triggered groups. 51.2% (127) patients of the total triggered group and 69.1% (520) patients of the total non-triggered group had normal vaginal delivery. It was also found that 46.8% (116) of the total triggered group and 30.5% (229) patients of the total non-triggered group underwent caesarean section.
Table 6 shows the correlation of the individual MEOWS chart parameters with the trigger zones in the triggered group.
Table 7 shows the comparison of neo-natal outcome at birth amongst the triggered and non-triggered groups. In the triggered group, 65.3% (162) patients had healthy neonates at birth, and in the non-triggered group, 82.40% (620) had healthy neonates at birth. Newborn intensive care unit (NICU) admission was seen in 29.8% (74) of neonates born to patients in the triggered group and 15% (113) of neonates born to patients in the non-triggered group at the time of birth. In the triggered group, intra-uterine death of the foetus was seen in 4.8% (12) patients, whereas in the non-triggered group, it was seen in 2.5% (19) patients.
Table 8 shows the distribution of patients according to the category of obstetric morbidity during the hospital stay amongst the triggered and non-triggered groups. Out of the total triggered group, 52.42% (130) patients were under category 1 (patients who did not have any obstetric morbidity during hospital stay), and out of the total non-triggered group, 97.3% (732) patients were under category 1. In the total triggered group, 47.58% (118) patients were under category 2 (patients who had obstetric morbidity during hospital stay) and 2.7% (20) patients of the total non-triggered group were under category 2. Out of the patients of the triggered group who were under category 2, that is, 47.68% (118), two of them had obstetric mortality. The cause of death was certified as eclampsia and acute respiratory distress syndrome, respectively.
Table 9 shows the performance of the MEOWS chart as a screening tool for predicting obstetric morbidity by its sensitivity, specificity, and predictive values. The MEOWS chart was found to be 85.51% sensitive and 84.92% specific with a positive predictive value of 47.58% and a negative predictive value of 97.34%. The accuracy of the MEOWS chart was 85%. The odds of having category 2 in the triggered group was 33.22 times more as compared to the non-triggered group.
Discussion
The reduction in the incidence of critical events is challenging for all the obstetric care providers. It has been clinically established that documented deterioration of physiological parameters precedes the catastrophic deterioration of patients in the hospital.[23,24] The MEOWS chart is specifically designed for obstetric patients for early detection of acute illness and timely management.[5]
As seen in Table 3, out of 1000 patients, 24.8% (248) patients had abnormal findings on the MEOWS chart who were categorized into the triggered group and 75.2% (752) patients had normal findings on the MEOWS chart and were categorized into the non-triggered group. It was similar to the study performed by Singh A et al.[11] (2016) which was carried out on 1065 population.
As seen in Table 4, there was no statistically significant difference in distribution of patients according to the age in triggered and non-triggered groups. The result of the present study was not similar to that of the study performed by Singh A et al.[11] (2016), where patients in extremes of age group (<20 and >30 years of age) were more in the triggered group than in the non-triggered group.
In the present study, the distribution of patients from the rural area was significantly more in the triggered group (78.6%) in comparison to the non-triggered group (71.8%). It was similar to the study performed by Singh A et al.[11] (2016). A study performed by Baskett et al.[2] (2009) did not use the MEOWS chart for correlation with residence, but their study was based on determination of the factors leading to maternal critical care. They reported that delay in seeking care and delay in transfer for medical care were one of the main factors leading to morbidity.
In the present study, amongst all socio-economic classes, distribution of patients with a lower socio-economic class was significantly more in the triggered group (64.1%) than in the non-triggered group (39.6%), whereas in the non-triggered group, the maximum number of patients were under an upper lower socio-economic class, that is, 48.3%. A study performed by Singh A et al.[11] (2016) had similar results.
In the present study, the distribution of patients who did not seek for ante-natal care was significantly more in the triggered group (39.9%) than in the non-triggered group (10.50%). In a study performed by Singh A et al.[11] (2016), the results were similar as the significant factor which was responsible for patients to trigger was the absence of ante-natal care. There are a few studies which correlate ante-natal care directly with obstetric morbidity. Studies performed by Karnad et al.[25] and Osinaike et al.[26] suggested poor quality of ante-natal care to be associated with poor maternal outcome.
In the present study, the distribution of patients who were in the gestational age from 28 to 37 weeks was significantly more in the triggered group (33.5%) than in the non-triggered group (19.7%). It was similar to the study performed by Singh A et al.[11] (2016).
In the present study, it signified that the nulliparous patients were significantly more in number in the triggered group (58.1%) than in the non-triggered group (43%). Nulliparous patients were at a higher risk of going into the trigger zone. A study performed by Singh A et al.[11] (2016) had similar findings.
In the present study, patients who had obstetric risk factors on admission had a higher risk of going into the trigger zone in comparison to the patients who did not have any obstetric condition on admission. 33.47% patients who had obstetric risk factors were in the triggered group as compared to the 10.11% patients in the non-triggered group. In a study conducted by Singh A et al.[11] (2016), in the triggered group, almost 50% had obstetric risk factors on admission. The results were similar to those of the present study.
In the present study, distribution of patients who had medical disorders on admission was significantly more in the triggered group (18.15%) than in the non-triggered group (3.32%). The result was similar to that of the study conducted by Singh A et al.[11] (2016).
It was concluded that the significant factors contributing to trigger included rural background, a lower socio-economic class, patients who did not seek for ante-natal care, nulliparous patients, and patients who had obstetric risk factors and medical disorders at the time of admission.
It was seen that in the present study that the proportion of interventions, that is, caesarean sections, instrumental deliveries, and obstetric hysterectomies, were significantly higher in patients who were in the triggered group (46.8%) when compared to those in the non-triggered group (30.5%) on the MEOWS chart. Similar findings were reported in the study performed by Singh A et al.[11] (2016) and Singh S et al.[12] (2012).
The result of the present study showed that the most common parameter to get de-ranged and put the patient into the trigger zone was the diastolic blood pressure (51.61%), followed by heart rate (50.4%), proteinuria (43.5%), systolic blood pressure (35.08%), respiratory rate (19.3%), colour of the liquor (17.7%), temperature (8.4%), oxygen saturation (6.8%), general condition (3.6%), neural response (3.2%), and lochia (1.2%). In a study performed by Singh A et al.[11] (2016) and Singh S et al.[12] (2012), the findings were similar to those of the present study. A study by Swanton et al.[27] (2009) based on assessing the uptake of early warning systems in obstetrics in UK also considered the diastolic blood pressure as the most crucial parameter.
In the present study, patients who were in the triggered group (28.8%) had significantly a greater number of NICU admissions and intra-uterine deaths in comparison to the non-triggered group (15%). The results were similar to those of the study performed by Singh A et al.[11] (2016) and Singh S et al.[12] (2012).
In the present study, out of the total triggered group, 47.58% patients had obstetric morbidity and 2.7%patients of the total non-triggered group had obstetric morbidity. Patients in the triggered group had higher chances of developing more morbidity in comparison to those in the non-triggered group. The results were similar to those of the study performed by Singh A et al.[11] (2016) and Singh S et al.[12] (2012).
In the present study, the sensitivity of the MEOWS chart was 85.51%, the specificity was 84.92%, the positive predictive value was 47.58%, and the negative predictive value was 97.34%. The accuracy of the MEOWS chart was 85%. The odds of a patient in the triggered group of having obstetric morbidity (category 2) was 33.22 times more as compared to patients in the non-triggered group.
A study done by Ryan et al.[10] (2017) also had similar results with a high sensitivity of the MEOWS chart. Similar results were seen with the study conducted by Singh A et al.[11] (2016) and Singh S et al.[12] (2012).
Although there has been research in rural areas in the recent times regarding the use of the MEOWS chart,[28,29] it remains an under-utilized tool with essential benefits for health care providers, hence making it an important aspect for study specially in the rural India.
As primary care clinicians are the first line of defence posted at the grass route level, they are often the first in contact for providing ante-natal care. Therefore, an insight about the benefits and potential use of the MEOWS chart is beneficial for them in order to provide better maternal care and to help reduce maternal mortality.
Take home message
The MEOWS chart is a potentially beneficial tool which is cost-effective and simple yet provides an insight into the maternal condition. It can be utilized in peripheral centres to help the treating clinicians timely refer the high-risk patients to well-equipped tertiary care hospitals.
Strengths: This study not only gives details into feto-maternal outcomes in triggered and non-triggered categories of the MEOWS chart but also compares and gives in-depth knowledge of comparison and correlation of socio-demographic parameters of triggered and non-triggered groups. Each parameter of the MEOWS chart was studied and correlated in detail with feto-maternal outcomes.
Limitations
The limitations of this study could be that as a screening tool, the studies performed with a larger sample size or multi-centric trials were needed and the cost involved in the monitoring system was not analysed.
Conclusion
The present study suggests that the MEOWS chart helps in screening and triaging the patients into triggered and non-triggered groups. By doing this, the triggered group patients can immediately be attended or transferred to tertiary health care centres for further evaluation by obstetric and multi-disciplinary experts.
With a good negative predictive value, the MEOWS chart re-assures that the probability of obstetric morbidity is very less and monitoring can be continued till patients fall in the triggered zone. Triggered category patients need further evaluation to rule out any related risk. Thus, the MEOWS chart should be used as a screening tool for prediction of obstetric morbidity.
Hence, the MEOWS chart should be used as a simple screening tool at all levels of health care facilities by medical and para-medical health care workers. The MEOWS chart should be included in standard screening and management protocols of obstetric patients in all health care facilities, especially at peripheral health care centres, while making guidelines an regarding peri-partum obstetric care.
Key points
When the MEOWS chart was used as a predictor of peri-partum obstetric morbidity in the current study, a significant difference was found between obstetric morbidities in normal (non-triggered) and abnormal (triggered) MEOWS chart findings.
- The occurrence of obstetric morbidity was more in the triggered group than in the non-triggered group.
- The sensitivity of the MEOWS chart was high (85.51%), the specificity was 84.92%, the positive predictive value was low, that is, 47.58%, and the negative predictive value was very high, that is, 97.34%.
- The accuracy of the MEOWS chart was 85%.
- The odds of a patient in the triggered group of having obstetric morbidity (category 2) was 33.22 times more as compared to patients in the non-triggered group.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Indian Council of Medical Research (ICMR) has funded this post graduate thesis research project.
Conflicts of interest
There are no conflicts of interest.
Acknowledgments
The financial support from Indian Council of Medical Research (ICMR, India) in terms of providing thesis funding to the first author is acknowledged. Authors acknowledge the support of all the medical and para-medical staff involved in the management of the patients. Authors would also like to thank the statistician from the department of community medicine.
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Keywords:
MEOWS chart; obstetric morbidity; triggered and non-triggered groups