Meows by Jorge Delgado Flores

European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17

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European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb

Evaluation of maternal early obstetric warning system (MEOWS chart) as a predictor of obstetric morbidity: a prospective observational study Anju Singh* , Kiran Guleria, Neelam B. Vaid, Sandhya Jain Department of Obstetric & Gynaecology, University College of Medical Sciences & Guru Teg Bahadur Hospital, Delhi, India

A R T I C L E I N F O

A B S T R A C T

Article history: Received 15 March 2016 Received in revised form 9 September 2016 Accepted 13 September 2016

Objectives: Maternal Early Obstetric Warning System (MEOWS) chart adopted from CEMACH 2003– 2005 report is based on the principle that abnormalities in physiological parameters precede critical illness. The ‘track and trigger’ of physiological parameters on this chart can aid in recognition of maternal morbidity at an early stage, ultimately halting the cascade of severe maternal morbidity and mortality. The objectives of our study were to evaluate MEOWS chart as a bedside screening tool for predicting obstetric morbidity and to correlate each physiological parameter individually with obstetric morbidity. Study design: It was a prospective observational study conducted in labour wards of Guru Teg Bahadur Hospital, Delhi, India from October 2012 to April 2014. Physiological parameters of 1065 study subjects (including pregnant women in labour >28 weeks of gestation and postpartum women up to 6 weeks after delivery) were recorded on MEOWS chart. A trigger was defined as a single markedly abnormal observation (red trigger) or the combination of two simultaneously mildly abnormal observation (two yellow triggers). Based on outcome at time of discharge, Category 1 (normal and recovered without morbidity) and Category 2 (recovered with morbidity or mortality) were defined. Chi-square and Fischer’s exact test were used for comparison between two groups. Performance of MEOWS chart was evaluated using Exact’s method. Relative risk of morbidity (odd’s ratio) and 95% confidence interval was calculated for individual parameter. p < 0.05 was considered as significant. Results: Two-hundred and eighty-four (26.6%) women triggered to abnormal zones on these charts. Onehundred and seventy-seven (16.61%) fulfilled the criteria for obstetric morbidity. MEOWS chart was 86.4% sensitive, 85.2% specific with a positive and negative predictive value of 53.8% and 96.9% respectively for prediction of obstetric morbidity. Individual parameters of MEOWS chart also had a significant correlation (p < 0.05) with obstetric morbidity. Conclusions: MEOWS chart emerged as a useful bedside screening tool for prediction of obstetric morbidity and should be used routinely in every obstetric unit. Strict monitoring and documentation of all the vital parameters should be fundamental part of any patient’s assessment to pick up acute illness at very early stage and to make a difference in final outcome. ã 2016 Elsevier Ireland Ltd. All rights reserved.

Keywords: MEOWS chart CEMACH report Trigger Obstetric morbidity

Introduction The development of early warning system charts started from the knowledge that abnormalities in physiological parameters precede critical illness in general as well as obstetric population [1,2]. These systems involve periodic measurement of basic vital parameters to track patient’s clinical condition over the time to gauze the risk of catastrophic event and prompt response if patient triggers to predeﬁned abnormal values. Recognition of patient’s

deteriorating condition at an early stage may result in timely intervention and improved outcome. An adverse pregnancy outcome can be seen as continuum of deteriorating event from normal/healthy pregnancy ! morbidity ! severe morbidity ! near miss ! death. The ‘track & trigger’ of physiological parameters on a chart can aid in early recognition and treatment of maternal morbidity, thus halting this cascade of severe maternal morbidity and mortality [3]. The 2003–2005 triennial Conﬁdential Enquiry into Maternal and Child Health (CEMACH) report recommended routine use of Maternal Early Obstetric Warning System (MEOWS) chart [3]. Although studies in medical and surgical patients have shown good performance of Early Warning System (EWS) but there are

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17

not enough studies on MEOWS chart to validate its use in obstetric population. The aim of our study was to evaluate MEOWS chart as a bedside screening tool in prediction of maternal morbidity by measuring its sensitivity, specificity and predictive values. Materials & methods Ethical approval was obtained from institutional ethical committee. This study was conducted in the Department of Obstetric & Gynaecology of University College of Medical Sciences (UCMS) and Guru Teg Bahadur Hospital (GTBH), Delhi from October 2012 to April 2014. MEOWS chart recommended in CEMACH 2003–2005 report was used for this study [3]. A total of 1065 women which included pregnant women in labour beyond 28 weeks gestation and up to 6 weeks postpartum were recruited as study subjects. All consecutive admissions to clean and septic labour wards were recruited into study depending upon duties of principal investigator. Measurement of temperature (oral), heart rate, blood pressure, respiratory rate, oxygen saturation (pulse oximeter), conscious level (AVPU: alert, responds to voice or pain and unresponsive), proteinuria (urine dipstick test), colour of liquor and lochia characteristics were documented (Appendix A of Supplementary material). The physiological parameters were recorded on the chart at admission and subsequently monitored according to the frequency given below: Women in labour ! 4 hourly till 24 h after delivery and then once a day till discharge. Postpartum hemorrhage ! 1 hourly for 4 h, then 4 hourly for next 24 h and thereafter once a day till discharge. Caesarean section or other procedure under anesthesia ! 1 hourly for 6 h, then 4 hourly for next 48 h and then once a day till discharge. Blood transfusion ! Immediately prior to start of transfusion and then 15 min into transfusion. Once a daily frequency of monitoring was reached, the study subjects were followed till the time of discharge from hospital. A trigger was defined as a single markedly abnormal observation (red trigger) or the combination of two simultaneously mildly abnormal observations (two yellow triggers) (Table 1). However, no intervention was done based on trigger and patients were managed according to hospital protocol. According to maternal outcome at time of discharge, study subjects were divided into Category 1 (Normal and those recovered without morbidity) and Category 2 (recovered with morbidity or mortality). Morbidity was defined according to Table 2. Microsoft Excel (version 2010) and statistical software SPSS (version 20.0) were used for data presentation and statistical analysis. Chi-square test and Fisher’s exact test were used to

compare socio-demographic features and interventions between triggered versus non-triggered group. Performance of MEOWS chart as a screening tool was evaluated by calculating its sensitivity, specificity and predictive values using Exact’s method. Relative risk of morbidity (odd’s ratio) and 95% confidence interval was calculated for individual parameter. We used the Poisson regression with log link with robust’s variance method to find the relative risk after adjusting potential confounders [9]. p-value <0.05 was considered as significant. Results Description of study population Completed MEOWS chart of 1065 study subjects was analysed. Study population was largely comprised of antenatal (98%), young females between 20–30 years of age belonging to either lower or middle socio-economic status. About two-third of the women had regular antenatal visits and 85% of the admissions were direct. Associated obstetric condition was present in 22% of cases with hypertensive disorders (9.8%) being most commonest followed closely by previous caesarean section (7.7%). Associated medical condition was present in 5% of cases; severe anaemia (2.4%) being the commonest (Fig. 1). Two hundred and eighty four (26.60%) women triggered to abnormal zones after admission (Fig. 2). One hundred and seventy seven (16.61%) fitted our criteria for morbidity (Fig. 3). The most common morbidity was hypertensive disorders (69.4%) followed by anaemia (14.12%) and haemorrhage (9.6%). Only one patient died due to complications of hypertensive disorder. The pattern of morbidity distribution in category 2 patients is shown in Fig. 4. A. Socio-demographic characteristics The significant factors contributing to trigger included age >30 years, muslim religion, rural background, lower socio-economic class, referred cases. The risk of being triggered was increased for primigravidae (45.7% vs 41.2%) and for postpartum women (4.2% vs 0.2%). Although the number of women who had not received antenatal care triggered more (38.7% vs 34.4%) but this was not statistically significant (Table 3). B. Need for intervention Significantly higher proportion of interventions i.e. instrumental delivery (3.2% vs 2.0%), caesarean section (28.9% vs 14.3%) and blood transfusion (20.4% vs 3.8%) was required in the women whose MEOWS charts triggered (Fig. 5). C. Neonatal outcome The composite neonatal outcome was worse in triggered group as they had significantly more number of patients with intrauterine fetal deaths (Table 4).

Table 1 Cut-off limits of trigger zones for individual parameters. Parameter

Red trigger

Yellow trigger

Respiratory rate; breaths/min Oxygen saturation; % Heart rate; beats/min Systolic BP; mmHg Diastolic BP; mmHg Lochia Proteinuria Colour of liquor Neuroresponse General condition

<10 or >30 <90 <30 or >120 <80 or >160 >90 Heavy/foul smell >2+ Green Unresponsive, pain –

21–30 – 100–120 or 30–40 80–90 or 150–160 80–90 – – – Voice Looks unwell

Performance of individual physiological parameters of MEOWS chart Among individual physiological parameters, the most frequent trigger was high diastolic blood pressure (33%). This was followed by heart rate (19.3%), abnormal liquor (7.23%), high systolic blood pressure (5.19%) and respiratory rate (2.06%) respectively (Table 5). Abnormal value in either yellow or red zone leads to signiﬁcant increase in morbidity.

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17

Table 2 Diagnostic criteria of obstetric morbidity. Obstetric morbidity

Diagnostic criteria

Hypertensive disorder of pregnancy Eclampsia Obstetric haemorrhage Suspected infection Pulmonary oedema Shock

Diastolic blood pressure of 90 mmHg or a systolic blood pressure level of 140 mmHg or higher after 20 weeks of gestation on two occasions atleast 4–6 h apart with or without proteinuria [4] Severe variety of preeclampsia characterized by sudden onset of generalized tonic-clonic seizures [4] Documented estimated blood loss >1500 ml, drop in hemoglobin concentration 3 g/dl or need for blood transfusion [5] Clinically suspected focus of infection positive laboratory cultures, treated with antibiotics [6] Breathlessness, crepitation requiring diuretics [7] Persistent severe hypotension defined as systolic blood pressure <90 mmHg for 60 min with a pulse rate atleast 120 despite aggressive fluid replacement [8] Carbohydrate intolerance of varied severity with onset or first recognition during present pregnancy Hyperglycemia, metabolic acidosis, ketones in urine [7] CT/MRI confirmed History of asthma and audible expiratory wheeze, with reduced peak expiratory flow rate [7] History of epilepsy, prolonged multiple seizures [7]

Gestational diabetes Diabetic ketoacidosis Intracranial bleed Acute asthma Status epilepticus

100 90 80

Percentage

70 60 50 40 30 20 10

Age (yrs)

Religion

Residence SE Status Admission Antenatal care

Period of Gesta on

Parity

Present

Absent

Present

Absent

1-4

Zero

Postpartum

>37 week

28-37 week

Not received

Received

Referred

Direct

Middle

Lower

Urban

Rural

Muslim

Hindu

>30

20-30

<20

Obs Medical Condi on Condi on

Fig. 1. Characteristics of study population.

The risk of morbidity was assessed based on abnormality of individual parameter of MEOWS chart (Table 6). Once, triggered into abnormal zone (yellow/red); the parameters like diastolic blood and systolic blood pressure, respiratory rate, neuroresponse, general condition (looks well or unwell), proteinuria increased the risk of maternal morbidity or mortality by 6–7 times. Abnormality in heart rate and temperature lead to increase in risk by 2–3 folds. However, colour of the liquor did not lead to signiﬁcant increase in

morbidity. Thus, derangement in value of any vital parameter may be an early indicator of impending morbidity. After adjusting for confounding factors i.e. age and underlying obstetric or medical condition at time of admission, the individual parameter trigger (i.e. abnormality in heart rate, systolic and diastolic blood pressure, temperature, neuroresponse) remained statistically signiﬁcant (p < 0.001) for predicting risk of obstetric morbidity (Table 7). Performance of MEOWS chart as a screening tool Out of 284 patients who triggered on MEOWS charts, only 153 could meet the criteria of obstetric morbidity. There were 24 patients who had morbidity but did not trigger on MEOWS chart (Fig. 6). The MEOWS chart was found to be 86.4% sensitive, 85.2% speciﬁc and had a positive and negative predictive value of 53.87% and 96.9% respectively for predicting obstetric morbidity. Comment

Fig. 2. Triggered versus non-triggered group in study population.

Early Warning System (EWS) was ﬁrst developed in UK by Morgan, Williams and Wright in 1997 [10]. The fact that

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17

abnormalities in physiological parameters is a preceding event in patients who suffer a cardiopulmonary arrest has already been highlighted in a number of studies and served as a basis of these systems [1,2,11]. Maternal mortality case reviews and CEMACH 2003–05 report have mentioned that even professionals failed to recognise early signs of maternal collapse [3]. Hence, a need is perceived for use of EWS for obstetric population also to predict maternal morbidity at an early stage [3,12,13]. The intercollegiate maternal critical care group has produced an obstetric early warning system (ObsEWS) to detect early deterioration and improve outcome in obstetrics [14]. Maternal Early Obstetric Warning System (MEOWS) chart recommended by CEMACH is speciﬁcally designed for obstetric population with some modiﬁcations in already existing early

Fig. 3. Two categories based on ﬁnal outcome.

80 69.49 70

Percentage

60 50 40 30 20

14.12 9.6

10 2.26

3.96

0.56

0 Hypertensive disorder

Anaemia

Haemorrhage

Suspected infection

Others

Mortality

Fig. 4. Pattern of obstetric morbidity. Table 3 Comparison of socio-demographic characteristics between triggered and non-triggered group. Characteristic Age (years) <20 20–30 >30 Religion Hindu Muslim Residence Rural Urban Socio-economic status Lower Upper lower Lower middle Upper middle Parity 0 1–4 >4 POG (weeks) 28–37 >37 Postpartum Antenatal care Received Not received Mode of admission Direct Referred *

Triggered group (n = 284) No. (%)

Non–triggered group (n = 781) No. (%)

p value

9 (3.16) 241 (84.85) 34 (11.97)

16 (2.04) 748 (95.7) 37 (4.7)

<0.001*

213 (75) 71 (25)

643 (82.33) 138 (17.66)

0.008*

25 (8.80) 259 (91.19)

27 (3.45) 754 (96.54)

<0.001*

41 (14.43) 103 (36.26) 107 (37.67) 33 (11.61)

72 (9.21) 295 (37.77) 308 (39.43) 106 (13.57)

0.100

130 (45.77) 152 (53.52) 2 (0.70)

322 (41.24) 457 (58.51) 2 (0.25)

0.010*

72 (25.35) 200 (70.42) 12 (4.22)

166 (21.25) 613 (78.48) 2 (0.25)

<0.001*

174 (61.26) 110 (38.73)

511 (65.42) 270 (34.57)

0.210

215 (75.70) 69 (24.29)

705 (90.26) 76 (9.73)

<0.001*

p value <0.05 was considered signiﬁcant.

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17

96.2

100 90

Non-triggered

Triggered

83.2

79.6

80 70

64.4

60 50 40 28.9

20.4

14.3

3.2

0.4

3.2

3.84

0 Normal delivery

Instrumental delivery

Ceasarean section

Hysterectomy

Conservative

Received

Inte rventi on

Not received

Transfusion

Fig. 5. Comparison of interventions between triggered and non-triggered group.

Table 4 Comparison of neonatal outcome between triggered and non-triggered group. Neonatal outcome

Triggered group No. (%)

Non-triggered group No. (%)

p value

Healthy Neonatal deaths Intrauterine fetal deaths Referred

265 (93.3) 8 (2.8) 11 (3.9) 0 (0.0)

750 (96.0) 20 (2.6) 10 (1.3) 1 (0.1)

0.053

P-value <0.05 was considered signiﬁcant.

warning system (EWS). The present study was carried out on 1065 obstetric admissions mainly comprising of young (20–30 years), antenatal (98%) females, mostly urban belonging to lower or middle socio-economic class. The validation study for MEOWS in literature by Singh et al. was done on 676 obstetric inpatients (between 20 weeks of gestation till 6 weeks postpartum) in UK [15]. Though their socio-demographic characteristics are not available for comparison but some differences due to different geographical areas, high economy, better literacy and better nutrition are expected. In present study, 26.6% of the study population triggered which is almost similar (30%) to the population who triggered in study by Singh et al. 86% of triggered population had obstetric illness. The signiﬁcant factors which were responsible for women to trigger

included age >30 years, muslim religion, rural background, lower socio-economic class, primigravidae, grand-multiparity, postpartum status, absence of antenatal care, referral from other health facility and presence of obstetric or medical condition. As there is no availability of data on socio-demographic and antecedent factors in literature on validation study of MEOWS, the association of these factors with trigger could not be compared. Being a developing country, low level of awareness, social taboos and tradition, difficult accessibility to health services in rural areas might be some of the causes for these associations in our study population. Though literature does support that most of aforementioned features such as elderly age, multiparity and low socioeconomic class can lead to increased obstetric morbidity [16,17]. Baskett et al. have reported that delay in seeking care and transfer as one of the main factors leading to morbidity [18]. Bajwa et al. in Banur, India also found poor transport facility, poor rural health infrastructure, custom and traditions to be contributing factors towards increase morbidity and mortality [19]. There was a significantly higher proportion of interventions in triggered population in our study. It was also reported by Singh et al. (caesarean, ventouse or forceps delivery: p < 0.0001) [15]. The composite neonatal outcome was found to be poorer in triggered group but no comparison could be made due to lack of such data in available literature on MEOWS. In our study, hypertensive disorders of pregnancy (69%) ranked first among the causes of obstetric morbidity followed by anaemia

Table 5 Frequency of trigger of individual physiological parameters of MEOWS chart for study population. Parameters

White trigger No. (%)

Yellow trigger No. (%)

Red trigger No. (%)

Total trigger No. (%)

Respiratory rate Saturation Temperature Heart rate Systolic blood pressure Diastolic blood pressure Lochia Proteinuria Liquor Neuroresponse Looks well/unwell

1043 (97.9) 1065 (100.0) 1059 (99.4) 859 (80.7) 1002 (94.1) 731 (68.6) 1063 (99.8) 1059 (99.4) 988 (92.8) 1061 (99.6) 1055 (99.1)

20 (1.9) – – 200 (18.8) 42 (3.9) 248 (23.3) – – – 2 (0.2) –

2 (0.2) 0 (0.0) 6 (0.6) 6 (0.6) 21 (2.0) 866 (8.1) 2 (0.2) 6 (0.6) 77 (7.2) 2 (0.2) 10 (0.9)

1065 1065 1065 1065 1065 1065 1065 1065 1065 1065 1065

(100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17 Table 6 Relative risk of morbidity with individual parameter trigger of MEOWS chart. Individual parameter as trigger

Relative risk of morbidity (odds ratio)

p value

Respiratory rate Oxygen saturation Temperature Heart rate Systolic blood pressure Diastolic blood pressure Lochia Proteinuria Liquor Neuroresponse Looks well/unwell

6.382 (5.379–7.573) – 3.043 (1.352–6.852) 2.996 (2.317–3.874) 6.798 (5.585–8.275) 7.496 (5.402–10.402) 6.069 (5.300–6.949) 6.224 (5.423–7.142) 0.615 (0.315–1.202) 6.133 (5.351–7.029) 6.317 (5.497–7.260)

<0.001 – 0.028 <0.001 <0.001 <0.001 0.002 <0.001 0.301 0.001 <0.001

p < 0.05 was taken as significant. Bold value signified statistically significant parameter as p value is <0.05.

Table 7 Adjusted risk of morbidity for individual parameter trigger. Individual parameter as trigger

Relative risk of morbidity Odds ratio (95% Cl)

p value

Respiratory rate Oxygen saturation Temperature Heart rate Systolic blood pressure Diastolic blood pressure Neuroresponse

5.39 (4.27–6.81)a – 2.45 (1.12–5.39)a 2.33 (1.77–3.06)a 2.57 (1.99–3.32)b 4.06 (2.95–5.60)b 7.66 (6.54–8.96)a

<0.001 – 0.025 <0.001 <0.001 <0.001 0.001

p < 0.05 was taken as signiﬁcant. a Adjusted for age and medical condition. b Adjusted for age, medical condition and obstetrical condition.

(14.12%), obstetric haemorrhage (9.6%) and sepsis (2.26%); which is similar to the studies from developing countries where haemorrhage and hypertensive disorders have been shown to be major contributors of morbidity and mortality with variation across and within geographic areas [20,21]. MEOWS as a screening tool For a screening tool to be of value, it should be cost effective, safe to use, easily acceptable by community, accurate and validated. Sensitivity and speciﬁcity are two components to determine validity. The accuracy is indicated by positive and negative predictive values which are dependent on prevalence of morbidity in the population. The MEOWS chart as an ideal screening tool should have a sensitivity and speciﬁcity close to 100% that means, most if not all of the triggered patients will be

correctly identified as having morbidity and number of misleading triggers should be very less. Though in practice, it is rarely the case. So a good balance between sensitivity and specificity is desirable. Since these charts are aimed at detection of maternal morbidity, the number of false positive (sensitivity) would increase burden on resources and create unnecessary anxiety but still is favoured over false negative. The reason being, false negative could have catastrophic consequences for the patients. Therefore, this chart as a good screening tool should be more sensitive with acceptable specificity. No national or international ‘Gold standard’ obstetric early warning scoring system exists. Although number of studies on pregnant patients are very few, a number of hospitals in UK already use them. Swanton et al. on his survey on UK maternity units in 2007 found that 30 (19%) maternity units were regularly using an EWS in obstetric population yet only 9 (6%) were using a system modified for parturients [22]. In published literature by Singh et al. 2012, MEOWS chart in UK population has been found to be 89% sensitive, 79% specific with a positive and negative predictive value of 39% and 98% respectively [15]. Though results of our study 86.4% sensitive and 85.2% specific are comparable to the study by Singh et al. the few minor differences could be explained by difference in prevalence of obstetric morbidity for Indian subcontinent. In a retrospective study done on 364 women with clinically diagnosed chorioamnionitis for prediction of sepsis, 6 different MEOWS had variable performance with 40–100% sensitivity, 4–97% specificity with a low positive predictive value of <2–15% for all and this study also found MEOWS with simpler designs to be more sensitive and useful [23]. Ethnographic analysis has also concluded that complexity of managing triggers and increase in overall workload can lead to loss of potential benefit of EWS as a safety tool [24]. Considering the drawbacks and to

Category 1

Category 2

100 86.4

85.2

80 70 60 50 40 30 20

14.8

13.6

10 0 Triggered

Non-triggered

Fig. 6. Comparison of ﬁnal outcome between triggered and non-triggered group.

A. Singh et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 207 (2016) 11–17 Table 8 Comparison of relative risk of morbidity for individual parameters. Character

Study by Singh et al.

Present study

Type of study Number of patients

Prospective 676

Prospective 1065

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. ejogrb.2016.09.014.

Parameter

Relative risk of morbidity Relative risk of morbidity OR (95% Cl) OR (95% Cl)

References

Heart rate Diastolic blood pressure Systolic blood pressure Respiratory rate Temperature Neuroresponse

7.0 (4.9–10.1) 6.6 (4.7–9.4) 5.4 (3.8–7.8) 4.5 (2.9–8.0) 3.4 (2.0–5.6) 0.0

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2.9 (2.3–3.8) 7.4 (5.4–10.4) 6.7 (5.5–8.2) 6.3 (5.3–7.5) 3.0 (1.3–6.8) 6.1 (5.3–7.0)

increase the effectiveness, the National Partnership for Maternal Safety have proposed a Maternal Early Warning Criteria which needs further evaluation [13]. Both in present study as well as in study by Singh et al. sensitivity of the MEOWS was much higher as compared to nonobstetric early warning systems. This can be attributed to use of morbidity as a final outcome rather than death or ICU admission which are relatively rare events in obstetric population. Individual parameters of MEOWS chart The most common parameter to have abnormal value in either yellow or red trigger zone as well as for the morbidity was high diastolic blood pressure followed by heart rate, systolic blood pressure, respiratory rate, proteinuria, general condition, neuroresponse in decreasing order of frequency. The reason for blood pressure being commonest could be that the value at which trigger was set is close to the value that defined morbidity. Secondly, hypertensive disorders were commonest in our study population. Literature has enough evidence regarding recognizable changes in vital parameters like heart rate, respiratory rate, blood pressure, level of consciousness etc. prior to any life threatening event. Swanton et al. have reported that diastolic blood pressure was included in all 9 obstetric specific EWS that they reviewed [22]. Goldhill et al. noted the most common abnormalities to be tachypnoea and altered level of consciousness in patients admitted to ICU [1]. Kause et al. also revealed hypotension and fall in consciousness level to be most common antecedent to cardiac arrest, death or emergency obstetric admissions [25]. Comparison of the relative risk of morbidity for individual parameter trigger showed that most of the parameters are predicting similar risk except heart rate (tachycardia) which had relatively higher risk and neuroresponse had no risk in study by Singh et al. as compared to present study (Table 8). This could be attributed to high prevalence of conditions like eclampsia, anaemia etc. in our study population. Hodgetts et al. and Duckitts et al. also reported contribution of vital signs on morbidity [26,27]. So, strict monitoring of all the parameters should be fundamental part of any patient’s assessment to pick up acute illness at very early stage and to make a difference in final outcome. Thus, MEOWS chart emerged as an useful bedside screening tool for predicting obstetric morbidity, meeting most of the criteria of ideal screening tool in our North-Indian obstetric population. It should be used routinely as bedside screening tool in every obstetric unit as recommended by CEMACH report for early recognition of any critical illness and periodic documentation of physiological parameters. We recommend further studies for validation of MEOWS chart in different clinical settings.