MAARIE Template for Evaluating Evidence Based Health Research (please use attached template) ?? Method- The ??purpose and population for the investigation 1. Study hypothesis What is the study
MAARIE Template for Evaluating Evidence Based Health Research (please use attached template)
Method- The purpose and population for the investigation
1. Study hypothesis
What is the study question being investigated?
2. Study population
What population is being investigated and what are the inclusion and exclusion criteria for the participants of the investigation?
3. Sample size and statistical power
How many individuals are included in the study and in the control groups? Are the numbers adequate to demonstrate statistical significance if the study hypothesis is true (what is the statistical power)?
Assignment- Selection of participants for the study and control groups
1. Process
What method is used to identify and assign individuals or populations to study and control groups?
2. Confounding variables
Are there differences between study and control groups, other than the factor being investigated, that may affect the outcome of the investigation?
3. Masking or blinding
Are the participants and/or the investigators aware of the participants' assignment to a particular study or control group?
Assessment- Measurement of outcomes or endpoints in the study and control groups
1. Appropriate
Does the measurement of outcomes address the study's question?
2. Accurate and precise
Is the measurement of outcomes an accurate and precise measure of the phenomenon that the investigators seek to assess?
3. Complete and unaffected by observation
Is the outcome measurement nearly 100% complete and is it affected by the participants’ or the investigators’ knowledge of the study group or control group assignment?
Results- Comparison of outcomes in the study and control groups
1. Estimation
What is the magnitude or strength of the relationship observed in the investigation?
2. Inference
What statistical technique(s) are used to perform statistical significance testing?
3. Adjustment
What statistical technique(s) are used to take into account or control for differences between the study group and the control group that may affect the results?
Interpretation- Meaning of the results for those included in the investigation
1. Contributory cause or efficacy
Does the factor being investigated alter the probability that the disease will occur (contributory cause) or work to reduce the probability of undesirable outcomes (efficacy)?
2. Harms
Are adverse events that affect the meaning of the results identified?
3. Subgroups and interactions
Do the outcomes in subgroups differ and are there interactions between factors that affect outcomes?
Extrapolation- Meaning for those not specifically included in the investigation
1. To similar individuals, groups, or populations
Do the investigators extrapolate or extend the conclusions to individuals, groups, or populations that are similar to those who participated in the investigation?
2. Beyond the data
Do the investigators extrapolate by extending the conclusions beyond the dose, duration, or other characteristics of the investigation?
3. To other populations
Do the investigators extrapolate to populations or settings that are quite different from those in the investigation?
Rev. 2021
Riegelman, R.K. & Nelson, B.A. (2021). Studying a study & testing a test. Wolters Kluwer.
Bovbjerg, M. L., Cheyney, M., & Everson, C. (January 01, 2016). Maternal and Newborn Outcomes Following Waterbirth: The Midwives Alliance of North America Statistics Project, 2004 to 2009 Cohort. Journal of Midwifery & Women's Health, 61, 1, 11-20.
Bovbjerg_et_al-2016-Journal_of_Midwifery_%26_Women-s_Health.pdf (attached)
MAARIE Template for Evaluating Evidence Based Health Research
Method- The purpose and population for the investigation 1. Study hypothesis What is the study question being investigated? 2. Study population What population is being investigated and what are the inclusion and exclusion criteria for the participants of the investigation? 3. Sample size and statistical power How many individuals are included in the study and in the control groups? Are the numbers adequate to demonstrate statistical significance if the study hypothesis is true (what is the statistical power)? |
Assignment- Selection of participants for the study and control groups 1. Process What method is used to identify and assign individuals or populations to study and control groups? 2. Confounding variables Are there differences between study and control groups, other than the factor being investigated, that may affect the outcome of the investigation? 3. Masking or blinding Are the participants and/or the investigators aware of the participants' assignment to a particular study or control group? |
Assessment- Measurement of outcomes or endpoints in the study and control groups 1. Appropriate Does the measurement of outcomes address the study's question? 2. Accurate and precise Is the measurement of outcomes an accurate and precise measure of the phenomenon that the investigators seek to assess? 3. Complete and unaffected by observation Is the outcome measurement nearly 100% complete and is it affected by the participants’ or the investigators’ knowledge of the study group or control group assignment? |
Results- Comparison of outcomes in the study and control groups 1. Estimation What is the magnitude or strength of the relationship observed in the investigation? 2. Inference What statistical technique(s) are used to perform statistical significance testing? 3. Adjustment What statistical technique(s) are used to take into account or control for differences between the study group and the control group that may affect the results? |
Interpretation- Meaning of the results for those included in the investigation 1. Contributory cause or efficacy Does the factor being investigated alter the probability that the disease will occur (contributory cause) or work to reduce the probability of undesirable outcomes (efficacy)? 2. Harms Are adverse events that affect the meaning of the results identified? 3. Subgroups and interactions Do the outcomes in subgroups differ and are there interactions between factors that affect outcomes? |
Extrapolation- Meaning for those not specifically included in the investigation 1. To similar individuals, groups, or populations Do the investigators extrapolate or extend the conclusions to individuals, groups, or populations that are similar to those who participated in the investigation? 2. Beyond the data Do the investigators extrapolate by extending the conclusions beyond the dose, duration, or other characteristics of the investigation? 3. To other populations Do the investigators extrapolate to populations or settings that are quite different from those in the investigation? |
Rev. 2021
Riegelman, R.K. & Nelson, B.A. (2021). Studying a study & testing a test. Wolters Kluwer.
Bovbjerg, M. L., Cheyney, M., & Everson, C. (January 01, 2016). Maternal and Newborn Outcomes Following Waterbirth: The Midwives Alliance of North America Statistics Project, 2004 to 2009 Cohort. Journal of Midwifery & Women's Health, 61, 1, 11-20.
Bovbjerg_et_al-2016-Journal_of_Midwifery_%26_Women-s_Health.pdf
,
Journal of Midwifery &Women’s Health www.jmwh.org Original Research
Maternal and Newborn Outcomes Following Waterbirth: The Midwives Alliance of North America Statistics Project, 2004 to 2009 Cohort Marit L. Bovbjerg, PhD, MS, Melissa Cheyney, PhD, CPM, LDM, Courtney Everson, MA, PhD
Introduction: Data on the safety of waterbirth in the United States are lacking.
Methods: We used data from the Midwives Alliance of North America Statistics Project, birth years 2004 to 2009. We compared outcomes of neonates born underwater waterbirth (n = 6534), neonates not born underwater nonwaterbirth (n = 10,290), and neonates whose mothers intended a waterbirth but did not have one intended waterbirth (n = 1573). Neonatal outcomes included a 5-minute Apgar score of less than 7, neonatal hospital transfer, and hospitalization or neonatal intensive care unit (NICU) admission in the first 6 weeks. Maternal outcomes included genital tract trauma, postpartum hospital transfer, and hospitalization or infection (uterine, endometrial, perineal) in the first 6 weeks. We used logistic regression for all analyses, controlling for primiparity.
Results:Waterbirth neonates experienced fewer negative outcomes than nonwaterbirth neonates: the adjusted odds ratio (aOR) for hospital trans- fer was 0.46 (95% confidence interval [CI], 0.32-0.68; P � .001); the aOR for infant hospitalization in the first 6 weeks was 0.75 (95%CI, 0.63-0.88; P � .001); and the aOR for NICU admission was 0.59 (95% CI, 0.46-0.76; P � .001). By comparison, neonates in the intended waterbirth group experienced more negative outcomes than the nonwaterbirth group, although only 5-minute Apgar score was significant (aOR, 2.02; 95% CI, 1.40-2.93; P � 0001). For women, waterbirth (compared to nonwaterbirth) was associated with fewer postpartum transfers (aOR, 0.65; 95% CI, 0.50-0.84; P = .001) and hospitalizations in the first 6 weeks (aOR, 0.72; 95% CI, 0.59-0.87; P � 0.001) but with an increased odds of genital tract trauma (aOR, 1.11; 95%CI, 1.04-1.18; P = .002).Waterbirth was not associated withmaternal infection.Women in the intended waterbirth group had increased odds for all maternal outcomes compared to women in the nonwaterbirth group, although only genital tract trauma was significant (aOR, 1.67; 95% CI, 1.49-1.87; P � .001).
Discussion:Waterbirth confers no additional risk to neonates; however, waterbirth may be associated with increased risk of genital tract trauma for women. J Midwifery Womens Health 2016;61:11–20 c© 2016 by the American College of Nurse-Midwives.
Keywords: childbirth, complications, perineal trauma, safety, waterbirth
INTRODUCTION
Waterbirth is highly controversial in the United States,1–8 despite being an accepted practice in other high-resource nations.9–12 Proponents of waterbirth cite anthropological ev- idence from Odent and Tjarkovsky regarding childbearing traditions that include immersion13,14; the maternal benefits of laboring in water, such as pain relief and reduced stress on tissues secondary to buoyancy15,16; the potential benefits to a neonate of being born into a warm, liquid environment similar to the amniotic fluid17; and a series of studies, mostly small and observational, suggesting no adverse effects for ei- ther the laboring woman or the neonate.18,19 By contrast, in the spring of 2014, the American College of Obstetricians and Gynecologists (ACOG) and the American Academy of Pedi- atrics (AAP) jointly issued clinical recommendations advising strongly against allowing women to labor in water after the first stage of labor is complete.3
Waterbirth is generally defined as a neonate being in- tentionally born underwater. Provided that the neonate is
Address correspondence to Marit Bovbjerg, PhD, MS, College of Public Health and Human Sciences, Oregon State University, Milam Hall 103, Corvallis, OR 97331. E-mail: [email protected]
promptly brought to the surface, it is thought that the diving reflex, which mechanically blocks the airway of submerged infants (although not older children or adults), will pre- vent the newborn from aspirating the water.20 The category waterbirth does not include women who labor in water but give birth to their newborn into air. Laboring in water is con- sidered safe; the current question in the literature is whether waterbirth is safe.3
Published reports of outcomes following waterbirth in the United States currently consist solely of case series1,2,4,5,21–24 rather than studies with robust designs and adequate power. However, there are several cohort studies from Europe describing waterbirth outcomes,25–35 nicely summarized by Nutter et al in a recent review.19 The results of these studies collectively suggest that waterbirth is not associated with an increased risk of morbidity for the newborn (eg, low Apgar score, neonatal intensive care unit [NICU] admission, neonatal injury, or death), although small sample sizes hinder comparisons for all but themost common events.18,19 Regard- ing maternal outcomes, previous literature suggests women do not experience an increase in perineal trauma, infection, or hemorrhage.18,19 Nonetheless, it can be argued that both the US population and US health care system are unique, and thus results from Europe might not be generalizable to the
1526-9523/09/$36.00 doi:10.1111/jmwh.12394 c© 2016 by the American College of Nurse-Midwives 11
✦ Using data collected from the Midwives Alliance of North America Statistics Project (MANA Stats 2004-2009), this study reports waterbirth outcomes for a large sample of midwife-attended births occurring at home and in birth centers in the United States (N = 18,343 women); 35% of the women (n = 6521 women; 13 sets of twins) had a waterbirth.
✦ Neonates of womenwho had awaterbirth were less likely to experience a low 5-minute Apgar score, neonatal transfer to the hospital, and hospitalization or neonatal intensive care unit admission in the first 6 weeks when compared to nonwaterbirth neonates.
✦ For women, waterbirth was associated with decreased odds of hospitalization, either immediately postpartum or within the first 6 weeks, but increased odds of genital tract trauma.
✦ Waterbirth was not associated with increased risk of maternal infection.
United States. The purpose of this study, therefore, was to re- port waterbirth outcomes from a large sample of midwife- led births occurring at home and in birth centers in the United States.
METHODS
Data Source and Sample Description
The data for this study come from the Midwives Alliance of North America Statistics Project, commonly referred to as MANA Stats.36 MANA Stats is an ongoing, Web-based data collection effort designed to capture complete courses of care from the medical records of women who have had midwife-led pregnancies and births. Any midwife, regardless of birth setting, is eligible to contribute data. However, in practice, most MANA Stats records are for planned home or planned birth center births (97.6% for the years 2004-2009) attended by certified professional midwives (CPMs) in the United States. Of the births in the 2004 to 2009 MANA Stats dataset, 73% of the births were attended by CPMs.36
A midwife who is a MANA Stats contributor enters data on all women in her care from the first prenatal visit through the final visit, which is usually at 6 weeks postpartum. Midwives are required to preregister or log patients into the MANA Stats system early in care, before the outcome of the pregnancy is known. This prospective logging helps to ensure that all births from participating midwives are captured, regardless of outcome, thus reducing selection bias in the sample.
Women give informed consent allowing their deidentified data to be included in MANA Stats, and the consent includes explicit permission for the data to be used for research. Should a woman decline consent, her data are not included, but this decision to decline consent would occur early in pregnancy and thus could not be affected by pregnancy outcome. In prac- tice, very few women decline this consent; based on practice data reported bymidwives, we estimate thatMANA Stats cap- tures 97% of births attended by midwife contributors.36 The high rate of maternal participation in this population is not unique to the MANA Stats dataset; it has also been reported in other studies enrolling women planning home and birth center births.37,38
The institutional review board at Oregon State University approved this analysis, which usesMANA Stats data for births
that occurred between 2004 and 2009. Evidence of reliabil- ity and validity of the MANA Stats 2004 to 2009 dataset, as well as detailed data collection protocols, is presented elsewhere.36
We limited our sample to births that were planned home births or planned birth center births at the onset of labor wherein the neonate was actually born in the intended set- ting (ie, no intrapartum transfer to a hospital occurred). Thus, excluded from the sample were the data from women who planned a hospital birth and from those for whom a hospital birth was not planned but occurred following an intrapartum transfer (Figure 1).
These cases were excluded for 2 reasons. First, during the research years (2004-2009), very few hospitals in the United States offered the option of giving birth underwater.39 Second, hospital births are almost always the most complicated preg- nancies and labors in the MANA Stats database; the major- ity of contributors to the project specialize in home or birth center birth and transfer care to hospitals only when com- plications arise.40 Thus, including women with more compli- cated pregnancies or labors resulting in the transfer of care to a hospital-based provider, either before or during labor, com- bined with the reduced likelihood of encountering the expo- sure, would have introduced bias in the direction of making waterbirth appear safer relative to nonwaterbirth. Mother– newborn dyads who transferred to the hospital during the postpartum period were retained in the sample because, if in fact waterbirth itself introduces risk (eg, infection, respi- ratory distress), we would expect to see more women and newborns with immediate postpartum newborn or maternal complications requiring transfer and possible hospitalization following waterbirth. We also excluded 12 singleton pregnan- cies for which the waterbirth variable was missing. Apply- ing these inclusion criteria resulted in a sample size of 18,397 neonates (N = 18,343 pregnancies), as shown in Figure 1.
Variables
The main exposure, waterbirth, was collected as a 3-level cat- egorical variable. To the question “Baby born underwater?” the midwife had 3 answer options: “no”; “yes”; or “intended, but not born underwater.” Throughout this article, we refer to these categories as nonwaterbirth, waterbirth, and intended waterbirth, respectively.
12 Volume 61, No. 1, January/February 2016
n=24,848 pregnancies (n=24,969 newborns; 119 sets of twins and 1 set of triplets)
21,414 pregnancies 21,495 newborns (81 sets of twins)
18,363 pregnancies 18,417 newborns (54 sets of twins)
3433 (3473 newborns) plus 1 record that had missing data = 3 434
Stopped receiving care from this midwife prior to the onset of labor
yes
no
Location of birth: home or birth center yes
no 2949 (2976 newborns) hospital 100 ‘other’ 2 missing
18,355 pregnancies 18,409 newborns (54 sets of twins)
Neonate born alive yes
no 8 IUFDs (intrauterine fetal demise) after the onset of labor, but prior to birth
10,252 pregnancies 10,290 newborns (38 sets of twins)
6521 pregnancies 6534 newborns (13 sets of twins)
1570 pregnancies 1573 newborns (3 sets of twins)
non -waterbirth
waterbirth
intended waterbirth
12 singleton pregnancies were missing data on waterbirth
Figure 1. Sample Size Delimitation Begins with all records entered into MANA Stats for birth years 2004 to 2009. Women who changed providers (ie, stopped receiving care from the midwife filling out the data form) prior to the onset of labor are excluded. Some of these women may be included as separate records if they changed providers to another MANA Stats contributor; however, many developed a complication requiring maternity specialty care and therefore would not be included. Also excluded are women who did not give birth at home or at a birth center, and mother—fetus dyads if the fetus died prior to birth. All numbers are counts of singleton pregnancies, unless otherwise indicated.
Abbreviation: MANA Stats, Midwives Alliance of North America Statistics.
Neonatal outcomes included a 5-minute Apgar score of less than 7 (yes/no), postpartum transfer to the hospital for a newborn indication (referred to hereafter as neonatal trans- fer, yes/no), any infant admission to the hospital during the first 6 weeks of life (yes/no), and any NICU admission during the first 6 weeks of life (yes/no). Although we knew the num- ber of events would be small based on our previous work with this dataset,33 we also included early (prior to 7 completed days of life) and late (at least 7 completed days of life, but not yet 28) neonatal deaths as end points.
Maternal outcomes included postpartum reproductive tract infection at any time during the first 6 weeks postpar- tum (presence of: uterine infection, urinary tract infection, or delayed perineal healing/infection), postpartum transfer for a maternal indication (referred to hereafter as postpartum transfer; yes/no), anymaternal admission to the hospital dur- ing the first 6 weeks postpartum (yes/no), and genital tract trauma. The degree of genital tract trauma was evaluated first as a simple dichotomous variable and then further as a mul- tilevel nominal variable with the following categories: none, episiotomy only, first- or second-degree perineal only, third-
or fourth-degree perineal only, mild labial only, more severe labial only (defined on the data collection formas required re- pair), other trauma requiring repair, trauma at multiple sites, and trauma not otherwise specified. The latter category con- sisted of women for whom the midwife indicated that, yes, there was trauma, but then did not answer the follow-up ques- tions regarding location and severity.
For the neonatal and postpartum transfers,midwiveswere able to indicate multiple indications for transfer. It is there- fore possible that one mother–newborn dyad could have ex- perienced both a postpartum transfer and a neonatal transfer if, for example, the midwife indicated both “extensive lacera- tion repair requiring anesthesia” and “evaluation of congenital anomalies” as reasons for transfer.
Analysis
We used logistic regression to analyze all dichotomous out- comes (5-minute Apgar score of � 7, neonatal transfer, NICU admission, infant hospitalization in the first 6 weeks, post- partum transfer, postpartum reproductive tract infection,
Journal of Midwifery &Women’s Health � www.jmwh.org 13
maternal hospitalization in the first 6 weeks, dichotomized trauma). Directed Acyclic Graph (DAG) methodology41,42 was used to determine potential confounders.Directed acyclic graphs are a type of causal model that allow the researcher to determine a complete set of potential confounders that maxi- mizes use of available data while simultaneously reducing bias that would result from adjusting for highly collinear covari- ables. The DAG/causal model that we drew for this analysis is available from the authors on request; as a result of the DAG analysis, we controlled for primiparity in all models.
The 3-level waterbirth exposure variable was entered into the models as a nominal variable, with nonwaterbirth as the reference category. Our results are thus presented as adjusted odds of a given outcome for waterbirth compared to nonwa- terbirth and, separately, adjusted odds of a given outcome for intended waterbirth compared to nonwaterbirth.
As expected, cell counts were very low for the neona- tal death outcomes. Thus, for these outcomes we report the raw data but did not calculate adjusted odds ratios and corre- sponding 95% confidence limits.
For the multilevel nominal outcome (genital tract trauma), we used multinomial (ie, not ordered) logistic regression and controlled for primiparity. No trauma was the reference category. Data were analyzed using SPSS 19.0.0.1 (IBM Corp, Armonk, NY) and S-Plus Version 8.1 (Tibco Spotfire, Seattle, WA).
RESULTS
We report results from 18,343 births, which included 18,397 neonates (see Figure 1). Of these, 10,252 women (10,290 neonates) were in the nonwaterbirth group, 6521 women (6534 neonates) were in the waterbirth group, and 1570 women (1573 neonates) were in the intended waterbirth group. Demographics of the women in this sample are shown in Table 1. Briefly, the majority were white, married, and col- lege educated. The mean age at conception was 29.9 years (standard deviation 5.3). Our sample does include larger proportions of both Amish/Mennonite (6.0%) and grand- multiparous women (8.5%), relative to the US population as a whole; as expected, there is a large overlap between these 2 groups. Additionally of note, 968 women had vaginal births after cesarean (VBACs), 134 gave birth to a neonate in breech presentation, and 54 women had twins. Because our sample was limited to those women who gave birth at home or in a birth center, all of these were vaginal births.
Neonatal Outcomes
Neonates born underwater (waterbirths) fared better than their nonwaterbirth counterparts on all neonatal outcome measures, when controlling for primiparity (Table 2). The ad- justed odds ratio (aOR) for neonatal transfer to the hospital, for waterbirth neonates compared to nonwaterbirth neonates, was 0.46 (95% confidence interval [CI], 0.32-0.68; P � .001). The aOR for NICU admission during the first 6 weeks was 0.59 (95% CI, 0.46-0.76; P � .001); the aOR for any hospital admission during the first 6 weeks was 0.75 (95% CI, 0.63- 0.88; P � .001) (Table 2). There was no evidence of 5-minute
Apgar scores below 7 being more common in the waterbirth group (aOR, 0.88; 95% CI, 0.65-1.19; P = .42).
By contrast, neonates whose mothers intended a water- birth but did not have one (intended waterbirths) fared worse than neonates whosemothers had not planned to give birth in the water. Neonates in the intended waterbirth category had a 102% increase i
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