Types of studies

All published, unpublished and ongoing randomized trials with reported data that assess clinical outcomes in women and their babies who where prescribed bed rest in hospital or at home for preventing preterm birth. Randomized, cluster‐randomized and quasi‐randomized controlled trials were all eligible for inclusion.

Types of participants

Pregnant women at high risk of spontaneous preterm birth.

High risk of spontaneous preterm birth can be defined according to:

1. previous history of preterm birth or second trimester miscarriage;

2. threatened preterm labour;

3. positive screening test results, e.g. fetal fibronectin or ultrasound assessment of cervical length;

4. maternal anthropometric measurements (e.g. attained weight at 24 to 28 weeks, pre‐pregnancy body mass index);

5. scoring systems based on a combination of different categories of risk factors, including those previously mentioned.

Trials assessing bed rest in women with preterm premature rupture of membranes or multiple pregnancies were not considered (see the related review Crowther 2010).

Types of interventions

As bed rest is an accepted standard initial therapy for women at high risk of preterm birth, it has usually been used as a control intervention in trials evaluating alternative forms of care for preventing preterm birth. However, our intention in this review was to evaluate the effectiveness of bed rest compared with no intervention. Therefore, we considered trials comparing prescription of bed rest at home or in hospital with no intervention. Trials with arms including more than one intervention would also be eligible if arms differed only in the prescription of bed rest (i.e. bed rest and drug versus drug alone). For trials comparing drugs, placebo and bed rest, placebo was considered as no intervention.

Types of outcome measures

Electronic searches

We searched the Cochrane Pregnancy and Childbirth Group’s Trials Register by contacting the Trials Search Co‐ordinator (18 December 2014).

The Cochrane Pregnancy and Childbirth Group’s Trials Register is maintained by the Trials Search Co‐ordinator and contains trials identified from:

1. monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);

2. weekly searches of MEDLINE (Ovid);

3. weekly searches of Embase (Ovid);

4. handsearches of 30 journals and the proceedings of major conferences;

5. weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.

Details of the search strategies for CENTRAL, MEDLINE and EMBASE, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the ‘Specialized Register’ section within the editorial information about the Cochrane Pregnancy and Childbirth Group.

Trials identified through the searching activities described above are each assigned to a review topic (or topics). The Trials Search Co‐ordinator searches the register for each review using the topic list rather than keywords.

In addition, we searched CENTRAL (2014, Issue 12) using the terms in Appendix 1.

We also searched MEDLINE (December 2014), EMBASE (December 2014) and LILACS (December 2014) using the terms in Appendix 1.

Searching other resources

We searched the reference lists of retrieved studies.

We did not apply any language or date restrictions.

Selection of studies

Two review authors (CS and FA) independently assessed for inclusion all the potential studies that were identify as a result of the search strategy. The two review authors resolved any disagreement by consensus or, if necessary, by a third review author (EB or JMB)

Data extraction and management

We designed a form to extract data. For eligible studies, two review authors extracted the data using the agreed form. We resolved discrepancies through discussion or, if required, we consulted a third author. We entered data into Review Manager software (RevMan 2014) and checked for accuracy.

Assessment of risk of bias in included studies

Two review authors independently assessed risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We resolved any disagreement by discussion or by involving a third review author.

Measures of treatment effect

Unit of analysis issues

Dealing with missing data

For included studies, we noted levels of attrition. Had we found high levels of missing data, we planned to explore the impact of including studies in the overall assessment of treatment effect by using sensitivity analysis.

For all outcomes, we carried out analyses on an intention‐to‐treat basis (i.e. we included all participants randomized to each group in the analyses, and all participants were analyzed in the group to which they were allocated, regardless of whether or not they received the allocated intervention). The denominator for each outcome in each trial was the number randomized minus any participants whose outcomes were known to be missing.

Assessment of heterogeneity

We assessed statistical heterogeneity in each meta‐analysis using the Tau², I² and Chi² statistics. We regarded heterogeneity as substantial if the Tau² was greater than zero and either an I² was greater than 30% or there was a low P value (< 0.10) in the Chi² test for heterogeneity. 

Assessment of reporting biases

In future updates, if there are 10 or more studies in the meta‐analysis, we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis

We carried out statistical analysis using the Review Manager software (RevMan 2014). We planned to use fixed‐effect meta‐analysis for combining data where it was reasonable to assume that studies were estimating the same underlying treatment effect and the trials’ populations and methods were judged sufficiently similar. If there was clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity was detected, we planned to use random‐effects meta‐analysis to produce an overall summary, if an average treatment effect across trials was considered clinically meaningful. If we finally used random‐effects analyses, the results would be presented as the average treatment effect with 95% confidence intervals, and the estimates of Tau² and I².

Subgroup analysis and investigation of heterogeneity

If we identified substantial heterogeneity, we planned to investigate it using subgroup analysis. We would have considered whether an overall summary was meaningful, and if it was, used random‐effects analysis to produce it.

There was not enough data included in analyses to carry out subgroup analysis.

In future updates, we will carry out the following subgroup analyses:

(1) Subgroups of participants according to method of risk assessment based on:

• previous obstetric history;

• threatened preterm labour;

• positive screening test results;

• maternal anthropometric measurements;

• selection by scoring systems.

(2) Subgroups of interventions:

• prescription of bed rest at home versus prescription of bed rest in hospital.

Subgroup analysis will be restricted to the review’s primary outcomes:

• preterm birth (less than 37 weeks);

• perinatal mortality;

• low birthweight (less than 2500 g);

• neonatal intensive care.

We will assess subgroup differences by interaction tests available within RevMan (RevMan 2014). We will report the results of subgroup analyses quoting the Chi² statistic and P value, and the interaction test I² value.

Sensitivity analysis

In future updates, if more data are available, we will carry out sensitivity analyses to explore the effect of trial quality assessed by concealment of allocation, high attrition rates, or both, with poor quality studies being excluded from the analyses in order to assess whether this makes any difference to the overall result.