Non‐surgical interventions for nasal congestion during pregnancy

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the effects of non‐surgical interventions for nasal congestion during pregnancy and to identify possible adverse effects associated with their use. 

Background

Description of the condition

Definition of nasal congestion

Nasal congestion, defined as a subjective perception of insufficient nasal cavity airflow, is caused by mucosal pathology and/or increased mucous secretions when anatomical variations have been excluded (Jessen 1997). The definition of nasal congestion is not uniform in the literature, where it can be referred to by synonyms including: nasal obstruction, nasal stuffiness and nasal blockage (Baraniuk 2011; Davis 2004; Naclerio 2010). However, some experts have clarified that nasal congestion is not the exclusive cause of nasal obstruction. In contrast with our definition, some researchers also suggest that nasal congestion indicates objective increased airway resistance rather than only a subjective feeling (Corey 2000; van Spronsen 2008). In this review, we are stressing subjective sensation and the exclusion of structural aetiologies contributing to nasal congestion for the following considerations. Firstly, the subjective sensation of insufficient airflow, regardless of objective obstruction, could contribute to adverse maternal and fetal outcomes (see Nasal congestion during pregnancy). Secondly, the subjective complaint of nasal stuffiness is a factor in the inclusion criteria of associated clinical trials (Venekamp 2014).

Nasal congestion during pregnancy

Nasal congestion is prevalent during pregnancy; 65% of 2264 women from one prospective study reported nasal congestion at some point in their pregnancy (Bende 1999). However, nasal congestion is a common symptom for various lower respiratory tract diseases, for which the realistic data on its incidence are hard to obtain (Philpott 2004).The most common clinical syndromes that lead to nasal congestion are rhinitis, rhino sinusitis, and upper respiratory viral infections (Corey 2000; Patou 2006). For instance, allergic rhinitis, a frequently reported condition, tends to be the most common cause and occurs during pregnancy in about 18% to 30% of women (Demoly 2003; Incaudo 2004). Pregnancy‐related rhinitis, a recently recognised issue, is clinically defined as nasal congestion presenting during the last six or more weeks of pregnancy without signs of infection and allergy, disappearing within two weeks after delivery; and it is generally reported to have an incidence of around 30% (Ellegard 1999; Ellegard 2000; Ellegard 2005). Since pregnancy aggravates pre‐existing nasal diseases and predisposes women to develop the onset of nasal disorders, the real incidence is somewhat underestimated. (Philpott 2004).

Nasal congestion can cause disturbed sleep, fatigue, anxiety, poor concentration and headache and reduced quality of life (Craig 1998; Edwards 2002; Juniper 1997; Shedden 2005). Studies have indicated that anxiety and disturbed sleep may interfere with fetal development and/or increased adverse fetal outcomes (Pien 2004; Stacey 2011; Teixeira 1999;). There is also evidence of a relationship between maternal mood and the long‐term behaviour of children (Maccari 2003; Van den Bergh 2005). Additionally, discomforting nasal breathing increases the tendency towards mouth breathing and snoring. Mouth breathing may reduce pulmonary vascular tone and/or oxygenation and potentially the oxygen supply to the fetus (Silkoff 2000; Thompson 2000). There are positive links between snoring and maternal hypertension and pre‐eclampsia, or fetal intrauterine growth restriction (IUGR) or lower Apgar scores (Edwards 2002; Franklin 2000; Izci 2003; Silverberg 2011). Uncontrolled nasal congestion could also exacerbate co‐existing diseases such as asthma (Incaudo 2004).

Description of the intervention

There are surgical options for treatment of some nasal concerns (see, for example, Khalil 2006; Lavinsky‐Wolff 2013; Ragab 2006; Stewart 2004a). However, because elective surgery is usually avoided in pregnancy (Walton 2006), this review will only focus on non‐surgical treatments for nasal congestion. Although pregnancy also imposes limitations on other available therapies (Gibert 2005; Metzger 1978), we elected to put no restriction on potential non‐surgical interventions at this stage. Instead, a prudent safety evaluation will be performed and all non‐surgical interventions treating nasal congestion during pregnancy will be considered in this review. The main interventions are classified into the following seven categories.

1. Decongestants (e.g. phenylpropanolamine, pseudoephedrine, xylometazoline and naphazoline) (Demoly 2003; Mazzotta 1999)

2. Anti‐allergy drugs (e.g. corticosteroids, antihistamines, mast cell stabilisers) (Bousquet 2006; Shedden 2005)

3. Immunotherapy (e.g. allergen‐specific immunotherapy) (Keles 2004; Scadding 2008)

4. Anti‐inflammatory drugs (e.g. corticosteroids) (Corey 2000; Kallen 1999)

5. Antibiotics (e.g. β‐lactam antibiotics) (Kenealy 2013; Sorri 1980)

6. Nasal dilation devices (e.g. external or internal dilation devices) (Kirkness 2000; Sadan 2005; Turnbull 1996)

7. Nasal irrigation (e.g. nasal sprayer, bulb syringe with a variety of saline and additives) (Garavello 2010)

8. Behaviour control (e.g. education, avoidance of allergen, raising the head of the bed, physical exercise) (Ellegard 2005; Gregory 1999)

9. 0ther available approaches (e.g. cooling compounds) (Eccles 2003)

It should be noted that some drugs present more than one pharmacological function and possibly combined interventions are required. Drugs may be administered topically or systemically.

How the intervention might work

Medical therapies can influence nasal congestion via three major distinct mechanisms: (1) by hampering the generation of related mediators; (2) by blocking the effects of mediators on targets such as nasal blood vessels; and (3) by mimicking the effects of sympathetic nerve transmitters and causing constriction of nasal blood vessels (Osur 2005). We acknowledge that the underlying mechanisms of these interventions are complex and not completely understood. Here we briefly discuss the dominant functions of some of the interventions.

Nasal decongestants are sympathomimetic drugs that cause vasoconstriction and decrease nasal mucosal swelling by stimulating α‐adrenergic receptors (Demoly 2003). Allergic rhinitis is common in pregnant women, and anti‐allergy drugs or specific immunotherapy could hinder the production of histamine, IgE (Immunoglobulin E) and other inflammatory mediators through competitive binding of H₁ receptors, stabilising the cell wall of the mast cell and causing desensitisation (Demoly 2003). Anti‐inflammatory drugs, mainly corticosteroids, could reduce inflammation by impairing the infiltration of inflammatory cells, diminishing permeability of the nasal mucosa, and possibly decreasing the release of mediators of mast cells (Kallen 1999; Salib 2002). Bacterial infections may accompany nasal congestion, and antibiotics could help relieve the symptoms of this condition (Wallance 2008). The nasal valve area is the narrowest region in the airway, which can be widened by mechanical devices, and both external and internal dilation devices show prominent effects without obvious side‐effects (Kirkness 2000). It is has been hypothesised that nasal irrigation promotes the improvement of nasal symptoms by improving mucociliary function, decreasing mucosal oedema and inflammation, and mechanically clearing secretions and crusts (Tomooka 2000). Raising the head of the bed could reduce the increased nasal congestion in the supine position (Ellegard 2005). Physical exercise has a decongestant effect and benefits sleep disturbance and fatigue due to nasal congestion (Ellegard 2005). Menthol causes an enhanced nasal sensation of airflow by introducing a cool feeling without changing airway resistance (Eccles 2003).

These interventions might provide symptom relief, measured using a Likert‐score, e.g. zero = no congestion through to four = total obstruction or the nasal obstruction symptom evaluation (NOSE) scale (Stewart 2004b) and/or life quality, e.g. Sino‐Nasal Outcome Test (Jiang 2014). Objective nasal restriction could also be eased, which could be evaluated by peak nasal inspiratory flow, performed by recording the maximum value of three breaths, rounded to the nearest 10L/min using a flow meter connected to an mask covering the nose (Spronsen 2008). Patients may report improved symptomatic score and/or life quality. Increased nasal patency may also be observed.

Some pharmacological interventions are teratogens and may exert long‐term adverse effects on offspring (Demoly 2003; Gibert 2005). Although these are not usually prescribed, it may remain prudent to consider the congential malformation rate, that is, the number of fetuses or newborns identified with congenital malformations divided by the total number of fetuses or newborns, regardless of time of delivery and state of fetuses or newborns (whether they are alive or not). Apart from reproductive toxicity, there are other drug side‐effects such as drowsiness ( e.g. first generation anti‐histamine), local irritation (e.g. decongestants), sore throat (e.g. topical corticosteroids) and epistaxis (nosebleeds) (e.g. topical corticosteroids) (Davis 2004). Additionally, concerns about adverse fetal outcomes such as stillbirth, miscarriage, preterm birth, IUGR and neurodevelopment delay have also been raised in some studies (Bjørn 2013; Ensio 2003; Källén 2006; Michael 2008; Morency 2007; Schatz 2004).

Why it is important to do this review

Although there is a wide range of non‐surgical interventions for nasal congestion, there is also a need for evidence‐based information to assist pregnant women and clinicians in their decision making (Sato 2012). Current clinical guidelines provide only limited information about the treatment for nasal congestion during pregnancy (Brożek 2010; Chow 2012; Scadding 2008). The efficacy and safety of non‐surgical interventions for nasal congestion during pregnancy needs to be systematically evaluated.

Objectives

To assess the effects of non‐surgical interventions for nasal congestion during pregnancy and to identify possible adverse effects associated with their use. 

Methods

Criteria for considering studies for this review

Types of studies

We will include randomised or quasi‐randomised controlled trials or cluster‐randomised trials, comparing one or more interventions for treating nasal congestion during pregnancy with placebo or no treatment, or comparing more than two therapeutic strategies. Trials, with or without full text, will be included regardless of publication status. Studies that present in abstract form only will be included. Cross‐over designed trials will be excluded from this review.

Types of participants

Pregnant women experiencing nasal congestion during pregnancy, regardless of maternal age, gestational age, gravidity and parity. We will impose no limits on frequency, duration and severity of nasal congestion.

Types of interventions

All medical interventions for treating nasal congestion, regardless of the dose, frequency, duration, or route of administration.

The interventions are categorised as the following:

• decongestants (e.g. phenylpropanolamine, pseudoephedrine);

• anti‐allergy drugs (e.g. corticosteroids, antihistamines, mast cell stabilisers);

• Immunotherapy (e.g. allergen‐specific immunotherapy);

• anti‐inflammatory drugs (e.g. corticosteroids);

• antibiotics (e.g. β‐lactam antibiotics);

• nasal dilation devices (e.g. external or internal dilation devices);

• nasal irrigation (e.g. nasal sprayer, bulb syringe with a variety of saline and additives);

• behaviour control (e.g. education, avoidance of allergen, raising the head of the bed, physical exercise);

• other available approaches (e.g. cooling compounds).

Comparisons can include:

• one of these interventions versus placebo or no treatment;

• a combination of these interventions versus placebo or no treatment;

• one of these interventions versus another of these interventions;

• a combination of these interventions versus one of these interventions;

• one of these interventions versus a variation on the same intervention (e.g. route of administration).

Types of outcome measures

Primary outcomes

1. Nasal congestion/discomfort, as defined by trial authors

2. Congenital malformation rate

Secondary outcomes

Adverse maternal outcomes

1. Hypertension

2. Pre‐eclampsia

3. Preterm rupture of membranes and preterm prelabour rupture of the membranes

4. Adverse side‐effects (sedation, local irritation, sore throat, epistaxis etc.)

Adverse fetal outcomes

Short term

1. Stillbirth

2. Miscarriage

3. Preterm birth

4. Intrauterine growth restriction

Long term

5. Neurodevelopment delay

Search methods for identification of studies

The following methods section of this protocol is based on a standard template used by the Cochrane Pregnancy and Childbirth Group.

Electronic searches

We will contact the Trials Search Co‐ordinator to search the Cochrane Pregnancy and Childbirth Group’s Trials Register.

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. monthly searches of CINAHL (EBSCO);

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

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

Details of the search strategies for CENTRAL, MEDLINE, Embase and CINAHL, 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 will search ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) for unpublished, planned and ongoing trial reports (see Appendix 1 for planned search terms to be used) .

Searching other resources

1. We will search the reference lists of relevant trials and reviews identified.

2. If necessary, we will contact the authors for details about published or ongoing trials and the pharmaceutical companies for more information.

3. We will contact organisations, individual experts working in this field for additional information.

We will not apply any language or date restrictions. 

Data collection and analysis

Selection of studies

Two review authors will independently assess for inclusion all the potential studies we identify as a result of the search strategy. We will resolve any disagreement through discussion or, if required, we will consult a third person.

Data extraction and management

We will design a form to extract data (see Appendix 2). For eligible studies, at least two review authors will extract the data using the agreed form. We will resolve discrepancies through discussion or, if required, we will consult a third person We will enter data into Review Manager software (RevMan 2014) and check for accuracy.

When information regarding any of the above is unclear, we will attempt to contact authors of the original reports to provide further details.

Assessment of risk of bias in included studies

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

(1) Random sequence generation (checking for possible selection bias)

We will describe for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.

We will assess the method as:

• low risk of bias (any truly random process, e.g. random number table; computer random number generator);

• high risk of bias (any non‐random process, e.g. odd or even date of birth; hospital or clinic record number);

• unclear risk of bias.   

(2) Allocation concealment (checking for possible selection bias)

We will describe for each included study the method used to conceal allocation to interventions prior to assignment and will assess whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.

We will assess the methods as:

• low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

• high risk of bias (open random allocation; unsealed or non‐opaque envelopes, alternation; date of birth);

• unclear risk of bias.   

(3.1) Blinding of participants and personnel (checking for possible performance bias)

We will describe for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess the methods as:

• low, high or unclear risk of bias for participants;

• low, high or unclear risk of bias for personnel.

(3.2) Blinding of outcome assessment (checking for possible detection bias)

We will describe for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received.  We will assess blinding separately for different outcomes or classes of outcomes.

We will assess methods used to blind outcome assessment as:

• low, high or unclear risk of bias.

(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)

We will describe for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re‐include missing data in the analyses which we undertake.

We will assess methods as:

• low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);

• high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation);

• unclear risk of bias.

(5) Selective reporting (checking for reporting bias)

We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found.

We will assess the methods as:

• low risk of bias (where it is clear that all of the study’s pre‐specified outcomes and all expected outcomes of interest to the review have been reported);

• high risk of bias (where not all the study’s pre‐specified outcomes have been reported; one or more reported primary outcomes were not pre‐specified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported);

• unclear risk of bias.

(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)

We will describe for each included study any important concerns we have about other possible sources of bias.

We will assess whether each study was free of other problems that could put it at risk of bias:

• low risk of other bias;

• high risk of other bias;

• unclear whether there is risk of other bias.

(7) Overall risk of bias

We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Handbook (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings.  We will explore the impact of the level of bias through undertaking sensitivity analyses ‐ seeSensitivity analysis. 

Measures of treatment effect

Dichotomous data

For dichotomous data, we will present results as summary risk ratio with 95% confidence intervals. 

Continuous data

For continuous data, we will use the mean difference if outcomes are measured in the same way between trials. We will use the standardised mean difference to combine trials that measure the same outcome, but use different methods.  

Unit of analysis issues

Cluster‐randomised trials

We will include cluster‐randomised trials in the analyses along with individually‐randomised trials. We will adjust their sample sizes using the methods described in the Handbook using an estimate of the intra‐cluster correlation co‐efficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster‐randomised trials and individually‐randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit is considered to be unlikely.

We will also acknowledge heterogeneity in the randomisation unit and perform a subgroup analysis to investigate the effects of the randomisation unit.

Other unit of analysis issues

Trials with more than two treatment groups

If we identify any multi‐arm trials, we will include these if any pair‐wise comparisons of the intervention groups are relevant to the review and meet our inclusion criteria. We will report all the intervention groups involved in the study in the 'Characteristics of included studies', but we will include only those intervention groups relevant to the review in the analysis. We will address pair‐wise comparisons in multi‐arm trials in relevant meta‐analyses if they are eligible for the analysis, and we will ensure that data from any individual arm are included only once when pooling data. If there are multiple intervention groups in a particular meta‐analysis, we will combine all relevant experimental intervention groups of the study into a single intervention group and combine all relevant control intervention groups into a single control group. For dichotomous outcomes, both the sample sizes and the number of people with events can be summed across the groups. For continuous outcomes, means and standard deviations can be combined using related formulae (Higgins 2011, Table7.7.a).

Dealing with missing data

For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

For all outcomes, we will carry out analyses, as far as possible, on an intention‐to‐treat basis, i.e. we will attempt to include all participants randomised to each group in the analyses, and all participants will be analysed 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 will be the number randomised minus any participants whose outcomes are known to be missing.

Assessment of heterogeneity

We will assess statistical heterogeneity in each meta‐analysis using the T², I² and Chi² statistics. We will regard heterogeneity as substantial if an I² is greater than 30% and either a T² is greater than zero, or there is a low P value (less than 0.10) in the Chi² test for heterogeneity. 

Assessment of reporting biases

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 will carry out statistical analysis using the Review Manager software (RevMan 2014). We will use fixed‐effect meta‐analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect: i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random‐effects meta‐analysis to produce an overall summary, if an average treatment effect across trials is considered clinically meaningful. The random‐effects summary will be treated as the average range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful, we will not combine trials.

If we use random‐effects analyses, the results will be presented as the average treatment effect with 95% confidence intervals, and the estimates of  T² and I².

Subgroup analysis and investigation of heterogeneity

If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random‐effects analysis to produce it.

We plan to carry out the following subgroup analyses.

1. Different aetiologies: pregnant rhinitis versus other rhinitis; allergic rhinitis versus non‐allergic rhinitis

2. Gestational age: first trimester versus second trimester; first trimester versus third trimester; second trimester versus third trimester

3. Study design: randomised trials versus quasi‐randomised trials

The following outcomes will be used in subgroup analysis.

1. Effectiveness of interventions

2. Congenital malformation rate

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

Sensitivity analysis

We will carry out sensitivity analysis to explore the effect of trial quality on important outcomes in the review. Where there is a high risk of bias in the allocation of participants to groups associated with a particular study or high levels of missing data, we will explore this by sensitivity analysis.

We will use the following primary outcomes in sensitivity analysis.

1. Nasal congestion/discomfort, as defined by trial authors

2. Congenital malformation rate

Appendices

Appendix 1. Search terms

nasal AND pregnancy

rhinitis AND pregnancy

sinusitis AND pregnancy

decongestants AND pregnancy

congestion AND pregnancy

Appendix 2. Standardised data extraction tool

Contact author, year of publication, country of origin, journal citation and language.

• Study methods ( e.g. trial design, duration)

• Interventions (type, dose, duration, route of delivery, control used, run‐in phase, treatment phase, follow‐up)

• Outcome data for each of the primary and secondary outcomes above

• Participants (number, age, source, duration of symptoms, previous treatments, underlying conditions, drop‐outs/withdrawals.

What's new

Date	Event	Description
8 August 2017	Amended	Added Published notes to clarify that this protocol has now been withdrawn from publication in the Cochrane Library

History

Protocol first published: Issue 4, 2015

Date	Event	Description
11 June 2015	Amended	Added Acknowledgements statement.

Contributions of authors

Dr Wei Wei and Dr Hongqian Liu both wrote the initial and final versions of the protocol. Prof He Wang, Prof Deying Kang and Prof Christine East commented on the final version of the protocol.

Sources of support

Internal sources

• Department of Obstetrics and Gynaecology, West China Second University Hospital, Sichuan University., China.

• Prenatal Diagnosis Center of Sichuan Province, China.

• Department of EBM and Clinical Epidemiology, West China Hospital, Sichuan University, China.

External sources

• No sources of support supplied

Declarations of interest

Wei Wei: none known.

Hongqian Liu: none known.

Deying Kang: none known.

He Wang: none known.

Christine East: has Career Development Fellowship funding from the Australian National Health and Medical Research Council ‐ the program of this fellowship includes systematic reviews.

Notes

This review will no longer be prepared by the review team and this protocol has now been withdrawn from publication in the Cochrane Library.

Withdrawn from publication for reasons stated in the review