Antibiotics for hospital‐acquired pneumonia in children

Abstract

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

To compare different antibiotics in order to identify effective and safe antibiotic drug therapies for children with hospital‐acquired pneumonia (HAP) (including ventilator‐associated pneumonia (VAP) and HAP without mechanical ventilation).

Background

Description of the condition

Hospital‐acquired pneumonia (HAP) or nosocomial pneumonia is a type of pneumonia that develops at least 48 hours after being admitted to hospital and that was not present at the time of hospital admission (NICE 2014). Ventilator‐associated pneumonia (VAP) is a subtype of HAP. VAP is a lung infection diagnosed in patients undergoing mechanical ventilation for at least 48 hours (ATS 2005). HAP and VAP are serious diseases that are often difficult to treat in clinical practice and remain an important cause of morbidity and mortality (Song 2008).

It is estimated that HAP has a rate of 5 to 10 per 1000 hospital admissions (ATS 2005). For patients in the intensive care unit (ICU), the incidence of HAP increases significantly; in both Europe and the United States, pneumonia is the most frequent cause of hospital‐acquired infection in ICUs (Richards 2000; Vincent 2009). Although nearly 90% of episodes of HAP occur during mechanical ventilation in ICU patients, it is often difficult to identify the exact incidence of VAP because of possible overlap with other lower respiratory tract infections, such as infectious tracheobronchitis in mechanically ventilated patients (ATS 2005). Depending on the case definition of pneumonia and the population under evaluation, the exact incidence varies widely (Eggimann 2003). Data published by the National Nosocomial Infection Surveillance program indicates that in paediatric ICUs, VAP is the second most frequent cause of nosocomial infection (Cernada 2013; Richards 1999). As such, VAP constitutes 20% of nosocomial infection in paediatric ICUs, with rates of six episodes per 1000 ventilator days (Cernada 2013).

Description of the intervention

Compared with community‐acquired pneumonia (CAP), HAP and VAP are more likely to be infections caused by colonised bacteria and multi‐drug resistant (MDR) pathogens (ATS 2005). The pathogens commonly associated with HAP/VAP are aerobic gram‐negative bacilli, such as Pseudomonas aeruginosa (P. aeruginosa), Escherichia coli (E. coli), Klebsiella pneumoniae (K. pneumoniae), and Acinetobacter species. For patients with HAP and VAP, the time of onset of pneumonia is important for specific pathogens and outcomes as an epidemiologic variable and risk factor. Early‐onset HAP and VAP, occurring within the first four days of hospitalisation, generally have a better prognosis, and the pathogens are more likely to be antibiotic‐sensitive bacteria, such as Streptococcus pneumoniae (S. pneumoniae), Haemophilus influenzae (H. influenzae), Staphylococcus aureus (S. aureus), E. coli and K. pneumoniae; while late‐onset HAP and VAP (five days or more of hospitalisation) are more likely to be caused by MDR pathogens (including S. aureus, P. aeruginosa, K. pneumoniae and Enterobacter spp et al), and results in increased patient mortality and morbidity. The number of patients with HAP caused by MDR pathogens such as methicillin‐resistantS. aureus (MRSA), P. aeruginosa and Acinetobacter spp et al shows an increasing trend. However, colonisation and infection with MDR pathogens is more likely to happen in patients with early‐onset HAP who have received prior antibiotics or who have had prior hospitalisation within the previous 90 days; these patients, they should be treated similar to patients with late‐onset HAP or VAP. According to the ATS guideline (ATS 2005), the key decision in initial empiric therapy is whether the patient has risk factors for MDR organisms rather than the time of onset of HAP/VAP (Selim 2010). Other risk factors for MDR pathogens include (ATS 2005):

1. antimicrobial therapy in the preceding 90 days;

2. current hospitalisation of five days or more;

3. high frequency of antibiotic resistance in the community or in the specific hospital unit;

4. immunosuppressive disease and/or therapy;

5. presence of risk factors for healthcare‐associated pneumonia (HCAP).

Empiric therapy is defined as the use of antibiotics before the confirmation of a definitive diagnosis of infection, and where the patient would face greater risk by observation than by treatment (Kim 1989). In contrast, the primary objective of directed therapy is to help confirm a suspected diagnosis, involving a specific treatment of pre‐determined duration (Kim 1989). The following statement explains the principles determining antimicrobial use for HAP: "Choose empiric antimicrobial wisely (broad‐spectrum), start early, hit hard with an appropriate dosing schedule, de‐escalate rapidly (narrow spectrum) and stop abruptly (post adequate duration)" (Morrow 2009). The ATS guideline indicates that individual empirical antibiotic selection should be based on the risk for MDR pathogens (Selim 2010). Inappropriate initial antimicrobial therapy refers to drugs not covered by the target pathogen, or pathogen resistance to the antimicrobial drug. The most important independent factor that affects mortality in HAP is inappropriate initial empiric therapy and the delayed application of antibiotics (Masterton 2008; Torres 2009). Therefore, once the diagnosis of bacterial HAP/VAP is established, even when bacteria are not found in respiratory secretions, there is a need for immediate broad‐spectrum antimicrobial drugs (Torres 2009). The initial empirical antibiotic selection should cover possible common bacteria, the patient should be treated and observed for the first three days, and then a decision should be made on whether to continue or change to other options according to the therapeutic response. Once pathogens are specific, treatment should immediately be changed to sensitive, targeted narrow‐spectrum antimicrobial drugs (Torres 2009). In addition, all antibiotics for HAP/VAP should be selected according to the local epidemiological data.

How the intervention might work

Pneumonia is the leading cause of mortality in children below the age of five (WHO 2015). Identifying pathogens in children with pneumonia is not easy, and to meet public health goals of reducing childhood mortality caused by pneumonia, appropriate antibiotic administration is employed in most instances (Lodha 2013). As appropriate antimicrobial treatment for patients with HAP will significantly improve prognosis, more rapid identification of infection and accurate selection of antimicrobial agents for patients are vital clinical goals we should focus on (Chastre 2002; Kollef 2003).

Why it is important to do this review

A guideline published in 2005 by the American Thoracic Society and Infectious Diseases Society of America recommended antibiotics specifically for adults with HAP (ATS 2005). The latest edition of Therapeutic Guidelines does not address children with HAP (only listing paediatric doses in an adult framework) (NICE 2014). Also, antibiotic administration is at the core of treatment of HAP in children, and its optimal management remains controversial. Therefore, it is important to know what the best management is for HAP in children.

Objectives

To compare different antibiotics in order to identify effective and safe antibiotic drug therapies for children with hospital‐acquired pneumonia (HAP) (including ventilator‐associated pneumonia (VAP) and HAP without mechanical ventilation).

Methods

Criteria for considering studies for this review

Types of studies

We will include all randomised controlled trials (RCTs) comparing antibiotic treatment regimens for children with HAP (including VAP and HAP without mechanical ventilation).

Types of participants

We will include children up to (not including) 18 years of age with HAP (including VAP and HAP without mechanical ventilation) diagnosed by clinical and/or radiological features and/or quantitative culture of respiratory specimens. We will also include studies of children with suspected HAP/VAP. The participants must have signs and symptoms of a pneumonia infection, including: fever; leukocytosis (increased numbers of white blood cells); and/or purulent tracheal secretions. We will exclude data from children with immune suppression or dysfunction related to primary diagnoses. We will exclude data from children at‐risk due to disorders such as cystic fibrosis, primary ciliary dyskinesia, congenital heart disease, etc. We will also exclude data from neonates.

Types of interventions

We will include studies comparing one antibiotic regimen with another antibiotic regimen or placebo. We will also include trials evaluating monotherapy versus combination therapy. We will classify antibiotic groups as follows.

1. β‐lactams.

2. Lincosamides.

3. Glycopeptide antibiotics.

4. Quinolones.

5. Aminoglycosides.

6. Macrolides.

7. Antibacerial oxazolidinone agents.

8. Anti anaerobic antibiotics fungi: e.g. Flagyl.

Types of outcome measures

Primary outcomes

1. Clinical cure. The definition of clinical cure is symptomatic and involves clinical recovery by the end of treatment.

2. Treatment failure rates. The definition of treatment failure is the presence of any of the following: development of chest indrawing, convulsions, drowsiness or inability to drink at any time, respiratory rate above the age‐specific cut‐off point on completion of treatment, or oxygen saturation of less than 90% (measured by pulse oximetry) after completion of the treatment. Loss to follow‐up or withdrawal from the study at any time after recruitment will indicate failure in the analysis.

3. Mortality rate.

Secondary outcomes

The clinically relevant outcome measures will be as follows.

1. Relapse rate: defined as children declared ’cured’, but developing recurrence of disease at follow‐up in a defined period.

2. Length of hospital stay: duration of total hospital stay (from day of admission to discharge) in days.

3. Need for change in antibiotics: children requiring change in antibiotics from the primary regimen.

4. Attributable adverse events and/or any events requiring discontinuation of the trial antibiotic.

Search methods for identification of studies

Electronic searches

We will identify trials from searches of the following databases:

1. Cochrane Acute Respiratory Infections Group Trials Register;

2. Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library;

3. MEDLINE (Ovid);

4. Embase.com;

5. LILACS;

6. Chinese Biomedical Literature Database (CBM).

The proposed MEDLINE strategy is shown in Appendix 1. We will combine this with the Cochrane highly sensitive search strategy for identifying randomised trials sensitivity‐ and precision‐maximising version (2008 revision) and adapt this for use in the other databases. We will also conduct a search of ClinicalTrials.gov (http://clinicaltrials.gov) and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/en/). We will search all databases from their inception to the present and we will not impose any restriction on the language of publication.

Searching other resources

We will contact authors/experts in the field for unpublished and ongoing trials. We will also check the reference lists of retrieved studies. We will not apply any language restrictions.

Data collection and analysis

Selection of studies

Two review authors (LJ, GG) will independently screen titles and abstracts for inclusion of all the potential studies we identify as a result of the search.

We will retrieve the full‐text study reports/publication and two review authors (LJ, CW) will independently screen the full‐text and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third review author (LZ). We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram (BMJ 2009) and 'Characteristics of excluded studies' table.

Data extraction and management

Two review authors (LJ, GG) will independently extract data using pre‐designed forms. We will resolve discrepancies through consensus or, if required, we will consult a third review author (DM). The extracted data will include the following information: details of source, eligibility, methods, participants, interventions, outcomes and results.

If any included studies involve both children and adults, we will extract data separately for children. If any of the information above is inadequate, we will contact the authors of the primary study to provide further details and clarification.

If any included studies are not in English or Chinese, we will contact translators with relevant language skills to help us extract the necessary data.

Assessment of risk of bias in included studies

Two review authors (LJ, YD) will independently assess risk of bias according to the following domains using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve disagreements by discussion among co‐authors.

1. Random sequence generation.

2. Allocation concealment.

3. Blinding of participants and personnel.

4. Blinding of outcome assessment.

5. Incomplete outcome data.

6. Selective outcome reporting.

7. Other bias.

We will grade each potential source of bias as high, low or unclear and provide a quote from the study report, together with a justification for our judgement in the 'Risk of bias' tables. We will summarise the risk of bias judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes, where necessary. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table.

When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome.

Assesment of bias in conducting the systematic review

We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

For dichotomous data, we will present results as summary risk ratios (RRs) or odds ratio (ORs) with 95% confidence intervals (CIs); we will also use the RR to measure time‐to‐event data. We will use the mean difference (MD) for measuring continuous data. For trials that measure the same outcome, but use different methods, we will use the standardised mean difference (SMD) to combine results.

Unit of analysis issues

We will include cluster‐randomised trials and cross‐over trials along with individually‐randomised trials. In this systematic review, we will treat each group or cluster in cluster‐randomised trials as the unit of analysis; we will use the intracluster correlation coefficient (ICC) to estimate the relative variability within and between clusters, according to the relevant section of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). For cross‐over trials with binary outcomes, we will adopt the Becker‐Balagtas approach to combine cross‐over trials with parallel trials for meta‐analysis (Stedman 2011). For cross‐over trials with continuous outcomes, each individual will act as the unit of analysis and we will conduct approximate paired analyses (Higgins 2011).

Dealing with missing data

We will conduct intention‐to‐treat analyses, when data on individuals are missing, such as when randomised participants are excluded from the analysis. We will follow recommendations in the Cochrane Handbook for Systematic Reviews of Interventions regarding strategies for dealing with missing data (Higgins 2011). These are:

1. whenever possible, we will contact the original investigators to request missing data;

2. we will make explicit the assumptions of any methods used to cope with missing data: for example, that the data are assumed missing at random, or that missing values were assumed to have a particular value such as a poor outcome;

3. we will perform sensitivity analyses to assess how sensitive results are to reasonable changes in the assumptions that are made; and

4. we will address the potential impact of missing data on the findings of the review in the discussion section.

The minimum number of contact attempts we will try will be three.

Assessment of heterogeneity

We will assess heterogeneity among studies in two ways. Firstly, we will assess heterogeneity at face value: heterogeneity in population, interventions, or outcomes. Secondly, we will use a Chi² test (P ≤ 0.10 is considered to be consistent with statistical heterogeneity) and the I² statistic to assess presence of statistical heterogeneity (> 50% is substantial heterogeneity, > 75% is considerable heterogeneity; Higgins 2011).

Assessment of reporting biases

We will use funnel plots to detect small‐study effects including publication bias, if we find a sufficient number of studies. 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 statistical heterogeneity is detected (I² statistic > 0%), 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 of the 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 I² statistic. If appropriate, a Network meta‐analyses would be considered.

GRADE and 'Summary of findings' table

We will create a 'Summary of findings' table using the following outcomes: clinical cure, treatment failure rates, relapse rate, need for change in antibiotics, mortality rate, length of hospital stay and adverse events reported. We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies which contribute data to the meta‐analyses for the prespecified outcomes (GRADE 2004). We will use methods and recommendations described in Section 8.5 and Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) using GRADEproGDT software (GRADEproGDT 2015). We will justify all decisions to down‐ or up‐grade the quality of studies using footnotes and we will make comments to aid the reader's understanding of the review where necessary.

Subgroup analysis and investigation of heterogeneity

We will perform a subgroup analysis of:

1. early‐onset HAP versus late‐onset HAP (HAP without mechanical ventilation);

2. early‐onset VAP versus late‐onset VAP.

Sensitivity analysis

We will perform a sensitivity analysis of the impact of high risk of bias on the outcome of the meta‐analysis.

Appendices

Appendix 1. Detailed search strategies

exp Pneumonia/ OR (pneumon* or bronchopneumon* or pleuropneumon* or tracheobronchit* or tracheo bronchit*).tw. OR (vap or hap or hcap).tw. OR Respiratory Tract Infections/ OR (respiratory infection* or respiratory tract infection*).tw. OR exp Ventilators, Mechanical/ OR ventilat*.tw. OR intubation/ OR intubation, intratracheal/ OR intubat*.tw. OR exp Drug Resistance, Bacterial/ OR drug resistance, multiple/ OR drug resistance, multiple, bacterial/ OR (bacteria* adj2 ((multidrug or multi‐drug or multiple drug or antibiotic) adj2 resistan*)).tw. OR (mdr or mdro).tw.

AND

exp Anti‐Bacterial Agents/ OR (antibiotic* or antibacterial* or anti‐bacterial* or antimicrobial* or anti‐microbial*).tw. OR Amikacin/ OR Colistin/ OR Vancomycin/ OR exp Gentamicins/ OR (amikacin* or colistin* or vancomycin* or gentamicin* or gentamycin*).tw,nm.

AND

exp Infant/ OR exp Child/ OR exp Adolescent/ OR exp Minors/ OR exp Puberty/ OR exp Pediatrics/ OR exp Schools/ OR (Infant* OR infancy OR Newborn* OR Baby* OR Babies OR Neonat* OR Preterm* OR Prematur* OR Postmatur* OR Child* OR Schoolchild* OR School age* OR Preschool* OR Kid or kids OR Toddler* OR Adoles* OR Teen* OR Boy* OR Girl* OR Minors* OR Pubert* OR Pubescen* OR Prepubescen* OR Paediatric* OR Paediatric* OR Peadiatric* OR Nursery school* OR Kindergar* OR Primary school* OR Secondary school* OR Elementary school* OR High school* OR Highschool*)

AND

((randomized controlled trial or controlled clinical trial).pt. or randomized.ab. or randomised.ab. or placebo.ab. or drug therapy.fs. or randomly.ab. or trial.ab. or groups.ab.) not (exp animals/ not humans.sh.)

What's new

Date	Event	Description
25 February 2019	Amended	Protocol for a Cochrane Review withdrawn from publication.
25 February 2019	New citation required and minor changes	Protocol for a Cochrane Review withdrawn from publication.

Contributions of authors

Roles and responsibilities
Task	Responsible
Protocol stage: draft the protocol	Lucan Jiang, Lingli Zhang
Review stage: select which trials to include (2 + 1 arbiter)	Lucan Jiang, Ge Gui, Chaomin Wan
Review stage: extract data from trials (2 + 1 arbiter)	Lucan Jiang, Ge Gui, Dezhi Mu
Review stage: enter data into RevMan	Lucan Jiang, Ge Gui
Review stage: carry‐out the analysis	Yanjun Duan, Lingli Zhang
Review stage: interpret the analysis	Yanjun Duan, Chaomin Wan
Review stage: draft the final review	Lucan Jiang, Dezhi Mu, Lingli Zhang
Update stage: update the review	Lucan Jiang, Lingli Zhang

Sources of support

Internal sources

• Sichuan University, China.

External sources

• Natural Science Foundation of China, China.

  Evidence based establishment of evaluation index system for paediatric rational drug use in China (No. 81373381)

Declarations of interest

Lucan Jiang: no known conflicts of interest. Dezhi Mu: no known conflicts of interest. Lingli Zhang: National Natural Science Foundation of China（No. 81373381&#65289. The grant of National Natural Science Foundation of China has no role in study design, data collection and analysis or preparation of this review. Ge Gui: no known conflicts of interest. Yanjun Duan: no known conflicts of interest. Chaomin Wan: no known conflicts of interest.

Notes

The authors of this protocol were not able to complete the review or comply with agreed editorial timelines. The review was therefore rejected on the grounds of timeliness.

Withdrawn from publication for reasons stated in the review