A Study of the Impact of Penicillin Allergy on Antimicrobial Resistance and ouTcomes
Conditions: Penicillin Allergy, Antimicrobial Drug Resistance, AMR
Sponsor: University of Leeds

 
1 
IMPAART STUDY PROTOCOL 
  
A study of the Impact of Penicillin 
Allergy on Antimicrobial Resistance and 
ouTcomes  
 
 
 
Version 1. 3 25/01/2022 
IRAS ID: 296638 
 
 
Contents 
1. 
BACKGROUND AND RATIONALE ............................................................................................ 2 
2. 
AIM & OBJECTIVES ..................................................................................................................... 4 
3. 
STUDY DESIGN ........................................................................................................................... 6 
4. 
STUDY PARTICIPANTS .............................................................................................................. 8 
5. 
SCREENING AND RECRUITMENT .......................................................................................... 9 
6. 
STUDY PROCEDURES ............................................................................................................... 9 
7. 
STATISTICAL ANALYSIS .......................................................................................................... 12 
8. 
ETHICAL PRINCIPLES .............................................................................................................. 13 
9. 
DATA PROTECTION.................................................................................................................. 15 
10. 
REFERENCES ........................................................................................................................ 16 
 
 
 

 
2 
1. BACKGROUND AND RATIONALE 
Effective and safe antibiotic prescribing for the treatment of infections is obstructed by incorrect 
penicillin allergy records for an estimated 2.7 million people in England (West et al., 2019).  In the 
UK, 6% of primary care and 14% of hospitalised patients are reported to have a penicillin allergy, 
but only a fraction of these patients have genuine allergy on further testing (Baxter et al., 2020, 
Shenoy et al., 2019, West et al., 2019). Patients who have a penicillin allergy record have a higher 
prevalence of antimicrobial resistance (AMR), have longer hospital stays, receive repeated 
courses of antibiotic therapy and have higher rates of in-hospital mortality when compared to 
patients without a penicillin allergy record (Macy and Contreras, 2014, Blumenthal et al., 2018, 
West et al., 2019). These patients are also more likely to receive broad spectrum antibiotics such 
as macrolides, tetracyclines, cephalosporins, fluroquinolones and clindamycin (West et al., 2019). 
Escalating antimicrobial resistance (AMR) is a global health concern, to which penicillin allergy 
contributes. In the context of the current global COVID-19 pandemic tackling AMR must be 
considered alongside managing the pandemic. Antibiotic use in patients with COVID-19 is high, 
with three quarters of inpatients being prescribed antibiotics (Langford et al., 2021) despite the 
prevalence of bacterial infections being reported as 7-9% (Langford et al., 2020, Lansbury et al., 
2020, Rawson et al., 2020). The effect of the pandemic on AMR is still uncertain, however 
disproportionate and unnecessary antibiotic prescribing in patients hospitalised with COVID-19 is 
likely to impact on AMR and on patient outcomes. A penicillin allergy record will influence antibiotic 
prescription and patients with a penicillin allergy record are more likely to receive broad spectrum 
antibiotics in place of recommended first line penicillin antibiotics when compared with patients 
without a penicillin allergy.  The impact of antibiotic prescribing in patients with COVID-19 who 
have a penicillin allergy has not been investigated. However, if we extrapolate from pre-pandemic 
data, we can assume that patients hospitalised with COVID-19 who have a penicillin allergy 
record and are treated for bacterial infections will be at risk of longer hospital stays, higher rates 
of treatment failure and have higher mortality when compared to patients without a penicillin 
allergy record.  
The focus of this research is the intersection between COVID-19, penicillin allergy and AMR. 
Penicillin allergy records are well recognised to have a significant impact on antibiotic prescribing, 
clinical outcomes and AMR. We will explore how antibiotic prescribing and clinical outcomes are 
impacted by penicillin allergy in patients with COVID-19, how penicillin allergy affects the oral and 
GI resistome (the composition of AMR genes present), and whether removing incorrect penicillin 
allergy records results in a change in the composition of the oral and GI resistome. 

 
3 
Studies analysing the oral resistome (composition of AMR genes found in the oral microbiota), 
have shown an abundance of AMR genes coding for macrolide, fluroquinolones and tetracycline 
resistance (Almeida et al., 2020, Carr et al., 2020, Lancaster et al., 2003). Additionally, studies 
have shown that antibiotic classes used in patients with penicillin allergy are more likely to select 
out resistance in the oral and gut microbiota.  Administration of azithromycin has been linked to 
increases in resistance genes to both macrolide and non-macrolide (aminoglycosides, beta-
lactams, trimethoprim, and metronidazole) antibiotics found in the gut microbiome (Doan et al., 
2020). Garcia-Rey et al demonstrated that rates of co-resistance to erythromycin and penicillin in 
Streptococcus pneumoniae was significantly more associated with the use of macrolides 
compared to β-lactam antibiotics (such as penicillins and cephalosporins) (Garcia-Rey et al., 
2002).  Additionally, the use of cephalosporins is more likely to select for penicillin resistance in 
Streptococcus pneumoniae when compared to aminopenicillins (Granizo et al., 2000, Garcia-Rey 
et al., 2002). An experimental mouse model found that treatment for urinary tract infection with 
ciprofloxacin or fosfomycin was more likely to select for resistance genes to multiple classes of 
antibiotics in the gut microbiome when compared with ampicillin (Xu et al., 2020).  
Justification for study:- 
• 
Poor antimicrobial stewardship is prevalent in treating patients with COVID-19 
• 
Penicillin allergy leads to increased antibiotic use, treatment failure and AMR. 
• 
Antibiotics used in place of narrow spectrum penicillin antibiotics in patients with penicillin 
allergy have a greater tendency to select for resistant bacteria. 
• 
Higher prevalence of AMR in the oral and GI tract microbiota may be contributing to higher 
rates of treatment failure and death seen in patients with penicillin allergy. 
• 
Understanding the resistome of patients with penicillin allergy will improve antibiotic 
prescribing and antibiotic stewardship. 
 
We plan to further investigate the relationships between antimicrobial resistance, penicillin allergy 
and patient outcomes in a programme of work that will run in conjunction with the ALABAMA trial. 
Our hypothesis is that patients with a penicillin allergy record are more likely to have resistance 
to non-penicillin antibiotics in their normal flora and that this will increase their risk of treatment 
failure with non-penicillin antibiotics. In particular, penicillin allergic patients admitted with COVID-
19 who have bacterial infections will have an increased risk of treatment failure and poor 
outcomes. 

 
4 
Shotgun metagenomics is the untargeted sequencing of all microbial genomes present in a 
sample. This method allows the detection of all micro-organisms present (including uncultivable 
bacteria) as well as enabling detection of AMR genes. We will utilise metagenomic methods 
including meta-transcriptomics which will enable analysis of differential gene expression to give 
use an in-depth profile of the microbiota as well as an inference of metabolic activity through gene 
expression. We will also undertake phenotypic validation of the inferred genotypic results using 
traditional culture and antibiotic susceptibility testing methods.   
 
2. AIM & OBJECTIVES 
 
Aim  
IMPAART will investigate the impact of penicillin allergy on AMR and health outcomes in patients 
with COVID-19. 
Objectives  
• 
To determine if, in patients admitted with COVID-19, the presence of a penicillin allergy 
record impacted on antibiotic prescribing, the rate of treatment failure of bacterial 
infections, length of hospital stay, Clostridioides difficile infection and mortality.  
• 
To profile the resistome in patients with a penicillin allergy record 
• 
To describe the differences in the presence and diversity of resistance genes in the oral 
and gastrointestinal microbiota of patients with and without a penicillin allergy record. 
• 
To determine if the abundance of antibiotic resistance genes can be reversed/reduced by 
correcting incorrect penicillin allergy records. 
 
Feasibility objectives 
• 
To determine how many ALABAMA trial participants are willing to consent to giving 
saliva/stool samples 
• 
To determine how many ALABAMA trial participants who have consented to saliva/stool 
sample collection actually provide saliva samples (during both face to face consultation 
and/or via the post) 
• 
To determine how many saliva/stool samples that are collected can be analysed by 
metagenomics and transcriptomics  

 
5 
• 
To determine the practicality of obtaining samples within specific time frames. 
 

 
6 
3. STUDY DESIGN 
 
This research will be conducted in three work streams (WS); WS1 will use data collected during 
the NIHR funded PEACH study and WS2 and 3 will run alongside the ALABAMA trial ‘AntiBiotics, 
Allergy and Microbial ResistAnce’:  
WS 1 -  A retrospective cohort study to determine how penicillin allergy impacts on antibiotic use 
and clinical outcomes in patients admitted with COVID-19 (Objective 1). This work stream is 
named IMPAART-C: A study of the Impact of Penicillin Allergy on Antimicrobial Resistance and 
health outcomes in patients with COVID-19. 
WS 2 - A cross-sectional study to investigate differences in the carriage of antimicrobial resistance 
genes in the oral and GI flora of patients with and without a penicillin allergy record (Objectives 
2,3 5-9). This study is a separate but related study to the ALABAMA trial.  
WS 3 - A feasibility study to investigate whether AMR genes are lost in patients who have their 
penicillin allergy label removed (Objectives 4, 5-9.) This study is related to the ALABAMA trial and 
will run in conjunction with it.  
 
3.1  WS1 outcomes  
Primary outcome 
• 
Mortality rates (day 60)  between patients with and without PenA  
Secondary outcomes 
• 
Length of hospital stay 
• 
ICU admission rates 
• 
Total antibiotic usage (including antibiotic agent, route of administration and durations) 
• 
Treatment failure (defined as re-prescription of an antibiotic within 28 days of index 
antibiotic prescription) 
• 
Number of patients with Clostridioides difficile infection 
• 
Mortality rates (day  30) between patients with and without PenA 
• 
Number of patients with infections with AMR organisms (Presence antimicrobial resistant 
secondary bacterial infection) 
 

 
7 
 
 
3.2  WS2 outcomes 
Primary outcome  
• 
The prevalence of antibiotic resistance genes in the mouth and GI tract of patients with 
and without a penicillin allergy record. 
Secondary outcomes 
• 
The measure the difference in diversity of antimicrobial resistance genes in the mouth and 
GI tract of patients with and without a penicillin allergy record. 
• 
The number of resistance genes to specific antibiotic classes present in the mouth and GI 
tract of patients with and without a penicillin allergy record. 
• 
To determine whether a metagenomic or transcriptomic approach could be used to predict 
phenotypic antibiotic susceptibility 
 
3.3  WS3 outcomes 
Feasibility outcomes 
• 
The number of patients recruited to ALABAMA who consent to participate in the sub-study 
• 
The number of participants who provide a sample at baseline 
• 
The number of participants who provide a second sample > 6 months after enrolment 
• 
The relationship between ARG abundance and treatment response failure 
• 
The relationship between ARG richness and treatment response failure. 
Clinical outcomes: 
The primary outcome is the change in antibiotic resistance gene abundance over time between 
trial arms, in the subset of trial patients who have at least one antibiotic prescription prior to their 
second sampling 
Secondary outcomes 
• 
To measure the change in the abundance and richness of antimicrobial resistance genes 
over time between trial arms 
• 
The relationship between ARG abundance & richness, and treatment response failure 
(defined as re-presentation with worsening or non-resolving symptoms following 
treatment with an antibiotic up to 28 days after initial antibiotic prescription) 
• 
The number and abundance of ‘non-penicillin’ antibiotic resistance genes 
• 
The number and abundance of ‘penicillin’ resistance genes 
 

 
8 
 
4. STUDY PARTICIPANTS 
 
4.1 WS1 participants  
PEACH study (HTA Project: NIHR132254 - Procalcitonin: Evaluation of Antibiotic use in COVID-
19 Hospitalised patients (PEACH); https://fundingawards.nihr.ac.uk/award/NIHR132254) 
participants, which includes adults and adolescents 16 years old and older, admitted to hospital 
between 1/2/20 and 30/06/20 with a positive SARS-CoV-2 test.  
Patients with their allergy status missing will be excluded, and the numbers will be recorded and 
presented.   
4.2 WS2 participants  
Inclusion (enrolled participants must fulfil all of the inclusion criteria) 
• 
Adult (≥18 years) patients with a penA or a matched* patients without a penA  
• 
Received antibiotics in the previous 24 months, but not currently receiving or recently 
treated with (within 28 days) antibiotics 
• 
Willing to provide saliva +/- stool samples 
 
* non-penA patients will be matched by age (within 5 years) and sex.  
Exclusion  
• 
Patients unable to give informed consent or who are unwilling/unable to provide saliva 
samples  
 
Target population: 35 participants PenA and 35 non-PenA 
4.3 WS3 participants  
Inclusion  
• 
Patients enrolled into the ALABAMA trial who are willing to provide samples for the sub-
study 
Exclusion  

 
9 
• 
Patients unable to give informed consent or who are unwilling/unable to provide saliva 
samples  
 
5. SCREENING AND RECRUITMENT 
 
5.1 WS2 screening and recruitment 
Participants will be recruited from patients attending the clinical immunology and allergy outpatient 
clinics and pre-operative assessment clinics at Leeds Teaching Hospitals NHS Trust. 
Clinic lists will be screened and if a patient is eligible they will be invited to participate during their 
clinic visit by a member of their direct care team who will refer them to a member of the study 
team who will be available during the visit. The participant will then be given a patient information 
sheet (PIS) and the study will be discussed with them. Informed consent will be taken after the 
patient has had time to consider the PIS and ask any questions. Consent will be taken by a 
member of the IMPAART research team.  Consent must be taken prior to the collection of any 
study samples.  
5.2 WS3 screening and recruitment 
All participants recruited for the ALABAMA study will receive relevant information regarding this 
sub-study during the ALABAMA trial baseline call or their PAAP clinic appointment (see appendix 
2). If they express interest in taking part in the sub-study, they will be able to give full informed 
consent (written or verbal) after discussing the study in full detail with the IMPAART or ALABAMA 
research nurse or doctor. 
 
6. STUDY PROCEDURES 
 
6.1 Sample collection for WS 2 and 3 
Baseline samples will be collected up to 6 weeks after enrolment. Participants in WS3 will be 
required to provide a second sample > 6 months after enrolment or PAAP test.  
Samples required: - 

 
10
• 
2x Saliva in OMNIgene ORAL™ Saliva collection tubes for metagenomic and 
transcriptomics 
• 
1x Saliva in Universal container for culture and antibiotic susceptibility testing (WS 
2 only) 
• 
1x Stool sample using a gFOBT (guaiac Fecal Occult Blood test) card. 
 
The saliva sample tubes and gFOBT cards will be provided together with sample collection 
instructions and will either be given directly to participants when recruited or posted out to them.  
Once participants collect their samples, they will post back the specimen using pre-paid postage 
boxes.   
Participants who are collecting samples at home, will receive a text messages reminder if samples 
are not returned within 2 to 3 weeks after receipt of the testing kit. Another text message reminder 
will be sent 2 to 3 weeks after the initial reminder text. If required three attempts will be made to 
contact participant by telephone if sample has not been sent in 28 days from initial text message.  
A participant will be considered to be “lost to follow up” if they do not provide a sample after these 
reminders. 
Samples will be stored in the University of Leeds Dental Institute. Samples will be processed both 
at the Dental Institute. and the Leeds Institute of Medical Research at the University of Leeds. 
 
 
6.2 Data collection  
Patient electronic medical records (PPM+ and SystmOne) will be accessed to obtain clinical 
data including age, sex, prior antibiotic use, co-morbidities and penicillin allergy history. Patient 
records (via System One) will be accessed to obtain clinical data including age, sex, prior 
antibiotic use, co-morbidities and antibiotic treatment.  
Where applicable treatment outcomes (success and failure) will be obtained from ALABAMA 
trial data. 
6.3 Culture and traditional (phenotypic) antibiotic susceptibility testing (saliva samples 
only) 

 
11
Upon receipt samples will be refrigerated and then processed within 72hrs. Saliva samples will 
be inoculated on to selective streptococci and staphylococci agar and incubated.  Susceptibility 
testing will be done using disk diffusion methods as per the European Committee on 
Antimicrobial susceptibility testing (EUCAST). 
6.4 Metagenomic sample handling and processing  
Samples will be stored at -80 degrees Celcius in the UoL and batch processed. DNA will be 
extracted using ZymoBIOMICS DNA Mini Kit and DNA sequenced the Illumina® Nextseq platform. 
6.5 Transcriptomic sample handling and processing  (saliva samples only) 
Sample processing and analysis will occur in UoL laboratories.  Samples will stored at −80°C as 
per manufacturer instructions until further processing. RNA will be extracted using 
ZymoBIOMICS™ RNA Mini Kit as per manufacturer protocol and will then be processed in batch 
using the NextSeq (Illumina®) platform. 
6.6  Participant follow up (WS 3 only) 
Participants will be followed up as per the ALABAMA Study protocol. Patients will be contacted 
by post and by text message to remind them to send required follow up samples. Participants will 
receive a text messages reminder if samples are not returned within 2 to 3 weeks after receipt of 
the testing kit. Another text message reminder will be sent 2 to 3 weeks after the initial reminder 
text. In addition to this, where required three attempts will be made to contact patient by telephone 
if participants have not provided the follow-up sample 28 days from initial text message.  A 
participant will be considered to be “lost to follow up” if they do not provide a sample after these 
reminders. 
6.7 Schedule of procedures WS 2 and 3 
Procedures 
Screening 
Baseline visit (face to face 
or via telephone) 
Follow up (WS 3 only) 
Informed consent 
 
X 
 
Assessment of 
eligibility 
X 
X 
 
Sample collection 
 
X 
 
Review of medical 
and antibiotic history 
 
X 
 

 
12
Second sample 
collection 
 
 
X 
Review of clinical 
outcomes 
 
 
X 
 
6.8 Excess sample storage / Biobanking  
Where applicable, any surplus samples will be stored and may be used for future research by 
researchers from Leeds Teaching Hospitals NHS Trust, the University of Leeds, as well as 
researchers from other institutions and commercial companies both in and outside the UK for 
ethically approved studies. This may include transfer of samples to a research tissue bank. 
7. STATISTICAL ANALYSIS  
7.1 Sample size  
7.1.1. Work stream 1: All eligible patients in the PEACH study will be included 
7.1.2. Work stream 2: A sample size of 35 patients in each arm is acceptable for pilot studies 
(Lancaster et al., 2004, Browne, 1995) and although this is not a definitive study, this 
sample size will provide 80% power to see a standardised effect size of 0.68 for a 
continuous measure of antimicrobial resistance.  This will give a medium to large effect 
size (Cohen, 1988). 
7.1.3. Work stream 3: No formal sample size has been calculated as this is a pilot study, 
however all patients recruited into the ALABAMA study from sites in Leeds or West 
Yorkshire are eligible for recruitment. 
 
7.2  Description of statistical methods 
Baseline characteristics will be descriptive, with categorical data presented as proportions (%) 
and continuous data as medians and interquartile ranges (IQR) or as means and standard 
deviations (SD). Multivariable logistic regression will be used to assess which clinical variables 
(age, sex, co-morbidity, PenA status and previous antibiotic history) are associated AMR).  
7.3  DNA sequence analysis  
The high-performance computer (HPC) infrastructure available at the University of Leeds 
(https://arc.leeds.ac.uk/) will be used to carry out metagenomic analyses of the microbial 

 
13
nucleotide sequence data (in FASTQ file format). Following quality trimming using FASTQC 
(https://www.bioinformatics.babraham.ac.uk/projects/fastqc/,) de novo gene assembly will be 
carried 
out 
on 
the 
read 
sequences 
using 
diamond 
(http://ab.inf.uni-
tuebingen.de/software/diamond/) 
and 
MG-RAST 
(https://www.mg-rast.org/) 
servers. 
Taxonomical and gene annotations will be done using the large NCBI non-redundant protein 
database (https://www.ncbi.nlm.nih.gov/guide/proteins/). The resistome profile will also be 
determined by mapping DNA contigs against the ARDB (antibiotic resistance genes database, 
https://card.mcmaster.ca/ and  https://ardb.cbcb.umd.edu/). Significant difference in functional 
capability between sample groups will tested with the Wald test using the DESeq2 R package 
(http://bioconductor.org/packages/release/bioc/html/DESeq2.html). 
 
8. ETHICAL PRINCIPLES 
These sub-studies will be conducted in line with the principles of the Declaration of Helsinki and 
conducted in accordance with relevant regulations and with Good Clinical Practice. 
The study protocols, patient information sheets and consent forms will be submitted to the 
Research Ethics Committee (REC) for approval prior to study initiation.  
Upon completion of the study, samples may be transferred to a Research Tissue Bank (RTB) 
licensed by the Human Tissue Authority.  
 
8.1 Informed consent 
Written informed consent will be obtained from participants in WS 2 and those in WS 3 who will 
be seen in the ALABAMA trial clinic for allergy testing. Potential participants will be given a 
Participant Information Sheet (PIS) and Informed Consent Form (ICF) to read, this will then be 
followed up with a discuss with a member of the IMPAART or ALABAMA study team who will be 
suitably qualified and experienced in taking informed consent.  
The potential participant will be given opportunities to ask questions and allowed as much time 
as they need consider the information. Where applicable participants attending ALABAMA trial 
clinics will have the PIS and consent form sent to them alongside their ALABAMA clinic letter.  

 
14
A copy of the completed Informed Consent Form (ICF) will be given to the participant and another 
filed in their medical notes. The original form will be retained in the study site file at the Leeds 
Teaching Hospitals NHS Trust. 
For patients who are recruited into WS 3 who will not have a face to face clinic appointment, 
verbal consent will be sought. A written Participant Information Sheet (PIS) and Informed Consent 
Form (ICF) will have been sent by post or email to the participant prior to the telephone consent 
appointment. During this telephone discussion, a member of the IMPAART study team will go 
through the PIS, the ICF and discuss the exact nature of the study; what it will involve for the 
participant; the potential risks and benefits involved in taking part. It will be clearly stated that the 
participant is free to withdraw from the study at any time for any reason without prejudice to future 
care or involvement in the ALABAMA trial, and without affecting their legal rights, and with no 
obligation to give the reason for withdrawal. The participant will be given the opportunity to ask 
questions and will be allowed as much time as required to consider the information. If needed a 
follow up call can be arranged to take consent.  If patient is willing to participate during the call, 
verbal consent will be obtained and recorded in a consent form that will be signed and dated by 
the IMPAART study team member taking consent.  
The original form will be retained in the study site file at the Leeds Teaching Hospitals NHS Trust. 
A copy of the completed Informed Consent Form (ICF) a copy will be filed in their medical notes 
and another copy will then be sent to the participant. They will be asked to sign a return slip to 
confirm their participation. The original ICF form completed via telephone consultation will be 
retained in the study site file at the Leeds Teaching Hospitals NHS Trust. A copy of this telephone 
completed ICF will be filed in the participants medical notes and another sent to the participant. 
Verbal consent may also be sought for any potential participants in WS2 or WS3 who during their 
clinic visit state that they wish to take more time to consider study participation.  For these 
participants a follow up call will be arranged so that any questions can be answered and verbal 
consent obtained if the participants are willing. 
 
 
 

 
15
9. DATA PROTECTION 
All participant data will be handled in compliance with the General Data Protection Regulation 
(GDPR) and Data Protection Act 2018. All study staff will ensure that the participants’ anonymity 
is maintained.  All data will be anonymised as soon as it is practical to do so and participants will 
be identified by a participant ID number on all study documents.  All documents will be stored 
securely on either NHS or University of Leeds computers and will only be accessible by study 
staff and authorised personnel. All research data will be retained for  5 years beyond the end of 
the study. If participants give consent any excess samples may be retained and stored in a 
research tissue bank. Otherwise, samples collected from participant samples will be retained for 
12 months after study end for verification and quality checking of research data, after which they 
will be destroyed in accordance with the Human Tissue Authority’s Code of Practice. All personal 
identifiable information will be removed from stored samples.  
  
 

 
16
10. REFERENCES 
 
ALMEIDA, V. S. M., AZEVEDO, J., LEAL, H. F., QUEIROZ, A. T. L., DA SILVA FILHO, H. P. & REIS, J. N. 
2020. Bacterial diversity and prevalence of antibiotic resistance genes in the oral 
microbiome. PLoS One, 15, e0239664. 
BAXTER, M., BETHUNE, C., POWELL, R. & MORGAN, M. 2020. Point prevalence of penicillin allergy 
in hospital inpatients. J Hosp Infect, 106, 65-70. 
BLUMENTHAL, K. G., LU, N., ZHANG, Y., LI, Y., WALENSKY, R. P. & CHOI, H. K. 2018. Risk of 
meticillin resistant Staphylococcus aureus and Clostridium difficile in patients with a 
documented penicillin allergy: population based matched cohort study. BMJ, 361, k2400. 
BROWNE, R. H. 1995. On the use of a pilot sample for sample size determination. Stat Med, 14, 
1933-40. 
CARR, V. R., WITHERDEN, E. A., LEE, S., SHOAIE, S., MULLANY, P., PROCTOR, G. B., GOMEZ-
CABRERO, D. & MOYES, D. L. 2020. Abundance and diversity of resistomes differ between 
healthy human oral cavities and gut. Nat Commun, 11, 693. 
COHEN, J. 1988. Statistical Power Analysis for the Behavioral Sciences, Routledge. 
DOAN, T., WORDEN, L., HINTERWIRTH, A., ARZIKA, A. M., MALIKI, R., ABDOU, A., ZHONG, L., 
CHEN, C., COOK, C., LEBAS, E., O'BRIEN, K. S., OLDENBURG, C. E., CHOW, E. D., PORCO, T. 
C., LIPSITCH, M., KEENAN, J. D. & LIETMAN, T. M. 2020. Macrolide and Nonmacrolide 
Resistance with Mass Azithromycin Distribution. N Engl J Med, 383, 1941-1950. 
GARCIA-REY, C., AGUILAR, L., BAQUERO, F., CASAL, J. & DAL-RE, R. 2002. Importance of local 
variations in antibiotic consumption and geographical differences of erythromycin and 
penicillin resistance in Streptococcus pneumoniae. J Clin Microbiol, 40, 159-64. 
GRANIZO, J. J., AGUILAR, L., CASAL, J., GARCIA-REY, C., DAL-RE, R. & BAQUERO, F. 2000. 
Streptococcus pneumoniae resistance to erythromycin and penicillin in relation to 
macrolide and beta-lactam consumption in Spain (1979-1997). J Antimicrob Chemother, 
46, 767-73. 
LANCASTER, G. A., DODD, S. & WILLIAMSON, P. R. 2004. Design and analysis of pilot studies: 
recommendations for good practice. J Eval Clin Pract, 10, 307-12. 
LANCASTER, H., READY, D., MULLANY, P., SPRATT, D., BEDI, R. & WILSON, M. 2003. Prevalence 
and identification of tetracycline-resistant oral bacteria in children not receiving antibiotic 
therapy. FEMS Microbiol Lett, 228, 99-104. 
LANGFORD, B. J., SO, M., RAYBARDHAN, S., LEUNG, V., SOUCY, J. R., WESTWOOD, D., DANEMAN, 
N. & MACFADDEN, D. R. 2021. Antibiotic prescribing in patients with COVID-19: rapid 
review and meta-analysis. Clin Microbiol Infect. 
LANGFORD, B. J., SO, M., RAYBARDHAN, S., LEUNG, V., WESTWOOD, D., MACFADDEN, D. R., 
SOUCY, J. R. & DANEMAN, N. 2020. Bacterial co-infection and secondary infection in 

 
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LANSBURY, L., LIM, B., BASKARAN, V. & LIM, W. S. 2020. Co-infections in people with COVID-19: 
a systematic review and meta-analysis. J Infect, 81, 266-275. 
MACY, E. & CONTRERAS, R. 2014. Health care use and serious infection prevalence associated 
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J. M., HEWISON, J. & SANDOE, J. A. T. 2019. 'Warning: allergic to penicillin': association 
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V., LI, Z. & ROUSE, R. 2020. The effect of antibiotics on the gut microbiome: a 
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18
11. APPENDIX 
 
Appendix 1: Workstream 2 patient flow 
 
 
PenA group  
Patient attending LTH or recruited to 
ALABAMA with PenA record 
 
Non PenA group  
Patient attending LTH matched with 
PenA group (1:1) with no known PenA  
 
Informed consent, eligibility 
assessment and enrolment  
Data and sample collection 
Culture and antibiotic 
susceptibility testing 
Shotgun Metagenomics 
Transcriptomics 

 
19
Appendix 2: Workstream 3 recruitment pathway (ALABAMA Trial procedures represented in bold)  
 
 
Participant randomised to the 
Penicillin allergy assessment pathway 
(PAAP) arm in the ALABAMA trial 
during baseline call and assessment 
with a member of the ALABAMA 
research team 
Participant randomised to usual care 
during baseline call and assessment 
with a member of the ALABAMA 
research team 
Research nurse/doctor making the call 
to ask participant if they are willing to 
participate in sub-study. 
If willing an appointment will be 
arranged for consent and PIS sent to 
patient. 
Telephone appointment with IMPAART 
research doctor  to discuss PIS and 
study with participant.  
If willing participant is verbally 
consented during the call and 
specimen collection kit sent to patient 
with pre-paid return box to return 
Participant enrolled into ALABAMA 
trial 
Participant becomes eligible for the 
IMPAART Study 
Participant attends LTHT clinic for 
PAAP  
Participant invited to participate in the 
IMPART study by a member of the 
ALABAMA research team. PIS given 
and study discussed with participant. If 
willing consent obtained and samples 
Participant followed up as per 
ALABAMA trial 
Second sample collected 6-9months 
after the 1
st sample