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Trying to make a difference, was it really planned?: the
journey of a clinical researcher
Trainees meeting 2015
Paul Little Professor of Primary Care Research
University of Southampton
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Really - me?
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The story of research: the story of a researcher
Outline: Antibiotics for common infections– How come infections?….
– Asking a series of questions • From Nepal (descriptive epidemiology) • …through Ivan Illich (sociology) • ….trialling pragmatic strategies (trials methodology)• ….and 'Killer bugs’ (microbiology) • …to complex intervention development to change
behaviours (health psychology)
– Recurring theme: good consultation skills
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The story of a researcher:
How come infections?
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Not initially!
Lifestyle change in hypertension (Brighton; Lord Trafford )
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Lord Trafford
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Why infections?: serendipity
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‘Behind every successful man is a surprised woman!’
What is the connection?
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.…..Neil Weir (ENT) and the charity BRINOS
(British Nepal Otology Service;medical team of the year 2013)
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BRINOS’s question?:
What is the prevalence, and main causes of ear disease and hearing impairment in Nepal?
Why Ear Disease in Nepal?• Deafness the biggest disability (WHO survey)
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Early research: how difficult could research be?...
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The inexperience of youth?
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• BRINOS is/was a small charity – Offered £20,000 to do the study…..
• Research in developing countries is difficult • and I still knew nothing...(at least I knew I knew nothing!?)
– Liverpool School Tropical Medicine (LSTM)– Professor Newell
The inexperience of youth?
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Professor Newell
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Methods
• Screened all reporting ear or hearing problems: field audiometer, otoscopy– and sample of those with ‘no problem’
• Stratified random sample n=15,845– Eastern (wet) and MidWest (dry) regions– 3 areas in each: terai, hills, mountain
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Map of Nepal
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Nepal - findings
• 16.6% had hearing impairment• Mostly due to otitis media• 55% school age otitis media
• Traditional remedies prevalent• animal urine, leaves!!
• 61% with ear pathology had never been to health post – and when they did, often no antibiotics!
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Back to the registrar year
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Why infections in a developed
country?…
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–The commonest symptoms:• impact NHS/society
sickness disability
–25-30% consult each year RTIs
–Very high expectations for antibiotics, most got antibiotics
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‘I’ve got tonsillitis again doctor’
Did the evidence support antibiotics?
BUT..its Friday pm, you are running late…… would you say no antibiotics to these ladies?
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Medicalising illness?
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Sociology: Ivan Illich – Medical Nemesis and ‘medicalisation’
‘Modern medicine is a negation of health. It isn't organized to serve human health, but only itself, as an institution. It makes more people sick than it heals’
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How important is medicalisation in
acute illness?
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The potential problem with medicalisation: the iceberg
Self care
Pharmacy/NHS direct
General practice: 1:9
Secondary care: 1:3300
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How to assess the importance of
medicalisation?
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Sore throat trial
Open trial of prescribing strategies:–No offer of antibiotics– Immediate antibiotic prescription –Delayed prescription
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The boss?...not again!?
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A great mentor, a good environment!
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Compete with training (LSHTM)
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Develop (‘bad’) open trial methodology– ?Drug vs no drug: NO: prescribing strategies
– ?Placebo blinded: NO: Patients had to know;
• Structured support for placebo effect
– ?Outcome ‘objective’? (inspect;swabs;pills count etc):
NO: all medicalising, needed light follow-up
• validated diary informed by qualitative work
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Main results sore throat trial (n=715)
010
2030
4050
6070
8090
100
% better satis belief Ab future
AntibioticNo antib.delayed
%
p<0.001p<0.001
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Even one antibiotic prescription is strongly
medicalising
..fuelling reconsultations,antibiotic use…
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Antibiotic prescriptions vs antibiotics usedFigure 1: Time trend in antibiotic prescribing to children in UK general practice 1993-2004 estimated from national prescribing data and the IMS GP prescribing database (1993=100)
0.0
20.0
40.0
60.0
80.0
100.0
120.0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
IMS data
PPA data
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Serendipity: patients’ perception of communication
• Satisfaction:– doctor dealing well
with concerns (chi square 362 kappa 0.79)
00.5
11.5
22.5
33.5
44.5
5
very not
z=3.3, p=0.001
satisfied
Durationdays
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Back to antibiotics……
Do antibiotics work any better in
the other infections we see? (series of studies:OM/chest/conjunctivitis/sinus)
More studies…..:…….similar messages!
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It is possible to get bored with the same message….
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More studies OM/sinusitis/chest infections:
Do Abs help symptoms? : not much!
Evidence from RCTs, systematic reviews
prior duration
duration after seeing doctor
total duration untreated
Benefit from antibiotics
NNT
otitis media
1-2 days 3-5 days 4 days 8-12 hours 18
sore throat
3 days 5 days 8 days 12-18 hours 10-20
sinusitis 5 days 7-10 days 12-15 days 24 hours 13
bronchitis 10 days 10-12 days 20-22 days 24 hours 10-20
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Increasing concern?:Headline News March 2012
• Resistance to antibiotics could bring "the end of modern medicine as we know it", WHO claim
………but is it our problem?
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Is it our problem?: yes!• Medicine > Agriculture• 80% of (medical) antibiotics are prescribed in
primary care– most patients still get antibiotics!
• But does our prescribing really impact resistance?
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Trends in Prescribing of Antibacterials in General Practice in England
© Copyright NHSBSA 2012
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Penicillins Tetracyclines MacrolidesCephalosporins Sulphonamides & trimethoprim QuinolonesMetronidazole & tinidazole All other antibacterial drugs
What is happening to primary care prescribing in England?: progress reversed 2004 onwards
7% increase
Trends in prescribing of antibacterials in General Practice in England
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What is going on?...time for qualitative work
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What do GPs think about resistance?
What are their key concerns?
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GPs views of resistance? (Wood et al)
• recognise the importance of resistance
• BUT: ..not a problem in their practice!
• Blame hospitals/other prescribers!
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GPs’ key concerns? (Kumar et al )
• Main concerns: severe symptoms, complications– Matches patient concern
• ad hoc targeting • pus, temperature,demographic, diet etc
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Can we improve the evidence for better targeting of antibiotics
for bacterial infections?
…..and will it make any difference!
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Flesh eating killer bugs! (=streptococci)
June 2014:
‘A long-serving and well-loved pastor has been killed by a flesh-eating bacteria’
(i.e. necrotising fasciitis)
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Can we target strep. in sore throat?
• Options for targeting– Clinical score? e.g. Centor (pus, nodes, fever, no cough):
– Developed for Lancefield Group A
– RADTs? (rapid streptococcal antigen tests)– Group A Strep only
• What about non Group A? (C,G)• Major virulence factors/rates of septicaemia similar
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Are C+G strep relevant?: probably!– Strep. in 34-40% (n=517;n=606)
• 25% C or G– similar clinical presentation to group A
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Predicting A/C/G streptococci?
FeverPAIN (AUC 0.70):•*Fever last 24h• Pus•*Attend rapidly (<=3 days)•*severely Inflamed tonsils• No cough or coryza (i.e. pharyngeal
illness)
*=univariate and multivariate in both cohorts
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Does better diagnosis/targetting (using a clinical score or RADTs)
lead to better outcome?
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PRISM Trial
– Empirical delayed prescribing (control )– 5 item clinical score (FeverPAIN)
• 0-1 <20% strep (none), • 2-3 39% strep (delayed), • 4+ 63% strep (immediate)
– RADT • Similar but test for higher scores (3+)
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Results: Delayed(control)
FeverPAIN RADT
Duration (moderately bad or worse Sx)
Median 5 days
HR 1.30* (1.03 to 1.63 )
HR 1.11(0.88 to 1.40)
Antibiotic use 75/164 (46%)
RR 0.71*(0.05 to 0.95)
RR 0.73*(0.52 to 0.98)
All models controlled for fever and symptom severity at baselineNo difference in returns within one month or following
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So better diagnosis (targeting using FeverPAIN) improves symptom control and lowers
antibiotic use
• RADTs similar but no clear advantages to a clinical score alone.
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Targeting:How common are complications
and can we predict them?
Does delayed prescribing prevent complications?
DESCARTE sore throat cohort
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• n>13,000!
• Multi-centre collaboration: Friendship groups SW SAPC– trusted colleagues to build major multi-centre
collaborations – The social nature of research
DESCARTE
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Results: Complications are uncommon
No antibiotics Antibiotics DelayedAntibiotics
Complications (total) 73/4536 (1.6%) 75/5750(1.3%) 16/1664 (1.0%)
Quinsy 11/4,536 (0.2%) 30/5750 (0.5%) 4/1,664 (0.2%)
Sinusitis 23/4,536(0.5%)
10/5750(0.2%) 2/1,664 (0.1%)
Otitis media
30/4,536(0.7%)
26/5750 (0.5%)
10/1,664 (0.6%)
Celluliltis/impetigo 10/4,536(0.2%)
9/5750 (0.2%) 0/1,664 (0.00%)
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Can we predict complications in sore throat?: Not very well!
• Only two variables:– severe tonsillar inflammation (OR 1.92) – severe earache (OR 3.02)
• modest utility AUROC 0.61 (chance=0.5!)– 70% complications when neither variable present!
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Delayed prescribing prevents complications as effectively as
immediate antibiotics.
No antibiotics Antibiotics DelayedAntibiotics
Adjusted RRs
StratifiedPropensity score(Multiple Imputation)
1.00 0.61(0.40;0.94)
0.55(0.31,0.98)
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..and lowers reconsultations more effectively than immediate
antibiotics
Adjustment No antibiotics Antibiotics DelayedAntibiotics
Adjusted RRsAll control for clustering
StratifiedPropensity score(Multiple Imputation)
1.00 0.76(0.68;0.86)
0.58(0.49,0.67)
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• So complications are uncommon, and we cannot very effectively predict them
• But if considering an antibiotic, consider delayed prescribing?– prevents complications, reduces reconsultations – at least as effective as immediate antibiotics.
DESCARTE sore throat cohort
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Targeting in chest infections?:
The patient: ‘I’ve got green sputum doctor’
The doctor: ‘how do I know antibiotics won’t work for my particular patient?’
(green sputum, smoker etc)?
…….the overall data is modest (few RCTs) and not helpful for subgroups?
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• 3012 adult patients with LRTI in 12 countries– acute cough (<28 d) main symptom
• or GP suspects acute bronchitis or pneumonia
• 2061 randomised: amoxycillin 1 gr TID or placebo
GRACE trial :
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GRACE Network: Again friendships to build major
collaborations!
1. General practice Respiratory Infections Network (GRIN)
2. Flexibility; trust;
.....?requiring less dosh for the University?
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Resolution of bad symptoms: overall data
Day 7-8 ‘survivor’
Log rank Hazard ratio P/NNT
Whole data set(n=1799)
0.465 vs 0.395
P=0.172 1.06
(0.96 to 1.18)
NNT 15
P=0.229
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Resolution of moderately bad symptoms ( whole data set)
0.0
00.2
50.5
00.7
51.0
0
0 10 20 30analysis time
groupnumber = 0 groupnumber = 1
Kaplan-Meier survival estimates
time to resolution of moderately bad symptoms
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What about my particular patient?Hazard ratio P
Interaction term?(p)
Smokersn=486
1.20(p=0.121)
1.23(1.01 to 1.50)
0.044
NNT 9
Age 60+n=550
0.86(p=0.166)
0.95(0.79 to 1.14)
0.555
NNT 143
Green Sputumn=346
1.28(p=0.059)
1.31(1.05 to 1.65)
0.019
NNT 8
Comorbid n=438
0.99(p=0.914)
1.06(0.86 to 1.31)
0.581
NNT 14
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Green sputum subgroup0.0
00.2
50.5
00.7
51.0
0
0 10 20 30analysis time
groupnumber = 0 groupnumber = 1
Kaplan-Meier survival estimates
time to symptom resolution - green phlegm subgroup
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Smokers0.0
00.2
50.5
00.7
51.0
0
0 10 20 30analysis time
groupnumber = 0 groupnumber = 1
Kaplan-Meier survival estimates
time to symptom resolution - current smoker subgroup
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Benefits vs harms: side effects!
• Nausea, rash, or diarrhoea
Antibiotic 29%
Placebo 24%• NNH 21
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Targetting?: 6 symptoms and signs predict consolidation
History (day 1)
Severe cough present
931 (33)
56 (40)
1.4 (1.0-2.0)
. 1.1 (0.7-1.6)
Phlegm present 2239 (79) 120 (86) 1.6 (1.0-2.6) N.A. Breathlessness present Severe breathlessness present
1594 (57) 197 (7)
96 (69) 17 (12)
1.7 (1.2-2.5) 1.9 (1.1-3.4)
1.4 (1.0-2.1) 1.3 (0.7-2.4)
0.025 0.419
Runny nose absent 807 (29) 61 (44) 2.0 (1.4-2.8) 1.9 (1.3-2.7) <0.001 Fever present 989 (35) 82 (59) 2.8 (2.0-3.9) N.A. Chest pain present Severe chest pain present
1304 (46) 141 (5)
80 (57) 13 (9)
1.6 (1.1-2.2) 2.1 (1.2-4.0)
1.2 (0.8-1.7) 1.5 (0.8-3.1)
0.402 0.224
Diarrhoea present 199 (7) 15 (11) 1.6 (0.9-1.8) 1.5 (0.8-1.8) 0.165 Physical examination (day 1) General toxicity 739 (26) 43 (31) 1.3 (0.9-1.8) 1.1 (0.7-1.6) 0.728 Diminished vesicular breathing 362 (13) 31 (22) 2.0 (1.3-3.1) 1.7 (1.1-2.6) 0.013 Crackles 264 (9) 44 (31) 5.3 (3.6-7.7) 3.5 (2.3-5.2) <0.001 Tachycardia (pulse >100 beats/min) 111 (4) 17 (12) 3.7 (2.2-6.5) 2.3 (1.3-4.3) 0.003 Tachypnoea (>24 breaths/min) 55 (2) 6 (4) 2.4 (1.0-5.7) 1.4 (0.9-2.0) 0.421 Blood pressure <90/60 mmHg 71 (3) 9 (6) 2.9 (1.4-5.9) N.A. Temperature >37.8°C 156 (6) 22 (16) 3.5 (2.1-5.7) 2.5 (1.4-4.4) <0.001
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Simple risk stratification
• 2 history: Breathless, no coryza• 2 chest signs: bronchial, crackles• 2 vital signs: pulse >100, temp. >37.8
• 0 = 1% have consolidation• 1-2= 5% (most here…)• 3 = 20%
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Will antibiotics work for my particular patient with a chest infection?:
• Modest benefits even in key clinical subgroups, modest disbenefits…
• Don’t prescribe for the vast majority! – Consider antibiotics/delayed antibiotics for
3+ key symptoms/signs?
So we need to be able to communicate effectively……
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Can we improve communication, and will it help reduce antibiotic use?
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Lack of time
Acute infection: a quick consultation?
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How to change clinician prescribing behaviour?
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GRACEINTRO (INternet TRaining for
antibiOtic use) Trial
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Web based training: four groups
• No training
• Communication– enhanced communication training + booklet
• CRP training – cut points; kit demonstration
• Both: Communication and CRP
n=6771 baseline Post-intervention n=4264
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Enhanced Communication/Information sharing
• Addressing the patients world– Concerns, – Expectations, – Attitudes
• Information exchange: booklet– Natural history; – Risks/benefits of antibiotics– Self-help – Safety netting
• Wrap up– Summarise– Check understanding, other concerns
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We can communicate effectively and it makes an important difference:
RR(adjusted for patient variables)
p
Control 1.0
CRP 0.47 (0.35 to 0.64) <0.001
Communic’n 0.66 (0.50 to 0.85) <0.001
Both 0.39 (0.28 to 0.54) <0.001
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Can we help symptoms with simple advice (PIPS study)?
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PIPS study • Randomised strategies
– analgesic strategies
• Paracetamol vs ibuprofen vs combination;
– steam inhalation (factorial design)
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Patients complied … BUT trivial differences in symptom severity overall
Pmol(control)
Ibuprofen Both
Whole cohort(743/889;84%)
1.67 +0.04(-0.11 to 0.19)
+0.11(-0.04 to 0.26)
• 10 symptoms: 0=no problem……6 as bad as it could be
Ibuprofen better in chest infections and for children
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Ibuprofen interfering with the immune response?:
More reconsultations:same/new/worse symptoms
Pmol(control)
Ibuprofen Both
Reconsultation(same Sx, new Sx, or worse Sx)
35/300(12%)
58/295(20%)**
48/295(17%) 1
Adjusted RR
1 1.67 (1.12 to 2.38)
1.49(0.98 to 2.18)
** p=<=0.01 1 p=0.06
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Complications higher
Pmol(control)
Ibuprofen Both
Complication 2/300 (0.6%)1 cellulitis1OM
11/295 (3.7%):1 Quinsy3 sinusitis1 meningitis1pneumonia5 OM(2 not new)
4/295 (1.4%):1 Quinsy2 sinusitis(1 not new)1 cerv. adenitis
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Steam?– No benefit– Mild thermal injury in 4 patients (2%) who
returned full diaries• No reconsultations with scalding
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We are probably doing more harm than good with widely given self help advice!
• ibuprofen little help overall– ? for chest infections and children. – BUT progression of symptoms/complications
• Advice to use steam does not help– and occasional harm
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Can we prevent infections?
The PRIMIT trial of a web based behavioural intervention to reduce infection transmission
(in press)
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Handwashing?
• Hand-washing widely advocated– e.g. H1N1 pandemic– but role of handwashing debated!
• No good randomised evidence among adults in our (resource rich) setting.
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Developing a complex intervention
• Initial qualitative/questionnaire studies: – Confirm useful target behaviour (handwashing)
• determinants; barries/facilitators
• Further qualitative/questionnaire studies: – (‘think aloud’) for draft materials– tested key assumptions
• Randomised pilot of prototype website: – Changed behaviour (increased handwashing) .
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Results: infections prevented 20,066 randomised
16,908 (84%) followed-up
Intervention Control p
Any RTI at 4 months 51% 59% <0.001
Any RTI (in household) 44% 49% <0.001
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Transmission reduced to and from household members
Intervention Control p
Transmission to household
7.8% 9% <0.001
Transmission from household
6.8% 8.8% <0.001
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Infections slightly less severe
Intervention Control p
Days more severe symptoms if RTI
4.1 days 4.3 days 0.008
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Reduced consultations, reduced GI infections
Intervention Control p
Consultations for RTIs (notes)
18.9% 20% <0.001
GI infections
21.5% 25% <0.001
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We can prevent infections!
• A free standing web intervention increases hand-washing – reduces infections, their severity, and transmission,
• ?Pandemic: will access internet for advice.
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Had enough?
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Have we learned anything useful?
• Antibiotic resistance: a public health problem we generate!• Antibiotic prescribing: medicalises, fuels demand/resistance• For symptoms: antibiotics overall/subgroups mostly not helpful
• A ‘bacterial’ score in sore throat helps symptoms, reduces antibiotics • Commonly given advice (steam/ibuprofen) is probably harmful!
• For complications:• Sore throat: Uncommon/difficult to predict:
– Good safety netting skills– if antibiotics are considered, consider delayed prescribing?
• Chest infections: basic clinical history/exam. help identify consolidation
• For prevention: a behavioural web handwashing intervention helps• prevents infections, reduces severity, and reduces transmission
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Reflections on infection research• Acute infections are relatively quick/easy consultations
in a world of increasing demands…BUT:– a central public health role– a central role for better communication
• a little more time, BUT saves time in future!• brief training for experienced GPs helps
• Practice changing research:– Good mentorship and training – Large collaborations (friendship!)
• Powered for subgroups/adverse outcome
– Mixed methods, carefully developing complex interventions • really understand and change behaviours!
• …Is such research valued?
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Having ideas and getting grants…..rejection?
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Rejection
Don’t let it get you down ?Recycle or resubmit:
• If the referees points are answerable
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Picking the ones to resubmit (otherwise they might get tired of
you!)
• BUT……..Keep going if it’s a good idea!
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Why we don’t write enough grants? Perfectionism?
• The best is the enemy of the good…… Insufficient protected time
• Structural (other responsibilities; competing demands)
• distraction;faffing……. Failure?......expectations?..assume
2:3 or more to go down• Aim to be working on 2-3 ideas at any
one time……• Try and recycle……
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Other excuses…..
• SO PUT ASIDE TIME IN THE DIARY• DON’T ANSWER EMAILS………….(AND DON’T HAVE A BEER BEFORE!)
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Success? (5 S’s)
Space/time, Story (idea), Sharp (methods),Support (peers/team/social)Stamina
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James McKenzie
‘For some years I went blundering on, gradually falling into a routine, i.e. giving some drug that seemed to act favourably on the patient, till I became dissatisfied with my work and resolved to try and improve my knowledge by more careful observation.’
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Lack of timeWhat aspects of communication
are important to patients?:
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Patient-centredness cohort
• Assessed patients’ perceptions of patient centredness:– develop questionnaire – assess domains empirically (factor analysis)
• Communication and Partnership• A personal Relationship• Health Promotion• A positive and Clear approach to the problem• Interest (of the doctor) in the effect of the illness on life
• Determine relationship of 5 domains to outcome (n=865; all conditions)
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Stem (unless specified): The doctor ..... % agree Factorloading
Factor 1 communication and partnership
Was interested in my worries about the problem 80 0.68Was interested when I talked about my symptoms 93 0.80Was interested in what I wanted to know 86 0.67(Full question:) I felt encouraged to ask questions 80 0.54Was careful to explain the plan of treatment 80 0.58Was sympathetic 85 0.59
Was interested in what I thought the problem was 80 0.80Discussed and agreed together what the problem was 75 0.62Was interested in what I wanted done 75 0.67Was interested in what treatment I wanted 62 0.52Discussed and reached agreement with me on the plan of treatment 76 0.56
Results: Factor analysis of patients’ perceptions
Cronbach’s alpha 0.96
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Relationship of domains to outcome: Satisfaction (MISS) : communication, positive
beta
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Enablement: interest in life, health promotion, positive
beta
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Symptom burden (MYMOP): positive, health promotion
beta
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Results III• Referrals less if ‘personal’ relationship
– odds ratio 0.70 (0.54 to 0.90)
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So are domains of communication important?
• There probably are distinct domains of patients perceptions of communication– Probably reliable– support the patient centred model
• Different domains => different outcomes (satisfaction, enablement,symptoms,referrals)– important for both patients and health service