Page 21 - 15Diarrhoeaandvomiting

Diarrhoea and vomiting caused by gastroenteritis in children under 5 years

Positive likelihood ratio A measure used to give an informative value of a test result and which is
(+LR) calculated as the ratio between sensitivity and 1 − specificity. It is used to
describe how much to increase the probability of a disease if the test is positive
(or rule in a disease). The higher the positive likelihood ratio (more than 1) for a
test result, the greater the likelihood of the disease.
Positive predictive value In diagnostic testing, this expresses the probability that someone with a positive
test result does have the condition of interest.
Power See statistical power.
Prevalence Prevalence and incidence are tools to describe how common a disease or an
event/outcome is with reference to the size of population. Prevalence is the
proportion of people in a defined population that have the disease or an event/
outcome at a specific time. In contrast to incidence, which quantifies disease
frequency among new cases only, prevalence measures disease frequency in
both old and new cases (all existing cases) at a particular time.
Primary care Health care delivered to patients outside hospitals. Primary care covers a range
of services provided by GPs, nurses and other healthcare professionals, dentists,
pharmacists and opticians.
Primary care trust (PCT) An NHS organisation responsible for improving the health of local people,
developing services provided by local GPs and their teams (called primary care)
and making sure that other appropriate health services are in place to meet local
people’s needs.
Primary outcome An outcome deemed a priori to be of greatest importance at the start of a research
study.
Probability How likely an event is to occur, for example how likely a treatment or intervention
will alleviate a symptom.
Probiotic A live microbial food which is intended to have beneficial effects by improving
the intestinal microbial balance of the host.
Prognostic factor Patient or disease characteristics, for example age or comorbidity, that influence
the course of the disease under study. In a randomised trial to compare two
treatments, chance imbalances in variables (prognostic factors) that influence
patient outcome are possible, especially if the size of the study is fairly small. In
terms of analysis, these prognostic factors become confounding factors.
Prospective study A study in which people are entered into the research and then followed up over
a period of time with future events recorded as they happen. This contrasts with
studies that are retrospective.
Protocol A plan or set of steps that defines appropriate action. A research protocol sets
out, in advance of carrying out the study, what question is to be answered and
how information will be collected and analysed. Guideline implementation
protocols set out how guideline recommendations will be used in practice by
the NHS, both at national and local levels.
P value If a study is done to compare two treatments then the P value is the probability
of obtaining the results of that study, or something more extreme, if there really
was no difference between treatments. (The assumption that there really is no
difference between treatments is called the ‘null hypothesis’.) Suppose the
P value was P = 0.03. What this means is that if there really was no difference
between treatments then there would only be a 3% chance of getting the kind
of results obtained. Since this chance seems quite low we should question the
validity of the assumption that there really is no difference between treatments.
We would conclude that there probably is a difference between treatments. By
convention, where the value of P is below 0.05 (i.e. less than 5%) the result is
considered to be statistically significant.
Pyloric stenosis Narrowing of the stomach outlet so that food cannot pass easily from it into the
intestine. This condition is usually seen in young infants, and is associated with
persistent vomiting.
Qualitative research Qualitative research is used to explore and understand people’s beliefs,
experiences, attitudes, behaviour and interactions. It generates non-numerical
data, for example a patient’s description of their pain rather than a measure

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