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    <title>OAR@UM Collection:</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/64215</link>
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    <pubDate>Thu, 28 May 2026 00:56:49 GMT</pubDate>
    <dc:date>2026-05-28T00:56:49Z</dc:date>
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      <title>Development of a prediction model for the diagnosis of suspected acute poisoning</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/33205</link>
      <description>Title: Development of a prediction model for the diagnosis of suspected acute poisoning
Abstract: The diagnosis of acute poisoning is based on clinical assessment, electrocardiography and&#xD;
laboratory investigations. Diagnosis of acute poisoning in patients with altered mental status is&#xD;
challenging because an accurate history may be unavailable or unreliable and clinicians rely on&#xD;
clinical assessment, whilst the role of screening toxicology tests in such patients is not clear.&#xD;
The aim of the project was to develop a prediction model derived from clinical risk factors that&#xD;
would help in the diagnosis of suspected acute poisoning. In the first phase of the project,&#xD;
reliability of a history of poisoning and characteristics of patients with suspected acute poisoning&#xD;
presenting to Mater Dei Hospital, Malta were investigated. The second phase of the project&#xD;
involved development, validation and testing of a prediction model for the diagnosis of acute&#xD;
poisoning in patients with altered mental status.&#xD;
The reliability of a history of poisoning was measured by a meta-analysis of studies comparing&#xD;
history of poisoning with diagnosis, showing that history was moderately reliable and varied with&#xD;
different drugs. Pooled kappa for the reliability of a history of paracetamol poisoning was 0.67&#xD;
(95%CI 0.64-0.71) whilst history of drugs of abuse was less reliable with a pooled kappa ranging&#xD;
from 0.35 (95%CI 0.14-0.56) for MDMA to 0.48 (95%CI 0.41-0.54) for opiates.&#xD;
Features of patients with suspected acute poisoning referred for toxicology investigations were&#xD;
evaluated by comparing clinical features with toxicology laboratory results evaluating&#xD;
demographics, differential diagnosis, range of ingested drugs and diagnostic yield. 51.7%&#xD;
(350/677) had confirmed acute poisoning, classified as primary alcohol intoxication and drug&#xD;
overdose in 28.3% (99/350) and 69.7% (244/350)' respectively. Toxicology testing was carried&#xD;
out on 677 patients of which 464/677 (68.5%) were positive. Univariate analysis identified&#xD;
significant diagnostic factors for acute poisoning and although individual parameters had limited&#xD;
prognostic value, composite clinical scores were accurate predictors of poisoning severity. Based&#xD;
on these results, it was determined that a prediction model would be suitable for diagnosis of&#xD;
poisoning in patients with altered mental status.&#xD;
In the second phase of the project, clinical data were gathered on patients presenting with&#xD;
altered mental state and their characteristics were studied. Mean age was 54 years and 55.4%&#xD;
(484/873) were males. Age and gender distribution varied according to diagnosis. Drug overdose&#xD;
and isolated alcohol intoxication was present in 21.4% (187/873) and 14.4% (126/873)&#xD;
&#xD;
respectively. A history of overdose was present in 17.1% (149/873) whilst 15.8% (138/873) had a&#xD;
history of alcohol ingestion. 45.5% of patients with AMS had a toxicology investigation of which&#xD;
66% had a detectable drug result. Univariate analysis identified significant diagnostic variables.&#xD;
A prediction model based on significant clinical risk factors was developed for use in stratifying&#xD;
risk of acute poisoning in patients with altered mental status. The model was validated internally&#xD;
and externally and a decision rule for use of screening tests was derived and tested. A simplified&#xD;
risk score was derived from the model and was found to have a negative predictive value of&#xD;
94.2%.&#xD;
In this project the diagnostic value of clinical factors in suspected acute poisoning was&#xD;
investigated and a prediction model based on selected predictive factors was developed,&#xD;
validated and applied into a decision rule that was simple to calculate and may be of value in a&#xD;
pre-hospital environment or at triage.
Description: PH.D.</description>
      <pubDate>Sun, 01 Jan 2017 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/33205</guid>
      <dc:date>2017-01-01T00:00:00Z</dc:date>
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