1. Mestrado Integrado em Medicina Introdução à Medicina II Turma 6 6fmup0910@gmail.com 06-04-2010 Professor Doutor Altamiro Pereira ARTIFICIAL INTELLIGENCE FOR CRITICAL CARE MONITORING AND DECISION SUPPORT Third Presentation IMPACT ON PATIENT OUTCOMES

2. Does the usage of monitoring or clinical decision support systems that include AI technology improve the quality of patient care? Professor Doutor Altamiro Pereira 06-04-2010 Research question Turma 6 6fmup0910@gmail.com

3. To review the usefulness of AI monitoring and CDS systems when applied to patients in the ICU by the interpretation of the patient outcomes Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Aim

4. To study the benefits and drawbacks of artificial intelligence monitoring and CDS systems for critical care when compared to non AI-methods. To find out the impact of the usage of AI systems in the different patient outcomes in ICU's. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Specific Objectives

5. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods Study design: Systematic review  1-An exhaustive search, in electronic databases, and inclusion of primary studies.  2-Quality assessment of included studies and data extraction (review, by two persons, of the title and the abstract or the article. Same process for the full article. A third opinion may be requested).  3-Synthesis of study results (SPSS and Review Manager).  4-Interpretation of results and report writing. Articles which report AI applications for monitoring (including warning (alert)), decision support or prescription support in the intensive care unit.

6. Data collection methods: → Search strategy Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods Articles included by reviewer Articles are searched in:  PubMed;  ISI Web of Knowledge;  SCOPUS. The query is based in the following keywords: AI and (critical care or ICU) and Trial With no date restriction

7. Query terms: Artificial intelligence: Computer reasoning, machine intelligence, machine learning, computer vision system, knowledge acquisition, fuzzy logic, expert systems, knowledge bases, neural networks (computer), neural network model, perceptron, direct support system, robotic, telerobotic; Intensive care unit: Critical care (unit), surgical intensive care (unit), neonatal intensive care (unit), infant newborn intensive care (unit), pediatric intensive care (unit), ICU, PICU, NICU, CC, burn(s) unit, respiratory care unit, coronary care unit. We also used the term “trial” in order to narrow down and specify our research. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods

8. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods Inclusion/ exclusion criteria: Inclusion criteria 1.Study design (clinical trials, cohort or case-control); 2.Study participants of included articles are patients in the intensive care unit; 3.Studies that describe AI systems’ intervention on monitoring, warning (alert), decision support or prescription support; 4. Study outcomes include mortality, morbidity, quality of life, length of stay or other patient outcomes. Exclusion criteria Articles that use data from the ICU as secondary data for the demonstration of AI systems based only on system's performance outcomes.

9. Data collection methods: → Validity assessment: Consort Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods To assess the validity of our articles, we will use the Consort, which stands for: CONsolidated Standards of Reporting Trials It also enables a greater level of understanding by the readers of the RCT’s analysed by this method. This statement helps authors in designing RCT’s (by following a group of guidelines and a flowchart).

10. Study variables: Characteristics of the articles (year, author and country of publishing, etc…) Type of study (number of participants, duration, etc…) Domain of application (neurological, respiratory, cardiovascular, etc…) Area of application (monitoring, clinical decision support.) The patients'outcomes described in each article (mortality rate, length of stay, quality of stay, morbidity, quality of life, cost of stay or other patient outcomes). Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods

11. Statistical analysis: Analysis of the study variables using the appropriate frequency measures; Possible associative analysis between factors and outcomes in the cases in which such aspects are included, resorting to adequate association measures. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Methods

12. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Search Results Search was conducted on the 7th of March, 2010

13. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Abstracts' review 28 articles: Included (5 articles were excluded due to absence of abstract) Number of third revisions (number of disagreements between reviewers): 27 222 articles: excluded

14. Professor Doutor Altamiro Pereira Turma 6 6fmup0910@gmail.com 06-04-2010 Reviewer Heterogeinity To evaluate if there is an association between the approval/rejection of a certain article and a certain reviewer, we proceeded to do a Chi-squared test. The result shows that there is an association. (Chi-squared test p=0,038). However, analysing the data, we also concluded that the reviewers agreed over 89% of the cases, even though the value is lower (60.7%) for included articles. Possible causes: Misunderstand of the criteria Certain reviewers being more inclined to reject/approve articles