In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Q: Paragraph: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time. 
 Title: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

A: True
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Q: Paragraph: Very limited evidence has been reported on host T cell responses to the pandemic H1N1 swine-origin influenza A virus (S-OIV) infection in humans. Therefore, we investigated the proportions of peripheral T cell subsets and analyzed the relationship of T helper subset changes with T cell activation during this infection. We found that these S-OIV-infected patients exhibited rapid lymphopenia, T cell activation and preferential loss of Th17 subset at the early stage of acute infection. Statistical analysis indicated that CD4 depletion and loss of Th17 cells, rather than Th1 or Treg cells, were correlated with CD4 T cell activation. More importantly, upregulated IFN-α likely contributed to the functional loss of Th17 cells. Thus, rapidly generalized lymphopenia, preferential loss of Th17 population and T cell activation presented as characteristics of the early immune response in S-OIV-infected patients. These findings, therefore, may be helpful for an earlier diagnosis and further studies of immune pathogenesis of S-OIV infection. 
 Title: Preferential loss of Th17 cells is associated with CD4 T cell activation in patients with 2009 pandemic H1N1 swine-origin influenza A infection

A: True
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Q: Paragraph: The best treatment strategy for severe acute respiratory syndrome (SARS) is still unknown. Ribavirin and corticosteroids were used extensively during the SARS outbreak. Ribavirin has been criticized for its lack of efficacy. Corticosteroids are effective in lowering the fever and reversing changes in the chest radiograph but have the caveat of encouraging viral replication. The effectiveness of corticosteroids has only been suggested by uncontrolled observations, and the role of these agents in therapy remains to be established by randomized controlled studies. Both ribavirin and corticosteroids have very significant side effects. The lopinavir/ritonavir combination has been shown to reduce the intubation rate and the incidence of adverse clinical outcomes when used with ribavirin. When patients deteriorate clinically despite treatment with ribavirin and corticosteroids, rescue treatment with convalescent plasma and immunoglobulin may be beneficial. Noninvasive positive pressure ventilation is a sound treatment for SARS patients with respiratory failure if administered with due precaution in the correct environment. Interferons and other novel agents may hold promise as useful anti-SARS therapies in the future. The experience with traditional Chinese medicine is encouraging, and its use as an adjuvant should be further investigated. 
 Title: Treatment of severe acute respiratory syndrome

A:
True
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