In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

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.
Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

Background: SARS coronavirus (SARS-CoV) was identified as the etiological agent of SARS, and extensive investigations indicated that it originated from an animal source (probably bats) and was recently introduced into the human population via wildlife animals from wet markets in southern China. Previous studies revealed that the spike (S) protein of SARS had experienced adaptive evolution, but whether other functional proteins of SARS have undergone adaptive evolution is not known. We employed several methods to investigate selective pressure among different SARS-CoV groups representing different epidemic periods and hosts. Our results suggest that most functional proteins of SARS-CoV have experienced a stepwise adaptive evolutionary pathway. Similar to previous studies, the spike protein underwent strong positive selection in the early and middle phases, and became stabilized in the late phase. In addition, the replicase experienced positive selection only in human patients, whereas assembly proteins experienced positive selection mainly in the middle and late phases. No positive selection was found in any proteins of bat SARS-like-CoV. Furthermore, specific amino acid sites that may be the targets of positive selection in each group are identified. This extensive evolutionary analysis revealed the stepwise evolution of different functional proteins of SARS-CoVs at different epidemic stages and different hosts. These results support the hypothesis that SARS-CoV originated from bats and that the spill over into civets and humans were more recent events.
Differential stepwise evolution of SARS coronavirus functional proteins in different host species

Background. The role of human adenoviruses (HAdVs) in chronic respiratory disease pathogenesis is recognized. However, no studies have performed molecular sequencing of HAdVs from the lower airways of children with chronic endobronchial suppuration. We thus examined the major HAdV genotypes/species, and relationships to bacterial coinfection, in children with protracted bacterial bronchitis (PBB) and mild bronchiectasis (BE). Methods. Bronchoalveolar lavage (BAL) samples of 245 children with PBB or mild (cylindrical) BE were included in this prospective cohort study. HAdVs were genotyped (when possible) in those whose BAL had HAdV detected (HAdV + ). Presence of bacterial infection (defined as 10 4 colony-forming units/mL) was compared between BAL HAdV + and HAdV negative (HAdV ) groups. Immune function tests were performed including blood lymphocyte subsets in a random subgroup. Results. Species C HAdVs were identified in 23 of 24 (96%) HAdV + children; 13 (57%) were HAdV-1 and 10 (43%) were HAdV-2. An HAdV + BAL was significantly associated with bacterial coinfection with Haemophilus influenzae, Moraxella catarrhalis, or Streptococcus pneumoniae (odds ratio [OR], 3.27; 95% confidence interval, 1.38-7.75; P = .007) and negatively associated with Staphylococcus aureus infection (P = .03). Young age was related to increased rates of HAdV + . Blood CD16 and CD56 natural killer cells were significantly more likely to be elevated in those with HAdV (80%) compared with those without (56.1%) (P = .027). Conclusions. HAdV-C is the major HAdV species detected in the lower airways of children with PBB and BE. Younger age appears to be an important risk factor for HAdV + of the lower airways and influences the likelihood of bacterial coinfection.
Adenovirus Species C Is Associated With Chronic Suppurative Lung Diseases in Children