Clinical Trials Focusing on Drug Control and Prevention of Ventilator-Associated Pneumonia: A Comprehensive Analysis of Trials Registered on ClinicalTrials.gov

Abstract

Objective: Clinical trials have emerged as the main force in driving the development of medicine. However, little is known about the current status of clinical trials regarding drug control and prevention of ventilator-associated pneumonia (VAP). This study aimed at providing a comprehensive landscape of these trials on the basis of ClinicalTrials.gov . Methods: A cross-sectional, descriptive study of clinical trials on drug control and prevention of VAP which have been registered on the ClinicalTrials.gov up to 25 th August 2018 was conducted. Results: A total of 109 eligible trials were identified. Trials were started from 1998 to 2018, and most trials focused on adult patients. More than half trials were completed, while only 11.9% trials had results available. Sample sizes were relatively large, with a median enrollment of 146. Universities were listed as the primary sponsor for 36.7% trials, industry for 28.4% trials and hospitals for 19.3% trials. Of the 109 VAP trials, 37 trials were from in Europe, 36 in North America and 27 in Asia. Among the 97 interventional trials, 32 were phase 3 trials, 21 were phase 4 trials, and 16 were phase 2 trials. Most interventional trials were randomized trials with a parallel assignment, and 57.7% trials were blinded. Of the 12 observational trials, 9 were cohort studies, and 10 trials were prosepctive studies. Drugs about oral care, preemptive antibiotics and probiotics were most investigated for prevention. A total of 61 trials investigated drugs for the treatment of VAP, mainly focused on antibiotics. A total of 36 kinds of antibiotics were investigated for monotherapy or combination therapy. Beta-lactams were most studied, followed by aminoglycosides and polypeptides. Conclusion: Most clinical trials registered on ClinicalTrials.gov about drugs for VAP were interventional trials with the purpose for treatment. A high proportion of interventional trials were randomized, parallel assigned and masked. Our analysis highlights the need for improvement in completeness of study results on the ClinicalTrials.gov .

Clinical Trials for Artificial Intelligence in Cancer Diagnosis: A Cross-Sectional Study of Registered Trials in ClinicalTrials.gov

“…The methodology of the study is similar to our previous study (14). This is a cross-sectional study, so a descriptive analysis was used to analyze the characteristics of registered trials.…”

“…According to our previous studies (14,15), we search the ClinicalTrials.gov on February 20, 2020, for trials on AI for cancer diagnosis. In case of missing any trials, we used the following words: artificial intelligence, deep learning, machine learning, etc.…”

Registered Interventional Clinical Trials for Old Populations With Infectious Diseases on ClinicalTrials.gov: A Cross-Sectional Study

“…In addition, there was an increasing concern of industry role in trial design, conduct, and funding ( Johnson and Stricker, 2010 ). A total of 62.3% trials were funded by industry, which was much more than drug control and prevention of ventilator-associated pneumonia ( Chen et al., 2018 ), suggesting the lack of other sources of funding in interventional clinical trials on infectious diseases in old populations. Study designs between industry-funded trials and non-industry-funded infectious disease trials were similar.…”

“…Several studies provided comprehensive details about registered trials in several fields ( Pasquali et al., 2012 ; Menezes et al., 2013 ; Hill et al., 2014 ; Chen et al., 2018 ); however, there is paucity of published works on the subject of intervention of infectious diseases in old populations. ( Califf et al., 2012 ) provides publicly accessible data of registered clinical trials, affords the most comprehensive source for identifying and tracking completed or ongoing trials, and is the best way to explore the characteristics of registered trials in particular fields ( Pasquali et al., 2012 ; Menezes et al., 2013 ; Hill et al., 2014 ; Chen et al., 2018 ). Thus, we performed the current cross-sectional study to investigate the characteristic of registered trials regarding intervention against infectious diseases in old populations.…”

Registered Trials on Artificial Intelligence Conducted in Emergency Department and Intensive Care Unit: A Cross-Sectional Study on ClinicalTrials.gov

“…Pre-registered in public registries is the most important strategy to ensure transparency ( 29 ) and now been required for all trials by The International Committee of Medical Journal Editors (ICMJE). Thus, analyzing registered trials will know the progress in such field, and many studies have been published to analyze registered trials in Clinicaltrials.gov , such as acupuncture ( 30 ), ventilator-associated pneumonia (VAP) ( 31 ), old populations with infectious diseases ( 32 ), and cancer diagnosis ( 33 ). However, there is no such study for AI in ED and ICU.…”