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2.
NPJ Digit Med ; 7(1): 14, 2024 Jan 23.
Article in English | MEDLINE | ID: mdl-38263386

ABSTRACT

Sepsis remains a major cause of mortality and morbidity worldwide. Algorithms that assist with the early recognition of sepsis may improve outcomes, but relatively few studies have examined their impact on real-world patient outcomes. Our objective was to assess the impact of a deep-learning model (COMPOSER) for the early prediction of sepsis on patient outcomes. We completed a before-and-after quasi-experimental study at two distinct Emergency Departments (EDs) within the UC San Diego Health System. We included 6217 adult septic patients from 1/1/2021 through 4/30/2023. The exposure tested was a nurse-facing Best Practice Advisory (BPA) triggered by COMPOSER. In-hospital mortality, sepsis bundle compliance, 72-h change in sequential organ failure assessment (SOFA) score following sepsis onset, ICU-free days, and the number of ICU encounters were evaluated in the pre-intervention period (705 days) and the post-intervention period (145 days). The causal impact analysis was performed using a Bayesian structural time-series approach with confounder adjustments to assess the significance of the exposure at the 95% confidence level. The deployment of COMPOSER was significantly associated with a 1.9% absolute reduction (17% relative decrease) in in-hospital sepsis mortality (95% CI, 0.3%-3.5%), a 5.0% absolute increase (10% relative increase) in sepsis bundle compliance (95% CI, 2.4%-8.0%), and a 4% (95% CI, 1.1%-7.1%) reduction in 72-h SOFA change after sepsis onset in causal inference analysis. This study suggests that the deployment of COMPOSER for early prediction of sepsis was associated with a significant reduction in mortality and a significant increase in sepsis bundle compliance.

3.
PLoS One ; 16(9): e0257147, 2021.
Article in English | MEDLINE | ID: mdl-34492074

ABSTRACT

Posttraumatic fibrotic scarring is a significant medical problem that alters the proper functioning of injured tissues. Current methods to reduce posttraumatic fibrosis rely on anti-inflammatory and anti-proliferative agents with broad intracellular targets. As a result, their use is not fully effective and may cause unwanted side effects. Our group previously demonstrated that extracellular collagen fibrillogenesis is a valid and specific target to reduce collagen-rich scar buildup. Our previous studies showed that a rationally designed antibody that binds the C-terminal telopeptide of the α2(I) chain involved in the aggregation of collagen molecules limits fibril assembly in vitro and reduces scar formation in vivo. Here, we have utilized a clinically relevant arthrofibrosis model to study the broad mechanisms of the anti-scarring activity of this antibody. Moreover, we analyzed the effects of targeting collagen fibril formation on the quality of healed joint tissues, including the posterior capsule, patellar tendon, and subchondral bone. Our results show that blocking collagen fibrillogenesis not only reduces collagen content in the scar, but also accelerates the remodeling of healing tissues and changes the collagen fibrils' cross-linking. In total, this study demonstrated that targeting collagen fibrillogenesis to limit arthrofibrosis affects neither the quality of healing of the joint tissues nor disturbs vital tissues and organs.


Subject(s)
Fibrillar Collagens/metabolism , Joint Diseases/pathology , Joint Diseases/physiopathology , Joints/physiopathology , Animals , Antibodies/metabolism , Biomarkers/blood , CHO Cells , Calcification, Physiologic , Cricetulus , Disease Models, Animal , Female , Fibrosis , Joint Capsule/metabolism , Joint Capsule/pathology , Joint Capsule/physiopathology , Male , Rabbits , Spectroscopy, Fourier Transform Infrared , Time Factors
4.
J Environ Manage ; 212: 266-277, 2018 Apr 15.
Article in English | MEDLINE | ID: mdl-29448181

ABSTRACT

When beach water monitoring programs identify poor water quality, the causes are frequently unknown. We hypothesize that management policies play an important role in the frequency of fecal indicator bacteria (FIB) exceedances (enterococci and fecal coliform) at recreational beaches. To test this hypothesis we implemented an innovative approach utilizing large amounts of monitoring data (n > 150,000 measurements per FIB) to determine associations between the frequency of contaminant exceedances and beach management practices. The large FIB database was augmented with results from a survey designed to assess management policies for 316 beaches throughout the state of Florida. The FIB and survey data were analyzed using t-tests, ANOVA, factor analysis, and linear regression. Results show that beach geomorphology (beach type) was highly associated with exceedance of regulatory standards. Low enterococci exceedances were associated with open coast beaches (n = 211) that have sparse human densities, no homeless populations, low densities of dogs and birds, bird management policies, low densities of seaweed, beach renourishment, charge access fees, employ lifeguards, without nearby marinas, and those that manage storm water. Factor analysis and a linear regression confirmed beach type as the predominant factor with secondary influences from grooming activities (including seaweed densities and beach renourishment) and beach access (including charging fees, employing lifeguards, and without nearby marinas). Our results were observable primarily because of the very large public FIB database available for analyses; similar approaches can be adopted at other beaches. The findings of this research have important policy implications because the selected beach management practices that were associated with low levels of FIB can be implemented in other parts of the US and around the world to improve recreational beach water quality.


Subject(s)
Bathing Beaches , Recreation , Water Quality , Environmental Monitoring , Feces , Florida , Humans , Water Microbiology
5.
Mar Pollut Bull ; 121(1-2): 160-167, 2017 Aug 15.
Article in English | MEDLINE | ID: mdl-28595980

ABSTRACT

Large databases of fecal indicator bacteria (FIB) measurements are available for coastal waters. With the assistance of satellite imagery, we illustrated the power of assessing data for many sites by evaluating beach features such as geomorphology, distance from rivers and canals, presence of piers and causeways, and degree of urbanization coupled with the enterococci FIB database for the state of Florida. We found that beach geomorphology was the primary characteristic associated with enterococci levels that exceeded regulatory guidelines. Beaches in close proximity to marshes or within bays had higher enterococci exceedances in comparison to open coast beaches. For open coast beaches, greater enterococci exceedances were associated with nearby rivers and higher levels of urbanization. Piers and causeways had a minimal contribution, as their effect was often overwhelmed by beach geomorphology. Results can be used to understand the potential causes of elevated enterococci levels and to promote public health.


Subject(s)
Bathing Beaches , Enterococcus , Water Microbiology , Bacteria , Environmental Monitoring , Feces , Florida
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