Development and Validation of a Machine Learning Model for Early Detection of Untreated Infection.

Background: Early diagnostic uncertainty for infection causes delays in antibiotic administration in infected patients and unnecessary antibiotic administration in noninfected patients.

Objective: To develop a machine learning model for the early detection of untreated infection (eDENTIFI), with the presence of infection determined by clinician chart review.

Derivation Cohort: Three thousand three hundred fifty-seven adult patients hospitalized between 2006 and 2018 at two health systems in Illinois, United States.

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events Among High-Risk Ward Patients.

Importance: Timely intervention for clinically deteriorating ward patients requires that care teams accurately diagnose and treat their underlying medical conditions. However, the most common diagnoses leading to deterioration and the relevant therapies provided are poorly characterized.

Objectives: We aimed to determine the diagnoses responsible for clinical deterioration, the relevant diagnostic tests ordered, and the treatments administered among high-risk ward patients using manual chart review.

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

Background And Objective: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validated while incorporating a Veteran sample.

Derivation Cohort: Adults (age ≥ 18 yr) hospitalized outside the ICU with a diagnosis of COVID-19 for model development to the Veterans Health Administration (VHA) (n = 80 hospitals).

Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score.

Objective: Early detection of clinical deterioration using machine learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not tested in important subgroups. Our objective was to develop and prospectively validate a gradient boosted machine model (eCARTv5) for identifying clinical deterioration on the wards.

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events among High-Risk Ward Patients.

Objective: Timely intervention for clinically deteriorating ward patients requires that care teams accurately diagnose and treat their underlying medical conditions. However, the most common diagnoses leading to deterioration and the relevant therapies provided are poorly characterized. Therefore, we aimed to determine the diagnoses responsible for clinical deterioration, the relevant diagnostic tests ordered, and the treatments administered among high-risk ward patients using manual chart review.

Identifying infected patients using semi-supervised and transfer learning.

Objectives: Early identification of infection improves outcomes, but developing models for early identification requires determining infection status with manual chart review, limiting sample size. Therefore, we aimed to compare semi-supervised and transfer learning algorithms with algorithms based solely on manual chart review for identifying infection in hospitalized patients.

Materials And Methods: This multicenter retrospective study of admissions to 6 hospitals included "gold-standard" labels of infection from manual chart review and "silver-standard" labels from nonchart-reviewed patients using the Sepsis-3 infection criteria based on antibiotic and culture orders.

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial.

Objectives: To determine the impact of a machine learning early warning risk score, electronic Cardiac Arrest Risk Triage (eCART), on mortality for elevated-risk adult inpatients.

Design: A pragmatic pre- and post-intervention study conducted over the same 10-month period in 2 consecutive years.

Setting: Four-hospital community-academic health system.

Identifying High-Risk Subphenotypes and Associated Harms From Delayed Antibiotic Orders and Delivery.

Objectives: Early antibiotic administration is a central component of sepsis guidelines, and delays may increase mortality. However, prior studies have examined the delay to first antibiotic administration as a single time period even though it contains two distinct processes: antibiotic ordering and antibiotic delivery, which can each be targeted for improvement through different interventions. The objective of this study was to characterize and compare patients who experienced order or delivery delays, investigate the association of each delay type with mortality, and identify novel patient subphenotypes with elevated risk of harm from delays.

Determining the Electronic Signature of Infection in Electronic Health Record Data.

Objectives: Recent sepsis studies have defined patients as "infected" using a combination of culture and antibiotic orders rather than billing data. However, the accuracy of these definitions is unclear. We aimed to compare the accuracy of different established criteria for identifying infected patients using detailed chart review.

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

Importance: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated.

Objective: To internally and externally validate a machine learning risk score to detect AKI in hospitalized patients.

Comparison of Early Warning Scoring Systems for Hospitalized Patients With and Without Infection at Risk for In-Hospital Mortality and Transfer to the Intensive Care Unit.

Importance: Risk scores used in early warning systems exist for general inpatients and patients with suspected infection outside the intensive care unit (ICU), but their relative performance is incompletely characterized.

Objective: To compare the performance of tools used to determine points-based risk scores among all hospitalized patients, including those with and without suspected infection, for identifying those at risk for death and/or ICU transfer.

Design, Setting, And Participants: In a cohort design, a retrospective analysis of prospectively collected data was conducted in 21 California and 7 Illinois hospitals between 2006 and 2018 among adult inpatients outside the ICU using points-based scores from 5 commonly used tools: National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), Between the Flags (BTF), Quick Sequential Sepsis-Related Organ Failure Assessment (qSOFA), and Systemic Inflammatory Response Syndrome (SIRS).

Science meets policy: A framework for determining impairment designation criteria for large waterbodies affected by cyanobacterial harmful algal blooms.

Toxic cyanobacterial harmful algal blooms (cyanoHABs) are one of the most significant threats to the security of Earth's surface freshwaters. In the United States, the Federal Water Pollution Control Act of 1972 (i.e.

Cellulose-based amorphous solid dispersions enhance rifapentine delivery characteristics in vitro.

The efficacy of rifapentine, an oral antibiotic used to treat tuberculosis, may be reduced due to degradation at gastric pH and low solubility at intestinal pH. We hypothesized that delivery properties would be improved in vitro by incorporating rifapentine into pH-responsive amorphous solid dispersions (ASDs) with cellulose derivatives including: hydroxypropylmethylcellulose acetate succinate (HPMCAS), cellulose acetate suberate (CASub), and 5-carboxypentyl hydroxypropyl cellulose (CHC). ASDs generally reduced rifapentine release at gastric pH, with CASub affording >31-fold decrease in area under the curve (AUC) compared to rifapentine alone.

Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation.

Background: Previous research investigating the impact of delayed intensive care unit (ICU) transfer on outcomes has utilized subjective criteria for defining critical illness.

Objective: To investigate the impact of delayed ICU transfer using the electronic Cardiac Arrest Risk Triage (eCART) score, a previously published early warning score, as an objective marker of critical illness.

Design: Observational cohort study.

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

Objective: Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter database.

Design: Observational cohort study.

Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward Patients.

Rationale: Tools that screen inpatients for sepsis use the systemic inflammatory response syndrome (SIRS) criteria and organ dysfunctions, but most studies of these criteria were performed in intensive care unit or emergency room populations.

Objectives: To determine the incidence and prognostic value of SIRS and organ dysfunctions in a multicenter dataset of hospitalized ward patients.

Methods: Hospitalized ward patients at five hospitals from November 2008 to January 2013 were included.

Differences in vital signs between elderly and nonelderly patients prior to ward cardiac arrest.

Objectives: Vital signs and composite scores, such as the Modified Early Warning Score, are used to identify high-risk ward patients and trigger rapid response teams. Although age-related vital sign changes are known to occur, little is known about the differences in vital signs between elderly and nonelderly patients prior to ward cardiac arrest. We aimed to compare the accuracy of vital signs for detecting cardiac arrest between elderly and nonelderly patients.

Multicenter development and validation of a risk stratification tool for ward patients.

Rationale: Most ward risk scores were created using subjective opinion in individual hospitals and only use vital signs.

Objectives: To develop and validate a risk score using commonly collected electronic health record data.

Methods: All patients hospitalized on the wards in five hospitals were included in this observational cohort study.

Structure elucidation of an unexpected product from dehydration of a beta-hydroxyketone.

The structure of an unexpected compound from the dehydration of an aldol addition product has been determined using 1-D and 2-D NMR techniques. This reaction is the last step in a new synthetic approach to the galanthan ring system. Complete 1H and 13C NMR assignments for two synthetic precursors are also reported.

A photochemical approach to the Galanthan ring system.

A five-step, atom-efficient synthesis of the Galanthan tetracyclic skeleton has been developed. The key step is an unusual intramolecular de Mayo reaction using an isocarbostyril substrate with a functionalized tether on nitrogen. The target molecule is produced in 35% overall yield from isocarbostyril.

Effect of spinal cord injury on the respiratory system.

There are >200,000 persons living with a spinal cord injury in the United States, with approximately 10,000 new cases of traumatic injury per year. Advances in the care of these patients have significantly reduced acute and long-term mortality rates, although life expectancy remains decreased. This article will review the alterations in respiratory mechanics resulting from a spinal cord injury and will examine the contribution of respiratory complications to morbidity and mortality associated with various types of spinal cord injury.

Successful pregnancy in a patient with spinal muscular atrophy and severe kyphoscoliosis.

Pregnancy imposes a load on the respiratory system that is usually easily assumed because of alterations in the thoracoabdominal architecture. It is presumed that the respiratory mechanical disadvantage of severe kyphoscoliosis and the muscle weakness of spinal muscular atrophy impede these adaptations sufficiently to preclude a successful gestation. We report the case of a successful pregnancy in a woman with spinal muscular atrophy, severe uncorrected scoliosis, and the lowest spirometric values reported in the literature without the use of ventilatory support.

Impact of respiratory complications on length of stay and hospital costs in acute cervical spine injury.

Context: Respiratory complications are frequent in patients with acute cervical spinal injury (CSI); however, the importance of respiratory complications experienced during the initial hospitalization following injury is unknown.

Objective: To determine if respiratory complications experienced during the initial acute-care hospitalization in patients with acute traumatic cervical spinal injury (CSI) are more important determinants of the length of stay (LOS) and total hospital costs than level of injury.

Design: A retrospective analysis of an inception cohort for the 5-year period from 1993 to 1997.