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Article: Discharges against medical advice: time to take another look. A retrospective review of discharges against medical advice focused on prevention.

Jaydev, Fnu / Gavin, Warren / Russ, Jason / Holmes, Emily / Kumar, Vinod / Sadowski, Joshua / Kara, Areeba

Hospital practice (1995)

2024 Volume 51, Issue 5, Page(s) 288–294

Abstract: Background: Discharges against medical advice (DAMA) increase the risk of death.: Methods: We retrieved DAMA from five hospitals within a large health system and reviewed 10% of DAMA from the academic site between 2016 and 2021.: Results: DAMA ... ...

Abstract	Background: Discharges against medical advice (DAMA) increase the risk of death. Methods: We retrieved DAMA from five hospitals within a large health system and reviewed 10% of DAMA from the academic site between 2016 and 2021. Results: DAMA increased at the onset of the pandemic. Patients who discharged AMA multiple times accounted for a third of all DAMA. Detailed review was completed for 278 patients who discharged AMA from the academic site. In this sample, women comprised 52% of those who discharged AMA multiple times. Relative to the proportion of all discharges from the academic site during the study period, Black patients were overrepresented among DAMA (21% vs. 34%, Conclusions: Drivers of AMA discharge may differ by AMA discharge frequency. Recognition of the common reasons for requesting premature discharge may help destigmatize AMA discharges and also identifies early assessments by social work colleagues as an important prevention strategy. Opportunities also exist in anticipating and preventing withdrawal symptoms and in revising hospital practices that contribute to DAMA.
MeSH term(s)	Female ; Humans ; Male ; Hospitals ; Patient Discharge ; Retrospective Studies ; Treatment Refusal
Language	English
Publishing date	2024-01-10
Publishing country	England
Document type	Journal Article
ZDB-ID	2570453-9
ISSN	2377-1003 ; 2154-8331 ; 8750-2836
ISSN (online)	2377-1003
ISSN	2154-8331 ; 8750-2836
DOI	10.1080/21548331.2023.2287431
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Article: Accuracy of the Simplified HOSPITAL Score in Predicting COVID-19 Readmissions-Exploring Outcomes from a Hospital-at-Home Program.

Gavin, Warren / Rager, Joshua / Russ, Jason / Subramoney, Kavitha / Kara, Areeba

Journal of healthcare management / American College of Healthcare Executives

2021 Volume 67, Issue 1, Page(s) 54–62

MeSH term(s)	COVID-19 ; Hospitals ; Humans ; Patient Readmission ; Retrospective Studies ; SARS-CoV-2
Language	English
Publishing date	2021-11-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	1418083-2
ISSN	1944-7396 ; 1096-9012
ISSN (online)	1944-7396
ISSN	1096-9012
DOI	10.1097/JHM-D-21-00092
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Article ; Online: Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

Kress, Gavin T / Chan, Fion / Garcia, Claudia A / Merrifield, Warren S

BMC medical informatics and decision making

2022 Volume 22, Issue 1, Page(s) 290

Abstract: Background: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in resistance ... ...

Abstract	Background: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in resistance and reversion to uncontrolled drug-resistant epilepsy and are often associated with significant adverse effects. This has led to a trial-and-error system in which physicians spend months to years attempting to identify the optimal therapeutic approach. Objective: To investigate the potential clinical utility from the context of optimal therapeutic prediction of characterizing cellular electrophysiology. It is well-established that genomic data alone can sometimes be predictive of effective therapeutic approach. Thus, to assess the predictive power of electrophysiological data, machine learning strategies are implemented to predict a subject's genetically defined class in an in silico model using brief electrophysiological recordings obtained from simulated neuronal networks. Methods: A dynamic network of isogenic neurons is modeled in silico for 1-s for 228 dynamically modeled patients falling into one of three categories: healthy, general sodium channel gain of function, or inhibitory sodium channel loss of function. Data from previous studies investigating the electrophysiological and cellular properties of neurons in vitro are used to define the parameters governing said models. Ninety-two electrophysiological features defining the nature and consistency of network connectivity, activity, waveform shape, and complexity are extracted for each patient network and t-tests are used for feature selection for the following machine learning algorithms: Neural Network, Support Vector Machine, Gaussian Naïve Bayes Classifier, Decision Tree, and Gradient Boosting Decision Tree. Finally, their performance in accurately predicting which genetic category the subjects fall under is assessed. Results: Several machine learning algorithms excel in using electrophysiological data from isogenic neurons to accurately predict genetic class with a Gaussian Naïve Bayes Classifier predicting healthy, gain of function, and overall, with the best accuracy, area under the curve, and F1. The Gradient Boosting Decision Tree performs the best for loss of function models indicated by the same metrics. Conclusions: It is possible for machine learning algorithms to use electrophysiological data to predict clinically valuable metrics such as optimal therapeutic approach, especially when combining several models.
MeSH term(s)	Humans ; Bayes Theorem ; Machine Learning ; Algorithms ; Support Vector Machine ; Epilepsy/diagnosis ; Epilepsy/genetics ; Computer Simulation ; Neurons ; Mutation
Language	English
Publishing date	2022-11-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2046490-3
ISSN	1472-6947 ; 1472-6947
ISSN (online)	1472-6947
ISSN	1472-6947
DOI	10.1186/s12911-022-02038-7
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Article ; Online: Changing faces of mitochondrial disease: autosomal recessive

Elwan, Menatalla / Schaefer, Andrew M / Craig, Kate / Hopton, Sila / Falkous, Gavin / Blakely, Emma L / Taylor, Robert W / Warren, Naomi

BMJ neurology open

2022 Volume 4, Issue 2, Page(s) e000352

Abstract: Background: Mitochondrial disorders are known to cause diverse neurological phenotypes which cause a diagnostic challenge to most neurologists. Pathogenic polymerase gamma (: Methods: We report a case of a 58-year-old man who presented with an eye ... ...

Abstract	Background: Mitochondrial disorders are known to cause diverse neurological phenotypes which cause a diagnostic challenge to most neurologists. Pathogenic polymerase gamma ( Methods: We report a case of a 58-year-old man who presented with an eye movement disorder then Parkinsonism who made his way through the myasthenia then the movement disorder clinic. Results: A diagnostic right tibialis anterior biopsy revealed classical hallmarks of mitochondrial disease, and genetic testing identified compound heterozygous pathogenic gene variants in the Conclusions: It is important to maintain a high index of suspicion of pathogenic
Language	English
Publishing date	2022-12-08
Publishing country	England
Document type	Journal Article
ISSN	2632-6140
ISSN (online)	2632-6140
DOI	10.1136/bmjno-2022-000352
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Article ; Online: Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks

Gavin T. Kress / Fion Chan / Claudia A. Garcia / Warren S. Merrifield

BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-

2022 Volume 16

Abstract: Abstract Background Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in ... ...

Abstract	Abstract Background Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in resistance and reversion to uncontrolled drug-resistant epilepsy and are often associated with significant adverse effects. This has led to a trial-and-error system in which physicians spend months to years attempting to identify the optimal therapeutic approach. Objective To investigate the potential clinical utility from the context of optimal therapeutic prediction of characterizing cellular electrophysiology. It is well-established that genomic data alone can sometimes be predictive of effective therapeutic approach. Thus, to assess the predictive power of electrophysiological data, machine learning strategies are implemented to predict a subject’s genetically defined class in an in silico model using brief electrophysiological recordings obtained from simulated neuronal networks. Methods A dynamic network of isogenic neurons is modeled in silico for 1-s for 228 dynamically modeled patients falling into one of three categories: healthy, general sodium channel gain of function, or inhibitory sodium channel loss of function. Data from previous studies investigating the electrophysiological and cellular properties of neurons in vitro are used to define the parameters governing said models. Ninety-two electrophysiological features defining the nature and consistency of network connectivity, activity, waveform shape, and complexity are extracted for each patient network and t-tests are used for feature selection for the following machine learning algorithms: Neural Network, Support Vector Machine, Gaussian Naïve Bayes Classifier, Decision Tree, and Gradient Boosting Decision Tree. Finally, their performance in accurately predicting which genetic category the subjects fall under is assessed. Results Several machine learning algorithms excel in using electrophysiological ...
Keywords	Machine learning ; Neural network ; Support vector machine ; Gaussian naïve bayes ; Decision tree ; Gradient boosting decision tree ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	006
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
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Article ; Online: The NightLife study - the clinical and cost-effectiveness of thrice-weekly, extended, in-centre nocturnal haemodialysis versus daytime haemodialysis using a mixed methods approach: study protocol for a randomised controlled trial.

Hull, Katherine L / Bramham, Kate / Brookes, Cassandra L / Cluley, Victoria / Conefrey, Carmel / Cooper, Nicola J / Eborall, Helen / Fotheringham, James / Graham-Brown, Matthew P M / Gray, Laura J / Mark, Patrick B / Mitra, Sandip / Murphy, Gavin J / Quann, Niamh / Rooshenas, Leila / Warren, Madeleine / Burton, James O

Trials

2023 Volume 24, Issue 1, Page(s) 522

Abstract: Background: In-centre nocturnal haemodialysis (INHD) offers extended-hours haemodialysis, 6 to 8 h thrice-weekly overnight, with the support of dialysis specialist nurses. There is increasing observational data demonstrating potential benefits of INHD ... ...

Abstract	Background: In-centre nocturnal haemodialysis (INHD) offers extended-hours haemodialysis, 6 to 8 h thrice-weekly overnight, with the support of dialysis specialist nurses. There is increasing observational data demonstrating potential benefits of INHD on health-related quality of life (HRQoL). There is a lack of randomised controlled trial (RCT) data to confirm these benefits and assess safety. Methods: The NightLife study is a pragmatic, two-arm, multicentre RCT comparing the impact of 6 months INHD to conventional haemodialysis (thrice-weekly daytime in-centre haemodialysis, 3.5-5 h per session). The primary outcome is the total score from the Kidney Disease Quality of Life tool at 6 months. Secondary outcomes include sleep and cognitive function, measures of safety, adherence to dialysis and impact on clinical parameters. There is an embedded Process Evaluation to assess implementation, health economic modelling and a QuinteT Recruitment Intervention to understand factors that influence recruitment and retention. Adults (≥ 18 years old) who have been established on haemodialysis for > 3 months are eligible to participate. Discussion: There are 68,000 adults in the UK that need kidney replacement therapy (KRT), with in-centre haemodialysis the treatment modality for over a third of cases. HRQoL is an independent predictor of hospitalisation and mortality in individuals on maintenance dialysis. Haemodialysis is associated with poor HRQoL in comparison to the general population. INHD has the potential to improve HRQoL. Vigorous RCT evidence of effectiveness is lacking. The NightLife study is an essential step in the understanding of dialysis therapies and will guide patient-centred decisions regarding KRT in the future. Trial registration: Trial registration number: ISRCTN87042063. Registered: 14/07/2020.
MeSH term(s)	Adult ; Humans ; Adolescent ; Cost-Benefit Analysis ; Renal Dialysis/adverse effects ; Renal Dialysis/methods ; Renal Replacement Therapy ; Quality of Life ; Randomized Controlled Trials as Topic
Language	English
Publishing date	2023-08-12
Publishing country	England
Document type	Clinical Trial Protocol ; Journal Article
ZDB-ID	2040523-6
ISSN	1745-6215 ; 1468-6694 ; 1745-6215
ISSN (online)	1745-6215
ISSN	1468-6694 ; 1745-6215
DOI	10.1186/s13063-023-07565-w
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Article: A Novel Ketone-Supplemented Diet Improves Recognition Memory and Hippocampal Mitochondrial Efficiency in Healthy Adult Mice.

Saito, Erin R / Warren, Cali E / Hanegan, Cameron M / Larsen, John G / du Randt, Johannes D / Cannon, Mio / Saito, Jeremy Y / Campbell, Rachel J / Kemberling, Colin M / Miller, Gavin S / Edwards, Jeffrey G / Bikman, Benjamin T

Metabolites

2022 Volume 12, Issue 11

Abstract: Mitochondrial dysfunction and cognitive impairment are common symptoms in many neurologic and psychiatric disorders, as well as nonpathological aging. Ketones have been suggested as therapeutic for their efficacy in epilepsy and other brain pathologies ... ...

Abstract	Mitochondrial dysfunction and cognitive impairment are common symptoms in many neurologic and psychiatric disorders, as well as nonpathological aging. Ketones have been suggested as therapeutic for their efficacy in epilepsy and other brain pathologies such as Alzheimer's disease and major depressive disorder. However, their effects on cognitive function in healthy individuals is less established. Here, we explored the mitochondrial and performative outcomes of a novel eight-week ketone-supplemented ketogenic (KETO) diet in healthy adult male and female mice. In a novel object recognition test, KETO mice spent more time with the novel, compared to familiar, object, indicating an improvement in recognition memory. High-resolution respirometry on permeabilized hippocampal tissue returned significant reductions in mitochondrial O
Language	English
Publishing date	2022-10-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662251-8
ISSN	2218-1989
ISSN	2218-1989
DOI	10.3390/metabo12111019
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Article ; Online: Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment (SMARTT): a study protocol for a phase IV pragmatic randomized controlled patient management strategy trial.

Van Rie, Annelies / De Vos, Elise / Costa, Emilyn / Verboven, Lennert / Ndebele, Felex / Heupink, Tim H / Abrams, Steven / Fanampe, Boitumelo / Van der Spoel Van Dyk, Anneke / Charalambous, Salome / Churchyard, Gavin / Warren, Rob

Trials

2022 Volume 23, Issue 1, Page(s) 864

Abstract: Background: Rifampicin-resistant tuberculosis (RR-TB) remains an important global health problem. Ideally, the complete drug-resistance profile guides individualized treatment for all RR-TB patients, but this is only practised in high-income countries. ... ...

Abstract	Background: Rifampicin-resistant tuberculosis (RR-TB) remains an important global health problem. Ideally, the complete drug-resistance profile guides individualized treatment for all RR-TB patients, but this is only practised in high-income countries. Implementation of whole genome sequencing (WGS) technologies into routine care in low and middle-income countries has not become a reality due to the expected implementation challenges, including translating WGS results into individualized treatment regimen composition. Methods: This trial is a pragmatic, single-blinded, randomized controlled medical device trial of a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB. Subjects are 18 years or older and diagnosed with pulmonary RR-TB in four of the five health districts of the Free State province in South Africa. Participants are randomized in a 1:1 ratio to either the intervention (a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB) or control (RR-TB treatment according to the national South African guidelines). The primary effectiveness outcome is the bacteriological response to treatment measured as the rate of change in time to liquid culture positivity during the first 6 months of treatment. Secondary effectiveness outcomes include cure rate, relapse rate (recurrence of RR-TB disease) and TB free survival rate in the first 12 months following RR-TB treatment completion. Additional secondary outcomes of interest include safety, the feasibility of province-wide implementation of the strategy into routine care, and health economic assessment from a patient and health systems perspective. Discussion: This trial will provide important real-life evidence regarding the feasibility, safety, cost, and effectiveness of a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB. Given the pragmatic nature, the trial will assist policymakers in the decision-making regarding the integration of next-generation sequencing technologies into routine RR-TB care in high TB burden settings. Trial registration: ClinicalTrials.gov NCT05017324. Registered on August 23, 2021.
MeSH term(s)	Algorithms ; Antitubercular Agents/adverse effects ; Clinical Trials, Phase IV as Topic ; Humans ; Mycobacterium ; Neoplasm Recurrence, Local ; Pragmatic Clinical Trials as Topic ; Randomized Controlled Trials as Topic ; Rifampin/adverse effects ; Tuberculosis, Multidrug-Resistant/diagnosis ; Tuberculosis, Multidrug-Resistant/drug therapy
Chemical Substances	Antitubercular Agents ; Rifampin (VJT6J7R4TR)
Language	English
Publishing date	2022-10-08
Publishing country	England
Document type	Clinical Trial Protocol ; Journal Article
ZDB-ID	2040523-6
ISSN	1745-6215 ; 1468-6694 ; 1745-6215
ISSN (online)	1745-6215
ISSN	1468-6694 ; 1745-6215
DOI	10.1186/s13063-022-06793-w
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Article ; Online: Off Target But Hitting the Mark.

Kara, Areeba / Mookherjee, Somnath / Gavin, Warren / McDonough, Karen

Journal of hospital medicine

2017 Volume 13, Issue 4, Page(s) 280–284

MeSH term(s)	Abdominal Pain/etiology ; Adult ; Cholecystectomy ; Doxycycline/therapeutic use ; Emergency Service, Hospital ; Female ; Humans ; Lyme Disease/diagnosis ; Lyme Disease/drug therapy ; Vomiting/etiology ; Weight Loss
Chemical Substances	Doxycycline (N12000U13O)
Language	English
Publishing date	2017-12-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	2233783-0
ISSN	1553-5606 ; 1553-5592
ISSN (online)	1553-5606
ISSN	1553-5592
DOI	10.12788/jhm.2887
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Article ; Online: Effective Management of Closed Hypereutrophic Estuaries Requires Catchment-Scale Interventions

Daniel A. Lemley / Stephen J. Lamberth / Warren Manuel / Monique Nunes / Gavin M. Rishworth / Lara van Niekerk / Janine B. Adams

Frontiers in Marine Science, Vol

2021 Volume 8

Abstract: Increased nutrient loading associated with rapid population growth is the leading cause of deteriorating water quality in urbanized estuaries globally. Small estuaries are particularly sensitive to changes when connection with the marine environment is ... ...

Abstract	Increased nutrient loading associated with rapid population growth is the leading cause of deteriorating water quality in urbanized estuaries globally. Small estuaries are particularly sensitive to changes when connection with the marine environment is restricted, or lost, because of high water retention. The temporarily closed Hartenbos Estuary (South Africa) is an example of how such pressures can culminate in a severely degraded ecosystem. Wastewater treatment work (WWTW) discharges introduce substantial volumes of freshwater (8,000 m3 d–1) and nutrient loads (38 kg DIN d–1 and 22 kg DIP d–1) into this estuary. This constant inflow has necessitated frequent artificial breaching (inducing alternating states) of the estuary mouth to prevent flooding of low-lying developments and, occasionally, to mitigate against extreme events such as fish kills and sewage spills. This study investigated the efficacy of artificial mouth breaching practices in eliciting responses in selected abiotic and biotic parameters. Microalgal (phytoplankton and benthic diatoms), benthic macrofauna and fish community dynamics were assessed in response to mouth state and water quality conditions using a seasonal monitoring programme. The hypereutrophic nature of the Hartenbos Estuary was highlighted by persistent high-biomass phytoplankton accumulations (>100 μg Chl-a l–1), extreme dissolved oxygen conditions (0.4–20.5 mg O2 l–1) and the predominance of harmful algal bloom (HAB) events comprising Nannochloropsis sp. and Heterosigma akashiwo. Artificial breaching of the mouth facilitated limited tidal exchange and occurred approximately bimonthly once water levels exceeded 1.9 m above mean sea level (MSL). Current pressures and management interventions have culminated in an ecosystem void of natural fluctuations and instead characterised by low diversity and shifts between undesirable states. This is highlighted by the near year-round dominance of only a few opportunistic species/groups tolerant of adverse conditions (e.g., ...
Keywords	eutrophication ; harmful algal blooms ; hypoxia ; mouth management ; nutrient loading ; Science ; Q ; General. Including nature conservation ; geographical distribution ; QH1-199.5
Subject code	333
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
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