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Article: What Twitter Can Tell Us About #IDWeek2020.

Medford, Richard J / Saleh, Sameh N

2020 Volume 8, Issue 5, Page(s) ofaa621

Abstract: We used topic modeling, subjectivity analysis, and social graph theory to analyze 11 944 tweets relating to IDWeek 2020. Twitter is a rich medium that can successfully disseminate knowledge and allow users to engage in social networks during a medical ... ...

Abstract	We used topic modeling, subjectivity analysis, and social graph theory to analyze 11 944 tweets relating to IDWeek 2020. Twitter is a rich medium that can successfully disseminate knowledge and allow users to engage in social networks during a medical conference, despite a virtual format.
Language	English
Publishing date	2020-12-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	2757767-3
ISSN	2328-8957
ISSN	2328-8957
DOI	10.1093/ofid/ofaa621
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Clot Thickens: Diagnosing Acute Pulmonary Embolism as a Trigger for Chronic Obstructive Pulmonary Disease Exacerbation in the Setting of Anticoagulation Failure.

Saleh, Sameh N / Mansi, Ishak A

European journal of case reports in internal medicine

2020 Volume 7, Issue 12, Page(s) 1884

Abstract: Chronic obstructive pulmonary disease (COPD) exacerbations are most commonly triggered by infections, but up to 25% of those that require hospitalization are thought to be triggered by acute pulmonary embolism. We present the case of a 71-year-old ... ...

Abstract	Chronic obstructive pulmonary disease (COPD) exacerbations are most commonly triggered by infections, but up to 25% of those that require hospitalization are thought to be triggered by acute pulmonary embolism. We present the case of a 71-year-old patient with a history of unprovoked pulmonary embolisms on anticoagulation therapy hospitalized for a COPD exacerbation. The exacerbation was triggered by an acute pulmonary embolism, representing anticoagulation failure. Learning points: Pulmonary embolism (PE) is an important trigger of COPD exacerbations and should be considered, especially when there is an unexplained abrupt or recurrent increase in the frequency or severity of exacerbations.Therapeutic anticoagulation does not preclude the presence of PE.Clinical risk stratification is a crucial component of medical decision-making.
Language	English
Publishing date	2020-09-23
Publishing country	Italy
Document type	Journal Article
ISSN	2284-2594
ISSN (online)	2284-2594
DOI	10.12890/2020_001884
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

Garduno-Rapp, Nelly Estefanie / Ng, Yee Seng / Weon, Jenny L / Saleh, Sameh N / Lehmann, Christoph U / Tian, Chenlu / Quinn, Andrew

American journal of clinical pathology

2024

Abstract: Objectives: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adult patients with incidental IDA may have gastrointestinal cancer. A diagnosis of IDA can be established through a combination of laboratory tests, but it ... ...

Abstract	Objectives: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adult patients with incidental IDA may have gastrointestinal cancer. A diagnosis of IDA can be established through a combination of laboratory tests, but it is often underrecognized until a patient becomes symptomatic. Based on advances in machine learning, we hypothesized that we could reduce the time to diagnosis by developing an IDA prediction model. Our goal was to develop 3 neural networks by using retrospective longitudinal outpatient laboratory data to predict the risk of IDA 3 to 6 months before traditional diagnosis. Methods: We analyzed retrospective outpatient electronic health record data between 2009 and 2020 from an academic medical center in northern Texas. We included laboratory features from 30,603 patients to develop 3 types of neural networks: artificial neural networks, long short-term memory cells, and gated recurrent units. The classifiers were trained using the Adam Optimizer across 200 random training-validation splits. We calculated accuracy, area under the receiving operating characteristic curve, sensitivity, and specificity in the testing split. Results: Although all models demonstrated comparable performance, the gated recurrent unit model outperformed the other 2, achieving an accuracy of 0.83, an area under the receiving operating characteristic curve of 0.89, a sensitivity of 0.75, and a specificity of 0.85 across 200 epochs. Conclusions: Our results showcase the feasibility of employing deep learning techniques for early prediction of IDA in the outpatient setting based on sequences of laboratory data, offering a substantial lead time for clinical intervention.
Language	English
Publishing date	2024-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2944-0
ISSN	1943-7722 ; 0002-9173
ISSN (online)	1943-7722
ISSN	0002-9173
DOI	10.1093/ajcp/aqae031
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Article ; Online: Reaching Populations at Risk for HIV Through Targeted Facebook Advertisements: Cost-Consequence Analysis.

Hanna, John J / Saleh, Sameh N / Lehmann, Christoph U / Nijhawan, Ank E / Medford, Richard J

JMIR formative research

2023 Volume 7, Page(s) e38630

Abstract: Background: An undiagnosed HIV infection remains a public health challenge. In the digital era, social media and digital health communication have been widely used to accelerate research, improve consumer health, and facilitate public health ... ...

Abstract	Background: An undiagnosed HIV infection remains a public health challenge. In the digital era, social media and digital health communication have been widely used to accelerate research, improve consumer health, and facilitate public health interventions including HIV prevention. Objective: We aimed to evaluate and compare the projected cost and efficacy of different simulated Facebook (FB) advertisement (ad) approaches targeting at-risk populations for HIV based on new HIV diagnosis rates by age group and geographic region in the United States. Methods: We used the FB ad platform to simulate (without actually launching) an automatically placed video ad for a 10-day duration targeting at-risk populations for HIV. We compared the estimated total ad audience, daily reach, daily clicks, and cost. We tested ads for the age group of 13 to 24 years (in which undiagnosed HIV is most prevalent), other age groups, US geographic regions and states, and different campaign budgets. We then estimated the ad cost per new HIV diagnosis based on HIV positivity rates and the average health care industry conversion rate. Results: On April 20, 2021, the potential reach of targeted ads to at-risk populations for HIV in the United States was approximately 16 million for all age groups and 3.3 million for age group 13 to 24 years, with the highest potential reach in California, Texas, Florida, and New York. When using different FB ad budgets, the daily reach and daily clicks per US dollar followed a cumulative distribution curve of an exponential function. Using multiple US $10 ten-day ads, the cost per every new HIV diagnosis ranged from US $13.09 to US $37.82, with an average cost of US $19.45. In contrast, a 1-time national ad had a cost of US $72.76 to US $452.25 per new HIV diagnosis (mean US $166.79). The estimated cost per new HIV diagnosis ranged from US $13.96 to US $55.10 for all age groups (highest potential reach and lowest cost in the age groups 20-29 and 30-39 years) and from US $12.55 to US $24.67 for all US regions (with the highest potential reach of 6.2 million and the lowest cost per new HIV diagnosis at US $12.55 in the US South). Conclusions: Targeted personalized FB ads are a potential means to encourage at-risk populations for HIV to be tested, especially those aged 20 to 39 years in the US South, where the disease burden and potential reach on FB are high and the ad cost per new HIV diagnosis is low. Considering the cost efficiency of ads, the combined cost of multiple low-cost ads may be more economical than a single high-cost ad, suggesting that local FB ads could be more cost-effective than a single large-budget national FB ad.
Language	English
Publishing date	2023-01-20
Publishing country	Canada
Document type	Journal Article
ISSN	2561-326X
ISSN (online)	2561-326X
DOI	10.2196/38630
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.

Lanier, Heather D / Diaz, Marlon I / Saleh, Sameh N / Lehmann, Christoph U / Medford, Richard J

PloS one

2022 Volume 17, Issue 6, Page(s) e0268409

Abstract: Introduction: The use of social media during the COVID-19 pandemic has led to an "infodemic" of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags # ... ...

Abstract	Introduction: The use of social media during the COVID-19 pandemic has led to an "infodemic" of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags #Scamdemic and #Plandemic. Methods: Using a Twitter scraping tool called twint, we collected 419,269 English-language tweets that contained "#Scamdemic" or "#Plandemic" posted in 2020. Using the Twitter application-programming interface, we extracted the same tweets (by tweet ID) with additional user metadata. We explored descriptive statistics of tweets including their content and user profiles, analyzed sentiments and emotions, performed topic modeling, and determined tweet availability in both datasets. Results: After removal of retweets, replies, non-English tweets, or duplicate tweets, 40,081 users tweeted 227,067 times using our selected hashtags. The mean weekly sentiment was overall negative for both hashtags. One in five users who used these hashtags were suspended by Twitter by January 2021. Suspended accounts had an average of 610 followers and an average of 6.7 tweets per user, while active users had an average of 472 followers and an average of 5.4 tweets per user. The most frequent tweet topic was "Complaints against mandates introduced during the pandemic" (79,670 tweets), which included complaints against masks, social distancing, and closures. Discussion: While social media has democratized speech, it also permits users to disseminate potentially unverified or misleading information that endangers people's lives and public health interventions. Characterizing tweets and users that use hashtags associated with COVID-19 pandemic denial allowed us to understand the extent of misinformation. With the preponderance of inaccessible original tweets, we concluded that posters were in denial of the COVID-19 pandemic and sought to disperse related mis- or disinformation resulting in suspension. Conclusion: Leveraging 227,067 tweets with the hashtags #scamdemic and #plandemic in 2020, we were able to elucidate important trends in public disinformation about the COVID-19 vaccine.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines ; Disinformation ; Humans ; Pandemics/prevention & control ; Retrospective Studies ; Social Media
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2022-06-22
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0268409
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: 1H-NMR metabolomics analysis identifies hypoxanthine as a novel metastasis-associated metabolite in breast cancer

Sarra B. Shakartalla / Naglaa S. Ashmawy / Mohammad H. Semreen / Bahgat Fayed / Zainab M. Al Shareef / Manju N. Jayakumar / Saleh Ibrahim / Mohamed Rahmani / Rania Hamdy / Sameh S. M. Soliman

Scientific Reports, Vol 14, Iss 1, Pp 1-

2024 Volume 17

Abstract: ... E-cadherin, N-cadherin and vimentin were examined. Some metabolites secreted from MDA-MB-231 cells ...

Abstract	Abstract Breast cancer is one of the leading causes of death in females, mainly because of metastasis. Oncometabolites, produced via metabolic reprogramming, can influence metastatic signaling cascades. Accordingly, and based on our previous results, we propose that metabolites from highly metastatic breast cancer cells behave differently from less-metastatic cells and may play a significant role in metastasis. For instance, we aim to identify these metabolites and their role in breast cancer metastasis. Less metastatic cells (MCF-7) were treated with metabolites secreted from highly metastatic cells (MDA-MB-231) and the gene expression of three epithelial-to-mesenchymal transition (EMT) markers including E-cadherin, N-cadherin and vimentin were examined. Some metabolites secreted from MDA-MB-231 cells significantly induced EMT activity. Specifically, hypoxanthine demonstrated a significant EMT effect and increased the migration and invasion effects of MCF-7 cells through a hypoxia-associated mechanism. Hypoxanthine exhibited pro-angiogenic effects via increasing the VEGF and PDGF gene expression and affected lipid metabolism by increasing the gene expression of PCSK-9. Notably, knockdown of purine nucleoside phosphorylase, a gene encoding for an important enzyme in the biosynthesis of hypoxanthine, and inhibition of hypoxanthine uptake caused a significant decrease in hypoxanthine-associated EMT effects. Collectively for the first time, hypoxanthine was identified as a novel metastasis-associated metabolite in breast cancer cells and represents a promising target for diagnosis and therapy.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Social media: A new tool for outbreak surveillance.

Wilson, Averi E / Lehmann, Christoph U / Saleh, Sameh N / Hanna, John / Medford, Richard J

Antimicrobial stewardship & healthcare epidemiology : ASHE

2021 Volume 1, Issue 1, Page(s) e50

Abstract: Social media platforms allow users to share news, ideas, thoughts, and opinions on a global scale. Data processing methods allow researchers to automate the collection and interpretation of social media posts for efficient and valuable disease ... ...

Abstract	Social media platforms allow users to share news, ideas, thoughts, and opinions on a global scale. Data processing methods allow researchers to automate the collection and interpretation of social media posts for efficient and valuable disease surveillance. Data derived from social media and internet search trends have been used successfully for monitoring and forecasting disease outbreaks such as Zika, Dengue, MERS, and Ebola viruses. More recently, data derived from social media have been used to monitor and model disease incidence during the coronavirus disease 2019 (COVID-19) pandemic. We discuss the use of social media for disease surveillance.
Language	English
Publishing date	2021-11-17
Publishing country	England
Document type	Journal Article ; Review
ISSN	2732-494X
ISSN (online)	2732-494X
DOI	10.1017/ash.2021.225
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: 1

Shakartalla, Sarra B / Ashmawy, Naglaa S / Semreen, Mohammad H / Fayed, Bahgat / Al Shareef, Zainab M / Jayakumar, Manju N / Ibrahim, Saleh / Rahmani, Mohamed / Hamdy, Rania / Soliman, Sameh S M

Scientific reports

2024 Volume 14, Issue 1, Page(s) 253

Abstract: ... epithelial-to-mesenchymal transition (EMT) markers including E-cadherin, N-cadherin and vimentin were examined. Some metabolites ...

Abstract	Breast cancer is one of the leading causes of death in females, mainly because of metastasis. Oncometabolites, produced via metabolic reprogramming, can influence metastatic signaling cascades. Accordingly, and based on our previous results, we propose that metabolites from highly metastatic breast cancer cells behave differently from less-metastatic cells and may play a significant role in metastasis. For instance, we aim to identify these metabolites and their role in breast cancer metastasis. Less metastatic cells (MCF-7) were treated with metabolites secreted from highly metastatic cells (MDA-MB-231) and the gene expression of three epithelial-to-mesenchymal transition (EMT) markers including E-cadherin, N-cadherin and vimentin were examined. Some metabolites secreted from MDA-MB-231 cells significantly induced EMT activity. Specifically, hypoxanthine demonstrated a significant EMT effect and increased the migration and invasion effects of MCF-7 cells through a hypoxia-associated mechanism. Hypoxanthine exhibited pro-angiogenic effects via increasing the VEGF and PDGF gene expression and affected lipid metabolism by increasing the gene expression of PCSK-9. Notably, knockdown of purine nucleoside phosphorylase, a gene encoding for an important enzyme in the biosynthesis of hypoxanthine, and inhibition of hypoxanthine uptake caused a significant decrease in hypoxanthine-associated EMT effects. Collectively for the first time, hypoxanthine was identified as a novel metastasis-associated metabolite in breast cancer cells and represents a promising target for diagnosis and therapy.
MeSH term(s)	Female ; Humans ; Breast Neoplasms/pathology ; Proton Magnetic Resonance Spectroscopy ; MCF-7 Cells ; Cell Line, Tumor ; Epithelial-Mesenchymal Transition/genetics ; Cell Movement ; Hypoxanthines/pharmacology
Chemical Substances	Hypoxanthines
Language	English
Publishing date	2024-01-02
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-50866-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Can we predict early 7-day readmissions using a standard 30-day hospital readmission risk prediction model?

Saleh, Sameh N / Makam, Anil N / Halm, Ethan A / Nguyen, Oanh Kieu

BMC medical informatics and decision making

2020 Volume 20, Issue 1, Page(s) 227

Abstract: Background: Despite focus on preventing 30-day readmissions, early readmissions (within 7 days of discharge) may be more preventable than later readmissions (8-30 days). We assessed how well a previously validated 30-day EHR-based readmission prediction ...

Abstract	Background: Despite focus on preventing 30-day readmissions, early readmissions (within 7 days of discharge) may be more preventable than later readmissions (8-30 days). We assessed how well a previously validated 30-day EHR-based readmission prediction model predicts 7-day readmissions and compared differences in strength of predictors. Methods: We conducted an observational study on adult hospitalizations from 6 diverse hospitals in North Texas using a 50-50 split-sample derivation and validation approach. We re-derived model coefficients for the same predictors as in the original 30-day model to optimize prediction of 7-day readmissions. We then compared the discrimination and calibration of the 7-day model to the 30-day model to assess model performance. To examine the changes in the point estimates between the two models, we evaluated the percent changes in coefficients. Results: Of 32,922 index hospitalizations among unique patients, 4.4% had a 7-day admission and 12.7% had a 30-day readmission. Our original 30-day model had modestly lower discrimination for predicting 7-day vs. any 30-day readmission (C-statistic of 0.66 vs. 0.69, p ≤ 0.001). Our re-derived 7-day model had similar discrimination (C-statistic of 0.66, p = 0.38), but improved calibration. For the re-derived 7-day model, discharge day factors were more predictive of early readmissions, while baseline characteristics were less predictive. Conclusion: A previously validated 30-day readmission model can also be used as a stopgap to predict 7-day readmissions as model performance did not substantially change. However, strength of predictors differed between the 7-day and 30-day model; characteristics at discharge were more predictive of 7-day readmissions, while baseline characteristics were less predictive. Improvements in predicting early 7-day readmissions will likely require new risk factors proximal to day of discharge.
MeSH term(s)	Aged ; Female ; Forecasting ; Hospitalization ; Hospitals ; Humans ; Male ; Middle Aged ; Patient Readmission ; Reference Standards ; Retrospective Studies ; Risk Factors ; Texas ; United States
Language	English
Publishing date	2020-09-15
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2046490-3
ISSN	1472-6947 ; 1472-6947
ISSN (online)	1472-6947
ISSN	1472-6947
DOI	10.1186/s12911-020-01248-1
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Article ; Online: Developing a COVID-19 WHO Clinical Progression Scale inpatient database from electronic health record data.

Ramaswamy, Priya / Gong, Jen J / Saleh, Sameh N / McDonald, Samuel A / Blumberg, Seth / Medford, Richard J / Liu, Xinran

Journal of the American Medical Informatics Association : JAMIA

2022 Volume 29, Issue 7, Page(s) 1279–1285

Abstract: Objective: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We ... ...

Abstract	Objective: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions. Materials and methods: Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers. Results: Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions. Discussion: Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS. Conclusion: We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.
MeSH term(s)	COVID-19 ; Databases, Factual ; Electronic Health Records ; Humans ; Inpatients ; World Health Organization
Language	English
Publishing date	2022-03-15
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocac041
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