knitr::opts_chunk$set(include = TRUE)- Use a real world API to make queries and process the data.
- Use regular expressions to parse the information.
- Practice your GitHub skills.
In this lab, we will be working with the NCBI
API to make queries and
extract information using XML and regular expressions. For this lab, we
will be using the httr, xml2, and stringr R packages.
This markdown document should be rendered using github_document
document.
library(httr)
library(tidyverse)
library(xml2)Build an automatic counter of sars-cov-2 papers using PubMed. You will need to apply XPath as we did during the lecture to extract the number of results returned by PubMed in the following web address:
https://pubmed.ncbi.nlm.nih.gov/?term=sars-cov-2
Complete the lines of code:
# Downloading the website
website <- xml2::read_html("https://pubmed.ncbi.nlm.nih.gov/?term=sars-cov-2")
#Alternative
alternative <- httr::GET(
url = "https://pubmed.ncbi.nlm.nih.gov/",
query = list(term = "sars-cov-2")
)
# Finding the counts
counts <- xml2::xml_find_first(website, "/html/body/main/div[9]/div[2]/div[2]/div[1]/span")
# Turning it into text
counts <- as.character(counts)
# Extracting the data using regex
stringr::str_extract(counts, "[0-9,]+")## [1] "33,814"
Don’t forget to commit your work!
You need to query the following The parameters passed to the query are documented here.
Use the function httr::GET() to make the following query:
-
Baseline URL: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
-
Query parameters:
- db: pubmed
- term: covid19 hawaii
- retmax: 1000
library(httr)
query_ids <- GET(
url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
query = list(db = "pubmed",
term = "covid19 hawaii",
retmax = 1000)
)
# Extracting the content of the response of GET
ids <- httr::content(query_ids)The query will return an XML object, we can turn it into a character
list to analyze the text directly with as.character(). Another way of
processing the data could be using lists with the function
xml2::as_list(). We will skip the latter for now.
Take a look at the data, and continue with the next question (don’t forget to commit and push your results to your GitHub repo!).
The Ids are wrapped around text in the following way: <Id>... id number ...</Id>. we can use a regular expression that extract that
information. Fill out the following lines of code:
# Turn the result into a character vector
ids <- as.character(ids)
# Find all the ids
ids <- stringr::str_extract_all(ids, "<Id>[0-9]+</Id>")[[1]]
# Remove all the leading and trailing <Id> </Id>. Make use of "|"
ids <- stringr::str_remove_all(ids, "<Id>|</Id>")With the ids in hand, we can now try to get the abstracts of the papers. As before, we will need to coerce the contents (results) to a list using:
-
Baseline url: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi
-
Query parameters:
- db: pubmed
- id: A character with all the ids separated by comma, e.g., “1232131,546464,13131”
- retmax: 1000
- rettype: abstract
Pro-tip: If you want GET() to take some element literal, wrap it
around I() (as you would do in a formula in R). For example, the text
"123,456" is replaced with "123%2C456". If you don’t want that
behavior, you would need to do the following I("123,456").
publications <- GET(
url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi",
query = list( db = "pubmed",
id = paste(ids,collapse = ","),
retmx = 1000,
rettype = "abstract"
)
)
# Turning the output into character vector
publications <- httr::content(publications)
publications_txt <- as.character(publications)With this in hand, we can now analyze the data. This is also a good time for committing and pushing your work!
Using the function stringr::str_extract_all() applied on
publications_txt, capture all the terms of the form:
- University of …
- … Institute of …
Write a regular expression that captures all such instances
institution <- str_extract_all(
publications_txt,
"University\\sof\\s[[:alpha:]]+|[[:alpha:]]+\\sInstitute\\sof\\s[[:alpha:]]+"
)
institution <- unlist(institution)
table(institution)## institution
## Australian Institute of Tropical Massachusetts Institute of Technology
## 9 1
## National Institute of Environmental Prophylactic Institute of Southern
## 3 2
## University of Arizona University of California
## 2 6
## University of Chicago University of Colorado
## 1 1
## University of Hawai University of Hawaii
## 20 38
## University of Health University of Illinois
## 1 1
## University of Iowa University of Lausanne
## 4 1
## University of Louisville University of Nebraska
## 1 5
## University of Nevada University of New
## 1 2
## University of Pennsylvania University of Pittsburgh
## 18 5
## University of Science University of South
## 14 1
## University of Southern University of Sydney
## 1 1
## University of Texas University of the
## 5 1
## University of Utah University of Wisconsin
## 2 3
Repeat the exercise and this time focus on schools and departments in the form of
- School of …
- Department of …
And tabulate the results
schools_and_deps <- str_extract_all(
publications_txt,
"School\\s+of\\s+[[:alpha:]]+|Department\\sof\\s[[:alpha:]]+"
)
unlist(schools_and_deps)## [1] "Department of Translational" "Department of Experimental"
## [3] "Department of Population" "School of Medicine"
## [5] "Department of Information" "School of Public"
## [7] "School of Natural" "Department of Geography"
## [9] "Department of Geography" "School of Nursing"
## [11] "School of Medicine" "School of Medicine"
## [13] "Department of Quantitative" "School of Medicine"
## [15] "Department of Medicine" "School of Medicine"
## [17] "Department of Medicine" "Department of Psychology"
## [19] "Department of Tropical" "Department of Psychiatry"
## [21] "Department of Psychiatry" "Department of Psychiatry"
## [23] "School of Medicine" "Department of Psychiatry"
## [25] "Department of Nephrology" "School of Medicine"
## [27] "Department of Nephrology" "School of Medicine"
## [29] "Department of Infectious" "School of Medicine"
## [31] "Department of Nephrology" "School of Medicine"
## [33] "Department of Infectious" "School of Medicine"
## [35] "Department of Internal" "School of Medicine"
## [37] "Department of Nephrology" "School of Medicine"
## [39] "Department of Nephrology" "School of Medicine"
## [41] "Department of Surgery" "Department of Anesthesiology"
## [43] "Department of Clinical" "Department of Clinical"
## [45] "Department of Anesthesiology" "Department of Anesthesiology"
## [47] "School of Medicine" "Department of Obstetrics"
## [49] "Department of Obstetrics" "School of Medicine"
## [51] "Department of Obstetrics" "Department of Obstetrics"
## [53] "School of Medicine" "Department of OB"
## [55] "School of Medicine" "Department of OB"
## [57] "School of Medicine" "Department of OB"
## [59] "School of Medicine" "Department of OB"
## [61] "School of Medicine" "Department of OB"
## [63] "School of Medicine" "Department of Biology"
## [65] "Department of Biology" "School of Public"
## [67] "School of Public" "Department of Biology"
## [69] "School of Public" "School of Public"
## [71] "School of Public" "Department of Nutrition"
## [73] "Department of Family" "School of Medicine"
## [75] "Department of Family" "School of Medicine"
## [77] "Department of Cell" "Department of Cell"
## [79] "Department of Cell" "Department of Cell"
## [81] "Department of Pediatrics" "School of Medicine"
## [83] "Department of Pediatrics" "School of Medicine"
## [85] "Department of Pediatrics" "Department of Pediatrics"
## [87] "Department of Pediatrics" "Department of Pediatrics"
## [89] "Department of Medicine" "Department of Pediatrics"
## [91] "Department of Pediatrics" "School of Medicine"
## [93] "School of Social" "School of Medicine"
## [95] "Department of Medicine" "School of Medicine"
## [97] "Department of Medicine" "School of Medicine"
## [99] "Department of Medicine" "School of Medicine"
## [101] "Department of Medicine" "School of Medicine"
## [103] "Department of Medicine" "School of Medicine"
## [105] "School of Medicine" "School of Medicine"
## [107] "School of Medicine" "School of Medicine"
## [109] "School of Medicine" "Department of Medicine"
## [111] "School of Medicine" "School of Medicine"
## [113] "School of Medicine" "School of Medicine"
## [115] "Department of Medicine" "School of Medicine"
## [117] "School of Medicine" "Department of Surgery"
## [119] "School of Medicine" "Department of Medicine"
## [121] "School of Medicine" "Department of Native"
## [123] "School of Medicine" "Department of Native"
## [125] "School of Medicine" "Department of Tropical"
## [127] "School of Medicine" "School of Medicine"
## [129] "Department of Tropical" "School of Medicine"
## [131] "School of Medicine" "Department of Tropical"
## [133] "School of Medicine" "School of Medicine"
## [135] "Department of Tropical" "School of Medicine"
## [137] "Department of Urology" "School of Medicine"
## [139] "Department of Pediatrics" "Department of Internal"
## [141] "Department of Internal" "Department of Pediatrics"
## [143] "Department of Pediatrics" "Department of Critical"
## [145] "School of Medicine" "Department of Internal"
## [147] "School of Medicine" "Department of Pediatrics"
## [149] "School of Medicine" "Department of Internal"
## [151] "School of Medicine" "School of Medicine"
## [153] "Department of Critical" "School of Medicine"
## [155] "School of Medicine" "School of Medicine"
## [157] "School of Medicine" "Department of Otolaryngology"
## [159] "Department of Otolaryngology" "Department of Otolaryngology"
## [161] "School of Medicine" "Department of Otolaryngology"
## [163] "Department of Communication" "School of Medicine"
## [165] "Department of Physical" "School of Medicine"
## [167] "Department of Rehabilitation" "Department of Veterans"
## [169] "Department of Medicine" "Department of Medicine"
## [171] "Department of Medicine" "Department of Medicine"
## [173] "Department of Medicine" "Department of Medicine"
## [175] "Department of Medicine" "Department of Medicine"
## [177] "Department of Medicine" "Department of Medicine"
## [179] "Department of Medicine" "Department of Medicine"
## [181] "Department of Medicine" "Department of Medicine"
## [183] "Department of Medicine" "Department of Medicine"
## [185] "Department of Medicine" "Department of Medicine"
## [187] "Department of Medicine" "Department of Medicine"
## [189] "Department of Medicine" "Department of Medicine"
## [191] "Department of Medicine" "Department of Medicine"
## [193] "Department of Medicine" "Department of Cardiology"
## [195] "Department of Epidemiology" "School of Public"
## [197] "Department of Medical" "Department of Nutrition"
## [199] "School of Public" "Department of Genetic"
## [201] "Department of Medicine" "Department of Medical"
## [203] "Department of Preventive" "School of Medicine"
## [205] "Department of Preventive" "Department of Computational"
## [207] "Department of Medical" "Department of Family"
## [209] "Department of Epidemiology" "School of Public"
## [211] "School of Medicine" "School of Medicine"
## [213] "Department of Epidemiology" "School of Public"
## [215] "Department of Medicine" "Department of Nutrition"
## [217] "School of Public" "Department of Epidemiology"
## [219] "School of Public" "Department of Epidemiology"
## [221] "School of Public" "Department of Medicine"
## [223] "Department of Environmental" "School of Public"
## [225] "Department of Medicine" "Department of Epidemiology"
## [227] "School of Public" "Department of Social"
## [229] "School of Public" "Department of Epidemiology"
## [231] "School of Public" "Department of Twin"
## [233] "Department of Medicine" "Department of Medicine"
## [235] "Department of Medicine" "Department of Medicine"
## [237] "Department of Epidemiology" "School of Public"
## [239] "Department of Twin" "Department of Nutrition"
## [241] "School of Public" "Department of Epidemiology"
## [243] "School of Public" "Department of Quantitative"
## [245] "School of Medicine" "Department of Quantitative"
## [247] "School of Medicine" "Department of Quantitative"
## [249] "School of Medicine" "Department of Quantitative"
## [251] "School of Medicine" "Department of Pediatrics"
## [253] "School of Medicine" "Department of Quantitative"
## [255] "School of Medicine" "School of Medicine"
## [257] "Department of Surgery" "Department of Surgery"
## [259] "School of Medicine" "Department of Surgery"
## [261] "Department of Neurology" "School of Medicine"
## [263] "Department of Microbiology" "School of Medicine"
## [265] "Department of Internal" "Department of Defense"
## [267] "School of Medicine" "Department of Anesthesiology"
## [269] "Department of Anesthesiology" "School of Medicine"
## [271] "School of Medicine" "Department of Physical"
## [273] "School of Medicine" "School of Medicine"
## [275] "Department of Physical" "School of Medicine"
## [277] "Department of Anesthesiology" "Department of Surgery"
## [279] "Department of Veterans"
table(schools_and_deps)## schools_and_deps
## Department of Anesthesiology Department of Biology
## 6 3
## Department of Cardiology Department of Cell
## 1 4
## Department of Clinical Department of Communication
## 2 1
## Department of Computational Department of Critical
## 1 2
## Department of Defense Department of Environmental
## 1 1
## Department of Epidemiology Department of Experimental
## 9 1
## Department of Family Department of Genetic
## 3 1
## Department of Geography Department of Infectious
## 2 2
## Department of Information Department of Internal
## 1 6
## Department of Medical Department of Medicine
## 3 44
## Department of Microbiology Department of Native
## 1 2
## Department of Nephrology Department of Neurology
## 5 1
## Department of Nutrition Department of OB
## 4 5
## Department of Obstetrics Department of Otolaryngology
## 4 4
## Department of Pediatrics Department of Physical
## 13 3
## Department of Population Department of Preventive
## 1 2
## Department of Psychiatry Department of Psychology
## 4 1
## Department of Quantitative Department of Rehabilitation
## 6 1
## Department of Social Department of Surgery
## 1 6
## Department of Translational Department of Tropical
## 1 5
## Department of Twin Department of Urology
## 2 1
## Department of Veterans School of Medicine
## 2 87
## School of Natural School of Nursing
## 1 1
## School of Public School of Social
## 20 1
We want to build a dataset which includes the title and the abstract of
the paper. The title of all records is enclosed by the HTML tag
ArticleTitle, and the abstract by Abstract.
Before applying the functions to extract text directly, it will help to
process the XML a bit. We will use the xml2::xml_children() function
to keep one element per id. This way, if a paper is missing the
abstract, or something else, we will be able to properly match PUBMED
IDS with their corresponding records.
pub_char_list <- xml2::xml_children(publications)
pub_char_list <- sapply(pub_char_list, as.character)Now, extract the abstract and article title for each one of the elements
of pub_char_list. You can either use sapply() as we just did, or
simply take advantage of vectorization of stringr::str_extract
abstracts <- str_extract(pub_char_list, "<Abstract>(\\n|.)+</Abstract>")
abstracts <- str_remove_all(abstracts, "</?[[:alnum:]]+>")
abstracts <- str_replace_all(abstracts, "\\s+"," ")How many of these don’t have an abstract? Now, the title
table(is.na(abstracts))##
## FALSE TRUE
## 25 15
titles <- str_extract(pub_char_list, "<ArticleTitle>(\\n|.)+</ArticleTitle>")
titles <- str_remove_all(titles, "</?[[:alnum:]]+>")
titles <- str_replace_all(titles,"\\s+"," ")Finally, put everything together into a single data.frame and use
knitr::kable to print the results
database <- data.frame(
PubMedID = ids,
Title = titles,
Abstracts = abstracts
)
knitr::kable(database)| PubMedID | Title | Abstracts |
|---|---|---|
| 32984015 | Perspective: Cancer Patient Management Challenges During the COVID-19 Pandemic. | On March 11, 2020, the WHO has declared the coronavirus disease 2019 (COVID-19) a global pandemic. As the last few months have profoundly changed the delivery of health care in the world, we should recognize the effort of numerous comprehensive cancer centers to share experiences and knowledge to develop best practices to care for oncological patients during the COVID-19 pandemic. Patients as well as physicians must be aware of all these constraints and profound social, personal, and medical challenges posed by the tackling of this deadly disease in everyday life in order to adjust to such a completely novel scenario. This review will discuss facing the challenges and the current approaches that cancer centers in Italy and United States are adopting in order to cope with clinical and research activities. Copyright © 2020 Terracciano, Buonerba, Scafuri, De Berardinis, Calin, Ferrajoli, Fabbri and Cimmino. |
| 32969950 | Workflow Solutions for Primary Care Clinic Recovery During the COVID-19 Pandemic: A Primer. | NA |
| 32921878 | Will COVID-19 be one shock too many for smallholder coffee livelihoods? | Coffee supports the livelihoods of millions of smallholder farmers in more than 52 countries, and generates billions of dollars in revenue. The threats that COVID-19 pose to the global coffee sector is daunting with profound implications for coffee production. The financial impacts will be long-lived and uneven, and smallholders will be among the hardest hit. We argue that the impacts are rooted in the systemic vulnerability of the coffee production system and the unequal ways the sector is organized: Large revenues from the sale of coffee in the Global North are made possible by mostly impoverished smallholders in the Global South. COVID-19 will accentuate the existing vulnerabilities and create new ones, forcing many smallholders into alternative livelihoods. This outcome, however, is not inevitable. COVID-19 presents an opportunity to rebalance the system that currently creates large profits on one end of the supply chain and great vulnerability on the other. © 2020 Elsevier Ltd. All rights reserved. |
| 32914097 | Spotlight on Nursing: Navigating Uncharted Waters: Preparing COVID-19 Capable Nurses to Work in a Transformed Workplace. | NA |
| 32914093 | Public Compliance with Face Mask Use in Honolulu and Regional Variation. | Infections with the SARS-CoV-2 virus are increasing in Hawai’i at alarming rates. In the absence of a SARS-CoV-2 virus vaccine, the options for control include social distancing, improved hygiene, and face mask use. There is evidence that mask use may decrease the rates of viral transmission. The rate of effective face mask use has not yet been established in Hawai’i. The authors performed an observational study at 2 locations in Honolulu and evaluated outdoor face mask use compliance in 200 people. Simultaneous observations were performed in a downtown Honolulu business area and in Waikiki, an area focusing on tourism. Overall, 77% of all subjects used face masks in an appropriate fashion, covering their nose and mouth, while 23% were either incorrectly masked or not masked. The rate of compliance with correct public mask use in downtown Honolulu (88%) was significantly higher than in Waikiki (66%) (P=.0003, Odds Ratio [95% Confidence Interval]=3.78 [1.82, 7.85]) These findings suggest that there are opportunities for improvement in rates of public face mask use and a potential decrease in the spread of COVID-19 in our population. Four proposed actions are suggested, including a reassessment of the face mask exemption requirements, enhanced mask compliance education, non-threatening communication for non-compliance, and centralization of information of the public compliance with face mask use. ©Copyright 2020 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| 32912595 | Ensuring mental health access for vulnerable populations in COVID era. | NA |
| 32907823 | Evidence based care for pregnant women with covid-19. | NA |
| 32907673 | Prediction and severity ratings of COVID-19 in the United States. | The objective of this paper is to predict the possible trajectory of coronavirus spread in the US. Prediction and severity ratings of COVID-19 are essential for pandemic control and economic reopening in the US. In this paper, we apply the Logistic and Gompertz model to evaluate possible turning points of COVID-19 pandemic in different regions of the US. By combining uncertainty and severity factors, this paper constructed an indicator to assess the severity of the coronavirus outbreak in various states of the US. Based on the index of severity ratings, different regions of the US are classified into four categories. The result shows that it is possible to identify the first turning point in Montana and Hawaii. It is unclear when the rest of the states in the US will reach the first peak. However, it can be inferred that 75% of regions in the US won’t reach the first peak of coronavirus before August 2, 2020. It is still essential for the majority of states in the US to take proactive steps to fight against COVID-19 before August 2, 2020. |
| 32888905 | Saliva is a reliable, non-invasive specimen for SARS-CoV-2 detection. | Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the cause of Coronavirus Disease 2019 (COVID-19). Although Real Time Reverse Transcription Polymerase Chain Reaction (qRT-PCR) of respiratory specimens is the gold standard test for detection of SARS-CoV-2 infection, collecting nasopharyngeal swabs causes discomfort to patients and may represent considerable risk for healthcare workers. The use of saliva as a diagnostic sample has several advantages. The aim of this study was to validate the use of saliva as a biological sample for diagnosis of COVID-19. This study was conducted at Infectious Diseases Research Laboratory (LAPI), in Salvador, Brazil. Participants presenting with signs/symptoms suggesting SARS-CoV-2 infection underwent a nasopharyngeal swab (NPS) and/or oropharyngeal swab (OPS), and saliva collection. Saliva samples were diluted in PBS, followed by RNA isolation and RT-Real Time PCR for SARS-CoV-2. Results of conventional vs saliva samples testing were compared. Statistical analyses were performed using Statistical Package for the Social Sciences software (SPSS) version 18.0. One hundred fifty-five participants were recruited and samples pairs of NPS/OPS and saliva were collected. The sensitivity and specificity of RT-PCR using saliva samples were 94.4% (95% CI 86.4-97.8) and 97.62% (95% CI 91.7-99.3), respectively. There was an overall high agreement (96.1%) between the two tests. Use of self-collected saliva samples is an easy, convenient, and low-cost alternative to conventional NP swab-based molecular tests. These results may allow a broader use of molecular tests for management of COVID19 pandemic, especially in resources-limited settings. Copyright © 2020 Sociedade Brasileira de Infectologia. Published by Elsevier España, S.L.U. All rights reserved. |
| 32881116 | Delivering Prolonged Exposure Therapy via Videoconferencing During the COVID-19 Pandemic: An Overview of the Research and Special Considerations for Providers. | Leveraging technology to provide evidence-based therapy for posttraumatic stress disorder (PTSD), such as prolonged exposure (PE), during the COVID-19 pandemic helps ensure continued access to first-line PTSD treatment. Clinical video teleconferencing (CVT) technology can be used to effectively deliver PE while reducing the risk of COVID-19 exposure during the pandemic for both providers and patients. However, provider knowledge, experience, and comfort level with delivering mental health care services, such as PE, via CVT is critical to ensure a smooth, safe, and effective transition to virtual care. Further, some of the limitations associated with the pandemic, including stay-at-home orders and physical distancing, require that providers become adept at applying principles of exposure therapy with more flexibility and creativity, such as when assigning in vivo exposures. The present paper provides the rationale and guidelines for implementing PE via CVT during COVID-19 and includes practical suggestions and clinical recommendations. Published 2020. This article is a U.S. Government work and is in the public domain in the USA. |
| 32837709 | Comparison of Telehealth-Related Ethics and Guidelines and a Checklist for Ethical Decision Making in the Midst of the COVID-19 Pandemic. | Applied behavior analysis (ABA) services have been provided primarily in the fields of health care and education across various settings using an in-person service delivery model. Due to the COVID-19 pandemic, the necessity of and demand for ABA services using telehealth have increased. The purpose of the present article was to cross-examine the ethical codes and guidelines of different, but related fields of practice and to discuss potential implications for telehealth-based ABA service delivery. We reviewed the telehealth-specific ethical codes and guidelines of the American Psychological Association, the American Academy of Pediatrics, and the National Association of Social Workers, along with the related ABA literature. These organizations addressed several useful and unique ethical concerns that have not been addressed in ABA literature. We also developed a brief checklist for ABA practitioners to evaluate their telehealth readiness by meeting the legal, professional, and ethical requirements of ABA services. © Association for Behavior Analysis International 2020. |
| 32763956 | Reactive arthritis after COVID-19 infection. | Reactive arthritis (ReA) is typically preceded by sexually transmitted disease or gastrointestinal infection. An association has also been reported with bacterial and viral respiratory infections. Herein, we report the first case of ReA after the he severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This male patient is in his 50s who was admitted with COVID-19 pneumonia. On the second day of admission, SARS-CoV-2 PCR was positive from nasopharyngeal swab specimen. Despite starting standard dose of favipiravir, his respiratory condition deteriorated during hospitalisation. On the fourth hospital day, he developed acute respiratory distress syndrome and was intubated. On day 11, he was successfully extubated, subsequently completing a 14-day course of favipiravir. On day 21, 1 day after starting physical therapy, he developed acute bilateral arthritis in his ankles, with mild enthesitis in his right Achilles tendon, without rash, conjunctivitis, or preceding diarrhoea or urethritis. Arthrocentesis of his left ankle revealed mild inflammatory fluid without monosodium urate or calcium pyrophosphate crystals. Culture of synovial fluid was negative. Plain X-rays of his ankles and feet showed no erosive changes or enthesophytes. Tests for syphilis, HIV, anti-streptolysin O (ASO), Mycoplasma, Chlamydia pneumoniae, antinuclear antibody, rheumatoid factor, anticyclic citrullinated peptide antibody and Human Leukocyte Antigen-B27 (HLA-B27) were negative. Gonococcal and Chlamydia trachomatis urine PCR were also negative. He was diagnosed with ReA. Nonsteroidal Anti-Inflammatory Drug (NSAID)s and intra-articular corticosteroid injection resulted in moderate improvement. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. |
| 32763350 | 3D printing of face shields to meet the immediate need for PPE in an anesthesiology department during the COVID-19 pandemic. | Anesthesia providers are at risk for contracting COVID-19 due to close patient contact, especially during shortages of personal protective equipment. We present an easy to follow and detailed protocol for producing 3D printed face shields and an effective decontamination protocol, allowing their reuse. The University of Nebraska Medical Center (UNMC) produced face shields using a combination of 3D printing and assembly with commonly available products, and produced a simple decontamination protocol to allow their reuse. To evaluate the effectiveness of the decontamination protocol, we inoculated bacterial suspensions of E. coli and S. aureus on to the face shield components, performed the decontamination procedure, and finally swabbed and enumerated organisms onto plates that were incubated for 12-24 hours. Decontamination effectiveness was evaluated using the average log10 reduction in colony counts. Approximately 112 face shields were constructed and made available for use in 72 hours. These methods were successfully implemented for in-house production at UNMC and at Tripler Army Medical Center (Honolulu, Hawaii). Overall, the decontamination protocol was highly effective against both E. coli and S. aureus, achieving a =4 log10 (99.99%) reduction in colony counts for every replicate from each component of the face shield unit. Face shields not only act as a barrier against the soiling of N95 face masks, they also serve as more effective eye protection from respiratory droplets over standard eye shields. Implementation of decontamination protocols successfully allowed face shield and N95 mask reuse, offering a higher level of protection for anesthesiology providers at the onset of the COVID-19 pandemic. In a time of urgent need, our protocol enabled the rapid production of face shields by individuals with little to no 3D printing experience, and provided a simple and effective decontamination protocol allowing reuse of the face shields. Copyright © 2020 Association for Professionals in Infection Control and Epidemiology, Inc. All rights reserved. |
| 32745072 | Obstetric hospital preparedness for a pandemic: an obstetric critical care perspective in response to COVID-19. | The Coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic has had a rapid and deadly onset, spreading quickly throughout the world. Pregnant patients have had high mortality rates, perinatal losses, and Intensive Care Unit (ICU) admissions from acute respiratory syndrome Coronavirus (SARS-CoV) and Middle East respiratory syndrome Coronavirus (MERS-CoV) in the past. Potentially, a surge of patients may require hospitalization and ICU care beyond the capacity of the health care system. This article is to provide institutional guidance on how to prepare an obstetric hospital service for a pandemic, mass casualty, or natural disaster by identifying a care model and resources for a large surge of critically ill pregnant patients over a short time. We recommend a series of protocols, education, and simulation training, with a structured and tiered approach to match the needs for the patients, for hospitals specialized in obstetrics. |
| 32742897 | COVID-19 outbreak on the Diamond Princess Cruise Ship in February 2020. | NA |
| 32692706 | Academic clinical learning environment in obstetrics and gynecology during the COVID-19 pandemic: responses and lessons learned. | COVID-19 pandemic is changing profoundly the obstetrics and gynecology (OB/GYN) academic clinical learning environment in many different ways. Rapid developments affecting our learners, patients, faculty and staff require unprecedented collaboration and quick, deeply consequential readjustments, almost on a daily basis. We summarized here our experiences, opportunities, challenges and lessons learned and outline how to move forward. The COVID-19 pandemic taught us there is a clear need for collaboration in implementing the most current evidence-based medicine, rapidly assess and improve the everchanging healthcare environment by problem solving and “how to” instead of “should we” approach. In addition, as a community with very limited resources we have to rely heavily on internal expertise, ingenuity and innovation. The key points to succeed are efficient and timely communication, transparency in decision making and reengagement. As time continues to pass, it is certain that more lessons will emerge. |
| 32690354 | Role of modelling in COVID-19 policy development. | Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus’s infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies. Copyright © 2020. Published by Elsevier Ltd. |
| 32680824 | Modelling insights into the COVID-19 pandemic. | Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that was declared a pandemic by the World Health Organization on 11th March, 2020. Response to this ongoing pandemic requires extensive collaboration across the scientific community in an attempt to contain its impact and limit further transmission. Mathematical modelling has been at the forefront of these response efforts by: (1) providing initial estimates of the SARS-CoV-2 reproduction rate, R0 (of approximately 2-3); (2) updating these estimates following the implementation of various interventions (with significantly reduced, often sub-critical, transmission rates); (3) assessing the potential for global spread before significant case numbers had been reported internationally; and (4) quantifying the expected disease severity and burden of COVID-19, indicating that the likely true infection rate is often orders of magnitude greater than estimates based on confirmed case counts alone. In this review, we highlight the critical role played by mathematical modelling to understand COVID-19 thus far, the challenges posed by data availability and uncertainty, and the continuing utility of modelling-based approaches to guide decision making and inform the public health response. †Unless otherwise stated, all bracketed error margins correspond to the 95% credible interval (CrI) for reported estimates. Copyright © 2020. Published by Elsevier Ltd. |
| 32666058 | The Daniel K. Inouye College of Pharmacy Scripts: Panic or Panacea, Changing the Pharmacist’s Role in Pandemic COVID-19. | NA |
| 32649272 | Combating COVID-19 and Building Immune Resilience: A Potential Role for Magnesium Nutrition? | In December 2019, the viral pandemic of respiratory illness caused by COVID-19 began sweeping its way across the globe. Several aspects of this infectious disease mimic metabolic events shown to occur during latent subclinical magnesium deficiency. Hypomagnesemia is a relatively common clinical occurrence that often goes unrecognized since magnesium levels are rarely monitored in the clinical setting. Magnesium is the second most abundant intracellular cation after potassium. It is involved in >600 enzymatic reactions in the body, including those contributing to the exaggerated immune and inflammatory responses exhibited by COVID-19 patients. A summary of experimental findings and knowledge of the biochemical role magnesium may play in the pathogenesis of COVID-19 is presented in this perspective. The National Academy of Medicine’s Standards for Systematic Reviews were independently employed to identify clinical and prospective cohort studies assessing the relationship of magnesium with interleukin-6, a prominent drug target for treating COVID-19. Clinical recommendations are given for prevention and treatment of COVID-19. Constant monitoring of ionized magnesium status with subsequent repletion, when appropriate, may be an effective strategy to influence disease contraction and progression. The peer-reviewed literature supports that several aspects of magnesium nutrition warrant clinical consideration. Mechanisms include its “calcium-channel blocking” effects that lead to downstream suppression of nuclear factor-Kß, interleukin-6, c-reactive protein, and other related endocrine disrupters; its role in regulating renal potassium loss; and its ability to activate and enhance the functionality of vitamin D, among others. As the world awaits an effective vaccine, nutrition plays an important and safe role in helping mitigate patient morbidity and mortality. Our group is working with the Academy of Nutrition and Dietetics to collect patient-level data from intensive care units across the United States to better understand nutrition care practices that lead to better outcomes. |
| 32596689 | Viewpoint: Pacific Voyages - Ships - Pacific Communities: A Framework for COVID-19 Prevention and Control. | NA |
| 32592394 | A role for selenium-dependent GPX1 in SARS-CoV-2 virulence. | NA |
| 32584245 | Communicating Effectively With Hospitalized Patients and Families During the COVID-19 Pandemic. | NA |
| 32501143 | The Impact of the COVID-19 Pandemic on Vulnerable Older Adults in the United States. | NA |
| 32486844 | Covid-19 and Diabetes in Hawaii. | NA |
| 32462545 | Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review. | The emergence of SARS-CoV-2/2019 novel coronavirus (COVID-19) has created a global pandemic with no approved treatments or vaccines. Many treatments have already been administered to COVID-19 patients but have not been systematically evaluated. We performed a systematic literature review to identify all treatments reported to be administered to COVID-19 patients and to assess time to clinically meaningful response for treatments with sufficient data. We searched PubMed, BioRxiv, MedRxiv, and ChinaXiv for articles reporting treatments for COVID-19 patients published between 1 December 2019 and 27 March 2020. Data were analyzed descriptively. Of the 2706 articles identified, 155 studies met the inclusion criteria, comprising 9152 patients. The cohort was 45.4% female and 98.3% hospitalized, and mean (SD) age was 44.4 years (SD 21.0). The most frequently administered drug classes were antivirals, antibiotics, and corticosteroids, and of the 115 reported drugs, the most frequently administered was combination lopinavir/ritonavir, which was associated with a time to clinically meaningful response (complete symptom resolution or hospital discharge) of 11.7 (1.09) days. There were insufficient data to compare across treatments. Many treatments have been administered to the first 9152 reported cases of COVID-19. These data serve as the basis for an open-source registry of all reported treatments given to COVID-19 patients at www.CDCN.org/CORONA . Further work is needed to prioritize drugs for investigation in well-controlled clinical trials and treatment protocols. |
| 32432219 | Insights in Public Health: COVID-19 Special Column: The Crisis of Non-Communicable Diseases in the Pacific and the Coronavirus Disease 2019 Pandemic. | Globally, coronavirus disease 2019 (COVID-19) is threatening human health and changing the way people live. With the increasing evidence showing comorbidities of COVID-19 and non-communicable diseases (NCDs), the Pacific region, where approximately 75% of deaths are due to NCDs, is significantly vulnerable during this crisis unless urgent action is taken. Whilst enforcing the critical mitigation measures of the COVID-19 pandemic in the Pacific, it is also paramount to incorporate and strengthen NCD prevention and control measures to safeguard people with NCDs and the general population; keep people healthy and minimise the impact of COVID-19. To sustain wellbeing of health, social relationships, and the economy in the Pacific, it is a critical time for all governments, development partners and civil societies to show regional solidarity in the fight against emerging COVID-19 health crisis and existing Pacific NCDs crisis through a whole of government and whole of society approach. ©Copyright 2020 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| 32432218 | COVID-19 Special Column: COVID-19 Hits Native Hawaiian and Pacific Islander Communities the Hardest. | NA |
| 32432217 | COVID-19 Special Column: Principles Behind the Technology for Detecting SARS-CoV-2, the Cause of COVID-19. | Nationwide shortages of tests that detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and diagnose coronavirus disease 2019 (COVID-19) have led the US Food and Drug Administration (FDA) to significantly relax regulations regarding COVID-19 diagnostic testing. To date the FDA has given emergency use authorization (EUA) to 48 COVID-19 in vitro diagnostic tests and 21 high complexity molecular-based laboratory developed tests, as well as implemented policies that give broad authority to clinical laboratories and commercial manufacturers in the development, distribution, and use of COVID-19 diagnostic tests. Currently, there are 2 types of diagnostic tests available for the detection of SARS-CoV-2: (1) molecular and (2) serological tests. Molecular detection of nucleic acid (RNA or DNA) sequences relating to the suspected pathogen is indicative of an active infection with the suspected pathogen. Serological tests detect antibodies against the suspected pathogen, which are produced by an individual’s immune system. A positive serological test result indicates recent exposure to the suspected pathogen but cannot be used to determine if the individual is actively infected with the pathogen or immune to reinfection. In this article, the SARS-CoV-2 diagnostic tests currently approved by the FDA under EUA are reviewed, and other diagnostic tests that researchers are developing to detect SARS-CoV-2 infection are discussed. ©Copyright 2020 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| 32427288 | ACE2 receptor expression in testes: implications in coronavirus disease 2019 pathogenesis†. | NA |
| 32420720 | Caring for Critically Ill Adults With Coronavirus Disease 2019 in a PICU: Recommendations by Dual Trained Intensivists. | In the midst of the severe acute respiratory syndrome coronavirus 2 pandemic, which causes coronavirus disease 2019, there is a recognized need to expand critical care services and beds beyond the traditional boundaries. There is considerable concern that widespread infection will result in a surge of critically ill patients that will overwhelm our present adult ICU capacity. In this setting, one proposal to add “surge capacity” has been the use of PICU beds and physicians to care for these critically ill adults. Narrative review/perspective. Not applicable. Not applicable. None. The virus’s high infectivity and prolonged asymptomatic shedding have resulted in an exponential growth in the number of cases in the United States within the past weeks with many (up to 6%) developing acute respiratory distress syndrome mandating critical care services. Coronavirus disease 2019 critical illness appears to be primarily occurring in adults. Although pediatric intensivists are well versed in the care of acute respiratory distress syndrome from viral pneumonia, the care of differing aged adult populations presents some unique challenges. In this statement, a team of adult and pediatric-trained critical care physicians provides guidance on common “adult” issues that may be encountered in the care of these patients and how they can best be managed in a PICU. This concise scientific statement includes references to the most recent and relevant guidelines and clinical trials that shape management decisions. The intention is to assist PICUs and intensivists in rapidly preparing for care of adult coronavirus disease 2019 patients should the need arise. |
| 32386898 | Geospatial analysis of COVID-19 and otolaryngologists above age 60. | The 2019 novel coronavirus (COVID-19) is disproportionately impacting older individuals and healthcare workers. Otolaryngologists are especially susceptible with the elevated risk of aerosolization and corresponding high viral loads. This study utilizes a geospatial analysis to illustrate the comparative risks of older otolaryngologists across the United States during the COVID-19 pandemic. Demographic and state population data were extracted from the State Physician Workforce Reports published by the AAMC for the year 2018. A geospatial heat map of the United States was then constructed to illustrate the location of COVID-19 confirmed case counts and the distributions of ENTs over 60 years for each state. In 2018, out of a total of 9578 practicing U.S. ENT surgeons, 3081 were older than 60 years (32.2%). The states with the highest proportion of ENTs over 60 were Maine, Delaware, Hawaii, and Louisiana. The states with the highest ratios of confirmed COVID-19 cases to the number of total ENTs over 60 were New York, New Jersey, Massachusetts, and Michigan. Based on our models, New York, New Jersey, Massachusetts, and Michigan represent states where older ENTs may be the most susceptible to developing severe complications from nosocomial transmission of COVID-19 due to a combination of high COVID-19 case volumes and a high proportion of ENTs over 60 years. Copyright © 2020 Elsevier Inc. All rights reserved. |
| 32371624 | The War on COVID-19 Pandemic: Role of Rehabilitation Professionals and Hospitals. | The global outbreak of coronavirus disease 2019 has created an unprecedented challenge to the society. Currently, the United States stands as the most affected country, and the entire healthcare system is affected, from emergency department, intensive care unit, postacute care, outpatient, to home care. Considering the debility, neurological, pulmonary, neuromuscular, and cognitive complications, rehabilitation professionals can play an important role in the recovery process for individuals with coronavirus disease 2019. Clinicians across the nation’s rehabilitation system have already begun working to initiate intensive care unit-based rehabilitation care and develop programs, settings, and specialized care to meet the short- and long-term needs of these individuals. We describe the anticipated rehabilitation demands and the strategies to meet the needs of this population. The complications from coronavirus disease 2019 can be reduced by (1) delivering interdisciplinary rehabilitation that is initiated early and continued throughout the acute hospital stay, (2) providing patient/family education for self-care after discharge from inpatient rehabilitation at either acute or subacute settings, and (3) continuing rehabilitation care in the outpatient setting and at home through ongoing therapy either in-person or via telehealth. |
| 32371551 | The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action. | The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health. ©2020 American Association for Cancer Research. |
| 32361738 | Risk Factors Associated with Clinical Outcomes in 323 COVID-19 Hospitalized Patients in Wuhan, China. | With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. Data are urgently needed about risk factors associated with clinical outcomes. A retrospective review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into three disease severity groups (non-severe, severe, and critical), based on initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify risk factors associated with clinical outcomes, and log-rank test was conducted for the association with clinical progression. Current standard treatments did not show significant improvement in patient outcomes. By univariate logistic regression analysis, 27 risk factors were significantly associated with clinical outcomes. Multivariate regression indicated age over 65 years (p<0.001), smoking (p=0.001), critical disease status (p=0.002), diabetes (p=0.025), high hypersensitive troponin I (>0.04 pg/mL, p=0.02), leukocytosis (>10 x 109/L, p<0.001) and neutrophilia (>75 x 109/L, p<0.001) predicted unfavorable clinical outcomes. By contrast, the administration of hypnotics was significantly associated with favorable outcomes (p<0.001), which was confirmed by survival analysis. Hypnotics may be an effective ancillary treatment for COVID-19. We also found novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19. © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com. |
| 32326959 | High-flow nasal cannula may be no safer than non-invasive positive pressure ventilation for COVID-19 patients. | NA |
| 32323016 | SAGES and EAES recommendations for minimally invasive surgery during COVID-19 pandemic. | The unprecedented pandemic of COVID-19 has impacted many lives and affects the whole healthcare systems globally. In addition to the considerable workload challenges, surgeons are faced with a number of uncertainties regarding their own safety, practice, and overall patient care. This guide has been drafted at short notice to advise on specific issues related to surgical service provision and the safety of minimally invasive surgery during the COVID-19 pandemic. Although laparoscopy can theoretically lead to aerosolization of blood borne viruses, there is no evidence available to confirm this is the case with COVID-19. The ultimate decision on the approach should be made after considering the proven benefits of laparoscopic techniques versus the potential theoretical risks of aerosolization. Nevertheless, erring on the side of safety would warrant treating the coronavirus as exhibiting similar aerosolization properties and all members of the OR staff should use personal protective equipment (PPE) in all surgical procedures during the pandemic regardless of known or suspected COVID status. Pneumoperitoneum should be safely evacuated via a filtration system before closure, trocar removal, specimen extraction, or conversion to open. All emergent endoscopic procedures performed during the pandemic should be considered as high risk and PPE must be used by all endoscopy staff. |
| 32314954 | COVID-19 Community Stabilization and Sustainability Framework: An Integration of the Maslow Hierarchy of Needs and Social Determinants of Health. | All levels of government are authorized to apply coronavirus disease 2019 (COVID-19) protection measures; however, they must consider how and when to ease lockdown restrictions to limit long-term societal harm and societal instability. Leaders that use a well-considered framework with an incremental approach will be able to gradually restart society while simultaneously maintaining the public health benefits achieved through lockdown measures. Economically vulnerable populations cannot endure long-term lockdown, and most countries lack the ability to maintain a full nationwide relief operation. Decision-makers need to understand this risk and how the Maslow hierarchy of needs and the social determinants of health can guide whole of society policies. Aligning decisions with societal needs will help ensure all segments of society are catered to and met while managing the crisis. This must inform the process of incremental easing of lockdowns to facilitate the resumption of community foundations, such as commerce, education, and employment in a manner that protects those most vulnerable to COVID-19. This study proposes a framework for identifying a path forward. It reflects on baseline requirements, regulations and recommendations, triggers, and implementation. Those desiring a successful recovery from the COVID-19 pandemic need to adopt an evidence-based framework now to ensure community stabilization and sustainability. |
| 32300051 | Insights from immuno-oncology: the Society for Immunotherapy of Cancer Statement on access to IL-6-targeting therapies for COVID-19. | NA |
| 32259247 | Pain Management Best Practices from Multispecialty Organizations During the COVID-19 Pandemic and Public Health Crises. | It is nearly impossible to overestimate the burden of chronic pain, which is associated with enormous personal and socioeconomic costs. Chronic pain is the leading cause of disability in the world, is associated with multiple psychiatric comorbidities, and has been causally linked to the opioid crisis. Access to pain treatment has been called a fundamental human right by numerous organizations. The current COVID-19 pandemic has strained medical resources, creating a dilemma for physicians charged with the responsibility to limit spread of the contagion and to treat the patients they are entrusted to care for. To address these issues, an expert panel was convened that included pain management experts from the military, Veterans Health Administration, and academia. Endorsement from stakeholder societies was sought upon completion of the document within a one-week period. In these guidelines, we provide a framework for pain practitioners and institutions to balance the often-conflicting goals of risk mitigation for health care providers, risk mitigation for patients, conservation of resources, and access to pain management services. Specific issues discussed include general and intervention-specific risk mitigation, patient flow issues and staffing plans, telemedicine options, triaging recommendations, strategies to reduce psychological sequelae in health care providers, and resource utilization. The COVID-19 public health crisis has strained health care systems, creating a conundrum for patients, pain medicine practitioners, hospital leaders, and regulatory officials. Although this document provides a framework for pain management services, systems-wide and individual decisions must take into account clinical considerations, regional health conditions, government and hospital directives, resource availability, and the welfare of health care providers. The Author(s) 2020. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. This work is written by a US Government employee and is in the public domain in the US. |
Done! Knit the document, commit, and push.
You can still share the HTML document on github. You can include a link
in your README.md file as the following:
View [here](https://ghcdn.rawgit.org/:user/:repo/:tag/:file)For example, if we wanted to add a direct link the HTML page of lecture 7, we could do something like the following:
View [here](https://ghcdn.rawgit.org/USCbiostats/PM566/master/static/slides/07-apis-regex/slides.html)