About: Development of a risk‐prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Development of a risk‐prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients
Creator	Al-Jahdali, Hamdan Alaqeel, Mody Alsaab, Hanan Baharoon, Salim Ahmed, Anwar Alshukairi, Abeer Johani, Sameera Alandonisi, Munzir Alghamdi, Mohammed Aloudah, Nouf Alsalamah, Majid Alyahya, Hamed Sakr, Ezzeldin Siddiq, Salma Subedar, Alaa
source	Medline; PMC
abstract	Introduction The Middle East respiratory syndrome coronavirus (MERS‐CoV) infection can cause transmission clusters and high mortality in hemodialysis facilities. We attempted to develop a risk‐prediction model to assess the early risk of MERS‐CoV infection in dialysis patients. Methods This two‐center retrospective cohort study included 104 dialysis patients who were suspected of MERS‐CoV infection and diagnosed with rRT‐PCR between September 2012 and June 2016 at King Fahd General Hospital in Jeddah and King Abdulaziz Medical City in Riyadh. We retrieved data on demographic, clinical, and radiological findings, and laboratory indices of each patient. Findings A risk‐prediction model to assess early risk for MERS‐CoV in dialysis patients has been developed. Independent predictors of MERS‐CoV infection were identified, including chest pain (OR = 24.194; P = 0.011), leukopenia (OR = 6.080; P = 0.049), and elevated aspartate aminotransferase (AST) (OR = 11.179; P = 0.013). The adequacy of this prediction model was good (P = 0.728), with a high predictive utility (area under curve [AUC] = 76.99%; 95% CI: 67.05% to 86.38%). The prediction of the model had optimism‐corrected bootstrap resampling AUC of 71.79%. The Youden index yielded a value of 0.439 or greater as the best cut‐off for high risk of MERS infection. Discussion This risk‐prediction model in dialysis patients appears to depend markedly on chest pain, leukopenia, and elevated AST. The model accurately predicts the high risk of MERS‐CoV infection in dialysis patients. This could be clinically useful in applying timely intervention and control measures to prevent clusters of infections in dialysis facilities or other health care settings. The predictive utility of the model warrants further validation in external samples and prospective studies.
has issue date	2018-04-14(xsd:dateTime)
bibo:doi	10.1111/hdi.12661
bibo:pmid	29656480
has license	no-cc
sha1sum (hex)	b61c65fd19e460ddc6fe50085d72c5404a253f6b
schema:url	https://doi.org/10.1111/hdi.12661
resource representing a document's title	Development of a risk‐prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients
has PubMed Central identifier	PMC7165861
has PubMed identifier	29656480
schema:publication	Hemodial Int
resource representing a document's body	covid:b61c65fd19e460ddc6fe50085d72c5404a253f6b#body_text
is schema:about of	named entity 'infection' named entity 'Health Sciences' named entity 'facilities' named entity 'King Saud' named entity 'health care' named entity 'Diabetes' named entity 'chest pain' named entity 'dialysis' named entity 'higher risk' named entity 'virus' named entity 'outpatient' named entity 'MERS-CoV' named entity 'Dialysis' named entity 'dialysis' named entity 'clinical outcomes' named entity 'vomiting' named entity 'gastrointestinal symptoms' named entity 'gastrointestinal symptoms' named entity 'bootstrap resampling' named entity 'MERS-CoV' named entity 'health care workers' named entity 'alanine transaminase' named entity 'infection' named entity 'infection' named entity 'infection' named entity 'hemodialysis' named entity 'health care' named entity 'infection' named entity 'x-ray' named entity 'bootstrap samples' named entity 'predictive utility' named entity 'MERS' named entity 'MERS-CoV' named entity 'MERS-CoV' named entity 'Dialysis' named entity 'infection' named entity 'dialysis' named entity 'probability' named entity 'Stata' named entity 'High fever' named entity 'infection control' named entity 'Dialysis' named entity 'case-control study' named entity 'Saudi Arabia' named entity 'AST' named entity 'odds ratio' named entity 'aspartate transaminase' named entity 'platelet count' named entity 'MERS-CoV' named entity 'sensitivity and specificity' named entity 'dialysis' named entity 'blood platelet' named entity 'randomly selected' named entity 'prospective study' named entity 'rRT-PCR' named entity 'MERS-CoV' named entity 'South Korea' named entity 'infection' named entity 'dialysis' named entity 'Saudi Ministry of Health' named entity 'AST' named entity 'clinical decision making' named entity 'risk stratification' named entity 'MERS-CoV' named entity 'infection' named entity 'MERS' named entity 'infection'

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