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Development of a risk score to guide targeted hepatitis C testing among human immunodeficiency virus patients in Cambodia
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作者 Anja De Weggheleire Jozefien Buyze +4 位作者 Sokkab An Sopheak Thai Johan van Griensven Sven Francque Lutgarde Lynen 《World Journal of Hepatology》 2021年第9期1167-1180,共14页
BACKGROUND The World Health Organization recommends testing all human immunodeficiency virus(HIV)patients for hepatitis C virus(HCV).In resource-constrained contexts with low-to-intermediate HCV prevalence among HIV p... BACKGROUND The World Health Organization recommends testing all human immunodeficiency virus(HIV)patients for hepatitis C virus(HCV).In resource-constrained contexts with low-to-intermediate HCV prevalence among HIV patients,as in Cambodia,targeted testing is,in the short-term,potentially more feasible and cost-effective.AIM To develop a clinical prediction score(CPS)to risk-stratify HIV patients for HCV coinfection(HCV RNA detected),and derive a decision rule to guide prioritization of HCV testing in settings where‘testing all’is not feasible or unaffordable in the short term.METHODS We used data of a cross-sectional HCV diagnostic study in the HIV cohort of Sihanouk Hospital Center of Hope in Phnom Penh.Key populations were very rare in this cohort.Score development relied on the Spiegelhalter and Knill-Jones method.Predictors with an adjusted likelihood ratio≥1.5 or≤0.67 were retained,transformed to natural logarithms,and rounded to integers as score items.CPS performance was evaluated by the area-under-the-ROC curve(AUROC)with 95% confidence intervals(CI),and diagnostic accuracy at the different cut-offs.For the decision rule,HCV coinfection probability≥1% was agreed as test-threshold.RESULTS Among the 3045 enrolled HIV patients,106 had an HCV coinfection.Of the 11 candidate predictors(from history-taking,laboratory testing),seven had an adjusted likelihood ratio≥1.5 or≤0.67:≥50 years(+1 point),diabetes mellitus(+1),partner/household member with liver disease(+1),generalized pruritus(+1),platelets<200×10^(9)/L(+1),aspartate transaminase(AST)<30 IU/L(-1),AST-to-platelet ratio index(APRI)≥0.45(+1),and APRI<0.45(-1).The AUROC was 0.84(95%CI:0.80-0.89),indicating good discrimination of HCV/HIV coinfection and HIV mono-infection.The CPS result≥0 best fits the test-threshold(negative predictive value:99.2%,95%CI:98.8-99.6).Applying this threshold,30%(n=926)would be tested.Sixteen coinfections(15%)would have been missed,none with advanced fibrosis.CONCLUSION The CPS performed well in the derivation cohort,and bears potential for other contexts of low-to-intermediate prevalence and little onward risk of transmission(i.e.cohorts without major risk factors as injecting drug use,men having sex with men),and where available resources do not allow to test all HIV patients as recommended by WHO.However,the score requires external validation in other patient cohorts before any wider use can be considered. 展开更多
关键词 Hepatitis C virus Hepatitis C/human immunodeficiency virus coinfection Clinical prediction rule Targeted screening Cambodia Development prediction model
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Towards automated calculation of evidence-based clinical scores
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作者 Christopher A Aakre Mikhail A Dziadzko Vitaly Herasevich 《World Journal of Methodology》 2017年第1期16-24,共9页
AIM To determine clinical scores important for automated calculation in the inpatient setting.METHODS A modified Delphi methodology was used to create consensus of important clinical scores for inpatient practice. A l... AIM To determine clinical scores important for automated calculation in the inpatient setting.METHODS A modified Delphi methodology was used to create consensus of important clinical scores for inpatient practice. A list of 176 externally validated clinical scores were identified from freely available internet-based services frequently used by clinicians. Scores were categorized based on pertinent specialty and a customized survey was created for each clinician specialty group. Clinicians were asked to rank each score based on importance of automated calculation to their clinical practice in three categories-"not important", "nice to have", or "very important". Surveys were solicited via specialty-group listserv over a 3-mo interval. Respondents must have been practicing physicians with more than 20% clinical time spent in the inpatient setting. Within each specialty, consensus was established for any clinical score with greater than 70% of responses in a single category and a minimum of 10 responses. Logistic regression was performed to determine predictors of automation importance.RESULTS Seventy-nine divided by one hundred and forty-four(54.9%) surveys were completed and 72/144(50%) surveys were completed by eligible respondents. Only the critical care and internal medicine specialties surpassed the 10-respondent threshold(14 respondents each). For internists, 2/110(1.8%) of scores were "very important" and 73/110(66.4%) were "nice to have". For intensivists, no scores were "very important" and 26/76(34.2%) were "nice to have". Only the number of medical history(OR = 2.34; 95%CI: 1.26-4.67; P < 0.05) and vital sign(OR = 1.88; 95%CI: 1.03-3.68; P < 0.05) variables for clinical scores used by internists was predictive of desire for automation. CONCLUSION Few clinical scores were deemed "very important" for automated calculation. Future efforts towards score calculator automation should focus on technically feasible "nice to have" scores. 展开更多
关键词 AUTOMATION Clinical prediction rule Decision support techniques Clinical decision support
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