CURB-65, CRB-65, Classification Tree Analysis (CTA) severity scores. Table S2. Predicted and observed risk of mortality based on CURB-65, CRB-65, Classification Tree Analysis (CTA), and CURB-45 severity scores among hospitalized adults with lower respiratory tract infections, South Africa, 2010–2011. Table S3. Predicted and observed risk of mortality based by ACHU (Age, confusion, HIV, urea) respiratory severity score among hospitalized adults with lower respiratory tract infections, South Africa, 2010–2011. (DOCX 21 kb

Adam Cohen (767228)

Adena Greenbaum (166127)

Alexander Millman (3711274)

Carrie Reed (123034)

Cheryl Cohen (194690)

Ebrahim Variava (403647)

Florette Treurnicht (88318)

Marietjie Venter (552145)

Meredith McMorrow (542445)

Michelle Groome (451457)

Shabir Madhi (767229)

Sibongile Walaza (694906)

Stefano Tempia (298304)

BMC Complementary and Alternative Medicine

PubMed

Alexander J. Millman

Adena Greenbaum

Sibongile Walaza

Adam L. Cohen

Michelle J. Groome

Carrie Reed

Meredith McMorrow

Stefano Tempia

Marietjie Venter

Florette K. Treurnicht

Shabir A. Madhi

Cheryl Cohen

Ebrahim Variava

Crossref

BMC Pulmonary Medicine

Development of a respiratory severity score for hospitalized adults in a high HIV-prevalence setting—South Africa, 2010–2011

Springer - Publisher Connector

Additional file 1: BMC Pulmonary_Severity Score Data.xlsx. Severity
Score Dataset. Dataset generated and used for analysis and creation of
the ACHU score. Two tabs are included 1) includes the data used for the
analysis 2) includes important notes related to the analytical methods
and definitions for several composite variables.Additional file 2: Table S1. CURB-65, CRB-65, Classification Tree
Analysis (CTA) severity scores. Table S2. Predicted and observed risk of
mortality based on CURB-65, CRB-65, Classification Tree Analysis (CTA),
and CURB-45 severity scores among hospitalized adults with lower
respiratory tract infections, South Africa, 2010–2011. Table S3. Predicted
and observed risk of mortality based by ACHU (Age, confusion, HIV, urea)
respiratory severity score among hospitalized adults with lower
respiratory tract infections, South Africa, 2010–2011.BACKGROUND : Acute lower respiratory tract infections (LRTI) are a frequent cause of hospitalization and mortality in
South Africa; however, existing respiratory severity scores may underestimate mortality risk in HIV-infected adults in
resource limited settings. A simple predictive clinical score for low-resource settings could aid healthcare providers
in the management of patients hospitalized with LRTI.
METHODS : We analyzed 1,356 LRTI hospitalizations in adults aged ≥18 years enrolled in Severe Acute Respiratory
Illness (SARI) surveillance in three South African hospitals from January 2010 to December 2011. Using demographic
and clinical data at admission, we evaluated potential risk factors for in-hospital mortality. We evaluated three
existing respiratory severity scores, CURB-65, CRB-65, and Classification Tree Analysis (CTA) Score assessing for
discrimination and calibration. We then developed a new respiratory severity score using a multivariable logistic
regression model for in-hospital mortality and assigned points to risk factors based on the coefficients in the
multivariable model. Finally we evaluated the model statistically using bootstrap resampling techniques.
RESULTS : Of the 1,356 patients hospitalized with LRTI, 101 (7.4%) died while hospitalized. The CURB-65, CRB-65, and
CTA scores had poor calibration and demonstrated low discrimination with c-statistics of 0.594, 0.548, and 0.569
respectively. Significant risk factors for in-hospital mortality included age ≥ 45 years (A), confusion on admission (C),
HIV-infection (H), and serum blood urea nitrogen >7 mmol/L (U), which were used to create the seven-point ACHU
clinical predictor score. In-hospital mortality, stratified by ACHU score was: score ≤1, 2.4%, score 2, 6.4%, score 3, 11.
9%, and score ≥ 4, 29.3%. Final models showed good discrimination (c-statistic 0.789) and calibration (chi-square 1.6,
Hosmer-Lemeshow goodness-of-fit p-value = 0.904) and discriminated well in the bootstrap sample (average
optimism of 0.003).
CONCLUSIONS : Existing clinical predictive scores underestimated mortality in a low resource setting with a high HIV
burden. The ACHU score incorporates a simple set a risk factors that can accurately stratify patients ≥18 years of
age with LRTI by in-hospital mortality risk. This score can quantify in-hospital mortality risk in an HIV-endemic,
resource-limited setting with limited clinical information and if used to facilitate timely treatment may improve
clinical outcomes.The Centers for Disease Control and Preventionhttp://www.biomedcentral.com/bmccom/plementalternmedam2017Medical Virolog

Millman, Alexander J.

Greenbaum, Adena

Walaza, Sibongile

Cohen, Adam L.

Groome, Michelle J.

Reed, Carrie

McMorrow, Meredith

Tempia, Stefano

Venter, Marietjie

Treurnicht, Florette K.

Madhi, Shabir A.

Cohen, Cheryl

Variava, Ebrahim

UPSpace at the University of Pretoria

Development of a respiratory severity score for hospitalized adults in a high  HIV-prevalence setting—South Africa, 2010-2011

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