Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease

Hakim, Maryam; Garden, Frances L.; Jennings, Matthew; Dobler, Claudia C.

doi:10.2147/clep.s149574

Cited by 65 publications

(61 citation statements)

References 32 publications

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“…Patients with the highest LACE+ scores were 2.18 to 2.42 times as likely to be seen in the ED, 1.93 to 5.16 times more likely to be readmitted, and 1.75 to 2.30 times more likely to have a reoperation than patients with lower LACE+ scores. These results support the conclusions of prior studies supporting LACE+ prediction of short‐term outcomes after hospital discharge 18,20,21,23 …”

Section: Discussionsupporting

confidence: 90%

“…The developers of LACE subsequently modified it to create the LACE+ index using multivariable logistic regressions to identify suitable predictors that were incorporated into the new index as per Sullivan et al 16 The final statistical evaluation of the LACE+ index's effectiveness using the Hosmer‐Lemeshow goodness‐of‐fit test was found to have good to excellent discriminative ability and improved predictive capacity relative to the original algorithm 17 . The LACE and LACE+ indices have each been tested in a number of medical and surgical populations with varying success 18‐25 . Although previous work has demonstrated that LACE is able to predict readmission risk after orthopedic surgery, 26 LACE+ has never been tested in an orthopedic surgery population.…”

Section: Introductionmentioning

confidence: 99%

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Composite score for prediction of 30‐day orthopedic surgery outcomes

Caplan

Winter

Glauser

et al. 2020

Journal Orthopaedic Research

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The LACE+ (Length of stay, Acuity of admission, Charlson Comorbidity Index score, and Emergency department visits in the past 6 months) risk‐prediction tool has never been tested in an orthopedic surgery population. LACE+ may help physicians more effectively identify and support high‐risk orthopedics patients after hospital discharge. LACE+ scores were retrospectively calculated for all consecutive orthopedic surgery patients (n = 18 893) at a multi‐center health system over 3 years (2016‐2018). Coarsened exact matching was employed to create “matched” study groups with different LACE+ score quartiles (Q1, Q2, Q3, Q4). Outcomes were compared between quartiles. In all, 1444 patients were matched between Q1 and Q4 (n = 2888); 2079 patients between Q2 and Q4 (n = 4158); 3032 patients between Q3 and Q4 (n = 6064). Higher LACE+ scores significantly predicted 30D readmission risk for Q4 vs Q1 and Q4 vs Q3 (P < .001). Larger LACE+ scores also significantly predicted 30D risk of ED visits for Q4 vs Q1, Q4 vs Q2, and Q4 vs Q3 (P < .001). Increased LACE+ score also significantly predicted 30D risk of reoperation for Q4 vs Q1 (P = .018), Q4 vs Q2 (P < .001), and Q4 vs Q3 (P < .001).

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Composite score for prediction of 30‐day orthopedic surgery outcomes

Caplan

Winter

Glauser

et al. 2020

Journal Orthopaedic Research

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“…In addition, a review concluded that age was consistently associated with short‐term mortality in hospitalized COPD adults . Age is a physiological parameter used in many disease indices and clinical scales such as the APACHE and LACE score. Multimorbidity, progressive muscle atrophy and lung function loss, declining biological cell and system dysfunction are among the factors underlying the increased mortality risk with aging .…”

Section: Discussionmentioning

confidence: 99%

Risk stratification for short‐term mortality at hospital admission for acute exacerbations of COPD

Sprooten

Rohde

Lawyer³

et al. 2019

Respirology

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Background and objective: Exacerbations of chronic obstructive pulmonary disease (ECOPD) are associated with increased in-hospital and short-term mortality. Developing an easy-to-use model to predict adverse outcomes will be useful in daily clinical practice and will facilitate management decisions. We aimed to assess mortality rates and potential predictors for short-term mortality after severe ECOPD. Classification and Regression Tree (CART) model was used to identify predictors of adverse outcome. Methods: A retrospective observational cohort study, including all patients admitted to Maastricht University Medical Center with ECOPD between June 2011 and December 2014 was performed. The last admission was taken into account, and its demographic, clinical and biochemical data were recorded. Results: A total of 364 hospitalized patients were enrolled. Mean (SD) age was 70.5 (10.2) years, 54.4% were male and mean FEV 1 45.2% (17.7) of predicted. The in-hospital and 90-day mortality were, respectively, 8.5 and 16.2%. Independent risk factors for 90-day mortality were: PaC0 2 (odds ratio (OR): 1.31; 95% confidence interval (CI): 1.00-0.35), age (OR: 1.09; CI: 0.06-0.11), body mass index (BMI) < 18.5 kg/m 2 (OR: 2.72; 95% CI: 0.53-1.47) and previous admission for ECOPD in last 2 years (OR: 1.29; 95% CI: −0.14, −0.65). The CART model selected PaCO 2 ≥ 9.1 kPa, age > 80 years, BMI < 18.5 kg/m 2 and previous admission for ECOPD as the most discriminatory factors. Conclusion: According CART analysis, high PaCO 2 and age, low BMI and previous admission for ECOPD in last 2 years were the strongest predictors of 90-day mortality in patients with severe ECOPD. In absence of any of these factors, no patients died, suggesting that this model indeed enables risk stratification.Data presented as n (%) or medium with standard deviation depicted after AE, unless otherwise stated. † (Pearson) chi-square. ABG, arterial blood gas; ALAT, alanineaminotranferase; ASAT, aminotransferase; BMI, body mass index; BP, blood pressure; CRP, C-reactive protein; CVP, central venous pressure; ECG, electrocardiogram; FiO 2 , fraction of inspired oxygen; LDH, lactic acid dehydrogenase; Na, sodium; NT proBNP, brain natriuremic peptide; SaO 2 , oxygen saturation measured in arterial blood gas; SpO 2 , oxygen saturation measured by pulse oximetry; WBC, white blood cell.Respirology (2019) 24, 765-776

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“…The lack of a significant association between high blood eosinophils and all-cause readmission at 30 and 60 days may be because only 30–60% of all-cause readmissions are attributable to COPD, with other causes being due to comorbidities or socioeconomic factors that may not be associated with blood eosinophils. 27 – 29 …”

Section: Discussionmentioning

confidence: 99%

<p>Blood Eosinophil Count and Hospital Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease</p>

Hegewald

Horne

Trudo

et al. 2020

COPD

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Purpose This retrospective, observational cohort study investigated the association of blood eosinophil counts within 1 week of hospitalization for acute exacerbation of COPD (AECOPD) with subsequent risk of all-cause and COPD-related readmission from a large integrated health system. Patients and Methods Electronic medical records were extracted for index hospitalization for AECOPD at all Intermountain Healthcare hospitals. The primary outcome was the relationship of blood eosinophil count to 30-day all-cause readmission; secondary outcomes were 60-day, 90-day, and 12-month all-cause readmission, COPD-related readmission, and empiric derivation of the eosinophil count with the highest area under the curve (AUC) for predicting 30-day all-cause readmission. Results Of 2445 included patients, 1935 (79%) had a blood eosinophil count <300 cells/µL and 510 (21%) had a count ≥300 cells/µL. Using a 300-cells/μL threshold, there was no significant difference between high and low eosinophil groups in 30-day (odds ratio [OR]=1.05, 95% confidence interval [CI]=0.75–1.47) or 60-day (OR=1.15, 95% CI=0.88–1.51) all-cause readmissions. However, patients with greater (versus lesser) eosinophil counts had increased 90-day and 12-month all-cause readmissions (OR=1.35, 95% CI=1.06–1.72, and OR=1.32, 95% CI=1.07–1.62). COPD-related readmission rates were significantly greater for patients with greater (versus lesser) eosinophil counts at 30, 60, and 90 days and 12 months (OR range=1.52–1.97). A total of 70 cells/µL had the most discriminatory power to predict 30-day all-cause readmission (highest AUC). Conclusion Eosinophil counts in patients with COPD were not associated with a difference in 30-day all-cause readmissions. However, greater eosinophil counts were associated with increased risk of all-cause readmission at 90 days and 12 months and COPD-related readmission at 30, 60, and 90 days and 12 months. Patients with eosinophils <70 cells/μL had the lowest risk for 30-day all-cause readmission. Blood eosinophils in patients hospitalized with AECOPD may be a useful biomarker for the risk of hospital readmission.

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Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease

Cited by 65 publications

References 32 publications

Composite score for prediction of 30‐day orthopedic surgery outcomes

Composite score for prediction of 30‐day orthopedic surgery outcomes

Risk stratification for short‐term mortality at hospital admission for acute exacerbations of COPD

<p>Blood Eosinophil Count and Hospital Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease</p>

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