A Comparison of Administrative and Physiologic Predictive Models in Determining Risk Adjusted Mortality Rates in Critically Ill Patients

Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients.We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland-Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission.We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r(2) for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model.In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to patients admitted to intensive care units. As patients and providers increasingly use publicly reported information in making health care decisions and referrals, it is critical that the provided information be understood. Our results suggest that severity of illness may influence the mortality index in administrative models. We suggest that when interpreting "report cards" or metrics, health care providers determine how the risk adjustment was made and compares to other risk adjustment models

The association between comorbidities and pain, physical function and quality of life following hip and knee arthroplasty

The aim of the study was to examine the relationship between comorbidities and pain, physical function and health-related quality of life (HRQoL) after total hip arthroplasty (THA) and total knee arthroplasty (TKA). A cross-sectional retrospective survey was conducted including 19 specific comorbidities, administered in patients who underwent THA or TKA in the previous 7–22 months in one of 4 hospitals. Outcome measures included pain, physical functioning, and HRQoL. Of the 521 patients (281 THA and 240 TKA) included, 449 (86 %) had ≥1 comorbidities. The most frequently reported comorbidities (>15 %) were severe back pain; neck/shoulder pain; elbow, wrist or hand pain; hypertension; incontinence of urine; hearing impairment; vision impairment; and cancer. Only the prevalence of cancer was significantly different between THA (n = 38; 14 %) and TKA (n = 52; 22 %) (p = 0.01). The associations between a higher number of comorbidities and worse outcomes were stronger in THA than in TKA. In multivariate analyses including all comorbidities with a prevalence of >5 %, in THA dizziness in combination with falling and severe back pain, and in TKA dizziness in combination with falling, vision impairments, and elbow, wrist or hand pain was associated with worse outcomes in most of the analyses. A broad range of specific comorbidities needs to be taken into account with the interpretation of patients’ health status after THA and TKA. More research including the ascertainment of comorbidities preoperatively is needed, but it is conceivable that in particular, the presence of dizziness with falling, pain in other joints, and vision impairments should be assessed and treated in order to decrease the chance of an unfavorable outcome

The 2021 Association Research Circulation Osseous Classification for Early-Stage Osteonecrosis of the Femoral Head to Computed Tomography–Based Study

© 2022 Elsevier Inc.Background: The Association Research Circulation Osseous developed a novel classification for early-stage (precollapse) osteonecrosis of the femoral head (ONFH). We hypothesized that the novel classification is more reliable and valid when compared to previous 3 classifications: Steinberg, modified Kerboul, and Japanese Investigation Committee classifications. Methods: In the novel classification, necrotic lesions were classified into 3 types: type 1 is a small lesion, where the lateral necrotic margin is medial to the femoral head apex; type 2 is a medium-sized lesion, with the lateral necrotic margin being between the femoral head apex and the lateral acetabular edge; and type 3 is a large lesion, which extends outside the lateral acetabular edge. In a derivation cohort of 40 early-stage osteonecrotic hips based on computed tomography imaging, reliabilities were evaluated using kappa coefficients, and validities to predict future femoral head collapse by chi-squared tests and receiver operating characteristic curve analyses. The predictability for future collapse was also evaluated in a validation cohort of 104 early-stage ONFH. Results: In the derivation cohort, interobserver reliability (k = 0.545) and intraobserver agreement (63%-100%) of the novel method were higher than the other 3 classifications. The novel classification system was best able to predict future collapse (P &lt; .05) and had the best discrimination between non-progressors and progressors in both the derivation cohort (area under the curve = 0.692 [0.522-0.863], P &lt; .05) and the validation cohort (area under the curve = 0.742 [0.644-0.841], P = 2.46 × 10−5). Conclusion: This novel classification is a highly reliable and valid method of those examined. Association Research Circulation Osseous recommends using this method as a unified classification for early-stage ONFH. Level of Evidence: Level III, diagnostic study.N