A prognostic index for 1-year mortality can also predict in-hospital mortality of elderly medical patients

Abstract

Elderly patients admitted to the hospital are at increased risk for both in-hospital and post-discharge mortality. Risk assessment models (RAMs) for in-hospital mortality are based mainly on physiological variables and a few laboratory data, whereas RAMs for late mortality usually include other domains such as disability and comorbidities. We aim to evaluate if a previous validated model for 1-year mortality (the Walter Score) would also work well in predicting in-hospital mortality. We retrospectively revised the medical records of patients admitted on our ward, from April to December, 2013. Data regarding gender, activities of daily living (ADLs), comorbidities, and routine laboratory tests were used to calculate a Modified Walter Score (MoWS). The main outcome measure was all cause, in-hospital mortality. The analysis involved 1,004 patients. Of these, 888 were discharged alive, and 116 (11.5 %) died during the hospitalization. The mean MoWS was 4.9 (±3.6) in the whole sample. Stratification into risk classes parallels with in-hospital mortality (Chi square for trend p < 0.001). When dichotomized, MoWS has a sensitivity of 97.4 % (95 % CI 92.1-99.3), and a specificity of 48.2 % (95 % CI 44.9-51.5) with a good prognostic accuracy (area under the ROC = 0.81; 95 % CI 0.78, 0.84). Subgroup analysis according to different age groups gives similar results. A simple RAM based on multiple domains, previously validated for predicting mortality of older adults within 1 year from the index hospitalization, can be useful at the moment of admission to Internal Medicine wards to accurately identify patients at low risk of in-hospital mortality.

<p>Validation and Comparison of a Modified Elixhauser Index for Predicting In-Hospital Mortality in Italian Internal Medicine Wards</p>

“…Elixhauser score with the one evaluated by Cei et al is due to the setting, ie, Italian internal medicine wards, and the good performance reported by Cei et al that was 0.81 (95% CI 0.78-0.84). 23 We found that our modified Elixhauser score performed similarly to Cei et al 23 clinical prognostic index, and when it was calculated using clinical data derived by charts review its prognostic performance improved due to the higher number of comorbid conditions detected reviewing every single case. We previously evaluated the usefulness of the modified Elixhauser score on risk factors for IHM in internal medicine wards patients with infectious diseases.…”

“…In this paper, we aimed to validate a modified Elixhauser score developed in 2017 by our group 21 and we found that its performance could be considered reasonable if calculated using administrative data recorded at the time of discharge and good if calculated using electronic medical charts. Moreover, using electronic medical charts its performance was better than a prognostic index derived from clinical data and evaluated by Cei et al in 2015 in a similar setting; 23 the reason for comparing the modified…”

“…Authors evaluated all medical charts and recorded comorbidity according to the modified Elixhauser score and according to a previous prognostic index derived from clinical data proposed by Cei et al in 2015 in elderly medical patients. 23 For the calculation of this latter index male gender (point=1), dependency in activities of daily living (1-4 ADLs points=2; 5 ADLs points=5), congestive heart failure (points=2), solitary or hematologic cancer (points=3), metastatic cancer (points=8), serum creatinine >3 mg/dl (points=2), serum album <3 g/dl (points=2) or between 3 and 3.4 g/dl (point=1) were evaluated. 23…”

“…23 For the calculation of this latter index male gender (point=1), dependency in activities of daily living (1-4 ADLs points=2; 5 ADLs points=5), congestive heart failure (points=2), solitary or hematologic cancer (points=3), metastatic cancer (points=8), serum creatinine >3 mg/dl (points=2), serum album <3 g/dl (points=2) or between 3 and 3.4 g/dl (point=1) were evaluated. 23…”