9 research outputs found

    Hamiltonian Monte Carlo for Regression with High-Dimensional Categorical Data

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    Latent variable models are increasingly used in economics for high-dimensional categorical data like text and surveys. We demonstrate the effectiveness of Hamiltonian Monte Carlo (HMC) with parallelized automatic differentiation for analyzing such data in a computationally efficient and methodologically sound manner. Our new model, Supervised Topic Model with Covariates, shows that carefully modeling this type of data can have significant implications on conclusions compared to a simpler, frequently used, yet methodologically problematic, two-step approach. A simulation study and revisiting Bandiera et al. (2020)'s study of executive time use demonstrate these results. The approach accommodates thousands of parameters and doesn't require custom algorithms specific to each model, making it accessible for applied researchersComment: 20 pages 5 figures, 2 table

    Inference for regression with variables generated from unstructured data

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    The leading strategy for analyzing unstructured data uses two steps. First, latent variables of economic interest are estimated with an upstream information retrieval model. Second, the estimates are treated as "data" in a downstream econometric model. We establish theoretical arguments for why this two-step strategy leads to biased inference in empirically plausible settings. More constructively, we propose a one-step strategy for valid inference that uses the upstream and downstream models jointly. The one-step strategy (i) substantially reduces bias in simulations; (ii) has quantitatively important effects in a leading application using CEO time-use data; and (iii) can be readily adapted by applied researchers

    Inference for Regression with Variables Generated from Unstructured Data

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    The leading strategy for analyzing unstructured data uses two steps. First, latent variables of economic interest are estimated with an upstream information retrieval model. Second, the estimates are treated as "data" in a downstream econometric model. We establish theoretical arguments for why this two-step strategy leads to biased inference in empirically plausible settings. More constructively, we propose a one-step strategy for valid inference that uses the upstream and downstream models jointly. The one-step strategy (i) substantially reduces bias in simulations; (ii) has quantitatively important effects in a leading application using CEO time-use data; and (iii) can be readily adapted by applied researchers

    The impact of frailty on ICU and 30-day mortality and the level of care in very elderly patients (≥ 80 years)

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    Purpose: Very old critical ill patients are a rapid expanding group in the ICU. Indications for admission, triage criteria and level of care are frequently discussed for such patients. However, most relevant outcome studies in this group frequently find an increased mortality and a reduced quality of life in survivors. The main objective was to study the impact of frailty compared with other variables with regards to short-term outcome in the very old ICU population. Methods: A transnational prospective cohort study from October 2016 to May 2017 with 30 days follow-up was set up by the European Society of Intensive Care Medicine. In total 311 ICUs from 21 European countries participated. The ICUs included the first consecutive 20 very old (≥ 80 years) patients admitted to the ICU within a 3-month inclusion period. Frailty, SOFA score and therapeutic procedures were registered, in addition to limitations of care. For measurement of frailty the Clinical Frailty Scale was used at ICU admission. The main outcomes were ICU and 30-day mortality and survival at 30 days. Results: A total of 5021 patients with a median age of 84 years (IQR 81–86 years) were included in the final analysis, 2404 (47.9%) were women. Admission was classified as acute in 4215 (83.9%) of the patients. Overall ICU and 30-day mortality rates were 22.1% and 32.6%. During ICU stay 23.8% of the patients did not receive specific ICU procedures: ventilation, vasoactive drugs or renal replacement therapy. Frailty (values ≥ 5) was found in 43.1% and was independently related to 30-day survival (HR 1.54; 95% CI 1.38–1.73) for frail versus non-frail. Conclusions: Among very old patients (≥ 80 years) admitted to the ICU, the consecutive classes in Clinical Frailty Scale were inversely associated with short-term survival. The scale had a very low number of missing data. These findings provide support to add frailty to the clinical assessment in this patient group. Trial registration: ClinicalTrials.gov (ID: NCT03134807)

    Sepsis at ICU admission does not decrease 30-day survival in very old patients: a post-hoc analysis of the VIP1 multinational cohort study

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    Background: The number of intensive care patients aged ≥ 80 years (Very old Intensive Care Patients; VIPs) is growing. VIPs have high mortality and morbidity and the benefits of ICU admission are frequently questioned. Sepsis incidence has risen in recent years and identification of outcomes is of considerable public importance. We aimed to determine whether VIPs admitted for sepsis had different outcomes than those admitted for other acute reasons and identify potential prognostic factors for 30-day survival. Results: This prospective study included VIPs with Sequential Organ Failure Assessment (SOFA) scores ≥ 2 acutely admitted to 307 ICUs in 21 European countries. Of 3869 acutely admitted VIPs, 493 (12.7%) [53.8% male, median age 83 (81-86) years] were admitted for sepsis. Sepsis was defined according to clinical criteria; suspected or demonstrated focus of infection and SOFA score ≥ 2 points. Compared to VIPs admitted for other acute reasons, VIPs admitted for sepsis were younger, had a higher SOFA score (9 vs. 7, p < 0.0001), required more vasoactive drugs [82.2% vs. 55.1%, p < 0.0001] and renal replacement therapies [17.4% vs. 9.9%; p < 0.0001], and had more life-sustaining treatment limitations [37.3% vs. 32.1%; p = 0.02]. Frailty was similar in both groups. Unadjusted 30-day survival was not significantly different between the two groups. After adjustment for age, gender, frailty, and SOFA score, sepsis had no impact on 30-day survival [HR 0.99 (95% CI 0.86-1.15), p = 0.917]. Inverse-probability weight (IPW)-adjusted survival curves for the first 30 days after ICU admission were similar for acute septic and non-septic patients [HR: 1.00 (95% CI 0.87-1.17), p = 0.95]. A matched-pair analysis in which patients with sepsis were matched with two control patients of the same gender with the same age, SOFA score, and level of frailty was also performed. A Cox proportional hazard regression model stratified on the matched pairs showed that 30-day survival was similar in both groups [57.2% (95% CI 52.7-60.7) vs. 57.1% (95% CI 53.7-60.1), p = 0.85]. Conclusions: After adjusting for organ dysfunction, sepsis at admission was not independently associated with decreased 30-day survival in this multinational study of 3869 VIPs. Age, frailty, and SOFA score were independently associated with survival

    Withholding or withdrawing of life-sustaining therapy in older adults (≥ 80 years) admitted to the intensive care unit

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    PURPOSE: To document and analyse the decision to withhold or withdraw life-sustaining treatment (LST) in a population of very old patients admitted to the ICU. METHODS: This prospective study included intensive care patients aged ≥ 80 years in 309 ICUs from 21 European countries with 30-day mortality follow-up. RESULTS: LST limitation was identified in 1356/5021 (27.2%) of patients: 15% had a withholding decision and 12.2% a withdrawal decision (including those with a previous withholding decision). Patients with LST limitation were older, more frail, more severely ill and less frequently electively admitted. Patients with withdrawal of LST were more frequently male and had a longer ICU length of stay. The ICU and 30-day mortality were, respectively, 29.1 and 53.1% in the withholding group and 82.2% and 93.1% in the withdrawal group. LST was less frequently limited in eastern and southern European countries than in northern Europe. The patient-independent factors associated with LST limitation were: acute ICU admission (OR 5.77, 95% CI 4.32-7.7), Clinical Frailty Scale (CFS) score (OR 2.08, 95% CI 1.78-2.42), increased age (each 5 years of increase in age had a OR of 1.22 (95% CI 1.12-1.34) and SOFA score [OR of 1.07 (95% CI 1.05-1.09 per point)]. The frequency of LST limitation was higher in countries with high GDP and was lower in religious countries. CONCLUSIONS: The most important patient variables associated with the instigation of LST limitation were acute admission, frailty, age, admission SOFA score and country. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NTC03134807)
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