330. Evaluating the Relationship Between Comorbidity Treatment Status and In-hospital Mortality Among COVID-19 Patients

Abstract Background Chronic comorbidities increase the risk of poor outcomes in patients with COVID-19. However, there are insufficient data to determine whether control of chronic comorbidities influences outcomes. The purpose of this study was to determine whether pharmacologic treatment for common comorbidities influences in-hospital mortality. Methods This multicenter, retrospective study included adult patients with diabetes, hypertension, and/or dyslipidemia who were hospitalized with COVID-19 in Southwest GA, U.S. Patients were divided into two groups based on treatment status, where treated was defined as documentation in the electronic medical record of outpatient pharmacologic therapy indicated for that specific comorbidity while untreated was defined as no record of pharmacologic therapy for one or more comorbidity. The primary outcome was to compare in-hospital mortality between treated and untreated COVID-19 patients. Secondary outcomes included comparing length of hospital stay, development of thrombotic events, requirement for vasopressors, mechanical ventilation, and transfer to the ICU between groups. Results A total of 360 patients were included with a median age of 66 years (IQR 56-75). The majority were African American (83%) and female (61%) with a median Charlson Comorbidity Index of 4 (IQR 2-6). Hypertension, diabetes, and dyslipidemia were present in 91%, 55%, and 45% of patients, respectively, of which 76% (n=274) were treated. Mortality was similar between treated and untreated patients (25% vs 20%, p=0.304). Average length of stay was 9.5 days (SD 8.7) in treated patients compared to 10.6 days (SD 9.1) in untreated patients (p=0.302). No differences were observed in the rates of thrombosis (3% vs 4%, p=0.765), receipt of vasopressors (23% vs 21%, p=0.741), mechanical ventilation (31% vs 27%, p=0.450), or transfer to the ICU (27% vs 14%, p=0.112). Conclusion Hospitalized COVID-19 patients being treated for hypertension, diabetes, and/or dyslipidemia have similar rates of complications and mortality compared to untreated patients. Further research is needed to determine whether degree of control of chronic comorbidities impacts COVID-19 outcomes. Disclosures All Authors: No reported disclosures

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Increased length of inpatient stay and poor clinical coding: audit of patients with diabetes

JRSM Short Reports ◽

10.1258/shorts.2011.011100 ◽

2011 ◽

Vol 2 (11) ◽

pp. 1-6 ◽

Cited By ~ 9

Author(s):

Harriet Daultrey ◽

Erine Gooday ◽

Ketan Dhatariya

Keyword(s):

Length Of Stay ◽

Average Length ◽

University Teaching ◽

National Data ◽

Clinical Coding ◽

Existing Problems ◽

Average Length Of Stay ◽

Patients With Diabetes ◽

Foot Problems ◽

Discharge Summaries

Objectives People with diabetes stay in hospital for longer than those without diabetes for similar conditions. Clinical coding is poor across all specialties. Inpatients with diabetes often have unrecognized foot problems. We wanted to look at the relationships between these factors. Design A single day audit, looking at the prevalence of diabetes in all adult inpatients. Also looking at their feet to find out how many were high-risk or had existing problems. Setting A 998-bed university teaching hospital. Participants All adult inpatients. Main outcome measures (a) To see if patients with diabetes and foot problems were in hospital for longer than the national average length of stay compared with national data; (b) to see if there were people in hospital with acute foot problems who were not known to the specialist diabetic foot team; and (c) to assess the accuracy of clinical coding. Results We identified 110 people with diabetes. However, discharge coding data for inpatients on that day showed 119 people with diabetes. Length of stay (LOS) was substantially higher for those with diabetes compared to those without (± SD) at 22.39 (22.26) days, vs. 11.68 (6.46) ( P < 0.001). Finally, clinical coding was poor with some people who had been identified as having diabetes on the audit, who were not coded as such on discharge. Conclusion Clinical coding – which is dependent on discharge summaries – poorly reflects diagnoses. Additionally, length of stay is significantly longer than previous estimates. The discrepancy between coding and diagnosis needs addressing by increasing the levels of awareness and education of coders and physicians. We suggest that our data be used by healthcare planners when deciding on future tariffs.

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Predicting the impact of new health technologies on average length of stay: Development of a prediction framework

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462305050671 ◽

2005 ◽

Vol 21 (4) ◽

pp. 487-491 ◽

Cited By ~ 6

Author(s):

Sue Simpson ◽

Claire Packer ◽

Andrew Stevens ◽

James Raftery

Keyword(s):

Length Of Stay ◽

Health Management ◽

Average Length ◽

New Technology ◽

Length Of Hospital Stay ◽

Health Technologies ◽

Average Length Of Stay ◽

Admission Policies ◽

Mechanism Of Impact ◽

The Impact

Objectives: The aim of this study was to develop a framework to predict the impact of new health technologies on average length of hospital stay.Methods: A literature search of EMBASE, MEDLINE, Web of Science, and the Health Management Information Consortium databases was conducted to identify papers that discuss the impact of new technology on length of stay or report the impact with a proposed mechanism of impact of specific technologies on length of stay. The mechanisms of impact were categorized into those relating to patients, the technology, or the organization of health care and clinical practice.Results: New health technologies have a variable impact on length of stay. Technologies that lead to an increase in the proportion of sicker patients or increase the average age of patients remaining in the hospital lead to an increase in individual and average length of stay. Technologies that do not affect or improve the inpatient case mix, or reduce adverse effects and complications, or speed up the diagnostic or treatment process should lead to a reduction in individual length of stay and, if applied to all patients with the condition, will reduce average length of stay.Conclusions: The prediction framework we have developed will ensure that the characteristics of a new technology that may influence length of stay can be consistently taken into consideration by assessment agencies. It is recognized that the influence of technology on length of stay will change as a technology diffuses and that length of stay is highly sensitive to changes in admission policies and organization of care.

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Psychiatric and substance abuse disorder diagnoses as predictors of length of hospital stay

Australian Health Review ◽

10.1071/ah960020 ◽

1996 ◽

Vol 19 (4) ◽

pp. 20 ◽

Cited By ~ 1

Author(s):

David I Ben-Tovim ◽

Rob Elzinga ◽

Phillip Burgess

Keyword(s):

Mental Health ◽

Substance Abuse ◽

Hospital Stay ◽

Average Length ◽

Diagnosis Related Groups ◽

Length Of Hospital Stay ◽

Classification Systems ◽

Substance Abuse Disorder ◽

Average Length Of Stay ◽

Related Group

The mental health and substance abuse components of AN-DRG 3 were examinedusing data from all inpatient separations in two Australian States over a two-yearperiod. Assignment to a mental health or a substance abuse diagnosis related group(DRG) predicted about 20- per cent of the variability in average length of stay ofpatients treated for such conditions. Assignment to a substance abuse DRG was amuch less robust predictor of length of hospital stay than assignment to a mental healthDRG. There was little variation between years or States. Day-only intent patientswere excluded, as were long-stay outliers identified using an inter-quartile rangetrimming process. Psychiatric DRGs are similar to a number of other non-surgicallyfocused diagnosis related groups in their capacity to predict length of hospital stay. Theyare likely to remain an important component of casemix classification systems.

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In-hospital outcomes of self-expanding and balloon-expandable transcatheter heart valves in Germany

Clinical Research in Cardiology ◽

10.1007/s00392-021-01928-6 ◽

2021 ◽

Author(s):

Peter Stachon ◽

Philip Hehn ◽

Dennis Wolf ◽

Timo Heidt ◽

Vera Oettinger ◽

...

Keyword(s):

Mechanical Ventilation ◽

Acute Kidney Injury ◽

Propensity Score ◽

Hospital Mortality ◽

Hospital Stay ◽

Major Bleeding ◽

Postoperative Delirium ◽

Kidney Injury ◽

Length Of Hospital Stay ◽

Hospital Outcomes

Abstract Introduction The effect of valve type on outcomes in transfemoral transcatheter aortic valve replacement (TF-TAVR) has recently been subject of debate. We investigate outcomes of patients treated with balloon-expanding (BE) vs. self-expanding (SE) valves in in a cohort of all these procedures performed in Germany in 2018. Methods All patients receiving TF-TAVR with either BE (N = 9,882) or SE (N = 7,413) valves in Germany in 2018 were identified. In-hospital outcomes were analyzed for the endpoints in-hospital mortality, major bleeding, stroke, acute kidney injury, postoperative delirium, permanent pacemaker implantation, mechanical ventilation > 48 h, length of hospital stay, and reimbursement. Since patients were not randomized to the two treatment options, logistic or linear regression models were used with 22 baseline patient characteristics and center-specific variables as potential confounders. As a sensitivity analysis, the same confounding factors were taken into account using the propensity score methods (inverse probability of treatment weighting). Results Baseline characteristics differed substantially, with higher EuroSCORE (p < 0.001), age (p < 0.001) and rate of female sex (p < 0.001) in SE treated patients. After risk adjustment, no marked differences in outcomes were found for in-hospital mortality [risk adjusted odds ratio (aOR) for SE instead of BE 0.94 (96% CI 0.76;1.17), p = 0.617] major bleeding [aOR 0.91 (0.73;1.14), p = 0.400], stroke [aOR 1.13 (0.88;1.46), p = 0.347], acute kidney injury [OR 0.97 (0.85;1.10), p = 0.621], postoperative delirium [aOR 1.09 (0.96;1.24), p = 0.184], mechanical ventilation > 48 h [aOR 0.98 (0.77;1.25), p = 0.893], length of hospital stay (risk adjusted difference in days of hospitalization (SE instead of BE): − 0.05 [− 0.34;0.25], p = 0.762) and reimbursement [risk adjusted difference in reimbursement (SE instead of BE): − €72 (− €291;€147), p = 0.519)] There is, however, an increased risk of PPI for SE valves (aOR 1.27 [1.15;1.41], p < 0.001). Similar results were found after application of propensity score adjustment. Conclusions We find broadly equivalent outcomes in contemporary TF-TAVR procedures, regardless of the valve type used. Incidence of major complications is very low for both types of valve.

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The epidemiological study of migraine and other headache syndromes in southern Brazil: hospitalizations and average length of stay in 2020.

10.5327/1516-3180.042 ◽

2021 ◽

Author(s):

Júlia Maria Orsini Zava ◽

Tais Lorrane Mendes Silva ◽

Gabriela Biazi Barbosa ◽

Fabio Rosnei da Silva ◽

Gabriela Dias Silva Dutra Macedo

Keyword(s):

Average Length ◽

Length Of Hospital Stay ◽

Epidemiological Survey ◽

Cross Sectional Study ◽

Age Group ◽

Southern Brazil ◽

Cross Sectional ◽

Southern States ◽

Average Length Of Stay ◽

Using Data

Introduction: Migraine is one of the most common headaches and a frequent population complaint, presenting different symptoms and intensities. Objective: The objective is to carry out an epidemiological survey and the average length of hospital stay in the southern states of Brazil. Methodology: This is an epidemiological, descriptive and cross-sectional study. Design and setting: Is a carried out using data collected from DATASUS, during 2020 year in southern Brazil. Results: In the proposed period, there were 2,662 hospitalizations, with the state of PR the largest number (1,760). As for the average hospitalization, the RS stands out with 4 days, SC presents 2.8 and PR with 2.3. Regarding the age group, in PR it is between 40-49 years old, SC between 30-39 and in RS 50-59. As for gender, the prevalence is higher among women, with 63.11% of the total. Conclusion:The data are in agreement with the literature, confirming that women are more affected, being justified by numerous factors, from hormonal variations to different responses to the perception of stress and pain. The high average length of hospitalizations indicates the need to develop policies to discuss the issue, providing adequate prophylaxis and therapy, reducing the number of the cases, the intensity of crises and hospitalizations.

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Factors Associated with the Poor Outcomes in Diabetic Patients with COVID-19

10.21203/rs.3.rs-34111/v1 ◽

2020 ◽

Author(s):

Hadith Rastad ◽

Hanieh-Sadat Ejtahed ◽

Armita Mahdavi Ghorabi ◽

Anis Safari ◽

Ehsan Shahrestanaki ◽

...

Keyword(s):

Mechanical Ventilation ◽

Hospital Mortality ◽

Creatinine Level ◽

Neutrophil Count ◽

Invasive Mechanical Ventilation ◽

Low Frequency ◽

Diabetic Patients ◽

Logistic Regression Models ◽

The Poor ◽

Poor Outcomes

Abstract Background: Diabetic’s patients are supposed to experience higher rates of COVID-19 related poor outcomes. We aimed to determined factors predicting poor outcomes in hospitalized diabetic patients with COVID-19. Methods: This retrospective cohort study included all adult diabetic patients with radiological or laboratory confirmed COVID-19 who hospitalized between 20 February 2020 and 27 April 2020 in Alborz province, Iran. Data on demographic, medical history, and laboratory test at presentation were obtained from electronic medical records. Diagnosis of diabetes mellitus was self-reported. Comorbidities including cancer, rheumatism, immunodeficiency, or chronic diseases of respiratory, liver, and blood were classified as “other comorbidities” due to low frequency. The assessed poor outcomes were in-hospital mortality, need to ICU care, and receiving invasive mechanical ventilation. Self-reported. Multivariate logistic regression models were fitted to quantify the predictors of in-hospital mortality from COVID-19 in patients with DM. Results: Of 455 included patients, 98(21.5%) received ICU care, 65(14.3%) required invasive mechanical ventilation, and 79 (17.4%) dead. In the multivariate model, significant predictors of “death of COVID-19” were age 65 years or older (OR (95% CI): 2.0 (1.16-3.44), chronic kidney disease (CKD) (2.05 (1.16 -3.62), presence of “other comorbidities” (2.20 (1.04-4.63)), neutrophil count ≥ 8.0 × 10⁹/L )6.62 (3.73-11.7 ((, Hb level <12.5 g/dl (2.05 (1.13-3.72)(, and creatinine level ≥1.36 mg/dl (3.10 (1.38-6.98)). (All p –values < 0.05). Some of these factors were also associated with other assessed poor outcomes, e.g., need to ICU care or invasive mechanical ventilation.Conclusions: Diabetic patients with age 65 years or older, comorbidity CKD, “other comorbidities”, as well as neutrophil count ≥ 8.0 × 10⁹/L, Hb level <12.5 g/dl, and creatinine level ≥1.36 mg/dl, were more likely to dead after COVID-19. Presence of hypertension and cardiovascular disease were associated with none of the poor outcomes.

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Factors associated with the poor outcomes in diabetic patients with COVID-19

10.21203/rs.3.rs-56358/v1 ◽

2020 ◽

Author(s):

Hadith Rastad ◽

Hanieh-Sadat Ejtahed ◽

Armita Mahdavi-Ghorabi ◽

Anis Safari ◽

Ehsan Shahrestanaki ◽

...

Keyword(s):

Mechanical Ventilation ◽

Hospital Mortality ◽

Creatinine Level ◽

Neutrophil Count ◽

Invasive Mechanical Ventilation ◽

Low Frequency ◽

Diabetic Patients ◽

Logistic Regression Models ◽

The Poor ◽

Poor Outcomes

Abstract Background Diabetic’s patients are supposed to experience higher rates of COVID-19 related poor outcomes. We aimed to determined factors predicting poor outcomes in hospitalized diabetic patients with COVID-19. Methods This retrospective cohort study included all adult diabetic patients with radiological or laboratory confirmed COVID-19 who hospitalized between 20 February 2020 and 27 April 2020 in Alborz province, Iran. Data on demographic, medical history, and laboratory test at presentation were obtained from electronic medical records. Diagnosis of diabetes mellitus was self-reported. Comorbidities including cancer, rheumatism, immunodeficiency, or chronic diseases of respiratory, liver, and blood were classified as “other comorbidities” due to low frequency. The assessed poor outcomes were in-hospital mortality, need to ICU care, and receiving invasive mechanical ventilation. Self-reported. Multivariate logistic regression models were fitted to quantify the predictors of in-hospital mortality from COVID-19 in patients with DM. Results Of 455 included patients, 98(21.5%) received ICU care, 65(14.3%) required invasive mechanical ventilation, and 79 (17.4%) dead. In the multivariate model, significant predictors of “death of COVID-19” were age 65 years or older (OR (95% CI): 2.0 (1.16–3.44), chronic kidney disease (CKD) (2.05 (1.16–3.62), presence of “other comorbidities” (2.20 (1.04–4.63)), neutrophil count ≥ 8.0 × 10⁹/L )6.62 (3.73–11.7 ((, Hb level < 12.5 g/dl (2.05 (1.13–3.72) (, and creatinine level ≥ 1.36 mg/dl (3.10 (1.38–6.98)). (All p –values < 0.05). Some of these factors were also associated with other assessed poor outcomes, e.g., need to ICU care or invasive mechanical ventilation. Conclusions Diabetic patients with age 65 years or older, comorbidity CKD, “other comorbidities”, as well as neutrophil count ≥ 8.0 × 10⁹/L, Hb level < 12.5 g/dl, and creatinine level ≥ 1.36 mg/dl, were more likely to dead after COVID-19. Presence of hypertension and cardiovascular disease were associated with none of the poor outcomes.

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Efficacy of probiotics in the prevention of VAP in critically ill ICU patients: an updated systematic review and meta-analysis of randomized control trials

Journal of Intensive Care ◽

10.1186/s40560-020-00487-8 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Priyam Batra ◽

Kapil Dev Soni ◽

Purva Mathur

Keyword(s):

Systematic Review ◽

Mechanical Ventilation ◽

Hospital Mortality ◽

Hospital Stay ◽

Critically Ill ◽

Meta Analysis ◽

Length Of Hospital Stay ◽

Mean Difference ◽

Icu Stay ◽

Length Of Icu Stay

Abstract Introduction Ventilator-associated pneumonia (VAP) is reported as the second most common nosocomial infection among critically ill patients with the incidence ranging from 2 to 16 episodes per 1000 ventilator days. The use of probiotics has been shown to have a promising effect in many RCTs. Our systematic review and meta-analysis were thus planned to determine the effect of probiotic use in critically ill ventilated adult patients on the incidence of VAP, length of hospital stay, length of ICU stay, duration of mechanical ventilation, the incidence of diarrhea, and the incidence of oropharyngeal colonization and in-hospital mortality. Methodology Systematic search of various databases (such as Embase, Cochrane, and Pubmed), published journals, clinical trials, and abstracts of the various major conferences were made to obtain the RCTs which compare probiotics with placebo for VAP prevention. The results were expressed as risk ratios or mean differences. Data synthesis was done using statistical software - Review Manager (RevMan) Version 5.4 (The Cochrane Collaboration, 2020). Results Nine studies met our inclusion criterion and were included in the meta-analysis. The incidence of VAP (risk ratio: 0.70, CI 0.56, 0.88; P = 0.002; I2 = 37%), duration of mechanical ventilation (mean difference −3.75, CI −6.93, −0.58; P 0.02; I2 = 96%), length of ICU stay (mean difference −4.20, CI −6.73, −1.66; P = 0.001; I2 = 84%) and in-hospital mortality (OR 0.73, CI 0.54, 0.98; P = 0.04; I2 = 0%) in the probiotic group was significantly lower than that in the control group. Probiotic administration was not associated with a statistically significant reduction in length of hospital stay (MD −1.94, CI −7.17, 3.28; P = 0.47; I2 = 88%), incidence of oro-pharyngeal colonization (OR 0.59, CI 0.33, 1.04; P = 0.07; I2 = 69%), and incidence of diarrhea (OR 0.59, CI 0.34, 1.03; P = 0.06; I2 = 38%). Discussion Our meta-analysis shows that probiotic administration has a promising role in lowering the incidence of VAP, the duration of mechanical ventilation, length of ICU stay, and in-hospital mortality.

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Abstract 368: Association of Atrial Fibrillation with In-hospital Outcomes in ST-Elevation Myocardial Infarction - A Propensity Matched Study

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.8.suppl_2.368 ◽

2015 ◽

Vol 8 (suppl_2) ◽

Author(s):

Prakash Harikrishnan ◽

Marjan Mujib ◽

Tanush Gupta ◽

Dhaval Kolte ◽

Chandrasekar Palaniswamy ◽

...

Keyword(s):

Myocardial Infarction ◽

Atrial Fibrillation ◽

Length Of Stay ◽

Hospital Mortality ◽

Average Length ◽

St Elevation Myocardial Infarction ◽

Hospital Charges ◽

Total Hospital ◽

Average Length Of Stay ◽

St Elevation

Background: Atrial fibrillation is a relatively common comorbid condition in patients with coronary artery disease. However, there are limited data on the association of atrial fibrillation (AF) with outcomes in ST-elevation myocardial infarction (STEMI). Methods: We queried the 2003-2011 Nationwide Inpatient Sample databases using the ICD-9 diagnosis codes, to identify all patients > 18 years admitted with a primary diagnosis of STEMI. We studied the association of AF with in-hospital outcomes in these patients both by regression analysis and propensity match to adjust for demographics, hospital characteristics and co-morbidities. Results: Of the total 452,772 (64.5% men) STEMI hospitalizations, AF was documented in 58,273 (12.9%) cases. Patients with AF were older (mean age 75±12 vs 64±14 years; p<0.001) and had a higher proportion of women (42.5% vs 34.5%; p<0.001) than patients without AF. STEMI patients with AF had a higher risk-adjusted in-hospital mortality (OR 1.15, 95% CI 1.12-1.19, p<0.001), longer average length of stay (7 days vs 4 days, P<0.001) and higher average total hospital charges ($74,082 vs $57,331, P<0.001) than those without AF. Using propensity matching, 57,388 STEMI patients with AF were compared with the same number of patients without AF. Within these matched cohorts, STEMI patients with AF had higher in-hospital mortality (16.7% vs 15.1%, OR 1.13, 95% CI 1.09-1.16; p<0.001), longer average length of stay (7 days vs 6 days, P<0.001), and higher average total hospital charges ($73,832 vs $65,201, P<0.001) than patients without AF. Conclusions: In patients hospitalized with STEMI, AF was independently associated with modestly higher in-hospital mortality, higher hospital charges, and longer length of stay.

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Efficacy of a triage system to reduce length of hospital stay

The British Journal of Psychiatry ◽

10.1192/bjp.bp.113.141051 ◽

2014 ◽

Vol 204 (6) ◽

pp. 480-485 ◽

Cited By ~ 12

Author(s):

P. Williams ◽

E. Csipke ◽

D. Rose ◽

L. Koeser ◽

P. McCrone ◽

...

Keyword(s):

Length Of Stay ◽

Average Length ◽

Length Of Hospital Stay ◽

Triage System ◽

Traditional System ◽

Average Length Of Stay ◽

Significant Difference ◽

Two Systems ◽

Admission System ◽

Novel Method

BackgroundAttempts have been made to improve the efficiency of in-patient acute care. A novel method has been the development of a ‘triage system’ in which patients are assessed on admission to develop plans for discharge or transfer to an in-patient ward.AimsTo compare a triage admission system with a traditional system.MethodLength of stay and readmission data for all admissions in a 1-year period between the two systems were compared using the participating trust's anonymised records.ResultsDespite reduced length of stay on the actual triage ward, the average length of stay was not reduced and the triage system did not lead to a greater number of readmissions. There was no significant difference in costs between the two systems.ConclusionsBased on our findings we cannot conclude that the triage system reduced length of stay, but we can conclude that it does not increase the number of readmissions as some have feared.

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