Correction to: Probabilities of ICU admission and hospital discharge according to patient characteristics in the designated COVID-19 hospital of Kuwait.
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ABSTRACT:
SUBMITTER: Kipourou DK
PROVIDER: S-EPMC8218567 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSubsequent epidemic waves have already emerged in many countries and in the absence of highly effective preventive and curative options, the role of patient characteristics on the development of outcomes needs to be thoroughly examined, especially in middle-east countries where such epidemiological studies are lacking. There is a huge pressure on the hospital services and in particular, on the Intensive Care Units (ICU). Describing the need for critical care as well as the chance of being discharged from hospital according to patient characteristics, is essential for a more efficient hospital management. The objective of this study is to describe the probabilities of admission to the ICU and the probabilities of hospital discharge among positive COVID-19 patients according to demographics and comorbidities recorded at hospital admission.MethodsA prospective cohort study of all patients with COVID-19 found in the Electronic Medical Records of Jaber Al-Ahmad Al-Sabah Hospital in Kuwait was conducted. The study included 3995 individuals (symptomatic and asymptomatic) of all ages who tested positive from February 24th to May 27th, 2020, out of which 315 were treated in the ICU and 3619 were discharged including those who were transferred to a different healthcare unit without having previously entered the ICU. A competing risk analysis considering two events, namely, ICU admission and hospital discharge using flexible hazard models was performed to describe the association between event-specific probabilities and patient characteristics.ResultsResults showed that being male, increasing age and comorbidities such as chronic kidney disease (CKD), asthma or chronic obstructive pulmonary disease and weakened immune system increased the risk of ICU admission within 10 days of entering the hospital. CKD and weakened immune system decreased the probabilities of discharge in both females and males however, the age-related pattern differed by gender. Diabetes, which was the most prevalent comorbid condition, had only a moderate impact on both probabilities (18% overall) in contrast to CKD which had the largest effect, but presented only in 7% of those admitted to ICU and in 1% of those who got discharged. For instance, within 5 days a 50-year-old male had 19% (95% C.I.: [15,23]) probability of entering the ICU if he had none of these comorbidities, yet this risk jumped to 31% (95% C.I.: [20,46]) if he had also CKD, and to 27% in the presence of asthma/COPD (95% C.I.: [19,36]) or of weakened immune system (95% C.I.: [16,42]).ConclusionsThis study provides useful insight in describing the probabilities of ICU admission and hospital discharge according to age, gender, and comorbidities among confirmed COVID-19 cases in Kuwait. A web-tool is also provided to allow the user to estimate these probabilities for any combination of these covariates. These probabilities enable deeper understanding of the hospital demand according to patient characteristics which is essential to hospital management and useful for developing a vaccination strategy.
| S-EPMC8072736 | biostudies-literature
Project description:[This corrects the article DOI: 10.1371/journal.pone.0211240.].
| S-EPMC6550420 | biostudies-literature
Project description:IntroductionPrevious studies have shown that patients admitted to the intensive care unit (ICU) after "office hours" are more likely to die. However these results have been challenged by numerous other studies. We therefore analysed this possible relationship between ICU admission time and in-hospital mortality in The Netherlands.MethodsThis article relates time of ICU admission to hospital mortality for all patients who were included in the Dutch national ICU registry (National Intensive Care Evaluation, NICE) from 2002 to 2008. We defined office hours as 08:00-22:00 hours during weekdays and 09:00-18:00 hours during weekend days. The weekend was defined as from Saturday 00:00 hours until Sunday 24:00 hours. We corrected hospital mortality for illness severity at admission using Acute Physiology and Chronic Health Evaluation II (APACHE II) score, reason for admission, admission type, age and gender.ResultsA total of 149,894 patients were included in this analysis. The relative risk (RR) for mortality outside office hours was 1.059 (1.031-1.088). Mortality varied with time but was consistently higher than expected during "off hours" and lower during office hours. There was no significant difference in mortality between different weekdays of Monday to Thursday, but mortality increased slightly on Friday (RR 1.046; 1.001-1.092). During the weekend the RR was 1.103 (1.071-1.136) in comparison with the rest of the week.ConclusionsHospital mortality in The Netherlands appears to be increased outside office hours and during the weekends, even when corrected for illness severity at admission. However, incomplete adjustment for certain confounders might still play an important role. Further research is needed to fully explain this difference.
| S-EPMC2940016 | biostudies-literature
Project description:BackgroundReduced body weight at the time of intensive care unit (ICU) admission is associated with worse survival, and a paradoxical benefit of obesity has been suggested in critical illness. However, no research has addressed the survival effects of disaggregated body constituents of dry weight such as skeletal muscle, fat, and bone density.MethodsSingle-center, prospective observational cohort study of medical ICU (MICU) patients from an academic institution in the USA. Five hundred and seven patients requiring CT scanning of chest or abdomen within the first 24 h of ICU admission were evaluated with erector spinae muscle (ESM) and subcutaneous adipose tissue (SAT) areas and with bone density determinations at the time of ICU admission, which were correlated with clinical outcomes accounting for potential confounders.ResultsLarger admission ESM area was associated with decreased odds of 6-month mortality (OR per cm2, 0.96; 95% CI, 0.94-0.97; p < 0.001) and disability at discharge (OR per cm2, 0.98; 95% CI, 0.96-0.99; p = 0.012). Higher bone density was similarly associated with lower odds of mortality (OR per 100 HU, 0.69; 95% CI, 0.49-0.96; p = 0.027) and disability at discharge (OR per 100 HU, 0.52; 95% CI, 0.37-0.74; p < 0.001). SAT area was not significantly associated with these outcomes' measures. Multivariable modeling indicated that ESM area remained significantly associated with 6-month mortality and survival after adjusting for other covariates including preadmission comorbidities, albumin, functional independence before admission, severity scores, age, and exercise capacity.ConclusionIn our cohort, ICU admission skeletal muscle mass measured with ESM area and bone density were associated with survival and disability at discharge, although muscle area was the only component that remained significantly associated with survival after multivariable adjustments. SAT had no association with the analyzed outcome measures.
| S-EPMC7507825 | biostudies-literature
Project description:ObjectivePerformance assessments based on in-hospital mortality for ICU patients can be affected by discharge practices such that differences in mortality may reflect variation in discharge patterns rather than quality of care. Time-specific mortality rates, such as 30-day mortality, are preferred but are harder to measure. The degree to which the difference between 30-day and in-hospital ICU mortality rates-or "discharge bias"-varies by hospital type is unknown. The aim of this study was to quantify variation in discharge bias across hospitals and determine the hospital characteristics associated with greater discharge bias.DesignRetrospective cohort study.SettingNonfederal Pennsylvania hospital discharges in 2008.PatientsEligible patients were 18 years old or older and admitted to an ICU.InterventionsNone.Measurements and main resultsWe used logistic regression with hospital-level random effects to calculate hospital-specific risk-adjusted 30-day and in-hospital mortality rates. We then calculated discharge bias, defined as the difference between 30-day and in-hospital mortality rates, and used multivariable linear regression to compare discharge bias across hospital types. A total of 43,830 patients and 134 hospitals were included in the analysis. Mean (SD) risk-adjusted hospital-specific in-hospital and 30-day ICU mortality rates were 9.6% (1.3) and 12.7% (1.5), respectively. Hospital-specific discharge biases ranged from -1.3% to 6.6%. Discharge bias was smaller in large hospitals compared with small hospitals, making large hospitals appear comparatively worse from a benchmarking standpoint when using in-hospital mortality instead of 30-day mortality.ConclusionsDischarge practices bias in-hospital ICU mortality measures in a way that disadvantages large hospitals. Accounting for discharge bias will prevent these hospitals from being unfairly disadvantaged in public reporting and pay-for-performance.
| S-EPMC7895487 | biostudies-literature
Project description:BackgroundVariation in intensive care unit (ICU) readmissions and in-hospital mortality after ICU discharge may indicate potential for improvement and could be explained by ICU discharge practices. Our objective was threefold: (1) describe variation in rates of ICU readmissions within 48 h and post-ICU in-hospital mortality, (2) describe ICU discharge practices in Dutch hospitals, and (3) study the association between rates of ICU readmissions within 48 h and post-ICU in-hospital mortality and ICU discharge practices.MethodsWe analysed data on 42,040 admissions to 82 (91.1%) Dutch ICUs in 2011 from the Dutch National Intensive Care Evaluation (NICE) registry to describe variation in standardized ICU readmission and post-ICU mortality rates using funnel-plots. We send a questionnaire to all Dutch ICUs. 75 ICUs responded and their questionnaire data could be linked to 38,498 admissions in the NICE registry. Generalized estimation equations analyses were used to study the association between ICU readmissions and post-ICU mortality rates and the identified discharge practices, i.e. (1) ICU discharge criteria; (2) bed managers; (3) early discharge planning; (4) step-down facilities; (5) medication reconciliation; (6) verbal and written handover; (7) monitoring of post-ICU patients; and (8) consulting ICU nurses. In all analyses, the outcomes were corrected for patient-related confounding factors.ResultsThe standardized rate of ICU readmissions varied between 0.14 and 2.67 and 20.8% of the hospitals fell outside the 95% control limits and 3.6% outside the 99.8% control limits. The standardized rate of post-ICU mortality varied between 0.07 and 2.07 and 17.1% of the hospitals fell outside the 95% control limits and 4.9% outside the 99.8% control limits. We could not demonstrate an association between the eight ICU discharge practices and rates of ICU readmissions or post-ICU in-hospital mortality. Implementing a higher number of ICU discharge practices was also not associated with better patient outcomes.ConclusionsWe found both variation in patient outcomes and variation in ICU discharge practices between ICUs. However, we found no association between discharge practices and rates of ICU readmissions or post-ICU mortality. Further research is necessary to find factors, which may influence these patient outcomes, in order to improve quality of care.
| S-EPMC5393034 | biostudies-literature
Project description:We investigated the causes of inpatient death after intensive care unit (ICU) discharge and determined predictors of in-hospital mortality in Korea. Using medical ICU registry data of Seoul National University Hospital, we performed a retrospective cohort study involving patients who were discharged alive from their first ICU admission with at least 24 hours of ICU length of stay (LOS). From January 2011 to August 2013, 723 patients were admitted to ICU and 383 patients were included. The estimated in-hospital mortality rate was 11.7% (45/383). The most common cause of death was respiratory failure (n = 25, 56%) followed by sepsis and cancer progression; the causes of hospital death and ICU admission were the same in 64% of all deaths; sudden unexpected deaths comprised about one-fifth of all deaths. In order to predict in-hospital mortality among ICU survivors, multivariate analysis identified presence of solid tumor (odds ratio [OR], 4.06; 95% confidence interval [CI], 2.01-8.2; P < 0.001), hematologic disease (OR, 4.75; 95% CI, 1.51-14.96; P = 0.013), Sequential Organ Failure Assessment (SOFA) score upon ICU admission (OR, 1.08; 95% CI, 0.99-1.17; P = 0.075), and hemoglobin (Hb) level (OR, 0.67; 95% CI, 0.52-0.86; P = 0.001) and platelet count (Plt) (OR, 0.99; 95% CI, 0.99-1.00; P = 0.033) upon ICU discharge as significant factors. In conclusion, a significant proportion of in-hospital mortality is predictable and those who die in hospital after ICU discharge tend to be severely-ill, with comorbidities of hematologic disease and solid tumor, and anemic and thrombocytopenic upon ICU discharge.
| S-EPMC5290115 | biostudies-literature
Project description:OBJECTIVES:One quarter of pediatric hospitalizations begin as direct admissions, defined as hospitalization without receiving care in the hospital's emergency department (ED). Direct admission rates are highly variable across hospitals, yet previous studies have not examined reasons for this variation. We aimed to determine the relationships between hospital and community factors and pediatric direct admission rates, and to evaluate the degree to which these characteristics explain variation in risk-adjusted direct admission rates. METHODS:We conducted a cross-sectional study of the Healthcare Cost and Utilization Project's Kids Inpatient Database, American Hospital Association Database, and Area Health Resource File, including children <18 years of age who were admitted for a medical hospitalization in states contributing data to all data sets. Using hierarchical generalized linear modeling, we generated risk-adjusted direct admission rates and used generalized linear models to assess the association of hospital and community characteristics with these risk-adjusted rates. RESULTS:We included 211,458 children discharged from 933 hospitals and 26 states; 20.2% were admitted directly. One-fifth of the variance in risk-adjusted direct admission rates was attributed to observed hospital and community factors. The greatest proportion of this explained variance was related to ED volume (37%), volume of pediatric hospitalizations (27%), and size of the pediatrician workforce (12%). CONCLUSIONS:Direct admission rates were associated with several hospital and community characteristics, but the majority of variation in hospitals' direct admission rates was not explained by these factors. These findings suggest opportunities for diverse hospital types to develop the infrastructure and communication systems necessary to support pediatric direct admissions.
| S-EPMC5924569 | biostudies-literature
Project description:The effect of advanced age per se versus severity of chronic and acute diseases on the short- and long-term survival of older patients admitted to the intensive care unit (ICU) remains unclear.Intensive care unit admissions to the surgical ICU and medical ICU of patients older than 65 years were analyzed. Patients were divided into three age groups: 65-74, 75-84, and 85 and above. The primary endpoints were 28-day and 1-year mortality.The analysis focused on 7,265 patients above the age of 65, representing 45.7 % of the total ICU population. From the first to third age group there was increased prevalence of heart failure (25.9-40.3 %), cardiac arrhythmia (24.6-43.5 %), and valvular heart disease (7.5-15.8 %). There was reduced prevalence of diabetes complications (7.5-2.4 %), alcohol abuse (4.1-0.6 %), chronic obstructive pulmonary disease (COPD) (24.4-17.4 %), and liver failure (5.0-1.0 %). Logistic regression analysis adjusted for gender, sequential organ failure assessment, do not resuscitate, and Elixhauser score found that patients from the second and third age group had odds ratios of 1.38 [95 % confidence interval (CI) 1.19-1.59] and 1.53 (95 % CI 1.29-1.81) for 28-day mortality as compared with the first age group. Cox regression analysis for 1-year mortality in all populations and in 28-day survivors showed the same trend.The proportion of elderly patients from the total ICU population is high. With advancing age, the proportion of various preexisting comorbidities and the primary reason for ICU admission change. Advanced age should be regarded as a significant independent risk factor for mortality, especially for ICU patients older than 75.
| S-EPMC5718912 | biostudies-literature
Project description:BackgroundTo determine the frequency of, and factors associated with, death in hospital following ICU discharge to the ward.MethodsThe Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE study was an international, multicenter, prospective cohort study of patients with severe respiratory failure, conducted across 459 ICUs from 50 countries globally. This study aimed to understand the frequency and factors associated with death in hospital in patients who survived their ICU stay. We examined outcomes in the subpopulation discharged with no limitations of life sustaining treatments ('treatment limitations'), and the subpopulations with treatment limitations.Results2186 (94%) patients with no treatment limitations discharged from ICU survived, while 142 (6%) died in hospital. 118 (61%) of patients with treatment limitations survived while 77 (39%) patients died in hospital. Patients without treatment limitations that died in hospital after ICU discharge were older, more likely to have COPD, immunocompromise or chronic renal failure, less likely to have trauma as a risk factor for ARDS. Patients that died post ICU discharge were less likely to receive neuromuscular blockade, or to receive any adjunctive measure, and had a higher pre- ICU discharge non-pulmonary SOFA score. A similar pattern was seen in patients with treatment limitations that died in hospital following ICU discharge.ConclusionsA significant proportion of patients die in hospital following discharge from ICU, with higher mortality in patients with limitations of life-sustaining treatments in place. Non-survivors had higher systemic illness severity scores at ICU discharge than survivors.Trial registrationClinicalTrials.gov NCT02010073 .
| S-EPMC8043098 | biostudies-literature