The Surgical Procedure Assessment (SPA) score predicts intensive care unit length of stay after cardiac surgery

Prevalence of symptoms of anxiety and depression one year after intensive care unit admission for COVID-19

BACKGROUND

To the best of our knowledge, the long term prevalence of symptoms of anxiety and depression in ICU admitted individuals after COVID-19 in Sweden during the first wave of the pandemic has not been investigated. Furthermore, no studies have exclusively investigated the risk factors for experiencing symptoms of anxiety and depression in this population.

AIM

The aim of this study was to determine the prevalence of symptoms of anxiety and depression at one year after ICU admission for COVID-19. An additional aim was to identify any early predictors that are associated with symptoms of anxiety and depression, at one year following ICU admission for COVID-19.

METHODS

This multicenter cohort study had a cross-sectional and a longitudinal design. The primary outcomes and dependent variables, symptoms of anxiety and depression, were assessed using the Hospital Anxiety and Depression Scale (HADS). The independent variables were related to demographic factors, comorbidities, and complications during COVID-19-related ICU admission. Logistic regression analyses were performed to identify any predictors of symptoms of anxiety and depression.

RESULTS

Out of 182 eligible individuals, 105 participated in the study. Symptoms of anxiety was found in 40 (38.1%) and depression in 37 (35.2%) of the participants. Using univariable logistic regression analyses, female sex was identified as a predictor of depression as defined by HADS at one year following ICU admission for COVID-19 (odds ratio 2.53, 95% confidence intervals 1.01-6.34, p-value 0.048).

CONCLUSIONS

The high prevalence of symptoms of anxiety and depression in ICU admitted individuals one year after COVID-19 is a public health issue of concern. Our findings imply that individuals who recovered after an ICU stay for COVID-19 may benefit from long-term follow-ups and continuous mental health support for more than a year following the ICU admission. For women specifically, this is true.

TRIAL REGISTRATION

The study was registered at researchweb.org on 28 May 2020 (Project number: 274477).

Predictors of Length of Stay in Intensive Care Unit after Coronary Artery Bypass Grafting: Development a Risk Scoring System

Introduction

To determine predictors of length of stay (LOS) in the intensive care unit (ICU) after coronary artery bypass grafting (CABG) and to develop a risk scoring system were the objectives of this study.

Methods

In this retrospective study, 1202 patients' medical records after CABG were evaluated by a research-made checklist. Tarone-Ware test was used to determine the predictors of patients' LOS in the ICU. Cox regression model was used to determine the risk factors and risk ratios associated with ICU LOS.

Results

The mean ICU LOS after CABG was 55.27±17.33 hours. Cox regression model showed that having more than two chest tubes (95% confidence interval [CI] 1.005-1.287, Relative Risk [RR]=1.138), occurrence of atelectasis (95% CI 1.000-3.007, RR=1.734), and occurrence of atrial fibrillation after CABG (95% CI 1.428-2.424, RR=1.861) were risk factors associated with longer ICU LOS. The discrimination power of this set of predictors was demonstrated with an area under the receiver operating characteristic curve and it was 0.69. A simple risk scoring system was developed based on three identified predictors that can raise ICU LOS.

Conclusion

The simple risk scoring system developed based on three identified predictors can help to plan more accurately a patient's LOS in hospital for CABG and can be useful in managing human and financial resources.

[Predictors of prolonged ICU stay following elective adult cardiac surgery: Monocentric retrospective study on 5 and half years]

AIM

The aim of our study was to identify predictors for prolonged ICU stay following elective adult cardiac surgery under cardiopulmonary bypass.

PATIENTS AND METHODS

A retrospective study was conducted during 5 years and a half period. Were included, patients age≥18 years old, underwent elective cardiac surgery under cardiopulmonary bypass. Patients who died within 48hours of surgery were excluded. Prolonged ICU stay was defined as stay in the ICU for 48hours or more.

RESULTS

During the review period, 610 patients were included. One hundred and sixty-four patients have required a prolonged ICU stay (26.9 %). In multivariate analysis, 5 predictors were identified: ejection fraction<30 % (OR 19.991, IC 95 % [1.382-289.1], P=0.028], pulmonary hypertension (OR 2.293, IC 95 % [1.058-4.973], P=0.036), prolonged ventilation (≥12hours) (OR 4.026, IC 95 % [2.407-6.733], P<0.001). Number of blood units transfused (OR 1.568, IC 95 % [1.073-2.291], and postoperative acute renal failure (OR 2.620, IC 95 % [1.026-6.690], P=0.044]. Prolonged ICU stay is significantly associated with prolonged hospital stay (17 days vs 13 days ; P<0.001) and higher in hospital mortality (22 % vs. 3 %, P<0.001).

CONCLUSION

The identification of these patients at risk of prolonged ICU stay is crucial. It will aid to plan prophylactic measures to optimize their support.

Systematic review of factors influencing length of stay in ICU after adult cardiac surgery

BACKGROUND

Intensive care unit (ICU) care is associated with costly and often scarce resources. In many parts of the world, ICUs are being perceived as major bottlenecks limiting downstream services such as operating theatres. There are many clinical, surgical and contextual factors that influence length of stay. Knowing these factors can facilitate resource planning. However, the extent at which this knowledge is put into practice remains unclear. The aim of this systematic review was to identify factors that impact the duration of ICU stay after cardiac surgery and to explore evidence on the link between understanding these factors and patient and resource management.

METHODS

We conducted electronic searches of Embase, PubMed, ISI Web of Knowledge, Medline and Google Scholar, and reference lists for eligible studies.

RESULTS

Twenty-nine papers fulfilled inclusion criteria. We recognised two types of objectives for identifying influential factors of ICU length of stay (LOS) among the reviewed studies. These were general descriptions of predictors and prediction of prolonged ICU stay through statistical models. Among studies with prediction models, only two studies have reported their implementation. Factors most commonly associated with increased ICU LOS included increased age, atrial fibrillation/ arrhythmia, chronic obstructive pulmonary disease (COPD), low ejection fraction, renal failure/ dysfunction and non-elective surgery status.

CONCLUSION

Cardiac ICUs are major bottlenecks in many hospitals around the world. Efforts to optimise resources should be linked to patient and surgical characteristics. More research is needed to integrate patient and surgical factors into ICU resource planning.

Factors associated with prolonged length of stay following cardiac surgery in a major referral hospital in Oman: a retrospective observational study

OBJECTIVES

Two objectives were set for this study. The first was to identify factors influencing prolonged postoperative length of stay (LOS) following cardiac surgery. The second was to devise a predictive model for prolonged LOS in the cardiac intensive care unit (CICU) based on preoperative factors available at admission and to compare it against two existing cardiac stratification systems.

DESIGN

Observational retrospective study.

SETTINGS

A tertiary hospital in Oman.

PARTICIPANTS

All adult patients who underwent cardiac surgery at a major referral hospital in Oman between 2009 and 2013.

RESULTS

30.5% of the patients had prolonged LOS (≥11 days) after surgery, while 17% experienced prolonged ICU LOS (≥5 days). Factors that were identified to prolong CICU LOS were non-elective surgery, current congestive heart failure (CHF), renal failure, combined coronary artery bypass graft (CABG) and valve surgery, and other non-isolated valve or CABG surgery. Patients were divided into three groups based on their scores. The probabilities of prolonged CICU LOS were 11%, 26% and 28% for group 1, 2 and 3, respectively. The predictive model had an area under the curve of 0.75. Factors associated with prolonged overall postoperative LOS included the body mass index, the type of surgery, cardiopulmonary bypass machine use, packed red blood cells use, non-elective surgery and number of complications. The latter was the most important determinant of postoperative LOS.

CONCLUSIONS

Patient management can be tailored for individual patient based on their treatments and personal attributes to optimise resource allocation. Moreover, a simple predictive score system to enable identification of patients at risk of prolonged CICU stay can be developed using data that are routinely collected by most hospitals.

Transfer Delays From the Neurologic Intensive Care Unit: A Prospective Cohort Study

INTRODUCTION

Neurocritical care beds are a scarce, valuable resource. The purpose of this pilot study was to quantify discharge delays from the neurologic intensive care unit (NICU) at a tertiary-care teaching hospital and to examine the impact on overall hospital length of stay (LOS). Secondary goals were to evaluate (1) the effect of NICU delays on patient physical/occupational therapy services and (2) the accuracy of clinician estimates of NICU discharge date and hospital LOS.

METHODS

We conducted a prospective cohort study of consecutive patients discharged over 1 month from NICU. A patient was defined to have experienced a delay when deemed medically ready for NICU discharge (ie, floor transfer) but without actual NICU discharge within 8 hours of the ready time.

RESULTS

Sixty-five patients were discharged from the NICU with an average delay of 25 hours 51 minutes (median 13 hours 3 minutes), of which 60% (39 of 65) of patients were delayed at least 8 hours, while 25% (16 of 65) were delayed at least 48 hours. The primary reason for delay was lack of floor bed availability. NICU admissions that experienced a delay did not have a significantly longer hospital LOS. Clinician estimates on admission of NICU discharge date were within 24 hours for 63% of admissions.

CONCLUSION

Discharge delays from the NICU were common but did not significantly increase hospital LOS in this cohort. Delays did not have a significant impact on total physical therapy or occupational therapy duration. Clinician estimates of NICU discharge dates were relatively accurate.