Surge effects and survival to hospital discharge in critical care patients with COVID-19 during the early pandemic: a cohort study

Abstract Background The early months of the COVID-19 pandemic were fraught with much uncertainty and some resource constraint. We assessed the change in survival to hospital discharge over time for intensive care unit patients with COVID-19 during the first 3 months of the pandemic and the presence of any surge effects on patient outcomes. Methods Retrospective cohort study using electronic medical record data for all patients with laboratory-confirmed COVID-19 admitted to intensive care units from February 25, 2020, to May 15, 2020, at one of 26 hospitals within an integrated delivery system in the Western USA. Patient demographics, comorbidities, and severity of illness were measured along with medical therapies and hospital outcomes over time. Multivariable logistic regression models were constructed to assess temporal changes in survival to hospital discharge during the study period. Results Of 620 patients with COVID-19 admitted to the ICU [mean age 63.5 years (SD 15.7) and 69% male], 403 (65%) survived to hospital discharge and 217 (35%) died in the hospital. Survival to hospital discharge increased over time, from 60.0% in the first 2 weeks of the study period to 67.6% in the last 2 weeks. In a multivariable logistic regression analysis, the risk-adjusted odds of survival to hospital discharge increased over time (biweekly change, adjusted odds ratio [aOR] 1.22, 95% CI 1.04–1.40, P = 0.02). Additionally, an a priori-defined explanatory model showed that after adjusting for both hospital occupancy and percent hospital capacity by COVID-19-positive individuals and persons under investigation (PUI), the temporal trend in risk-adjusted patient survival to hospital discharge remained the same (biweekly change, aOR 1.18, 95% CI 1.00–1.38, P = 0.04). The presence of greater rates of COVID-19 positive/PUI as a percentage of hospital capacity was, however, significantly and inversely associated with survival to hospital discharge (aOR 0.95, 95% CI 0.92–0.98, P < 0.01). Conclusions During the early COVID-19 pandemic, risk-adjusted survival to hospital discharge increased over time for critical care patients. An association was also seen between a greater COVID-19-positive/PUI percentage of hospital capacity and a lower survival rate to hospital discharge.

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Surge Effects and Survival to Hospital Discharge in Critical Care Patients with COVID-19 During the Early Pandemic: A Cohort Study

10.21203/rs.3.rs-111259/v2 ◽

2021 ◽

Author(s):

Christopher Dale ◽

Rachael Starcher ◽

Shu Ching Chang ◽

Ari Robicsek ◽

Guilford Parsons ◽

...

Keyword(s):

Logistic Regression ◽

Critical Care ◽

Cohort Study ◽

Intensive Care ◽

Hospital Discharge ◽

Multivariable Logistic Regression Analysis ◽

Hospital Capacity ◽

Multivariable Logistic Regression ◽

Critical Care Patients ◽

Over Time

Abstract BackgroundThe early months of the COVID-19 pandemic were fraught with much uncertainty and some resource constraint. We assessed the change in survival to hospital discharge over time for intensive care unit patients with COVID-19 during the first three months of the pandemic and the presence of any surge effects on patient outcomes.MethodsRetrospective cohort study using electronic medical record data for all patients with laboratory-confirmed COVID-19 admitted to intensive care units from February 25, 2020 to May 15, 2020 at one of 26 hospitals within an integrated delivery system in the Western United States. Patient demographics, comorbidities and severity of illness were measured along with medical therapies and hospital outcomes over time. Multivariable logistic regression models were constructed to assess temporal changes in survival to hospital discharge during the study period.ResultsOf 620 patients with COVID-19 admitted to the ICU (mean age 63.5 years (SD 15.7) and 69% male), 403 (65%) survived to hospital discharge and 217 (35%) died in the hospital. Survival to hospital discharge increased over time, from 60.0% in the first two weeks of the study period to 67.6% in the last two weeks. In a multivariable logistic regression analysis, the risk-adjusted odds of survival to hospital discharge increased over time (bi-weekly change, adjusted odds ratio [aOR] 1.22, 95%CI 1.04-1.40, P = 0.02). Additionally, an a priori-defined explanatory model showed that after adjusting for both hospital occupancy and percent hospital capacity by COVID-19 positive individuals and persons under investigation (PUI), the temporal trend in risk-adjusted patient survival to hospital discharge remained the same (bi-weekly change, aOR 1.18, 95% CI 1.00 to 1.38, P = 0.04). The presence of greater rates of COVID-19 positive/PUI as a percentage of hospital capacity was, however, significantly and inversely associated with survival to hospital discharge (aOR 0.95, 95% CI 0.92 to 0.98, P < 0.01). ConclusionsDuring the early COVID-19 pandemic, risk-adjusted survival to hospital discharge increased over time for critical care patients. An association was also seen between a greater COVID-19 positive/PUI percentage of hospital capacity and a lower survival rate to hospital discharge.

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Surge Effects and Survival to Hospital Discharge in Critical Care Patients with COVID-19 During the Early Pandemic: A Cohort Study

10.21203/rs.3.rs-111259/v1 ◽

2020 ◽

Author(s):

Christopher Dale ◽

Rachael Starcher ◽

Shu Ching Chang ◽

Ari Robicsek ◽

Guilford Parsons ◽

...

Keyword(s):

Logistic Regression ◽

Critical Care ◽

Cohort Study ◽

Intensive Care ◽

Intensive Care Units ◽

Hospital Discharge ◽

Hospital Capacity ◽

Multivariable Logistic Regression ◽

Critical Care Patients ◽

Over Time

Abstract BackgroundThe early months of the COVID-19 pandemic were fraught with much uncertainty and some resource constraint. We assessed the change in survival to hospital discharge over time for intensive care unit patients with COVID-19 during the first three months of the pandemic and the presence of any surge effects on patient outcomes.MethodsRetrospective cohort study with electronic medical record data of all patients with laboratory-confirmed COVID-19 admitted to intensive care units from February 25, 2020 to May 15, 2020 admitted to intensive care units of 26 hospitals of an integrated delivery system in the Western United States. Patient demographic, comorbidity and severity of illness were measured along with exposure to pharmacologic and medical therapies and hospital outcomes over time. Multivariable logistic regression models were constructed to assess the change in survival to hospital discharge over time during the study period.ResultsOf 620 patients with COVID-19 admitted to the study ICUs (mean age 63.5 years (SD 15.7) and 69% male), 403 (65%) survived to hospital discharge and 217 (35%) died in hospital. Survival to hospital discharge increased over the study period from 60.0% in the first two weeks of patient admission to 67.6% in the last two weeks. In a multivariable logistic regression analysis, the risk-adjusted odds of survival to hospital discharge increased over time (bi-weekly change, adjusted odds ratio [aOR] 1.22, 95%CI 1.04-1.40, P = 0.02). Additionally, an a priori-defined explanatory model showed that after adjusting for both hospital occupancy and COVID positive/PUI percent hospital capacity, and the same set of covariates, the temporal trend in risk-adjusted patient survival to hospital discharge remained the same (bi-weekly change, aOR 1.18, 95% CI 1.00 to 1.38, P = 0.04) and a greater COVID positive/PUI percentage of hospital capacity remained significantly and inversely associated with survival to hospital discharge (aOR 0.95, 95% CI 0.92 to 0.98, P < 0.01).ConclusionsDuring the the early COVID-19 pandemic, risk-adjusted survival to hospital discharge increased over time for critical care patients. This may have been partially explained by surge affects, as measured by a greater COVID positive/PUI percentage of hospital capacity.

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Identifying Risk Factors for Pressure Injury in Adult Critical Care Patients

American Journal of Critical Care ◽

10.4037/ajcc2020243 ◽

2020 ◽

Vol 29 (3) ◽

pp. 204-213 ◽

Cited By ~ 2

Author(s):

Jill Cox ◽

Marilyn Schallom ◽

Christy Jung

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Critical Care ◽

Intensive Care ◽

Decision Tree ◽

Scale Score ◽

Critically Ill Patients ◽

Braden Scale ◽

Pressure Injury ◽

Critical Care Patients

Background Critically ill patients have a variety of unique risk factors for pressure injury. Identification of these risk factors is essential to prevent pressure injury in this population. Objective To identify factors predicting the development of pressure injury in critical care patients using a large data set from the PhysioNet MIMIC-III (Medical Information Mart for Intensive Care) clinical database. Methods Data for 1460 patients were extracted from the database. Variables that were significant in bivariate analyses were used in a final logistic regression model. A final set of significant variables from the logistic regression was used to develop a decision tree model. Results In regression analysis, cardiovascular disease, peripheral vascular disease, pneumonia or influenza, cardiovascular surgery, hemodialysis, norepinephrine administration, hypotension, septic shock, moderate to severe malnutrition, sex, age, and Braden Scale score on admission to the intensive care unit were all predictive of pressure injury. Decision tree analysis revealed that patients who received norepinephrine, were older than 65 years, had a length of stay of 10 days or less, and had a Braden Scale score of 15 or less had a 63.6% risk of pressure injury. Conclusion Determining pressure injury risk in critically ill patients is complex and challenging. One common pathophysiological factor is impaired tissue oxygenation and perfusion, which may be nonmodifiable. Improved risk quantification is needed and may be realized in the near future by leveraging the clinical information available in the electronic medical record through the power of predictive analytics.

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Predicting the Risk for Hospital-Acquired Pressure Ulcers in Critical Care Patients

Critical Care Nurse ◽

10.4037/ccn2017548 ◽

2017 ◽

Vol 37 (4) ◽

pp. e1-e11 ◽

Cited By ~ 11

Author(s):

Xiaohong Deng ◽

Ting Yu ◽

Ailing Hu

Keyword(s):

Logistic Regression ◽

Critical Care ◽

Intensive Care ◽

Decision Tree ◽

Pressure Ulcers ◽

Prediction Models ◽

Risk Prediction Models ◽

Braden Scale ◽

Hospital Acquired ◽

Critical Care Patients

BACKGROUND Assessments of risk for pressure ulcers in critical care patients may not include important predictors. OBJECTIVE To construct risk-prediction models of hospital-acquired pressure ulcers in intensive care patients and compare the models’ predictive validities with validity of the Braden Scale. METHODS Data were collected retrospectively on patients admitted to intensive care from October 2011 through October 2013. Logistic regression and decision trees were used to construct the risk-prediction models. Predictive validity was measured by using sensitivity, specificity, positive and negative predictive values, and area under the curve. RESULTS With logistic regression analysis, 6 factors were significant independent predictors. With the decision tree, 4 types of high-risk populations were identified. Predictive validity of Braden Scale scores was lower than the validities of the logistic regression and the decision tree models. CONCLUSION Risk for hospital-acquired pressure ulcers is overpredicted with the Braden Scale, with low specificity and low positive predictive value

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Comparison of laparoscopic and hand-assisted laparoscopic nephrectomy for inflammatory renal disease: which is the preferred approach?

Therapeutic Advances in Urology ◽

10.1177/1756287220984046 ◽

2021 ◽

Vol 13 ◽

pp. 175628722098404

Author(s):

Xudong Guo ◽

Hanbo Wang ◽

Yuzhu Xiang ◽

Xunbo Jin ◽

Shaobo Jiang

Keyword(s):

Logistic Regression ◽

Renal Disease ◽

Complication Rate ◽

Adverse Outcomes ◽

Laparoscopic Nephrectomy ◽

Multivariable Logistic Regression Analysis ◽

Invasive Approach ◽

Intraoperative Complication ◽

Multivariable Logistic Regression ◽

Significant Difference

Aims: Management of inflammatory renal disease (IRD) can still be technically challenging for laparoscopic procedures. The aim of the present study was to compare the safety and feasibility of laparoscopic and hand-assisted laparoscopic nephrectomy in patients with IRD. Patients and methods: We retrospectively analyzed the data of 107 patients who underwent laparoscopic nephrectomy (LN) and hand-assisted laparoscopic nephrectomy (HALN) for IRD from January 2008 to March 2020, including pyonephrosis, renal tuberculosis, hydronephrosis, and xanthogranulomatous pyelonephritis. Patient demographics, operative outcomes, and postoperative recovery and complications were compared between the LN and HALN groups. Multivariable logistic regression analysis was conducted to identify the independent predictors of adverse outcomes. Results: Fifty-five subjects in the LN group and 52 subjects in the HALN group were enrolled in this study. In the LN group, laparoscopic nephrectomy was successfully performed in 50 patients (90.9%), while four (7.3%) patients were converted to HALN and one (1.8%) case was converted to open procedure. In HALN group, operations were completed in 51 (98.1%) patients and conversion to open surgery was necessary in one patient (1.9%). The LN group had a shorter median incision length (5 cm versus 7 cm, p < 0.01) but a longer median operative duration (140 min versus 105 min, p < 0.01) than the HALN group. There was no significant difference in blood loss, intraoperative complication rate, postoperative complication rate, recovery of bowel function, and hospital stay between the two groups. Multivariable logistic regression revealed that severe perinephric adhesions was an independent predictor of adverse outcomes. Conclusion: Both LN and HALN appear to be safe and feasible for IRD. As a still minimally invasive approach, HALN provided an alternative to IRD or when conversion was needed in LN.

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Predictors of Anxiety-Induced Sleep Disturbance among in-School Adolescents in Ghana: Evidence from the 2012 Global School-Based Health Survey

Behavioral Sciences ◽

10.3390/bs11020020 ◽

2021 ◽

Vol 11 (2) ◽

pp. 20 ◽

Cited By ~ 1

Author(s):

Bright Opoku Ahinkorah ◽

Richard Gyan Aboagye ◽

Francis Arthur-Holmes ◽

Abdul-Aziz Seidu ◽

James Boadu Frimpong ◽

...

Keyword(s):

Logistic Regression ◽

Sleep Disturbance ◽

Emotional Disorders ◽

Health Survey ◽

Safety Concern ◽

Statistical Significance ◽

Outcome Variable ◽

Multivariable Logistic Regression Analysis ◽

School Based ◽

Multivariable Logistic Regression

(1) Background: Psychological problems of adolescents have become a global health and safety concern. Empirical evidence has shown that adolescents experience diverse mental health conditions (e.g., anxiety, depression, and emotional disorders). However, research on anxiety-induced sleep disturbance among in-school adolescents has received less attention, particularly in low- and middle-income countries. This study’s central focus was to examine factors associated with t anxiety-induced sleep disturbance among in-school adolescents in Ghana. (2) Methods: Analysis was performed using the 2012 Global School-based Health Survey (GSHS). A sample of 1342 in-school adolescents was included in the analysis. The outcome variable was anxiety-induced sleep disturbance reported during the past 12 months. Frequencies, percentages, chi-square, and multivariable logistic regression analyses were conducted. Results from the multivariable logistic regression analysis were presented as crude and adjusted odds ratios at 95% confidence intervals (CIs) and with a statistical significance declared at p < 0.05. (3) Results: Adolescents who went hungry were more likely to report anxiety-induced sleep disturbance compared to their counterparts who did not report hunger (aOR = 1.68, CI = 1.10, 2.57). The odds of anxiety-induced sleep disturbance were higher among adolescents who felt lonely compared to those that never felt lonely (aOR = 2.82, CI = 1.98, 4.01). Adolescents who had sustained injury were more likely to have anxiety-induced sleep disturbance (aOR = 1.49, CI = 1.03, 2.14) compared to those who had no injury. Compared to adolescents who never had suicidal ideations, those who reported experiencing suicidal ideations had higher odds of anxiety-induced sleep disturbance (aOR = 1.68, CI = 1.05, 2.71). (4) Conclusions: Anxiety-induced sleep disturbance among in-school adolescents were significantly influenced by the psychosocial determinants such as hunger, loneliness, injury, and suicidal ideation in this study. The findings can help design appropriate interventions through effective strategies (e.g., early school-based screening, cognitive-behavioral therapy, face-face counseling services) to reduce psychosocial problems among in-school adolescents in Ghana.

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Hyperoxia is associated with adverse outcomes in the cardiac intensive care unit: insights from the Medical Information Mart for Intensive Care (MIMI-III) database

European Heart Journal ◽

10.1093/ehjci/ehaa946.1837 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

A.Y Lui ◽

L Garber ◽

M Vincent ◽

L Celi ◽

J Masip ◽

...

Keyword(s):

Intensive Care Unit ◽

Logistic Regression ◽

Intensive Care ◽

Hospital Mortality ◽

Adverse Outcomes ◽

Rank Test ◽

Positive Pressure ◽

Cardiac Intensive Care Unit ◽

Multivariable Logistic Regression ◽

Cardiac Intensive Care

Abstract Background Hyperoxia produces reactive oxygen species, apoptosis, and vasoconstriction, and is associated with adverse outcomes in patients with heart failure and cardiac arrest. Our aim was to evaluate the association between hyperoxia and mortality in patients (pts) receiving positive pressure ventilation (PPV) in the cardiac intensive care unit (CICU). Methods Patients admitted to our medical center CICU who received any PPV (invasive or non-invasive) from 2001 through 2012 were included. Hyperoxia was defined as time-weighted mean of PaO2 >120mmHg and non-hyperoxia as PaO2 ≤120mmHg during CICU admission. Primary outcome was in-hospital mortality. Multivariable logistic regression was used to assess the association between hyperoxia and in-hospital mortality adjusted for age, female sex, Oxford Acute Severity of Illness Score, creatinine, lactate, pH, PaO2/FiO2 ratio, PCO2, PEEP, and estimated time spent on PEEP. Results Among 1493 patients, hyperoxia (median PaO2 147mmHg) during the CICU admission was observed in 702 (47.0%) pts. In-hospital mortality was 29.7% in the non-hyperoxia group and 33.9% in the hyperoxia group ((log rank test, p=0.0282, see figure). Using multivariable logistic regression, hyperoxia was independently associated with in-hospital mortality (OR 1.507, 95% CI 1.311–2.001, p=0.00508). Post-hoc analysis with PaO2 as a continuous variable was consistent with the primary analysis (OR 1.053 per 10mmHg increase in PaO2, 95% CI 1.024–1.082, p=0.0002). Conclusions In a large CICU cohort, hyperoxia was associated with increased mortality. Trials of titration of supplemental oxygen across the full spectrum of critically ill cardiac patients are warranted. Funding Acknowledgement Type of funding source: None

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Assessment of Hospital Rooming-in Practice in Abu Dhabi, United Arab Emirates: A Cross-Sectional Multi-Center Study

Nutrients ◽

10.3390/nu12082318 ◽

2020 ◽

Vol 12 (8) ◽

pp. 2318

Author(s):

Zainab Taha ◽

Ahmed Ali Hassan ◽

Ludmilla Wikkeling-Scott ◽

Ruba Eltoum ◽

Dimitrios Papandreou

Keyword(s):

Logistic Regression ◽

Hospital Stay ◽

United Arab Emirates ◽

Gestational Age ◽

World Health ◽

Abu Dhabi ◽

Multivariable Logistic Regression Analysis ◽

Original Research ◽

Convenience Sample ◽

Multivariable Logistic Regression

The World Health Organization (WHO) recommends rooming-in to reduce infant mortality rates. Little research has been done to assess practices such as rooming-in and its relation to breastfeeding in the United Arab Emirates (UAE). The aim of this study was to examine the prevalence of rooming-in during hospital stay among mothers with infants six months old and below, in addition to other associated factors in Abu Dhabi, UAE. This study utilized a sub-sample extracted from a dataset based on a convenience sample of mothers who were recruited from governmental maternal and child health centers as well as from the community. The purpose of the original research was to evaluate infant and young children’s feeding practices. A pre-tested questionnaire was used during interviews with mothers once ethical clearance was in place. Multivariable logistic regression was conducted to describe the results. The original sample included 1822 participants, of which 804 infants met the inclusion criteria. The mean age for mothers and infants was 30.3 years and 3.5 months, respectively. The rate of rooming-in during hospital stay was 97.5%. Multivariable logistic regression analysis indicated factors associated with not rooming-in were low maternal age (Adjusted Odds Ratios (AOR) = 1.15, 95% confidence interval (CI): 1.03, 1.30), low gestational age (GA) (AOR = 1.90, 95% CI: 1.52, 2.36), abnormal pre-pregnancy body mass index (BMI) (AOR = 3.77, 95 % CI: 1.22, 11.76), and delayed initiation of breastfeeding (AOR = 4.47, 95 % CI: 1.08, 18.48). In the context of the high rate of rooming-in revealed in this study, there should be a focus on those groups who do not room-in (i.e., younger women and those with babies of a younger gestational age). Rooming-in practice provides self-confidence in taking care of a baby, knowledge about breastfeeding, and stimulates early-phase lactation.

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Acute Chest Syndrome Among Hospitalized Children with Vaso-Occlusive Crisis: A Nationwide Study in the United States

Blood ◽

10.1182/blood.v130.suppl_1.687.687 ◽

2017 ◽

Vol 130 (Suppl_1) ◽

pp. 687-687

Author(s):

Takuto Takahashi ◽

Yusuke Okubo ◽

Atsuhiko Handa ◽

Scott T. Miller

Keyword(s):

Logistic Regression ◽

De Novo ◽

Pharmaceutical Research ◽

The United States ◽

Acute Chest Syndrome ◽

Multivariable Logistic Regression Analysis ◽

Hospitalization Rates ◽

Multivariable Logistic Regression ◽

Prophylactic Measures ◽

Inpatient Database

Abstract Background: Acute chest syndrome (ACS) remains a leading cause of mortality among children with sickle cell disease (SCD); overall, nearly 50% of ACS is diagnosed during hospitalizations for other complications including painful vaso-occlusive crises (VOC). Methods: The present study assesses epidemiological features of children hospitalized with VOC and evaluates factors potentially associated with development of ACS utilizing the large national all-payer Kid's Inpatient Database over a recent 9 year period. Records of children (age < 20 years) were reviewed from 2003, 2006, 2009, and 2012) and multivariable logistic regression was used to assess risk factors and adjust for patient and hospital characteristics. Results: Total annual hospitalization rates with VOC were variable, ranging from 26.4 per 100,000 children in 2009 to 29.5 in 2012. Multivariable logistic regression analysis showed children age 5-9 years had 2.38 times higher odds of developing ACS than children age 15-19 (95%CI, 2.22 to 2.56). Comorbidity of asthma was a risk factor for ACS (OR, 1.44; 95%CI, 1.36 to 1.53). ACS was as common in Hb SC patients hospitalized for VOC as those with SS. Conclusion: These data demonstrate that despite increasing use of hydroxyurea in children shown in other reports, there has been no reduction in hospitalization rate for pain, and even young children are at risk for ACS. Though de novo ACS is less common in Hb SC, vigilance and prophylactic measures are required for those hospitalized for pain. Further studies are needed to assess the efficacy of prophylactic interventions including bronchodilator therapy for asthmatics hospitalized for VOC. Disclosures Miller: Pfizer Pharmaceutical: Research Funding.

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Family Behaviors as Unchanging Obstacles in End-of-Life Care: 16-Year Comparative Data

American Journal of Critical Care ◽

10.4037/ajcc2020661 ◽

2020 ◽

Vol 29 (4) ◽

pp. e81-e91

Author(s):

Renea L. Beckstrand ◽

Jasmine B. Jenkins ◽

Karlen E. Luthy ◽

Janelle L. B. Macintosh

Keyword(s):

Intensive Care Unit ◽

Critical Care ◽

Intensive Care ◽

End Of Life ◽

Health Care Providers ◽

End Of Life Care ◽

Critical Care Nurses ◽

Life Care ◽

Care Providers ◽

Over Time

Background Critical care nurses routinely care for dying patients. Research on obstacles in providing end-of-life care has been conducted for more than 20 years, but change in such obstacles over time has not been examined. Objective To determine whether the magnitude scores of obstacles and helpful behaviors regarding end-of-life care have changed over time. Methods In this cross-sectional survey study, questionnaires were sent to 2000 randomly selected members of the American Association of Critical-Care Nurses. Obstacle and helpful behavior items were analyzed using mean magnitude scores. Current data were compared with data gathered in 1999. Results Of the 2000 questionnaires mailed, 509 usable responses were received. Six obstacle magnitude scores increased significantly over time, of which 4 were related to family issues (not accepting the poor prognosis, intrafamily fighting, overriding the patient’s end-of-life wishes, and not understanding the meaning of the term lifesaving measures). Two were related to nurse issues. Seven obstacles decreased in magnitude, including poor design of units, overly restrictive visiting hours, and physicians avoiding conversations with families. Four helpful behavior magnitude scores increased significantly over time, including physician agreement on patient care and family access to the patient. Three helpful behavior items decreased in magnitude, including intensive care unit design. Conclusions The same end-of-life care obstacles that were reported in 1999 are still present. Obstacles related to family behaviors increased significantly, whereas obstacles related to intensive care unit environment or physician behaviors decreased significantly. These results indicate a need for better end-of-life education for families and health care providers.

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