Insulin-like growth factor-1 and delirium in critically ill mechanically ventilated patients: a preliminary investigation

ABSTRACTBackground: Delirium occurs frequently in the intensive care unit (ICU), but its pathophysiology is still unclear. Low levels of insulin-like growth factor 1 (IGF-1), a hormone with neuroprotective properties, have been associated with delirium in some non-ICU studies, but this relationship has not been examined in the ICU. We sought to test the hypothesis that low IGF-1 concentrations are associated with delirium during critical illness.Methods: Mechanically ventilated medical ICU patients were prospectively enrolled, and blood was collected after enrollment for measurement of IGF-1 using radioimmunometric assay. Delirium and coma were identified daily using the Confusion Assessment Method for the ICU and the Richmond Agitation-Sedation Scale, respectively. The association between IGF-1 and delirium was evaluated with logistic regression. In addition, the association between IGF-1 and duration of normal mental state, measured as days alive without delirium or coma, was assessed using multiple linear regression.Results: Among 110 patients, the median age was 65 years (IQR, 52–75) and APACHE II was 27 (IQR, 22 –32). IGF-1 levels were not a risk factor for delirium on the day after IGF-1 measurement (p = 0.97), at which time 65% of the assessable patients were delirious. No significant association was found between IGF-1 levels and duration of normal mental state (p = 0.23).Conclusions: This pilot study, the first to investigate IGF-1 and delirium in critically ill patients, found no association between IGF-1 and delirium. Future studies including serial measurements of IGF-1 and IGF-1 binding proteins are needed to determine whether this hormone has a role in delirium during critical illness.

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Advanced Age Is Associated With Catatonia in Critical Illness: Results From the Delirium and Catatonia Prospective Cohort Investigation

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.673166 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jennifer Connell ◽

Ahra Kim ◽

Nathan E. Brummel ◽

Mayur B. Patel ◽

Simon N. Vandekar ◽

...

Keyword(s):

Intensive Care ◽

Critical Illness ◽

Critically Ill ◽

Rating Scale ◽

Medical Center ◽

Adult Population ◽

Academic Medical Center ◽

Confusion Assessment Method ◽

Assessment Method ◽

Advanced Age

Introduction: Catatonia, characterized by motor, behavioral and affective abnormalities, frequently co-occurs with delirium during critical illness. Advanced age is a known risk factor for development of delirium. However, the association between age and catatonia has not been described. We aim to describe the occurrence of catatonia, delirium, and coma by age group in a critically ill, adult population.Design: Convenience cohort, nested within two clinical trials and two observational cohort studies.Setting: Intensive care units in an academic medical center in Nashville, TN.Patients: 378 critically ill adult patients on mechanical ventilation and/or vasopressors.Measurements and Main Results: Patients were assessed for catatonia, delirium, and coma by independent and blinded personnel, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit (ICU) and the Richmond Agitation and Sedation Scale. Of 378 patients, 23% met diagnostic criteria for catatonia, 66% experienced delirium, and 52% experienced coma during the period of observation. There was no relationship found between age and catatonia severity or age and presence of specific catatonia items. The prevalence of catatonia was strongly associated with age in the setting of critical illness (p < 0.05). Delirium and comas' association with age was limited to the setting of catatonia.Conclusion: Given the significant relationship between age and catatonia independent of coma and delirium status, these data demonstrate catatonia's association with advanced age in the setting of critical illness. Future studies can explore the causative factors for this association and further elucidate the risk factors for acute brain dysfunction across the age spectrum.

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Insulin-like growth factor 1 and delirium

International Psychogeriatrics ◽

10.1017/s1041610212000464 ◽

2012 ◽

Vol 24 (11) ◽

pp. 1872-1872 ◽

Cited By ~ 2

Author(s):

Catherine Motosko ◽

Kristine Brown ◽

Madan Kwatra

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Growth Factor ◽

Preliminary Investigation ◽

Serum Levels ◽

Insulin Like Growth Factor ◽

Icu Patients ◽

Mechanically Ventilated ◽

Mechanically Ventilated Patients ◽

Ventilated Patients

The paper by Morandi et al. (2011), entitled “Insulin-like growth factor-1 and delirium in critically ill mechanically ventilated patients: a preliminary investigation,” is of great interest due to its lack of finding a correlation between serum levels of insulin-like growth factor-1 (IFG-1) and delirium in intensive care unit (ICU) patients.

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ICU delirium burden predicts functional neurologic outcomes

PLoS ONE ◽

10.1371/journal.pone.0259840 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0259840

Author(s):

Luis Paixao ◽

Haoqi Sun ◽

Jacob Hogan ◽

Katie Hartnack ◽

Mike Westmeijer ◽

...

Keyword(s):

Critical Illness ◽

Confusion Assessment Method ◽

Assessment Method ◽

Neurologic Outcome ◽

Post Discharge ◽

Mechanically Ventilated ◽

Neurological Outcomes ◽

Survival Status ◽

Neurologic Outcomes ◽

Icu Delirium

Background We investigated the effect of delirium burden in mechanically ventilated patients, beginning in the ICU and continuing throughout hospitalization, on functional neurologic outcomes up to 2.5 years following critical illness. Methods Prospective cohort study of enrolling 178 consecutive mechanically ventilated adult medical and surgical ICU patients between October 2013 and May 2016. Altogether, patients were assessed daily for delirium 2941days using the Confusion Assessment Method for the ICU (CAM-ICU). Hospitalization delirium burden (DB) was quantified as number of hospital days with delirium divided by total days at risk. Survival status up to 2.5 years and neurologic outcomes using the Glasgow Outcome Scale were recorded at discharge 3, 6, and 12 months post-discharge. Results Of 178 patients, 19 (10.7%) were excluded from outcome analyses due to persistent coma. Among the remaining 159, 123 (77.4%) experienced delirium. DB was independently associated with >4-fold increased mortality at 2.5 years following ICU admission (adjusted hazard ratio [aHR], 4.77; 95% CI, 2.10–10.83; P < .001), and worse neurologic outcome at discharge (adjusted odds ratio [aOR], 0.02; 0.01–0.09; P < .001), 3 (aOR, 0.11; 0.04–0.31; P < .001), 6 (aOR, 0.10; 0.04–0.29; P < .001), and 12 months (aOR, 0.19; 0.07–0.52; P = .001). DB in the ICU alone was not associated with mortality (HR, 1.79; 0.93–3.44; P = .082) and predicted neurologic outcome less strongly than entire hospital stay DB. Similarly, the number of delirium days in the ICU and for whole hospitalization were not associated with mortality (HR, 1.00; 0.93–1.08; P = .917 and HR, 0.98; 0.94–1.03, P = .535) nor with neurological outcomes, except for the association between ICU delirium days and neurological outcome at discharge (OR, 0.90; 0.81–0.99, P = .038). Conclusions Delirium burden throughout hospitalization independently predicts long term neurologic outcomes and death up to 2.5 years after critical illness, and is more predictive than delirium burden in the ICU alone and number of delirium days.

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Serum melatonin concentration in critically ill patients randomized to sedation or non-sedation

Annals of Intensive Care ◽

10.1186/s13613-021-00829-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jakob Oxlund ◽

Torben Knudsen ◽

Thomas Strøm ◽

Jørgen T. Lauridsen ◽

Poul J. Jennum ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Critically Ill ◽

Critically Ill Patients ◽

Confusion Assessment Method ◽

Assessment Method ◽

Secondary Outcome ◽

Melatonin Level ◽

Melatonin Concentration ◽

Mechanically Ventilated

Abstract Background Abolished circadian rhythm is associated with altered cognitive function, delirium, and as a result increased mortality in critically ill patients, especially in those who are mechanically ventilated. The causes are multifactorial, of which changes in circadian rhythmicity may play a role. Melatonin plays a crucial role as part of the circadian and sleep/wake cycle. Whether sedation effects circadian regulation is unknown. Hence, the objective of this study was to evaluate the melatonin concentration in critically ill patients randomized to sedation or non-sedation and to investigate the correlation with delirium. Methods All patients were included and randomized at the intensive care unit at the hospital of southwest Jutland, Denmark. Seventy-nine patients completed the study (41 sedated and 38 non-sedated). S-melatonin was measured 3 times per day, (03.00, 14.00, and 22.00), for 4 consecutive days in total, starting on the second day upon randomization/intubation. The study was conducted as a sub-study to the NON-SEDA study in which one hundred consecutive patients were randomized to sedation or non-sedation with a daily wake-up call (50 in each arm). Primary outcome: melatonin concentration in sedated vs. non-sedated patients (analyzed using linear regression). Secondary outcome: risk of developing delirium or non-medically induced (NMI) coma in sedated vs. non-sedated patients, assessed by CAM-ICU (Confusion Assessment Method for the Intensive Care Unit) analyzed using logistic regression. Results Melatonin concentration was suppressed in sedated patients compared to the non-sedated. All patients experienced an elevated peak melatonin level early on in the course of their critical illness (p = 0.01). The risk of delirium or coma (NMI) was significantly lower in the non-sedated group (OR 0.42 CI 0.27; 0.66 p < 0.0001). No significant relationship between delirium development and suppressed melatonin concentration was established in this study (OR 1.004 p = 0.29 95% CI 0.997; 1.010). Conclusion Melatonin concentration was suppressed in sedated, critically ill patients, when compared to non-sedated controls and the frequency of delirium was elevated in sedated patients. Trail registration Clinicaltrials.gov (NCT01967680) on October 23, 2013.

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A Systematic Review and Pooled Prevalence of Paediatric Delirium in Critically Ill Children

International Journal of Pharmacy Practice ◽

10.1093/ijpp/riab015.038 ◽

2021 ◽

Vol 29 (Supplement_1) ◽

pp. i31-i32

Author(s):

D Semple ◽

M M Howlett ◽

J D Strawbridge ◽

C V Breatnach ◽

J C Hayden

Keyword(s):

Risk Factors ◽

Critical Care ◽

Critically Ill ◽

Observational Studies ◽

Confusion Assessment Method ◽

Assessment Method ◽

Assessment Tools ◽

Critically Ill Children ◽

Confusion Assessment ◽

Pooled Prevalence

Abstract Introduction Paediatric Delirium (PD) is a neuropsychiatric complication that occurs during the management of children in the critical care environment (Paediatric Intensive Care (PICU) and Neonatal Intensive Care (NICU). Delirium can be classified as hypoactive (decreased responsiveness and withdrawal), hyperactive (agitation and restlessness), and mixed (combined) (1). PD can be assessed using a number of assessment tools. PD has been historically underdiagnosed or misdiagnosed, having many overlapping symptoms with other syndrome such as pain and iatrogenic withdrawal syndrome (2). An appreciation of the extent of PD would help clinicians and policy makers drive interventions to improve recognition, prevention and management of PD in clinical practice. Aim To estimate the pooled prevalence of PD using validated assessment tools, and to identify risk factors including patient-related, critical-care related and pharmacological factors. Methods A systematic search of PubMed, EMBASE and CINAHL databases was undertaken. Eligible articles included observational studies or trials that estimated a prevalence of PD in a NICU/PICU population using a validated PD assessment tool. Validated tools are the paediatric Confusion Assessment Method-ICU (pCAM-ICU), the Cornell Assessment of Pediatric Delirium (CAPD), the PreSchool Confusion Assessment Method for the ICU (psCAM-ICU), pCAM-ICU severity scale (sspCAM-ICU), and the Sophia Observation Withdrawal Symptoms scale Paediatric Delirium scale (SOS-PD) (1). Only full text studies were included. No language restrictions were applied. Two reviewers independently screened records. Data was extracted using a pre-piloted form and independently verified by another reviewer. Quality was assessed using tools from the National Institutes of Health. A pooled prevalence was calculated from the studies that estimated PD prevalence using the most commonly applied tool, the CAPD (1). Results Data from 23 observational studies describing prevalence and risk factors for PD in critically ill children were included (Figure 1). Variability in study design and outcome reporting was found. Study quality was generally good. Using the validated tools prevalence ranged from 10–66% of patients. Hypoactive delirium was the most prevalent sub-class identified. Using the 13 studies that used the CAPD tool, a pooled prevalence of 35% (27%-43% 95%CI) was calculated. Younger ages, particularly less than two years old, sicker patients, particularly those undergoing mechanical and respiratory ventilatory support were more at risk for PD. Restraints, the number of sedative medications, including the cumulative use of benzodiazepines and opioids were identified as risk factors for the development of PD. PD was associated with longer durations of mechanical ventilation, longer stays and increased costs. Data on association with increased mortality risk is limited and conflicting. Conclusion PD affects one third of critical care admissions and is resource intense. Routine assessment in clinical practice may facilitate earlier detection and management strategies. Modifiable risk factors such as the class and number of sedative and analgesic medications used may contribute to the development of PD. Early mobility and lessening use of these medications present strategies to prevent PD occurrence. Longitudinal prospective multi-institutional studies to further investigate the presentations of the different delirium subtypes and modifiable risk factors that potentially contribute to the development of PD, are required. References 1. Semple D (2020) A systematic review and pooled prevalence of PD, including identification of the risk factors for the development of delirium in critically ill children. doi: 10.17605/OSF.IO/5KFZ8 2. Ista E, te Beest H, van Rosmalen J, de Hoog M, Tibboel D, van Beusekom B, et al. Sophia Observation withdrawal Symptoms-Paediatric Delirium scale: A tool for early screening of delirium in the PICU. Australian Critical Care. 2018;31(5):266–73

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Assessment of delirium in children admitted into the Intensive Care Unit: psCAM-ICU Tool

Avances en Enfermería ◽

10.15446/av.enferm.v38n2.78690 ◽

2020 ◽

Vol 38 (2) ◽

pp. 140-148

Author(s):

Ángela María Henao Castaño ◽

Edwar Yamith Pinzon Casas

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Critically Ill ◽

Pediatric Intensive Care ◽

Confusion Assessment Method ◽

Assessment Method ◽

Primary Diagnosis ◽

Critically Ill Children ◽

Associated Risk Factors ◽

Prolonged Hospital

Background: Delirium has been identified as a risk factor for the mortality of critically ill patients, generating great social and economic impacts, since patients require more days of mechanical ventilation and a prolonged hospital stay in the intensive care unit (ICU), thus increasing medical costs. Objective: To describe the prevalence and characteristics of delirium episodes in a sample of 6-month to 5-year-old children who are critically ill. Methods: Cohort study at a Pediatric Intensive Care Unit (PICU) in Bogotá (Colombia). Participants were assessed by the Preschool Confusion Assessment Method for the ICU (psCAM-ICU) within the first twenty-four hours of hospitalization. Results: One quarter of the participants (25.8%) presented some type of delirium. Among them, two sub-types of delirium were observed: 62.5% of the cases were hypoactive and 37.5% hyperactive. Moreover, from them, six were male (75%) and 2 female (25%). Primary diagnosis was respiratory tract infection in 62.55% of the patients, while respiratory failure was diagnosed in the remaining 37.5%. Conclusions: The implementation of delirium monitoring tools in critically ill children provides a better understanding of the clinical manifestation of this phenomenon and associated risk factors in order to contribute to the design of efficient intervention strategies.

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