Risk factors associated with the development of delirium in general ICU patients. A prospective observational study.

OBJECTIVE: We aimed to analyze risk factors related to the development of delirium, aiming for early intervention in patients with greater risk.
MATERIAL AND METHODS: Observational study, including prospectively collected patients treated in a single general ICU. These were classified into two groups, according to whether they developed delirium or not (screening performed using CAM-ICU tool). Demographics and clinical data were analyzed. Multivariate logistic regression analyses were performed to quantify existing associations.
RESULTS: 1462 patients were included. 93 developed delirium (incidence: 6.3%). These were older, scored higher on the Clinical Frailty Scale, on the risk scores on admission (SAPS-3 and SOFA), and had a greater number of organ failures (OF). We observed more incidence of delirium in patients who (a) presented more than two OF (20.4%; OR 4.9; CI95%: 2.9-8.2), and (b) were more than 74 years old albeit having <2 OF (8.6%; OR 2.1; CI95%: 1.3-3.5). Patients who developed delirium had longer ICU and hospital length-of-stays and a higher rate of readmission.
CONCLUSIONS: The highest risk observed for developing delirium clustered in patients who presented more than 2 OF and patients over 74 years old. The detection of patients at high risk for developing delirium could imply a change in management and improved quality of care.

Introduction

Delirium is a severe neuropsychiatric disorder of organic origin characterized by the appearance of alterations in both consciousness and cognitive functions [1]. The development of delirium is associated with multiple complications: increased mortality [2], longer duration of mechanical ventilation, higher reintubation rate, and increased hospital stay [3-5]. Unfortunately, despite the increasing number of delirium publications in recent years, it remains an underdiagnosed and somewhat underestimated problem [6].

Effective treatment of delirium has proven troublesome. Therefore, prophylactic strategies become paramount. In addition, knowing the different risk factors and the degree of their association with the development of delirium can help identify patients at high risk. In this regard, some of the risk factors identified in previously published studies [7-9] (which are in line with the experience in our center) include: advanced age, personal history of previous high blood pressure or cognitive impairment, urgent surgery, or trauma before admission to the Intensive Care Unit (ICU), high APACHE II score (Acute Physiology and Chronic Health Evaluation) upon admission, and need for mechanical ventilation. Moreover, knowledge of the risk factors associated with delirium development and their implication in the patient’s prognosis (both short and long-term) may imply a change in our daily practice [8, 10–13].

The detection of these high-risk patients could reinforce preventive measures. However, it remains to be defined which interventions are the most effective. Clinical guidelines [8] have recommended using a bundle approach (e.g., ABCDEF bundle) to target eliminating multiple modifiable risk factors of ICU, reducing the chances of suffering delirium, or shortening its duration once established. Bundle interventions have been proposed to be more effective than any single-component strategy, but studies are still inconsistent and present contradictory data [14, 15].

Moreover, no pharmacological agent has demonstrated efficacy in treating or preventing delirium. Therefore, the current guidelines [8] suggest against routine use of dexmedetomidine [16, 17], statins [18] or ketamine [19] to prevent delirium. Thus, there is still much to be done and much to be researched to tackle delirium and its consequences. Meanwhile, as healthcare professionals dedicated to critical patient care, we are responsible for identifying and treating the effects of critical illness on patients, both inside and outside the ICU.

Our hypothesis implies the association between the presence of delirium during ICU admission and a worse immediate prognosis. Therefore, our study’s primary goal is to ana lyze the differences between patients who develop delirium and patients who do not develop delirium during ICU admission. Secondarily, we aim to study their characteristics to detect risk factors associated with delirium’s appearance during ICU admission and its impact on the patient’s early prognosis in our population.

Materials and methods

We conducted an observational study including prospectively collected data of a cohort of patients admitted to a general ICU from October 1, 2016, up to -and including- May 1, 2019. Our general ICU is in a second-level hospital, including all types of medical patients and 24-hour coverage by general surgeons, urology, orthopedic surgery, and gynecology/obstetrics, excluding cardiothoracic and neurosurgical patients.

Data were collected prospectively in the Registry of the Intensive Care Unit of the University Hospital of Henares. The research was approved by the Francisco de Vitoria University’s Healthcare Ethics Committee (44/2018). Participation and acceptance of inclusion of patient’s data into the Registry were obtained by signing the informed consent document (by the patient or by an authorized surrogate in case the patient was unable to express their opinion). The study includes all patients admitted during the mentioned period who agreed to participate in the Registry. Exclusion criteria were patients under 18 years old and patients who required transfer to another hospital (given the impossibility of correct data collection and follow-up upon discharge from the ICU).

We collected relevant demographic and clinical data in every patient, including sex, age, Clinical Frailty Scale (CFS) [20-22], admission type, reason for admission, comorbidities (cardiovascular, respiratory, renal, hepatic, cancer disease, endocrine), specific measures of critical patient management (mechanical ventilation, continuous extrarenal clearance technique, isolation, continuous neuromuscular blockade (NMB), prone) and development of organ failure(s) (OF) during ICU admission. We used the Simplified Acute Physiology Score (SAPS-3) and SOFA score (Sequential Organ Failure Assessment) on admission as validated scores for severity of illness [23, 24]. Organ failure was defined by SOFA score above two as individual scores for each organ, determining progression of organ dysfunction. In addition, invasive mechanical ventilation duration was calculated by adding up the time (in days) of all consecutive invasive ventilation episodes during the same ICU admission and rounded to the nearest whole day. The team of physicians routinely collects CFS, SAPS-3, and SOFA scores.

Patients were then classified into two groups, according to whether they developed delirium during ICU stay. Delirium screening using the CAM-ICU (Confusion Assessment Method for the Intensive Care Unit [25]) was performed by our nursing staff every eight hours (once every shift), and, in case of doubt, it was discussed with the attending physician. This delirium assessment instrument is highly reliable in the hands of health care providers. It comprises four features assessing: acute change or fluctuation in mental status, inattention, disorganized thinking, or an altered level of consciousness. To be diagnosed with delirium, the patient needed to have a RASS (Richmond Agitation Sedation Scale, [26]) score above -3, a positive CAM-ICU (defined as an acute change or fluctuation in mental status, accompanied by inattention, and either disorganized thinking or an altered level of consciousness) [27-29].

Our standard of care implies applying a protocol for the prevention, diagnosis, and early treatment of delirium based on the ABCDEF bundle on all patients [30]. Thus, our first objective is to optimize prevention measures by assessing analgesia, sedation, and care, trying to maintain multimodal analgesia with the lowest possible opioid dose, maintaining the lowest possible sedation except where deep sedation is necessary, and promoting early mobilization, optimizing the environment, and promoting the family’ presence.

Statistical analysis

Discrete variables were expressed as a number and percentage, while continuous variables are expressed as medians (with interquartile range). Variables were explored to evaluate their normal distribution using the Kolmogorov-Smirnov test. Firstly, Pearson’s or Chi-square test (alternatively Fisher’s exact test for expected values<5) or Mann-Whitney’s U were used to perform the exploratory analyses to find significant differences. Variables with a p-value under 0,05 were taken as statistically significant. Finally, odds ratios (OR) with 95% confidence interval (CI) were used when comparing characteristics between patients who had developed delirium and delirium-free patients during ICU stay.

Secondly, we performed a univariate analysis of delirium incidence. Thirdly, a multivariate logistic regression analysis was carried out to quantify the existing associations. The multivariate analysis included all variables that proved significant associations with a p-value under 0.10 in the univariate analysis, considering an alpha error of 5%. Lastly, we performed a recursive partitioning test employing a CHAID (Chi-square Automatic Interaction Detection) classification tree. Statistical analyses were performed using the SPSS software package version 20.0 for Windows.

Results

During the study period, 1534 patients were admitted to our ICU. Seventy-two patients were excluded from the statistical analysis (due to loss of data related to hospital transfer), obtaining a cohort of 1462 adult patients. The demographic and clinical characteristics of the n = 1462 patients (already divided into two groups) are summarised in Table 1.

Table 1

Demographics and clinical characteristics of the studied population.

		Delirium	No delirium	p
Number of patients, n (%)		93 (6)	1369 (94)	-
Age, yr, median (IQR)		71 (60–81)	66 (55–74)	< 0,001
Sex, n (%)	Male	58 (62,3)	790 (57,7)	0,38
	Female	35 (37,6)	579 (42,3)
Clinical Frailty Scale, median (IQR)		3 (3–4)	3 (2–3)	< 0,001
Admission type, n (%)	Emergency surgery	14 (15)	196 (14,3)	0,035
	Scheduled surgery	18 (19,4)	437 (31,9)
	Medical patient	61 (65,5)	736 (53,8)
Main diagnosis on admission, n (%)	Acute respiratory failure	22 (14)	148 (10,8)	< 0,001
	Postoperative	25 (26,9)	553 (40,4)
	Sepsis	19 (20,4)	150 (11)
	Acute coronary syndrome	5 (5,4)	202 (14,8)
	Coma	9 (9,7)	42 (3,1)
	Cardiac arrest	4 (18,3)	19 (1,4)
	Other	9 (9,7)	254 (18,6)
Comorbidities, n (%)	Cardiovascular	59 (63,4)	720 (52,3)	0,04
	Respiratory	27 (29)	328 (24)	0,27
	Renal	50 (53,4)	334 (24,4)	<0,001
	Hepatic	15 (16,1)	220 (16,1)	0,99
	Cancer disease	26 (28)	489 (35,7)	0,13
	Endocrine	45 (48,4)	39 (2,8)	0,086
SAPS 3 score, median (IQR)		59 (49–66)	45 (38–55)	<0,001
SOFA score, median (IQR)		5 (2–8)	1 (0–4)	<0,001
Organ-supportive treatments	Invasive MV, n (%)	58 (62,4)	351 (25,6)	<0,001
	Days under invasive MV, days (IQR)	6,5 (3–15)	2 (1–5)	<0,001
	Reintubation, n (%)	5 (5,4)	13 (9,5)	<0,001
	Non-invasive MV, n (%)	10 (10,7)	88 (6,4)	0,11
	CRRT, n (%)	5 (5,4)	64 (4,7)	0,76
Isolation	Preventive isolation on suspicion of MDR, n (%)	27 (29)	199 (14,4)	<0,001
	Confirmed isolation due to positive MDR, n (%)	14 (15)	58 (4,2)	<0,001
Need of prone position, n (%)		4 (4,3)	8 (0,6)	0,005
Neuromuscular blockade, n %)		6 (6,5)	5 (0,4)	<0,00
Organ failure, n (%)	Cardiovascular	70 (75,3)	424 (31)	<0,001
	Respiratory	63 (67,7)	475 (34,7)	<0,001
	Renal	50 (53,8)	334 (24,4)	<0,001
	Hepatic	13 (14)	68 (5)	<0,001
	Hematologic	13 (14)	102 (7,5)	0,02
Number of organ failure/s, median (IQR)		3 (2–4)	0 (0–2)	<0,001

Yr = years; IQR = interquartile range; MV = mechanical ventilation; CRRT = continuous renal replacement therapy; MDR = multidrug-resistant bacteria.

Dashes indicate no data.

Ninety-three patients developed delirium (incidence of 6.3%). Patients who developed delirium during ICU stay were older (p<0.001) and had a higher score in the CFS. In this group, reasons for ICU admission included pre-ICU emergency surgery or a medical admission (acute respiratory failure, sepsis, coma, or cardiac arrest). SAPS-3 (59 vs. 45, p<0.01) and SOFA score (5 vs. 1, p<0.001) on admission were higher in the delirium group. Patients with delirium also presented a higher incidence of cardiovascular (p 0.04) and renal comorbidities (p<0.001). Moreover, they required invasive mechanical ventilation in a higher percentage of the cases, plus they presented longer invasive mechanical ventilation duration (6.5 vs. two days, p<0.001). Regarding the development of organ failure(s), patients who developed delirium had a higher incidence of cardiovascular, respiratory, renal, hepatic, and hematological failures. Likewise, they required higher preventive (29% vs 14%, p<0.01) and confirmed (15% vs. 4%, p<0.01) isolation due to multidrug-resistant bacteria (MDR).

When studying outcomes (early prognosis, Table 2), patients who developed delirium presented longer ICU length-of-stay (7 vs. 2, p<0.001) and longer hospital stay once discharged from ICU (10 vs. 6, p<0.001). Furthermore, they presented an increased unplanned ICU readmission rate (7% vs. 3%, p<0.014). However, we did not find differences in mortality (upon ICU and ward discharge).

Table 2

Short-term outcomes.

	Delirium	No delirium	p
LOS ICU, days, median (IQR)	7 (3–15)	2 (1–4)	<0,001
LOS hospital after ICU discharge, days, median (IQR)	10 (5–18)	6 (3–11)	< 0,001
Unplanned readmission to ICU, n (%)	7 (7%)	40 (3%)	0,014
Mortality upon ICU discharge, n (%)	0 (0%)	47 (3,4)	0,07
Mortality upon hospital discharge, n (%)	5 (5,4)	39 (2,85)	0,72

LOS = length of stay; IQR = interquartile range; ICU = intensive care unit.

We initially performed a univariate analysis with all statistically significant variables: age above 74, Clinical Frailty Scale above 3, specific reason for admission (acute respiratory failure, sepsis, coma, cardiac arrest, urgent surgery), comorbidities (cardiovascular and renal), SAPS-3 score above 56, SOFA score on admission above 4, invasive mechanical ventilation, reintubation rate, preventive and confirmed isolation due to MDR, prone position, NMB, organ failures (respiratory, cardiovascular, renal, hepatic and hematological) and the number of failed organs above 2 (S1 Table).

In the multivariate analysis (Table 3), the use of neuromuscular blockade (OR 7.2, 95% CI 1.99–26.27) and the number of failed organs above 2 (OR 4.9, 95% CI 2.9–8.2) were the strongest independent predictors of transitioning to delirium. We also observed high odds ratio for age above 74 (OR 2.1; 95% CI 1.3–4.5), coma as the reason for ICU admission (OR 2.5, 95% CI 1.1–5.8), need for invasive mechanical ventilation (OR 1.92, 95% CI 1.1–3.3) and confirmed isolation due to MDR (OR 2.4, 95% CI 1.2–4.8). Finally, we should clarify that most patients presented a toxic/metabolic/respiratory origin coma, and few were secondary to primary neurological problems.

Table 3

Multivariate analysis.

VARIABLE	OR (95% IC)
Age above 74 yrs	2,1 (1,3–3,5)
Coma on ICU admission	2,5 (1,07–5,8)
> 2 organ failures	4,9 (2,9–8,2)
Invasive MV	1,9 (1,1–3,3)
Confirmed isolation due to MDR	2,4 (1,2–4,6)
Neuromuscular blockade	7,2 (2–26,3)

Yrs = years; ICU = intensive care unit; MV = mechanical ventilation; MDR = multidrug-resistant bacteria.

Regarding the recursive partitions test using a CHAID classification tree, we observed a higher incidence of delirium in patients who presented more than two OF (20.4%) and patients with less than two OF, a higher incidence over 74 years of age (8.6%).

Discussion

In this study, trying to find risk factors associated with delirium development, we found that the highest risk observed for developing delirium clustered in patients who presented more than two OF and patients over 74 years old. Furthermore, in our cohort, patients who developed delirium showed a longer ICU length of stay, a longer length of hospitalization after discharge from ICU, and an increased ICU readmission rate (7%), with no differences in mortality.

Considering the results we obtained in the multivariate analysis, patients in coma on admission to the ICU, patients who required invasive mechanical ventilation or continuous NMB, and patients who needed isolation due to an identified MDR were also at high risk of developing delirium. When compared with risk factors assessed in published studies [7-9], we highlight the lack of information regarding the relationship between the development of delirium and the use of NMB and between the development of delirium and contact isolation required after confirmation of the presence of MDR. The risk of delirium development observed in patients requiring NMB may be linked with the concurrent use of deep sedation. Still, one could raise a question: is one pharmacological group of NMBs more associated with delirium than another? On the other hand, the presence of MDR implies specific contact measures, making the family visit and contact with the patient more difficult, in addition to the need for broad-spectrum antibiotics, which could also play a role in the development of delirium.

Knowledge of the risk factors associated with delirium development among critical patients is essential for optimal patient management. In essence, it provides insight into a complex syndrome, facilitates the detection of high-risk patients, and allows us to improve prevention programs. One of the first attempts to identify those variables associated with an increased risk of delirium in critically ill patients [7] recognized the following with a strong level of evidence: trauma or emergency surgery before ICU admission, APACHE II score, coma, delirium on the previous day, use of mechanical ventilation and metabolic acidosis; multiorgan failure had moderate evidence (OR varying from 1.09 to 8.8). Regarding current guidelines [8], Devlin et al. found strong evidence for age, dementia or prior coma, pre-ICU emergency surgery or trauma, sex opioid use, mechanical ventilation, benzodiazepine use, and blood transfusion; while moderate evidence was found for a history of hypertension, admission due to neurologic disease, trauma and use of psychoactive medication. Whilst the APACHE score presented a strong association with delirium development, the SOFA score was inconclusive. Our study observed a statistically significant difference between SAPS-3 and SOFA scores when comparing non-delirium and delirium patients. When performing univariate analysis (S1 Table) we found an OR 4,07 (95% 2,65–6,23) for SAPS-3 score above 56 and an OR 4,05 (95% 2,64–6,21) for SOFA score above 4. Upon multivariate analysis, we observed an OR for multiorgan failure of 4.9, with a narrower confidence interval (95% CI 2.9–8.2) than the one observed by Zaal et al. [7].

The development of delirium is associated with a worse short-term prognosis, such as increased mortality, cognitive impairment, longer duration of mechanical ventilation, and longer length of stay in the ICU [5]. Even though we did not find differences in mortality, our patients who developed delirium presented more prolonged ICU and hospital length-of-stay (median of seven days in ICU, plus ten days in the wards). It should be noted that a longer duration in ICU is associated with an increase in morbidity and mortality, partially explained by potentially modifiable ICU factors such as the use of corticosteroids, neuromuscular blocking agents, benzodiazepines, or mechanical ventilation (already known risk factors for delirium) [31]. Along with this, and even though it was out of our study’s scope, we must highlight that delirium is also associated with worse long-term prognosis, such as persistent cognitive impairment [32-34] and disability in activities of daily living, including worse motor-sensory function [35, 36].

We would also like to focus on the associated increase in ICU readmission rate (7% in our cohort), similar to the results published in other studies [37, 38]. Besides, previous studies have shown risk factors associated with unscheduled admissions, such as indices of pre-existing ill-health, previous prolonged ICU length of stay, administration of steroids, need for blood products, need for extrarenal clearance techniques, or primary diagnosis of respiratory, gastrointestinal, metabolic or renal pathology [39-41]. Readmission to the ICU has proven frequent and strongly related to poor outcomes [42]. However, measures to prevent them remain elusive, as only a small percentage of readmissions are reported to be preventable [43].

This specific group of patients shows a high risk of unscheduled hospital readmissions and an increased risk of developing post-ICU syndrome, already known to profoundly affect patients’ perceived quality of life [44-46]. Prolonged exposure to risk factors from the ICU environment, including delirium development (with the consequent risk of developing secondary functional disability), makes this group of patients very vulnerable. Improving our understanding of risk factors amenable to intervention could improve our clinical management, plus develop post-ICU care programs. It has, therefore, important implications for research and public health policies.

Our study has several potential limitations. The main one is the relatively low incidence of delirium in our cohort (6.3%). Previous reports [47-49] from mixed ICU populations have demonstrated an incidence ranging between 30 to 80% observed in studies involving exclusively mechanical ventilated patients. Possible reasons for our low incidence could be (1) not including cardiac, thoracic, nor neuro-surgery due to the characteristics of our ICU, (2) an underdiagnosis of the condition (loss of cases related to undiagnosed hypoactive delirium [50]), (3) fluctuating handling of CAM-ICU screening tool likely related to frequent staff changes within the nursing pool or (4) optimized analgosedation management and preventive measures, which have been improved in recent years (although we do not have reliable data before 2016 to be able to compare whether this hypothesis is true). Delirium screening scales have the limitation of tagging but not necessarily identifying delirium. PADIS [8] supplemental material brings to light the controversy between delirium assessment reliability and sedation or consciousness, suggesting that the level of arousal could influence delirium assessment. CAM-ICU performed in routine practice has high specificity but low sensitivity, hampering early detection of delirium [51].

Two distinct clinical states (sedation and delirium, both associated with morbidity and mortality risks) can appear as a positive CAM-ICU screen and are considered equivalent to a ’delirium diagnosis.’ However, sedation-associated positive delirium scores that normalize when sedation is lightened [52] confer no greater risk than documented in critically ill adults without delirium. Moreover, transient CAM-ICU positivity in the context of deep sedation behaves very differently than CAM-ICU positivity or ongoing delirium symptoms with RASS levels of, or near, 0.

Two other limitations to consider are the study’s unicentric character and the somewhat limited number of patients, and the reliance on medical record data, introducing the potential for missing data. Regarding these two statements, in the first place, we believe the unicentric character could favor data homogeneity and consistency of the applied management. In the second place, although a lack of data is real, our ICU medical team tries to reduce this bias as much as possible by carrying out periodic reviews of the database.

The present study also has several strengths. We managed to include a high sample size considering our relatively small ICU capacity (between 8 and 10 available ICU beds), and we applied a reasonably new statistical model, which allowed us to detect the group most at risk of developing delirium. Different lines of action have been generated from the study, targeting a specific high-risk group and implying a change in our day-to-day work. Firstly, we have reinforced prevention measures (ABCDEF bundle) both within the ICU and within the hospital wards (thanks to our ICU outreach team) and encouraged a rigorous and systematic use of screening tools (CAM-ICU) within our ICU population. Furthermore, we have reinforced the presence of family members within the ICU, extending visiting hours, providing psychological screening and support, increasing the awareness of possible long-term consequences of intensive care among ICU survivors, and engaging them in the care of their relatives.

Secondly, and thanks to the great collaboration of our nursing team, high-risk patients are closely followed-up once discharged through the Continuity-of-Care Nursing team; this has led to our first multidisciplinary protocol for the management of post-ICU syndrome (coordinating both the hospital team and the Primary Care health centers attached to the hospital area to which we belong). During hospital admission, we support a nurse-led follow-up lead, coordinating with healthcare professionals and resource planning, and organizing a ward-discharge plan with the corresponding level of health care, guaranteeing the continuity of care. Our post-discharge follow-up program assures a satisfactory hand-off with the hospital ward team and discusses the next steps with the patient and family. They also provide a support program for families and caregivers, keeping in mind the patient’s values and wishes in the shared decision-making process. As for the post-discharge recovery, the principal targets are to return the patient to baseline by promoting continuous care, sharing knowledge, professional experience, and resource availability among professionals at all levels of care. A comprehensive assessment of the patient at the Primary Care Provider is performed. An evaluation is carried out at intervals defined by the Primary Care and Continuity-of-Care Nursing team [53, 54]. It remains to be seen whether these changes affect long-term morbidity and mortality, including a decrease in unplanned hospital and ICU readmission rates.

Conclusions

The detection of patients at high risk for developing delirium could imply a change in management and improved quality of care, emphasizing prevention measures, including close follow-up once discharged and collaboration with primary care. In our cohort, patients over 74 years old and those who presented more than two OF had the highest risk. Other identified relevant risk factors were coma on ICU admission, invasive mechanical ventilation, continuous NMB and patients who needed isolation due to identified MDR. Moreover, patients with delirium showed a more prolonged ICU and hospital length-of-stay and an increased CU readmission rate.

Our commitment towards critical care patients prompts us for early-diagnosis improvement through the systematic use of screening tools and the meticulous implementation of prevention programs. We must empower health professionals with information, education, and resources. The cornerstone would be achieving a multidisciplinary collaboration for managing these patients, improving their long-term prognosis and quality of life.

Univariate analysis.

(DOCX)

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Abbreviations list.

(DOCX)

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8 Jun 2021

PONE-D-21-09224

Risk factors associated with the development of delirium. A prospective observational study

PLOS ONE

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Reviewers' comments:

Reviewer #1: Major and minor concerns:

- Current Guidelines describe a meta-analysis of existing risk factors from a great number of studies and cohorts. So, the topic isn’t new and a lot of studies on delirium risk factors are available. The reported risk factors in this study aren’t innovative and go in line with current guidelines. A systematic comparison with risk factors from current guideline could be an additional result to add value to the manuscript.

- A delirium incidence of 6.3% on an ICU is comparably low. Regarding a sensitive delirium screening (3 times a day with CAM-ICU), please describe your population more precisely, also the group of patients without delirium. Maybe your ICU population has lower risk for delirium compared to other populations (e.g. no heart surgery patients).

- Who performed Delirium screening and Clinical Frailty Scale? Are these routine data from clinical staff?

- Please put data from univariate analysis at least in a supplement.

- The discussion should focus more on the results from multivariate analysis. The conclusion that sicker and older patients have a higher risk for delirium is too little, because it is know from preexisting literature. What is new? What is the difference? What implementation strategies will be made to prevent delirium on their ICU?

It is a simple, well-executed prospective cohort description. Perhaps you can put some more work into comparing them to the existing literature and highlighting the specifics of their work.

Reviewer #2: Overall:

This is a somewhat clearly written manuscript outlining an observational study to identify risk factors of delirium. The project doesn’t really add anything new to the literature as no new risk factors have been identified. The low delirium rate in the population is problematic and the rationale for this has not been flushed out. Methodologic issues and limitations on reporting (standard of care, missing data) may have contributed to the findings. There are grammatical errors and word choices that impair understanding in some areas.

Abstract:

The abstract should clearly state that the dataset used is from a registry.

Tool used for delirium detection is not provided in the abstract.

Introduction:

The introduction is a bit disorganized and doesn’t support the need for the project well. The authors propose delirium is under-recognized in the ICU but do not provide a reference for this statement. The authors list a number of risk factors for delirium, but there isn’t a statement about whether these are adequate. The limitations on prevention and treatments for ICU delirium has been outlined, but these are not tied to the study and how additional risk factors could/would modify patient care paradigms and/or improve outcomes.

Methods:

Page 4, paragraph 1: Please define use of the term ‘polyvalent’. This doesn’t seem to be the correct word.

Page 4, paragraph 2: Please spell out the acronym RASS and provide a reference for this tool.

While the project study subjects enrolled prospectively, the reliance on medical record data introduces potential for a substantial amount of missing data and this has not been addressed.

A more detailed description of standard of care in relation to delirium should be provided. It would be helpful to know if the unit utilizes a ‘bundle’ (and which one) to prevent delirium which may contribute to the low delirium rate found in this study.

Did subjects receive a daily sedation break? This would be important for evaluating the project.

Please provide an operational definition of ‘organ failure’.

Potential collinearity between variables may be a problem with the analysis but it does not appear this has been evaluated.

Patients who are comatose can not be assessed with the CAM-ICU as they are not responsive. Subjects with coma on admission were included but it’s not clear how this was handled. It’s also not possible to assess patients for delirium while under complete neuromuscular blockade. How was the determination of delirium made or ruled out in these cases?

Results:

The delirium rate is very low for this cohort (6%). This should be discussed further within the manuscript.

Missing data, especially for delirium assessment/identification, should be reported.

Discussion and Limitations:

Discussion of the low delirium rate is not well developed. Further exploration of this is necessary.

Conclusions:

Conclusions are very brief and don’t add to the manuscript. It is primarily a restatement of results and call to action for health care providers.

Tables and Figures:

Tables are helpful and provide additional content complementing the text.

The figure is not viewable in the pdf. It is difficult to understand what is being presented or how it relates to the study.

Reviewer #3: Thank you for this interesting article dealing with risk factors for the delirium occurence in ICU patients. The article is straightforward written and of clinical importance. However, there are still some points that need to be addressed in order to improve the article. Also, I have some concerns to recommend the acceptance of the present article, since there is a large amount of delirious publications existing and it should be well explained, how this present article may add and supplement the understanding of the delirium etiopathogenesis. I would therefore suggest to majorily revise your manuscript.

- Headline should be more specific according to your study objectives. The setting should mentioned. Specify also the population on which your conclusion sould be drawn (general ICU patients, neurological/ surgical/ cardiovascular etc.).

- The term „APACHE II before admission“ should be more specific. (in which direction is delirium risk increased?)

- Correct „the use a bundle approach“, „its´“

- The second passage of the introduction should be better referenced after the second sentence.

- Abbreviations (e.g. SCCM, CAM-ICU, RASS) should be written out when first used. Please add a abbreviation list for specification (for e.g. in the supplementary materials).

- Inclusion and exclusion criteria sould be stated more profoundly. How was the willingness for study participation was ascertained when patients were sedated or could not communicate? Particularly in case of a delirium this is of major interest from an ethical point of view.

- The „new data protection regulation“ – what is meant by this term. It is enough to state that the study protocol was approved by the Ethics Committee (EC). Please add the number you received from the EC, accordingly.

- When did the CAM-ICU assessment take place. Please add a timeline/ timeframe. Who assessed the delirium state and how often was the assessment realized? What was the interrater-reliability like?

- How was the SAP3 score SOFA score assessed. Please integrate this in the method section and specify who assessed the scores (by experienced physicians?).

- p < .0001 should be changed to p < .001

- Please specify in the statistics sections: what is meant with the phrase „continuous variables were stratified…“. Please give an example. Also, „the cut-off point…“ was standardized. How was this standardized? What is meant by 0.1? Is it a p-value?

- Also the recursive partitioning test sounds to me a bit arbitrary. Could you please give a reference for this method. On which base where the variables for classification chosen? Based on the results of the multivariate analysis? What does the understanding of the CHAID classification add to the results?

- Please add „n = …“ when patient numbers are presented.

- „In this group, reasons for ICU admission included pre-ICU emergency surgery or a medical admission (acute respiratory failure, sepsis, coma, or cardiac arrest)“ – Where can the rate of pre-ICU emergency surgery be drawn from the table?

- Tables and figures should be presented chronologically after the manuscript text.

- Finally, it should be more clarified what is new and outstanding on this research topic. What change in delirium management can be conveyed from your results? What does this imply for future research?

- Give the reason why you state an evaluation of „moderate evidence“ for multiorgan function in the discussion section.

- How is the post-ICU follow-up realized? This sounds very progressive and sounds interesting for future research and to become routine clinical practice for prevention of long-term complications from ICU.

- Please speciy early aggressive treatment and other risk factors (other than what).

- How would you address the fact that delirium is associated with a higher risk for need of invasive mechanical ventilation? Vice verse, mechanical ventilation may increase the risk for delirium evolvement. How or in which direction would you evaluate the causative path, based on your data?

- Please let the Englisch language be checked via proof-reading by a native speaker.

- Please add line numbers on each page to facilitate the review process.

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Submitted filename: R1_PONE-D-21-09224.docx

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5 Jul 2021

RESPONSE TO REVIEWERS

Reviewer #1

Current Guidelines describe a meta-analysis of existing risk factors from a great number of studies and cohorts. So, the topic isn’t new and a lot of studies on delirium risk factors are available. The reported risk factors in this study aren’t innovative and go in line with current guidelines. A systematic comparison with risk factors from current guideline could be an additional result to add value to the manuscript.

Thank you for your review, suggestions, and comments.

Following your recommendation, we have included a more extensive reference to the systematic review of risk factors carried out and published in the 2018 guidelines (with the statistical data provided in the guidelines as supplementary material).

A delirium incidence of 6.3% on an ICU is comparably low. Regarding a sensitive delirium screening (3 times a day with CAM-ICU), please describe your population more precisely, also the group of patients without delirium. Maybe your ICU population has lower risk for delirium compared to other populations (e.g., no heart surgery patients).

Following your advice, we have described in more detail the general characteristics of patients admitted to the ICU (as indicated, we do not have patients from cardiothoracic surgery or neurosurgery).

Who performed Delirium screening and Clinical Frailty Scale? Are these routine data from clinical staff?

Delirium screening is performed by our nursing staff, whilst CFS, SAPS-3 and SOFA scores are collected by the medical team. It’s part of our daily routine for several years now. Moreover, in case of doubt with any of the scores, we discuss it between the team members, and we collect in the Registry the agreed value.

Please put data from univariate analysis at least in a supplement.

We have included the data from the univariate analysis as Supplementary material – Supplementary Table 1.

The discussion should focus more on the results from multivariate analysis. The conclusion that sicker and older patients have a higher risk for delirium is too little, because it is known from preexisting literature. What is new? What is the difference? What implementation strategies will be made to prevent delirium on their ICU?

Thank you for your comment. Following the suggestion, we have modified the discussion section by focusing more on the result of the multivariate analysis and possible strategies we could take to improve care for this group of patients.

Reviewer #2

The abstract should clearly state that the dataset used is from a registry. Tool used for delirium detection is not provided in the abstract.

Thank you for your review and comments. We have modified the abstract, following your suggestion.

The introduction is a bit disorganized and doesn’t support the need for the project well. The authors propose delirium is under-recognized in the ICU but do not provide a reference for this statement. The authors list a number of risk factors for delirium, but there isn’t a statement about whether these are adequate. The limitations on prevention and treatments for ICU delirium has been outlined, but these are not tied to the study and how additional risk factors could/would modify patient care paradigms and/or improve outcomes.

We have modified the introduction and have also provided one reference (no. 6) supporting the statement of “underdiagnosed and underestimated problem”.

Page 4, paragraph 1: Please define use of the term ‘polyvalent’. This doesn’t seem to be the correct word.

The term “polyvalent” has been replaced by “general”.

Page 4, paragraph 2: Please spell out the acronym RASS and provide a reference for this tool.

We have followed your indications and included a reference (JAMA 2003;289(22):2983-91).

While the project study subjects enrolled prospectively, the reliance on medical record data introduces potential for a substantial amount of missing data and this has not been addressed.

Thanks again. We have considered your comments and addressed this potential limitation in our discussion.

A more detailed description of standard of care in relation to delirium should be provided. It would be helpful to know if the unit utilizes a ‘bundle’ (and which one) to prevent delirium which may contribute to the low delirium rate found in this study.

Thank you for your helpful comment. We have added a paragraph within “Material and Methods” briefly describing our protocol.

Did subjects receive a daily sedation break? This would be important for evaluating the project.

Within our analgesia/sedation protocol we adjust sedation according to nursing needs (nursing-protocolized targeted sedation). We have adopted the term “dynamic sedation”, trying to keep patients with the least sedation possible, maintaining sedation levels around RASS 0 and -1 whenever possible.

Please provide an operational definition of ‘organ failure’.

We have included an operational definition of organ failure in “Material and Methods”, based on SOFA score above 2 for specific organs.

Potential collinearity between variables may be a problem with the analysis but it does not appear this has been evaluated.

All the clinically relevant studied variables were included in the analysis. We did not intend to obtain a generalizable mathematical model.

Patients who are comatose cannot be assessed with the CAM-ICU as they are not responsive. Subjects with coma on admission were included but it’s not clear how this was handled. It’s also not possible to assess patients for delirium while under complete neuromuscular blockade. How was the determination of delirium made or ruled out in these cases?

During the administration of neuromuscular blockade, the CAM-ICU is not assessable given that deep sedation is maintained (RASS -5). CAM-ICU cannot be carried out until we are able to decrease sedation to a value of RASS above -3; patients who required deep sedation and NMB were able to fulfill CAM-ICU criteria at some point of their ICU admission. Regarding coma as main reason for admission, we should clarify that most of the comas were of toxic/metabolic/respiratory origin, and few were secondary to primary neurological status/pathology (given that we are not a reference center for neurocritical patients). We have, following your suggestion, added a small explanation regarding this last point.

The delirium rate is very low for this cohort (6%). This should be discussed further within the manuscript.

We understand that one of the limitations of this study is, as you point out, the low incidence of delirium. Following your advice, we have added additional comments within the discussion.

Missing data, especially for delirium assessment/identification, should be reported.

We have followed your indications and addressed this potential limitation in our discussion.

Discussion of the low delirium rate is not well developed. Further exploration of this is necessary.

We have broadened this section within the discussion.

Conclusions are very brief and don’t add to the manuscript. It is primarily a restatement of results and call to action for health care providers.

We have tried to complete the conclusions section following your feedback.

Tables are helpful and provide additional content complementing the text. The figure is not viewable in the pdf. It is difficult to understand what is being presented or how it relates to the study.

Considering the problems caused by the interpretation of the figure and given that the relevant information is reflected in the text, we have decided to remove the figure from the final version of the manuscript. We thank you for your input in this regard.

Reviewer #3

Headline should be more specific according to your study objectives. The setting should be mentioned. Specify also the population on which your conclusion should be drawn (general ICU patients, neurological/ surgical/ cardiovascular etc.).

Thank you for your review and comments. We have modified manuscript’s headline following your input.

The term „APACHE II before admission“ should be more specific. (in which direction is delirium risk increased?)

APACHE (Acute Physiology and Chronic Health Evaluation) is a scoring system using routinely collected data and providing an accurate, objective description for a broad range of intensive care unit admissions, measuring severity of illness in critically ill patients. Previous studies regarding risk factors for delirium have found a strong association between high scoring in APACHE II and delirium development. We understand that in the introduction section, we mentioned apache II as a risk factor associated with the development of delirium.

Correct „the use a bundle approach“, „its´“

We have made the correction.

The second passage of the introduction should be better referenced after the second sentence.

We have updated the references in that paragraph.

Abbreviations (e.g., SCCM, CAM-ICU, RASS) should be written out when first used. Please add a abbreviation list for specification (for e.g. in the supplementary materials).

We have corrected manuscript and provided a supplementary document with a list of abbreviations.

Inclusion and exclusion criteria should be stated more profoundly. How was the willingness for study participation was ascertained when patients were sedated or could not communicate? Particularly in case of a delirium this is of major interest from an ethical point of view. The „new data protection regulation“ – what is meant by this term. It is enough to state that the study protocol was approved by the Ethics Committee (EC). Please add the number you received from the EC, accordingly.

We thank you for your insightful comment. We have changed the paragraph on consent, providing more information related to the process, as well as inclusion and exclusion criteria. We have also provided the assigned number by the Research Ethics Committee of the university.

When did the CAM-ICU assessment take place. Please add a timeline/ timeframe. Who assessed the delirium state and how often was the assessment realized? What was the interrater-reliability like?

Following your advice, we have provided more information on how CAM-ICU was performed (by nursing staff, once every shift = once every eight hours). Moreover, our ICU protocol related to the early detection of delirium and optimization of preventive measures had been in place for several years prior to the study. At the time all ICU staff received appropriate training, in an attempt to standardize individual criteria. Also, in case of doubt, they were discussed with the attending physician.

How was the SAP3 score SOFA score assessed. Please integrate this in the method section and specify who assessed the scores (by experienced physicians?).

We thank you for your comment CFS, SAPS-3 and SOFA scores were routinely collected by the team of physicians. We have provided this information in the manuscript.

p < .0001 should be changed to p < .001

We have modified it accordingly.

Please specify in the statistics sections: what is meant with the phrase „continuous variables were stratified…“. Please give an example. Also, „the cut-off point…“ was standardized. How was this standardized? What is meant by 0.1? Is it a p-value? Also the recursive partitioning test sounds to me a bit arbitrary. Could you please give a reference for this method. On which base where the variables for classification chosen? Based on the results of the multivariate analysis? What does the understanding of the CHAID classification add to the results?

Thank you for your feedback. We have tried to simplify the paragraph related to multivariate analysis. Recursive partitioning is a statistical method for multivariable analysis that creates a decision tree that strives to correctly classify members of the population by splitting it into sub-populations based on several dichotomous independent variables. CHAID is therefore a decision tree model that create classification systems that predict or classify future observations based on a set of decision rules. i.e., it involves a multivariate analysis where variables are automatically stratified according to importance, creating a risk map of different risk groups, allowing measures to be taken according to these groups.

Please add „n = …“ when patient numbers are presented.

Corrected.

In this group, reasons for ICU admission included pre-ICU emergency surgery or a medical admission (acute respiratory failure, sepsis, coma, or cardiac arrest)“ – Where can the rate of pre-ICU emergency surgery be drawn from the table?

Regarding emergency surgery as admission type: 14.4% (n = 196) in the group of patients who did not develop delirium, and 15% (n = 14) in the group of patients who developed delirium during ICU admission. Data extracted from Table 1.

Tables and figures should be presented chronologically after the manuscript text.

Following the journal's instructions for authors, we inserted the tables just after the paragraph that mentions them (“Tables should be included directly after the paragraph in which they are first cited”).

Finally, it should be more clarified what is new and outstanding on this research topic. What change in delirium management can be conveyed from your results? What does this imply for future research?

We understand that delirium is a topic that has already been subject to many publications. Nevertheless, and in view of what has happened over the last year (with the exponential increase in the incidence of delirium among COVID-19 patients), we consider that it is still an unresolved and important issue, where more research is needed (both in prevention, early diagnosis, and treatment). Following your recommendation, we have broadened our discussion section.

Give the reason why you state an evaluation of „moderate evidence“ for multiorgan function in the discussion section.

Moderate evidence regarding association of multiorgan failure and development of delirium was found in the study by Zaal et al (reference number 7). We simply record this statistical result in the manuscript, since we found a similar OR, with a narrower confidence interval.

How is the post-ICU follow-up realized? This sounds very progressive and sounds interesting for future research and to become routine clinical practice for prevention of long-term complications from ICU.

We would like to thank you for your comment, as it gives us the opportunity to explain our project. We have modified the last section of the discussion by adding a summary of our post-ICU patient care protocol, which was launched four years ago.

Please specify early aggressive treatment and other risk factors (other than what).

Following your indications, we have modified the paragraph and deleted the sentence, as it was misleading.

How would you address the fact that delirium is associated with a higher risk for need of invasive mechanical ventilation? Vice verse, mechanical ventilation may increase the risk for delirium evolvement. How or in which direction would you evaluate the causative path, based on your data?

Mechanical ventilation has been found to be an independent risk factor or delirium, although the specific pathogenesis is not well known. It may have to do with the effect of mechanical ventilation itself on intrathoracic and intravascular pressures, which ultimately exert a distant effect on the brain (probably with both physical and biochemical side effects). On the other hand, mechanical ventilation is associated with the need for sedation (both mild and deep), and this is also associated with an increased risk of developing delirium (especially if the drugs of choice are benzodiazepines or opioids).

Please let the English language be checked via proof-reading by a native speaker.

Following your comment, a native English speaker has revised the final version of the manuscript.

Please add line numbers on each page to facilitate the review process.

Thank you for your comment. We have inserted numbered lines in the manuscript.

Submitted filename: Response to reviewers.docx

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19 Jul 2021

Risk factors associated with the development of delirium in general ICU patients. A prospective observational study.

PONE-D-21-09224R1

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25 Aug 2021

PONE-D-21-09224R1

Risk factors associated with the development of delirium in general ICU patients. A prospective observational study.

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