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. 2025 Jun 6;20(6):e0324099. doi: 10.1371/journal.pone.0324099

Impact of self-perceived discomfort in critically ill patients on the occurrence of psychiatric symptoms in post-intensive care syndrome (PICS): A prospective observational study

Romain Ronflé 1,*, Julie Hermitant 1, Christine Conti-Zolin 1, Laurent Lefebvre 1, Thibault Helbert 1, Aurélien Culver 1, Florence Molenat 1, Baptiste Borwel 2, Mohamed Boucekine 3, Pierre Kalfon 4, Marc Leone 5,*
Editor: Michihiro Tsubaki,6
PMCID: PMC12143565  PMID: 40478829

Abstract

Background

Mental health impairments after intensive care unit (ICU) discharge include anxiety, depression, and post-traumatic stress disorder [PTSD], forming part of the post-intensive care syndrome (PICS). We assessed the effects of discomfort on the occurrence of psychiatric symptoms as a part of PICS.

Methods

This prospective observational study conducted from September 2022 to June 2023 included all patients aged ≥ 18 years who survived an ICU stay of ≥3 days. To assess patient discomfort during the ICU stay, we used the Inconforts des Patients de REAnimation (IPREA) questionnaire. The primary outcome was the occurrence of anxiety, depression, or PTSD after ICU discharge. Secondary outcomes were the quality of life in ICU survivors and the clinical impression of physicians and psychologists to predict post-ICU psychiatric symptoms.

Results

Of the 173 patients included initially, 109 were finally analysed. An IPREA score ≥ 13 was strongly associated with an increased risk of post-ICU psychiatric symptoms (odds ratio: 3.8, 95% confidence interval: 1.4–10.3, p = 0.008). The patients with post-ICU psychiatric symptoms had a reduced quality of life. The clinical impression of physicians and psychologists at ICU discharge for the risk of psychiatric symptoms 3 months after the ICU stay was not selective.

Conclusions

Self-perceived discomfort in ICU survivors was the most predictive factor of the development of post-ICU psychiatric symptoms.

Introduction

Critically ill patients in intensive care unit (ICU) are exposed to stressful conditions and experience discomfort [1]. ICU survivors present an increased risk of longer-term psychopathological issues [2], primarily anxiety, depression, and post-traumatic stress disorder (PTSD). Symptoms of anxiety and depression occur respectively in 25% to46%, and approximately 29% of patients, after discharge [3]. PTSD has largely been reported after ICU discharge [4,5]. Moreover, when symptoms of any of these psychiatric disorders are present, they occur with symptoms of the other two disorders in 65% of cases [2].

Physical, cognitive, and mental health impairment occurring after ICU discharge is known as post-intensive care syndrome (PICS) [6]. Up to a third of ICU survivors experience psychiatric impairment [7]. Significant risk factors for PICS include older age, female sex, previous mental health problems, disease severity, negative ICU experience, and delirium [8]. Unpleasant memories of real events during ICU stay may provide some protection from PICS symptoms. Conversely, when memories of delusions are prominent, PICS symptoms may be higher [1].

ICU patients are subjected to multiple sources of discomfort, including environment or types of care [9,10], all of which affect their outcome after ICU discharge. To assess the discomfort of ICU patients, the Inconforts des Patients de REAnimation (IPREA) questionnaire was established [11]. Given that only a few studies have measured the effects of self-perceived discomfort on post-ICU psychiatric symptoms, we assessed these effects on the occurrence of psychiatric symptoms compared with already known risk factors. Secondly, we analysed the effect of discomfort on the post-ICU patient’s quality of life. Finally, we evaluated the clinical global impression of physicians and psychologists to predict the occurrence of post-ICU psychiatric symptoms.

Materials and methods

Setting

We conducted this prospective and observational study in the mixed medical–surgical ICU of Centre Hospitalier du Pays d’Aix, Aix-en-Provence, France. The study was approved by the Ethics Committee of Rouen University, France (approval number: 2022-A01063-40). We obtained the patient’s or relatives’ written consent for using these data at this ICU discharge. The study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations for cohort studies. Our study protocol is available as supporting information from the authors. The authors confirm that all ongoing and related trials for this study are registered (clinicaltrial.gov; NCT06238557).

Patients

From 8th September 2022 to 14th October 2023, all patients aged ≥18 years who survived an ICU stay of ≥3 days were deemed eligible for inclusion in this study. We excluded patients under guardianship, patients with mental disability (neurodevelopmental, intellectual, or cognitive), patients who did not understand French sufficiently to be questioned, and patients included in another interventional study. We also excluded patients who denied the use of personal data or did not respond after 3-month ICU discharge.

Study design

First, we collected on ICU discharge the IPREA score, memories during ICU stay, and self-perceived frightening experiences from ICU admission to ICU discharge. The clinical global impression of the physician and psychologist in charge of the patient about the risk of psychiatric components of PICS were assessed simultaneously. Then 3 months after ICU discharge, the questionnaire of anxiety, depression, and PTSD was conducted via conference call or through self-assessment. Finally, the patient’s quality of life after ICU discharge was investigated.

Measurement

The included patients’ clinicodemographic data were collected from electronic medical records: demographics (sex, age, preexisting psychopathology (depressive disorder, anxiety disorder, schizophrenia, bipolar disorder, post-traumatic stress disorder), condition of admission (surgical or nonsurgical), health status before the ICU stay (the Knaus score), and health status at ICU admission (Simplified Acute Physiology Score of 2 [SAPS2] and Sepsis-related Organ Failure Assessment [SOFA] score). We also recorded any stressful procedures that the patients underwent during their ICU stay: invasive mechanical ventilation, noninvasive ventilation, tracheotomy, renal replacement therapy, central venous or arterial catheter insertion (and number), nasogastric tube insertion, bronchoscopy, digestive endoscopy, chest drainage, external electrical shock, lumbar puncture, intrahospital transport, and external defibrillation. The number of stressful procedures was recorded as follows: one point for each procedure (among the 14 aforementioned procedures). The number of days of benzodiazepine and/or neuroleptic medication was used to report on acute agitation. Finally, ICU length of stay, memories during sedation (remember information during medically induced coma), and the occurrence of frightening experiences were also recorded.

To assess patient discomfort during the ICU stay, we calculated the self-reported discomfort score by using the 18-item French-language IPREA questionnaire (S1 Table), which was validated by the IPREA group in a large sample of critically ill patients hospitalised in 34 French ICUs [12].

The IPREA score was calculated as the mean of the 18 scores reported for each item multiplied by 10, yielding a score ranging from 0 to 100, with higher scores indicating increased discomfort. Any physician of our ICU could administer the questionnaire provided and underwent specific training. The questions were asked in random order to reduce bias.

Outcomes

The primary outcome was the psychiatric component of PICS, defined as the occurrence of anxiety, depression or PTSD. The occurrence of at least one of the three psychiatric symptoms is sufficient to complete the primary outcome. Anxiety and depression were evaluated using a validated tool: the 14-item Hospital Anxiety and Depression Scale (HADS) [13], which includes 7 questions each on depression and anxiety, each scored on a 4-point Likert scale ranging from 0 (no impairment) and 3 (severe impairment). A cutoff score of ≥8 for either anxiety or depression subscales indicated the presence of the respective condition. We applied HADS boundaries for mild, moderate, and severe symptoms to those exhibiting symptoms. PTSD was assessed using the PTSD Checklist for DSM-5 (PCL-5), a 20-item self-report measure of the 20 DSM-5 symptoms of PTSD [14]. Included in the scale are four domains consistent with the four criteria of PTSD in DSM-5: Reexperiencing (criterion B), Avoidance (criterion C), Negative Alterations in Cognition and Mood (criterion D), and Hyperarousal (criterion E). To define a case, we treated each item rated as 2 = “Moderately” or higher as a symptom endorsed and then followed the DSM-5 diagnostic rule: ≥1 Criterion B item (questions 1–5), ≥  Criterion C item (questions 6–7), ≥2 Criterion D items (questions 8–14), and ≥2 Criterion E items (questions 15–20).

The secondary outcome was the quality of life after 3-month ICU discharge, which was evaluated using the World Health Organisation Quality of Life-BREF (WHOQOL-BREF) questionnaire. The score is calculated by adding up the responses to the questions and transforming them to a scale from 0 to 100, with higher scores indicating a better quality of life. We preferred this questionnaire over the SF-36 as it includes items on the environment. Moreover, we developed a risk score to predict post-ICU psychiatric symptoms based on the major risk factors identified in our cohort. Finally, the clinical impression of the ICU physician and psychologist at ICU discharge for the risk of psychiatric symptoms 3 months after ICU stay was studied. At the ICU discharge, ICU physicians and psychologists met the patient for a clinical interview to assess the occurrence of psychiatric symptoms or not (anxiety, depression or PTSD; associated or not) before scoring his or her self-perceived discomfort. They used clinical experience and patients’ clinical data only (health status at ICU admission, condition of admission, number of stressful procedures, ICU length of stay, memories during sedation and frightening experiences).

Statistical analysis

Continuous variables are expressed as means ± standard deviation or median (interquartile range) and were compared using Student’s t test. Categorical variables are expressed as frequency and percentage and were compared using the chi-square test or Fisher’s exact test. Multivariate logistic regression models were used to identify independent risk factors for psychiatric symptoms. Multivariate logistic regression model was constructed following the commonly recommended guideline of maintaining approximately 10 outcome events per predictor variable to mitigate the risk of model overfitting and excessive complexity [15]. The selection of variables was based on a univariate analysis threshold (p < 0.2) combined with clinical relevance and prior evidence on known confounders. Results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). In all analyses, two-tailed p < 0.05 was considered significant. Next, we built a risk score for post-ICU psychiatric symptoms with the significant parameters. Variables were categorized to improve clinical interpretability and define homogeneous risk groups, with cutoff values determined using receiver operating characteristic (ROC) curves and the Youden index. ROC curve analyses were performed to assess the effectiveness of our score in predicting psychiatric symptoms. The cutoff for prediction of psychiatric symptoms was also determined using ROC curves and the Youden index. We conducted internal validation of our score in the cohort with values of sensitivity, specificity, negative predictive value, and positive predictive value. To evaluate the stability and robustness of our findings, we conducted sensitivity analyses by testing multiple model specifications with varying covariate selections. This approach allowed us to confirm the consistency and reliability of our main conclusions across different analytical frameworks. AIC and BIC values were also reported for each multivariate model to assess model fit and complexity. A size-proportional Venn diagram was made to represent the psychiatric issue components (PTSD, anxiety, and depression). Agreement between the patient’s feeling of distress as assessed by the physician or psychologist at ICU discharge to the occurrence of psychiatric symptoms at 3-months was evaluated using the Cohen’s kappa coefficient, which measures inter-rater reliability beyond chance, with p-values assessing its significance against zero. Taking into account the previous hypotheses, to highlight an odds ratio of 1.64 per unit of standard deviation of the IPREA score (i.e., an increase in risk of 4.5% per unit of IPREA score), with an alpha risk of 5% and a power of 80%, the minimum number of patients was determined to be 153; therefore, the number of patients expected to be included was 183 to account for loss in follow-up (20%). This number of patients is expected to show an area under the curve (AUC) of 0.7 with a 95% CI of 0.19 (153 patients required: 46 PICS and 107 no PICS).

All analyses were performed with available data using SPSS v19 (IBM) and R statistical software.

Results

During the study period, 173 patients were included. Of these inclusions, 64 were excluded from the analysis for the following reasons: 11 died during the follow-up, 7 had significant missing data, and 46 did not respond. Finally, the data of 109 patients were analysed (S1 Fig). Table 1 presents their clinicodemographic characteristics.

Table 1. Patients’ characteristics.

Variables Cohort (n = 173)
Demographics
Age, y, median (Q25-Q75) 67 (51-74)
Male sex, n (%) 117 (68)
Knaus Score, n (%)
▪ Normal health status 53 (31)
▪ Moderate activity limitation 80 (46)
▪ Severe activity limitation 39 (22)
▪ Bedridden patient 1 (1)
Preexisting psychopathology, n (%) 23 (13)
Diagnosis and severity
Reason for ICU admission, n (%)
▪ Surgical 40 (23)
▪ Non surgical 133 (77)
SAPS2 score, median (Q25-Q75) 38 (26-50)
SOFA score on admission, median (Q25-Q75) 4 (2-7)
Evolution
ICU length of stay, d, median (Q25-Q75) 6 (4-10)
Organ failure
Mechanical ventilation, n (%)* 112 (65)
▪ Invasive 68 (39)
▪ Non invasive 79 (46)
Catecholamines, n (%) 77 (45)
Renal remplacement therapy, n (%) 26 (15)
Density of stressful procedures, mean ± SD 4 ± 2
ICU experience
Score derived from IPREA questionnaire, mean ± SD 20 ± 14
Presence of a subjective trauma, n (%) 55 (32)
Delusion, n (%) 14 (8)
Use of benzodiazepines and/or neuroleptics for restless, n (%) 81 (47)

Values are expressed as number (%), mean ± SD and median (Q25-Q75). SOFA Sepsis-related Organ Failure Assessment, SAPS2 Simplified Acute Physiology Score of 2, ICU Intensive Care Unit, IPREA inconfort des patient de reanimation, *Some patients had both.

We observed no statistical difference between the included patients and those lost to follow-up (sex, age, or preexisting psychiatric disorder). We reported an average of four stressful invasive procedures for each patient. The median self-perceived discomfort score derived from IPREA was 20 ± 14. The three highest scores were anxiety (3.8 ± 3.4), thirst (3.0 ± 3.5), and shortness of breath (3.0 ± 3.3, S2 Table).

The primary outcome was observed in 44 (40%) patients of our cohort study. Twenty (48%) patients had at least two psychiatric symptoms (Fig 1). The median HADS anxiety, depression, and PCL-5 total scores were respectively 5 (2–8), 3 (2–7), and 9 (4–16) (S1 Fig, Flowchart).

Fig 1. Occurrence of psychiatric symptoms 3-months after ICU stay in ICU survivors.

Fig 1

PTSD, post-traumatic stress disorder.

From the univariate analysis, we selected several factors for predicting psychiatric symptoms: age, IPREA score, female sex, preexisting psychiatric disorder and health status with limitation of activity (p < 0.2). To predict post-ICU psychiatric symptoms, the best threshold for IPREA score was 13 (sensitivity: 82%, specificity: 46%, PPV: 51%, NPV: 79%, and Youden: 0.28), and the best threshold for age was 52 years (sensitivity: 37%, specificity: 85%, PPV: 62%, NPV: 67%, and Youden: 0.22). In multivariate analysis, an IPREA score ≥ 13 was strongly associated with an increased risk of post-ICU psychiatric symptoms (OR: 3.8, 95% CI: 1.4–10.3, p = 0.008) (Table 2).

Table 2. Effect of variables on the PICS occurence at 3 months in multivariate analysis.

OR (95% CI) p value
Model 1 (AIC = 28, BIC = 39)
IPREA score ≥ 13 3.9 (1.5 - 10.3) 0.007
Psychiatric history 3.5 (0.9 - 13.3) 0.06
Age ≤ 52 y 2.6 (1 - 6.8) 0.06
Model 2 (AIC = 42, BIC = 55)
IPREA score ≥ 13 3.8 (1.4 - 10.3) 0.008
Psychiatric history 3.6 (0.9 - 14) 0.06
Age ≤ 52 y 3.3 (1.1 - 9.8) 0.03
Health status with limitation of activitya 1.9 (0.6 - 5.4) 0.2
Model 3 (AIC = 58, BIC = 74)
IPREA score ≥ 13 3.4 (1.2 - 9.4) 0.02
Psychiatric history 3.5 (0.9 - 13.3) 0.07
Age ≤ 52 y 3.7 (1.2 - 11.2) 0.02
Health status with limitation of activitya 2 (0.7 - 6) 0.2
Female sex 1.7 (0.7 - 4.4) 0.3

aDetermined by the Knaus score, ranging from moderate limitation of activity to bedridden patient.

PICS, post intensive care syndrome; OR, odds ratio; CI, confidence interval.

Age ≤ 52 years was also associated with increased risk (OR: 3.3, 95% CI: 1.1–9.8, p = 0.03).

We then built a predictive score of psychiatric symptoms with three variables: IPREA score ≥ 13, preexisting psychiatric disorder, and age ≤ 52 years, with each variable counting as one point. A risk score ≥ 2 was the best cutoff associated with psychiatric symptoms for ICU survivors (OR: 6.2, 95% CI: 2.4–16, p < 0.001) with an AUC of 72% (63–82%) (sensitivity: 47%; specificity: 88%, PPV: 71%, NPV: 71%, and Youden: 0.34) (Fig 2).

Fig 2. Risk score of psychiatric symptoms 3 months after ICU stay in ICU survivors.

Fig 2

*p < 0.05.

No difference was found in patient’s characteristics between those achieving the primary outcome and those not achieving the primary outcome, except for the IPREA questionnaire and preexisting psychiatric disorders (Table 3).

Table 3. Patients’ characteristics comparison between observed primary outcome group and opposite group.

Variables Observed primary outcome group (n = 44) Opposite group (n = 65) p value
Age, y, mean ± SD 59 ± 17 65 ± 13 0.12
Male sex, n (%) 28 (64) 49 (75) 0.20
Health status with limitation of activity, n (%) 32 (73) 46 (71) 0.99
Preexisitng psychopathology, n (%) 9 (21) 4 (6) 0.03
SAPS2 score, mean ± SD 39 ± 17 39 ± 14 0.96
SOFA score, mean ± SD 5 ± 3 5 ± 3 0.82
ICU length of stay, d, mean ± SD 11 ± 13 12 ± 16 0.18
Mechanical ventilation, n (%) 17 (39) 27 (42) 0.84
Density of stressful procedures, mean ± SD 3 ± 2 4 ± 3 0.54
Score derived from IPREA questionnaire, mean ± SD 23 ± 12 20 ± 13 0.05
Days of benzodiazepines/ neuroleptics use, d, mean ± SD 6 ± 8 6 ± 4 0.28
Presence of a trauma, n (%) 18 (41) 21 (33) 0.42
Delusion, n (%) 5 (11) 4 (6) 0.48
Physical health, mean ± SD 49 ± 18 64 ± 16 <0.001
Psychological health, mean ± SD 56 ± 20 70 ± 14 <0.001
Social relationships, mean ± SD 63 ± 22 75 ± 14 0.003
Environmental health, mean ± SD 66 ± 17 80 ± 14 <0.001

Values are expressed as number (%), mean ± SD and median (Q25–Q75).

SOFA, Sepsis-related Organ Failure Assessment; SAPS2, Simplified Acute Physiology Score of 2; ICU, Intensive Care Unit; IPREA, discomfort intensive care patients.

The patients for whom the primary outcome was observed had their quality of life reduced according to the WHOQOL-BREF questionnaire: 49% for physical health, 56% for psychological health, 63% for social relationships, and 66% for environmental health (p < 0.01 for each, Table 3). Finally, the clinical impression of the physician and psychologist at ICU discharge for the risk of psychiatric symptoms 3 months after ICU stay was not selective (κ = 0.04 and 0, p = 0.7 and 0.96, respectively).

Discussion

Our study explored predictive factors of psychiatric symptoms in PICS 3-months after an ICU stay. Our findings suggest that self-perceived discomfort during ICU stay is associated with an increased risk of psychiatric symptoms. Preexisting psychiatric disorders and age ≤52 years were associated with an increased risk of anxiety, depression, or PTSD. Thus, we proposed a score featuring self-perceived patient discomfort, preexisting psychiatric disorders, and age ≤52 years to predict the occurrence of psychiatric symptoms and long-term outcomes in ICU survivors. In addition, we suggested that patients who developed psychiatric symptoms after an ICU stay had a significant decrease in the quality of life.

Our findings are in line with those reported in previous studies. Kalfon et al. developed and validated the 18-item IPREA score for patients’ self-perceived ICU discomfort [11,12]. In our study, the mean IPREA score was low, but this was in line with other studies [11,16]. Self-perceived discomfort appears to be a useful tool which can predict psychiatric symptoms and should be considered by healthcare workers to identify sources of discomfort, enabling them to adapt environment and care to minimise the risk of PICS. The implementation of specific measures that included a programme of reduction discomfort by healthcare teams resulted in a significant decrease in the IPREA score [16]. The reduction of self-perceived discomfort by a adjusted multicomponent programme could also reduce the prevalence of PTSD symptoms in ICU survivors [17]. As predicted, self-perceived discomfort measured at the end of the ICU stay was increased in ICU survivors with psychiatric symptoms at 3 months after ICU discharge. In another study, patients with PTSD symptoms 1 year after the ICU stay had higher overall discomfort scores than those without such symptoms [17].

In our study, age ≤52 years increased the occurrence of psychiatric symptoms. At first, increased age was an independent predictor of a low discomfort score in multivariate analysis [18]. Kalfon et al. observed a significantly lower age for patients with PTSD symptoms at the 1-year follow-up [17]. A systematic review of ICU survivors reported that younger age predicted post-ICU PTSD [19]. High levels of PTSD symptoms were less likely to occur in older patients, with symptoms declining after the age of 50 years [20].

Preexisting psychiatric disorders are likely to increase the risk of psychiatric symptoms in PICS. Preexisting anxiety has shown to be a risk factor for PTSD in urban populations [21]. A meta-analysis found that only pre-ICU comorbid psychopathology was a risk factor for PTSD [4]. Patel et al. confirmed the identification of this pre-ICU risk factor [5]. Indeed, they reported both preexisting depression and preexisting PTSD as risk factors for PTSD in ICU survivors. Screening by health care teams for preexisting psychiatric status of ICU patients could be a first step.

We developed a score for different variables readily available in daily practice to assess the risk of psychiatric symptoms in ICU survivors. In the same way, Wade et al. created the intensive care psychological assessment tool to detect acute psychological distress and assess the risk of future psychological morbidity in critically ill patients [22].

Whether illness severity or invasive procedure serve as ICU risk factors for psychiatric components of PICS remains controversial. In our study, illness severity as reported through different scores (SAPS2 and SOFA) was not associated with the occurrence of psychiatric symptoms. Broomhead et al. confirmed that illness severity at ICU admission was consistently not a risk factor for PICS [23]. However, illness severity was associated with post-ICU anxiety, depression, and PTSD in other studies [3,8]. As predicted, we did not find any impact of either type or number of invasive procedures on the development of psychiatric symptoms. Fear experienced acutely during these invasive procedures and frightening memories about them seem to be the most important issue.

Our primary endpoint was the occurrence of anxiety, depression, or PTSD, and 48% of the our patients with one of these conditions had another, consistent with the finding of Hatch et al. in a UK-wide prospective cohort study [2]. Moreover, we observed a significant effect of post-ICU anxiety, depression, or PTSD on the quality of life of ICU survivors. Other studies highlighted the adverse effects of post-ICU psychiatric symptoms on the long-term outcomes of ICU survivors. Post-ICU depressive and PTSD symptoms may be associated with both physical and mental health aspects of quality of life [19,24,25]. Through these various data, we attempted to underline the reliability of our primary outcome.

Ours is the first study to assess the clinical impressions of physicians and psychologists in charge of ICU patients for the risk of psychiatric components in PICS. Notably, we reported no correlation between clinical global impressions and the occurrence of psychiatric symptoms in ICU survivors. We strongly highlighted the benefit of using variables to help physicians and psychologists predict psychiatric outcomes in ICU survivors.

Our study has several limitations. First, we excluded more patients than expected due to an increase in lost follow-up data. We observed 46 (26%) excluded patients for missing data, due to no respond after 3-month of follow up (20% initially planned). However, the proportion of included patients with complete follow-up data at 3-months was slightly over 50%? This was comparable to many studies on post-ICU psychiatric symptoms [4,5,17]. Moreover, we observed 44 (25%) patients for whom the primary outcome was reached. That was in line with our required number of patients to show an AUC of 0.7 with a 95% CI of 0.19 (153 patients required: 46 with PICS and 107 without PICS). Secondly, female sex was not associated with an increased risk of psychiatric symptoms in multivariate analysis. Several studies have reported that women are at higher risk of PTSD symptoms than men. Preexisting psychiatric disorders were probably underestimated, explaining the lack of difference in our multivariate analysis. Thirdly, we did not use a PCL-5 cutoff to determine post-ICU PTSD symptoms. Several studies selected a PCL-5 cutoff score of 31 or 33 [26]. Half of our post-ICU patients with PTSD had a PCL-5 score of ≥31. Physical health and function, such as ICU-acquired weakness, may also affect mental health outcomes and may limit the understanding of the relationship between self-perceived discomfort and psychiatric outcomes [25]. Baseline of patient quality of life may have influenced the development of psychiatric outcomes after the ICU stay. Future research to explore the interplay between quality of life, ICU-related discomfort and psychiatric outcomes would offer a more holistic understanding of post-ICU recovery. Finally, frightening memories or delusions were not correlated with post-ICU psychiatric symptoms. We explain this by self-perceived patient reporting data instead of standardised reporting data. Future studies should consider these limitations to validate the efficacy of our predictive factors.

Conclusion

Self-perceived discomfort in ICU survivors was the most predictive factor for developing post-ICU psychiatric symptoms in PICS. Our data indicated that a score combining age ≤52 years, preexisting psychiatric symptoms, and self-perceived discomfort could predict the occurrence of anxiety, depression, or PTSD 3 months after ICU discharge. The increasing number of ICU survivors means that future studies and a continuous quality health care improvement strategy must focus on improving long-term patients’ outcomes and quality of life after ICU stay.

Supporting information

S1 Fig. Flowchart.

(TIF)

pone.0324099.s001.tif (49.2KB, tif)
S1 Table. The French IPREA questionnaire for assessing self-reported discomforts perceived by the critically ill patients, original version.

(DOCX)

pone.0324099.s002.docx (15.1KB, docx)
S2 Table. Self-reported discomforts perceived by the critically ill patients.

(DOCX)

pone.0324099.s003.docx (15.6KB, docx)
S1 File. Renamed 71e78.

(XLSX)

pone.0324099.s004.xlsx (65.7KB, xlsx)

Acknowledgments

The authors are indebted to the nursing staff and psychologist of polyvalent intensive care units for providing the best care to their patients.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Michihiro Tsubaki

14 Jan 2025

Dear Dr. Ronflé,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: No

Reviewer #2: N/A

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The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: Thank you for the opportunity to review your study titled:

"Impact of self-perceived discomfort in critically ill patients on the occurrence of psychiatric symptoms in post-intensive care syndrome (PICS): A prospective observational study."

This study addresses an important topic with significant clinical relevance. However, several critical aspects of the methodology, statistical analysis, and results require further clarification and refinement. Specifically, issues related to the validation of measurement tools, transparency in statistical methods, and the rationale behind key analytical choices need to be addressed to ensure the robustness and reproducibility of the findings.

The comments provided below highlight areas requiring substantial revision. Addressing these concerns will significantly improve the clarity, accuracy, and scientific rigor of the manuscript.

A major revision is necessary to address these methodological and analytical concerns effectively.

Please refer to the detailed comments in the sections below.

Outcomes

Validation of French Version Scales:

It should be clarified whether the French versions of the scales used in this study have been validated. References to French domestic publications or conference presentations would be acceptable to support this validation.

Clinical Impression at ICU Discharge:

The study mentions the clinical impression of ICU physicians and psychologists at discharge to predict psychiatric symptoms three months post-ICU stay. However, the methodology lacks sufficient detail regarding how these predictions were made. Specifically:

Were predictions based solely on clinical interviews or supported by structured data?

What criteria or scoring methods were used to assess the risk?

These details are essential for evaluating the reliability and reproducibility of the findings.

Statistical Analysis

T-test vs. Welch’s Test:

Welch's t-test is generally considered more robust when there are concerns about equal variances between groups. The manuscript does not address whether the assumption of equal variances was tested. It would be more appropriate to use either Welch's t-test exclusively or clearly justify the choice of the standard t-test.

Categorical Variables:

For categorical variables, Fisher's exact test is preferable due to its robustness, especially for smaller sample sizes. Using only Fisher’s exact test could simplify and strengthen the statistical approach.

Multivariate Model Construction:

It is unclear whether the multivariate models were built using a forced-entry method or another approach (e.g., stepwise selection). The manuscript should explicitly state the method used for model construction.

Results

Cutoff Values:

The rationale for using cutoff values instead of continuous variables is not provided. Continuous data might offer more granularity and statistical power. Additionally, the precision of the cutoff values seems questionable and should be justified statistically.

Reason for Three Models:

The reason for constructing three separate models is not explained. Furthermore, no model fit indices (e.g., AIC, BIC, or R-squared) are reported, making it impossible to determine which model performs best.

Expression of Primary Outcome:

The phrase "achieved primary outcome" implies a positive connotation, which might not be appropriate in this context. A more neutral expression, such as "primary outcome was assessed" or "primary outcome was observed," would be preferable.

Statistical Method for Clinical Impression:

The statistical method used to analyze "the clinical impression of the physician and psychologist" is not mentioned in the Methods section. This lack of clarity prevents a proper evaluation of the robustness of the results.

Reviewer #2: Review Comments to the Author

General Comment

The manuscript provides valuable insights into the role of self-perceived discomfort during ICU stays as a predictive factor for post-ICU psychiatric disorders. The methodology is sound, and the statistical analyses are appropriate for the study objectives. However, some areas require further clarification and refinement to enhance the robustness and interpretability of the findings.

Specific Comments

Sample Size and Attrition

The final analysis included 109 participants, which is below the minimum required sample size of 153 calculated during the study design phase. While the study provides meaningful results, the reduced sample size may limit the statistical power and generalizability of the findings.

Furthermore, the high attrition rate (37%, with 64 participants excluded due to loss to follow-up or incomplete data) is a concern. Although the authors report no significant differences between included and excluded participants, the impact of this attrition on the representativeness of the cohort should be discussed in more detail. It is recommended that future studies adopt measures to minimize attrition, such as more robust follow-up mechanisms or alternative methods for data collection.

Adjustment for Confounders

The study effectively uses multivariable logistic regression to adjust for confounding factors, including age, pre-existing psychiatric disorders, and IPREA scores. However, quality of life (QoL) was evaluated as a secondary outcome and not included as a potential confounding factor in the analysis. Considering that QoL is closely associated with both ICU experiences and psychiatric outcomes, its exclusion as a covariate may limit the understanding of its role in mediating or moderating the relationship between self-perceived discomfort and psychiatric outcomes. Future studies could benefit from incorporating QoL as a covariate to disentangle its effects and provide more nuanced insights.

Role of QoL in the Analysis

While the study highlights the impact of psychiatric symptoms on QoL, it does not assess whether baseline QoL or changes in QoL might influence the development of psychiatric symptoms. Including QoL as a covariate or mediator in the statistical models could improve the comprehensiveness of the findings and clarify causal pathways.

Clarification in the Discussion

The discussion could be strengthened by acknowledging these limitations, particularly the small sample size, high attrition rate, and the exclusion of QoL as a covariate. Additionally, providing recommendations for future research to explore the interplay between QoL, ICU-related discomfort, and psychiatric outcomes would offer a more holistic understanding of post-ICU recovery.

Conclusion

The manuscript makes a significant contribution to understanding post-ICU psychiatric disorders, but addressing the sample size limitations, high attrition rate, and the interplay between QoL and psychiatric outcomes would improve its clinical relevance. I recommend revising the discussion to acknowledge these limitations and consider their implications for future research. These enhancements would increase the robustness of the findings and their applicability in clinical settings.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2025 Jun 6;20(6):e0324099. doi: 10.1371/journal.pone.0324099.r003

Author response to Decision Letter 0


12 Mar 2025

Response to Reviewer #1

Dear Reviewer,

Your comment about our manuscript made us possible to greatly improve him.

We hope that these responses will satisfy you.

Sincerely yours

Reviewer #1:

This study addresses an important topic with significant clinical relevance. However, several critical aspects of the methodology, statistical analysis, and results require further clarification and refinement. Specifically, issues related to the validation of measurement tools, transparency in statistical methods, and the rationale behind key analytical choices need to be addressed to ensure the robustness and reproducibility of the findings. The comments provided below highlight areas requiring substantial revision. Addressing these concerns will significantly improve the clarity, accuracy, and scientific rigor of the manuscript. A major revision is necessary to address these methodological and analytical concerns effectively.

We apologize if our manuscript suffers from several critical aspects of the methodology, statistical analysis and result. We carry out a new complete proofreading and we give you a total revised and cleaned manuscript.

Reviewer #1: Outcomes

Validation of French Version Scales:

It should be clarified whether the French versions of the scales used in this study have been validated. References to French domestic publications or conference presentations would be acceptable to support this validation.

At first, The IPREA study group used the 16-item version of the IPREA questionnaire to explore self-perceived discomfort (10.1007/s00134-010-1902-9, 10.1007/s00134-017-4991-x, 10.1007/s00134-018-05511-y).

The IPREA study group also proposed adding two items to the initial version of the IPREA questionnaire, leading to an 18-item version (ICU-related feelings of depression and ICU-related breathing discomfort). The 18-item version of IPREA was validated in a multicenter, cluster-randomized, controlled, two-parallel group French study. A total of 994 patients were included. This study confirms that this French questionnaire asking about patients’ self-perceived ICU discomforts are reliable and valid (10.1186/s12955-019-1101-5).

Text added in Materials and methods :

The 18-item French-language IPREA questionnaire (Supplementary Table 1), which was validated by the IPREA group in a large sample of critically ill patients hospitalised in 34 French ICUs (12).

Clinical Impression at ICU Discharge:

The study mentions the clinical impression of ICU physicians and psychologists at discharge to predict psychiatric symptoms three months post-ICU stay. However, the methodology lacks sufficient detail regarding how these predictions were made. Specifically:

Were predictions based solely on clinical interviews or supported by structured data?

What criteria or scoring methods were used to assess the risk?

These details are essential for evaluating the reliability and reproducibility of the findings.

We agree with your suggestions

Text added in materials and methods:

ICU physicians and psychologists met the patient for a clinical interview to assess the occurrence of psychiatric symptoms or not (anxiety, depression or PTSD; associated or not) before scoring his or her self-perceived discomfort. They used clinical experience and patients’ clinical data only (health status at ICU admission, condition of admission, number of stressful procedures, ICU length of stay, memories during sedation and frightening experiences).

Reviewer #1: Statistical Analysis

T-test vs. Welch’s Test:

Welch's t-test is generally considered more robust when there are concerns about equal variances between groups. The manuscript does not address whether the assumption of equal variances was tested. It would be more appropriate to use either Welch's t-test exclusively or clearly justify the choice of the standard t-test.

We opted to use the Mann-Whitney U test instead of Welch's t-test for comparing our continuous variables because it provides an even more flexible approach, as it does not rely on variance assumptions at all. Additionally, for small to moderate sample sizes, non-parametric methods often yield greater statistical power.

Categorical Variables:

For categorical variables, Fisher's exact test is preferable due to its robustness, especially for smaller sample sizes. Using only Fisher’s exact test could simplify and strengthen the statistical approach.

We agree with your suggestion.

We have adjusted the p-values by using Fisher’s Exact Test instead of the Chi-square test as recommended.

Text added in result : p value in Table 3

Multivariate Model Construction:

It is unclear whether the multivariate models were built using a forced-entry method or another approach (e.g., stepwise selection). The manuscript should explicitly state the method used for model construction.

The selection of variables included in our multivariate model was based on both statistical recommendations and clinical and scientific considerations. Considering the limited sample sizes, we followed the rule of thumb of having approximately 10 outcome events per predictor to avoid overly complex models and overfitting (Peduzzi et al.,1996). Given that our sample included n = 44 events, we adhered to this principle and limited the model to four variables to ensure reliable estimates.

Also, the choice of the four variables was guided by the univariate analysis p<0.2 and clinical relevance on known confounding factors. To assess the stability and robustness of our findings, we also tested multiple models, varying the included covariates. This sensitivity analysis helped to confirm that our main conclusions remained consistent across different model specifications.

Text added in materials and methods:

Multivariate logistic regression model was constructed following the commonly recommended guideline of maintaining approximately 10 outcome events per predictor variable to mitigate the risk of model overfitting and excessive complexity (15). The selection of variables was based on a univariate analysis threshold (p < 0.2) combined with clinical relevance and prior evidence on known confounders.

Reviewer #1: Results

Cutoff Values:

The rationale for using cutoff values instead of continuous variables is not provided. Continuous data might offer more granularity and statistical power. Additionally, the precision of the cutoff values seems questionable and should be justified statistically.

The categorization of variables was chosen to enhance clinical interpretability and ensure homogeneous risk groups. Keeping variables continuous in multivariate models did not reveal a clear effect, making categorization a more suitable approach.

Additionally, models with continuous variables showed poorer fit (higher AIC and BIC), further justifying categorization. While we acknowledge the potential gain in statistical power with continuous variables, this was not a limitation here, as a significant effect was detected using categorized variables.

For reference, the table below presents the models with variables in their continuous form.

Table 2. Effect of variables on the PICS occurence at 3 months in multivariate analysis

OR (95% CI) p value

Model 1 (AIC=139.8, BIC=150.5)

IPREA score 0.98 (0.95 – 1.01) 0.248

Psychiatric history 3.4 (0.94 – 12.39) 0.06

Age 1.03 (1 – 1.06) 0.06

Model 2 (AIC=141.5, BIC=154.9)

IPREA score 0.98 (0.95 – 1.01) 0.29

Psychiatric history 3.6 (1 – 13.27) 0.054

Age 1.04 (1 – 1.07) 0.024

Health status with limitation of activity a 2 (0.7 - 5.67) 0.20

Model 3 (AIC=143.1, BIC=159.2)

IPREA score 0.99 (0.95 – 1.02) 0.43

Psychiatric history 3.48 (0.94 – 12.85) 0.06

Age 1.04 (1 – 1.1) 0.02

Health status with limitation of activity a 2.2 (0.75 – 6.4) 0.15

Female sex 1.85 (0.74 - 4.6) 0.19

Text added in material and methods:

Variables were categorized to improve clinical interpretability and define homogeneous risk groups, with cutoff values determined using receiver operating characteristic (ROC) curves and the Youden index.

Reason for Three Models:

The reason for constructing three separate models is not explained. Furthermore, no model fit indices (e.g., AIC, BIC, or R-squared) are reported, making it impossible to determine which model performs best.

To assess the stability and robustness of our findings, we tested multiple models, varying the included covariates. This sensitivity analysis helped to confirm that our main conclusions remained consistent across different model specifications. We have provided AIC and BIC for each multivariate model to facilitate model comparison and assess which model performs best.

Text added in methods:

To evaluate the stability and robustness of our findings, we conducted sensitivity analyses by testing multiple model specifications with varying covariate selections. This approach allowed us to confirm the consistency and reliability of our main conclusions across different analytical frameworks. AIC and BIC values were also reported for each multivariate model to assess model fit and complexity.

Text added in result:

AIC and BIC in Table 2

Expression of Primary Outcome:

The phrase "achieved primary outcome" implies a positive connotation, which might not be appropriate in this context. A more neutral expression, such as "primary outcome was assessed" or "primary outcome was observed," would be preferable.

We agree about your suggestion. We applied the correction in your manuscript.

Text added in result and table:

The primary outcome was observed in 44 (40%) patients of our cohort study.

The patients for whom the primary outcome was observed had their quality of life reduced according to the WHOQOL-BREF questionnaire.

Statistical Method for Clinical Impression:

The statistical method used to analyze "the clinical impression of the physician and psychologist" is not mentioned in the Methods section. This lack of clarity prevents a proper evaluation of the robustness of the results.

We explicit the method in the article and reword the sentence.

Text added in methods:

Agreement between the patient's feeling of distress as assessed by the physician or psychologist at ICU discharge to the occurrence of psychiatric symptoms at 3-months was evaluated using the Cohen's kappa coefficient, which measures inter-rater reliability beyond chance, with p-values assessing its significance against zero.

Response to Reviewer #2

Dear Reviewer,

The new version of our manuscript includes all your suggestions.

We hope that these responses will satisfy you.

Sincerely yours

Reviewer #2: General Comment

The manuscript provides valuable insights into the role of self-perceived discomfort during ICU stays as a predictive factor for post-ICU psychiatric disorders. The methodology is sound, and the statistical analyses are appropriate for the study objectives. However, some areas require further clarification and refinement to enhance the robustness and interpretability of the findings.

We hope to carefully clarify your suggestions.

Reviewer #2: Specific Comments

Sample Size and Attrition

The final analysis included 109 participants, which is below the minimum required sample size of 153 calculated during the study design phase. While the study provides meaningful results, the reduced sample size may limit the statistical power and generalizability of the findings.

Furthermore, the high attrition rate (37%, with 64 participants excluded due to loss to follow-up or incomplete data) is a concern. Although the authors report no significant differences between included and excluded participants, the impact of this attrition on the representativeness of the cohort should be discussed in more detail. It is recommended that future studies adopt measures to minimize attrition, such as more robust follow-up mechanisms or alternative methods for data collection.

Thank you for your comment. We agree with you that high attrition is a comment. In your study, we observed 26% (46) of excluded patients for missing data due to no respond about the 3-month follow up. It is more than expected in your methodology (20% initially planned). However, the proportion of included patients with complete follow-up data at 3-months was slightly over 50% and, although comparable to that of many studies on post-ICU psychiatric symptoms (4,5,16). Moreover, we observed 44 patients for whom the primary outcome was observed. That in line of our patient number needed to show an area under the curve (AUC) of 0.7 with a 95% CI of 0.19 (153 patients required: 46 PICS and 107 no PICS).

Text added in discussion:

We observed 46 (26%) excluded patients for missing data, due to no respond after 3-month of follow up (20% initially planned). However, the proportion of included patients with complete follow-up data at 3-months was slightly over 50%? This was comparable to many studies on post-ICU psychiatric symptoms (4,5,17). Moreover, we observed 44 (25%) patients for whom the primary outcome was reached. That was in line with our required number of patients to show an AUC of 0.7 with a 95% CI of 0.19 (153 patients required: 46 with PICS and 107 without PICS).

Adjustment for Confounders

The study effectively uses multivariable logistic regression to adjust for confounding factors, including age, pre-existing psychiatric disorders, and IPREA scores. However, quality of life (QoL) was evaluated as a secondary outcome and not included as a potential confounding factor in the analysis. Considering that QoL is closely associated with both ICU experiences and psychiatric outcomes, its exclusion as a covariate may limit the understanding of its role in mediating or moderating the relationship between self-perceived discomfort and psychiatric outcomes. Future studies could benefit from incorporating QoL as a covariate to disentangle its effects and provide more nuanced insights.

We are in line about your thinking. The increasing number of ICU survivors means that future studies and a continuous quality health care improvement strategy must focus on improving long-term patients' outcomes and quality of life after ICU stay. However, in our study, we assessed the quality of ICU patients’ life after the ICU stay in order to highlight the impact of self-perceived discomfort and also post intensive care syndrome on quality of life. This data does not include in our multivariate analysis because she was observed not at ICU discharge but 3-month after. Measuring quality of life at ICU discharge seems not suitable for us.

If we incorporated quality of life as an adjustment variable in the multivariate models, the conclusions remain unchanged from those presented in our study. Since AIC and BIC values were better without this variable, we propose maintaining the original results.

Table 2. Effect of variables on the PICS occurence at 3 months in multivariate analysis

OR (95% CI) p value

Model 4 (AIC=49.5, BIC=62.9)

IPREA score ⩾ 13 3.7 (1.4 - 10) 0.009

Psychiatric history 3.5 (0.9 - 13.4) 0.06

Age ⩽ 52 y 2.6 (1 - 6.8) 0.06

QoL 0.7 (0.4 – 1.3) 0.32

Model 5 (AIC=66, BIC=82.1)

IPREA score ⩾ 13 3.8 (1.4 - 10) 0.01

Psychiatric history 3.6 (0.9 - 14) 0.06

Age ⩽ 52 y 3.2 (1.1 - 9.5) 0.03

Health status with limitation of activity a 1.8 (0.6 - 5.2) 0.3

QoL 0.8 (0.4 – 1.4) 0.38

Model 6 (AIC=87.3, BIC=106.1)

IPREA score ⩾ 13 3.4 (1.2 - 9.1) 0.02

Psychiatric history 3.5 (0.9 - 13.3) 0.07

Age ⩽ 52 y 3.6 (1.2 - 11.1) 0.02

Health status with limitation of activity a 2 (0.7 – 5.7) 0.22

Female sex 1.7 (0.7 - 4.5) 0.3

QoL 0.8 (0.4 – 1.4) 0.35

On the other hand, physical health and function, such as ICU-acquired weakness at ICU discharge, may also affect mental health outcomes. This data was not reported in our study. We included this comment in our discussion.

Text added in discussion:

Physical health and function, such as ICU-acquired weakness, may also affect mental health outcomes and may limit the understanding of the relationship between self-perceived discomfort and psychiatric outcomes (25).

Role of QoL in the Analysis

While the study highlights the impact of psychiatric symptoms on QoL, it does not assess whether baseline QoL or cha

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Decision Letter 1

Michihiro Tsubaki

22 Apr 2025

<p>Impact of self-perceived discomfort in critically ill patients on the occurrence of psychiatric symptoms in post-intensive care syndrome (PICS): A prospective observational study

PONE-D-24-52846R1

Dear Dr. Ronflé,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Acceptance letter

Michihiro Tsubaki

PONE-D-24-52846R1

PLOS ONE

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Flowchart.

    (TIF)

    pone.0324099.s001.tif (49.2KB, tif)
    S1 Table. The French IPREA questionnaire for assessing self-reported discomforts perceived by the critically ill patients, original version.

    (DOCX)

    pone.0324099.s002.docx (15.1KB, docx)
    S2 Table. Self-reported discomforts perceived by the critically ill patients.

    (DOCX)

    pone.0324099.s003.docx (15.6KB, docx)
    S1 File. Renamed 71e78.

    (XLSX)

    pone.0324099.s004.xlsx (65.7KB, xlsx)
    Attachment

    Submitted filename: response to reviewers plos one 2.docx

    pone.0324099.s006.docx (46.3KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


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