Relationship between no-visitation policy and the development of delirium in patients admitted to the intensive care unit.

BACKGROUND: Due to the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) pandemic, many hospitals imposed a no-visitation policy for visiting patients in hospitals to prevent the transmission of SARS-CoV-2 among visitors and patients. The objective of this study was to investigate the association between the no-visitation policy and delirium in intensive care unit (ICU) patients.
METHODS: This was a single-center, before-after comparative study. Patients were admitted to a mixed medical-surgical ICU from September 6, 2019 to October 18, 2020. Because no-visitation policy was implemented on February 26, 2020, we compared patients admitted after this date (after phase) with the patients admitted before the no-visitation policy (before phase) was implemented. The primary outcome was the incidence of delirium during the ICU stay. Cox regression was used for the primary analysis and was calculated using hazard ratios (HRs) and 95% confidence intervals (CIs). Covariates were age, sex, APACHE II, dementia, emergency surgery, benzodiazepine, and mechanical ventilation use.
RESULTS: Of the total 200 patients consecutively recruited, 100 were exposed to a no-visitation policy. The number of patients who developed delirium during ICU stay during the before phase and the after phase were 59 (59%) and 64 (64%), respectively (P = 0.127). The adjusted HR of no-visitation policy for the number of days until the first development of delirium during the ICU stay was 0.895 (0.613-1.306).
CONCLUSION: The no-visitation policy was not associated with the development of delirium in ICU patients.

Introduction

Delirium is an important problem for critically ill patients, occurring in 83% of mechanically ventilated patients during their intensive care unit (ICU) stay, and in approximately 30% of patients during their ICU stay [1-3]. The development of delirium during ICU stay is associated with longer hospital stays and higher mortality rates [1, 4]. Various interventions have been conducted to prevent delirium in critically ill patients [5, 6]. Among these interventions, visitation has been considered as a possible measure to prevent delirium [7]. The types of visitations in the ICU can be categorized in several ways [8]. In open visitation, visitors are allowed to visit at any time and approximately 30% of the world’s ICUs use this method [9]. Next, in restricted visitation, visitors are not allowed to visit except during the hours they are allowed to visit. According to a worldwide survey, approximately 70% of ICUs have restricted visitation [9]. Additionally, in flexible visitation, which was used in past research interventions, visitors were allowed 12 hours of visitation per day [7, 10]. Hospital or ICU-based no-visitation policy is generally not allowed due to ethical and common-sensical reasons, except for the measurement of infection. In Japan, many ICUs have restricted visitation, and 75% of ICUs have a time limit for a single visitation [11].

Previous studies have indicated that flexible visitation policies have been associated with a lower incidence of delirium as compared to restricted visitation policies in ICUs [7, 12]. However, in a recent randomized controlled trial (RCT) that examined the effect of flexible and restricted visitation on the development of delirium, no significant effect of flexible visitation on preventing delirium was confirmed [10]. That is, a longer visitation time was not associated with the development of delirium. However, few studies have examined whether a no-visiting policy influenced the development of delirium. When visitation is prohibited, patients are unable to see their families or loved ones, which may contribute to the development of delirium.

In December 2019, the first coronavirus disease 2019 (COVID-19) case was identified in Wuhan, Hubei Province, China. The COVID-19 has since become a pandemic. In Japan, COVID-19 has repeatedly spread and decreased. To prevent the introduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from outside the hospital, some hospitals in Japan have taken measures to prohibit family members from visiting patients.

A previous before-after comparative study examining whether no-visitation policy is associated with the development of delirium in the emergency admission population during the COVID-19 pandemic [13] concluded that a no-visitation policy was associated with a higher incidence of delirium. However, no studies have been conducted with intensive care unit (ICU) patients. Thus, the purpose of this study was to examine the hypothesis that the no visitation policy was associated with a higher incidence of delirium in critically ill patients. The primary outcome was the incidence of delirium during the ICU stay in this study.

Materials and methods

Study design

This was a single-center, before-after comparative, retrospective, and observational study. To prevent the transmission of SARS-CoV-2 between patients and visitors, from February 26, 2020, the hospital imposed a no-visitation policy on visitors to hospitalized patients. This study retrospectively compared the development of delirium before and after the implementation of the no-visitation policy.

Setting

This study was conducted in the medical-surgical ICU of the Kin-ikyo Chuo Hospital in Sapporo City, Japan. The hospital has 450 beds of which 6 are ICU beds.

The data was collected from September 6, 2019 to October 18, 2020. The period before the implementation of the no-visitation policy lasted between September 6, 2019 and February 25, 2020, and the period after the implementation of the no-visitation policy lasted between February 27, 2020 and October 18, 2020.

Participants

The inclusion criterion for patients in this study was patients aged 18 years or older who stayed in the ICU for more than 48 hours. The exclusion criteria for this study were patients: (1) readmitted to the ICU during the study period; (2) in a constant coma (Richmond Agitation-Sedation Scale score ≤ -4) during the ICU stay, (3) with delirium at the time of ICU admission, (4) with apparent central nervous system disease as revealed by diagnostic imaging, and (5) with difficulty in communicating [14].

The recruitment process is shown in Fig 1. First, patients who were admitted at the time when the no-visitation policy was began to be implemented were excluded because they had been exposed to both visitation policies. Next, patients who were admitted after the implementation of the no-visitation policy were consecutively screened and enrolled until this number reached 100, according to the sample size calculation. Subsequently, patients who were admitted before the implementation of the no-visitation policy were consecutively screened retrospectively from the time of implementation of the no-visitation policy and enrolled until this number reached 100.

Fig 1

Schematic illustration of the recruitment process.

Before the no-visitation policy (before phase)

Before the implementation of the no-visitation policy, the ICU implemented a restricted visitation policy. Visitors were allowed to visit during the following times: (1) 11:00∼12:00, (2) 14:30∼16:00, and (3) 18:30∼20:00. We defined this phase as the “before phase.”

No-visitation policy in the study (after phase)

No-visitation policy meant that visitors were completely prohibited from visiting the patient while the patient was hospitalized. This phase was defined as “after phase.” However, there were a few cases where family members were allowed to visit, such as when the patient’s death was inevitable, with the physician or nurse manager’s permission. Virtual visiting and telephone communication between patients and their families was uncommon at this time in the ICU. Based on the family’s request and equipment availability, such as cell phones, tablets, and smartphones, we arranged virtual visits or telephone communication between the patient and family.

Variable/Data collection

We retrospectively collected data from the electronic medical records for this study. We collected patients’ characteristics including age, sex, and past medical history, such as dementia and mental disorders. Clinical data, including the primary reason for ICU admission, the Acute Physiology and Chronic Health Evaluation II (APACHE II), and the Sequential Organ Failure Assessment (SOFA) within 24 hours of ICU admission were also collected. Additionally, duration of mechanical ventilation, ICU length of stay, hospital length of stay, opioid use, sedatives use, mortality, use of continuous renal replacement therapy, use of intra-aortic balloon pumping, use of extra corporeal oxygen exchange during ICU stay were recorded. Sepsis was defined as the presence of an infectious disease diagnosis and an elevated SOFA score of two or more points [15]. Benzodiazepines use was defined as continuous intravenous benzodiazepines for more than 24 hours. Mental disorders comprised any mental illness, including schizophrenia and depression. However, dementia was not considered as a mental disorder in this study because we used it as a covariate in the analysis.

To detect delirium, the Intensive Care Delirium Screening Checklist (ICDSC) [16] was obtained from the electronic medical chart. The ICDSC was routinely evaluated three times a day (at 08:00,16:00, and 24:00) by trained ICU nurses and recorded on the medical chart three times a day until patients were discharged from the ICU. The ICDSC is a 0–8-point scale, with a score of four or higher indicating that the patient had delirium [16]. The diagnostic characteristics of ICDSCs were evaluated. The sensitivity and specificity of the Japanese version of the ICDSC with a cutoff of four points were as follows: 97% sensitivity and 97% specificity of the ICDSC for delirium [17]. Additionally, a meta-analysis revealed that the pooled sensitivity and specificity of the ICDSC were 74% (95% CI: 65.3 to 81.5%) and 81.9% (95% CI: 76.7 to 86.4%), respectively [18]. If a patient scored four or more points on the ICDSC at least once during the day, the patient was considered to have delirium in this study. Visitation for patients was noted in the medical records, and we extracted the data throughout the study period.

Sample size

To analyze the association between the number of days until the development of delirium and visitation policies, the sample size was calculated as follows: the incidence of delirium as an event was assumed to be 40% based on previous literature [1-3]. The covariates to be adjusted in the Cox proportional-hazards model were set to 7. Based on these conditions, we used the rule that 10 events per variable were required to perform a Cox proportional-hazards regression and set the required sample size to 200 [19, 20].

Statistical analysis

The data obtained were expressed as median and interquartile range (IQR) for continuous variables and as proportions for categorical variables. Fisher’s exact, χ-square, and Wilcoxon rank-sum tests were used to compare patient characteristics in the two phases.

The patients were divided into two groups, before and after the implementation of the no-visitation policy, and were compared using Kaplan-Meier curves with the number of days until the development of delirium as the outcome. The log-rank test was used to compare the two groups. In the multivariate analysis, we used the Cox proportional-hazards models to analyze the association between the number of days until the onset of delirium as the objective variable and the visitation policies. We calculated the hazard ratio (HR) and 95% confidence interval (CI) for the development of delirium. We predefined covariates for multivariable analysis based on past studies and clinical expert knowledge. We selected age [21-23], sex, APACHE II [21], history of dementia [24], ICU admission after emergency surgery [22, 23], use of benzodiazepine [21, 23, 25], and mechanical ventilation use [26] for covariates. To avoid multicollinearity, the APACHE II score was calculated without using age as a covariate. Dose of opioids was not included in the model, because most patients receiving opioids were also receiving mechanical ventilation.

Simple imputation was used to handle missing values [27] for the ICDSC. We defined deficit as the day when none of the three evaluations were recorded. The missing values of the ICDSC were replaced by the average of the day before or after. For other missing variables, we planned to use multiple imputations.

All statistical tests were two-tailed, and the statistical significance was set at 0.05. We used R statistical software (version 4.0.2, The R Foundation for Statistical Computing, Vienna, Austria, https://www.r-project.org/) for the statistical analysis.

Sensitivity analysis

We conducted a sensitivity analysis to test the robustness of the model’s assumptions. We conducted three sensitivity analyses.

First, we conducted a multivariate logistic regression analysis and analyzed the relationship between the development of delirium and the visitation policies. The same covariates were included in this model for multivariable adjustment.

Second, in order to remove the effects of duration of mechanical ventilation on our findings, we changed the covariate of mechanical ventilation use as binomial variable to the duration of mechanical ventilation, and conducted the Cox proportional-hazards model. All covariates included in the primary analysis were also included into the model, with the exception of mechanical ventilation use.

Third, a previous study reported the occurrence of false positives when the ICDSC was used to determine delirium in patients with dementia and mental disorders [16]. Therefore, we conducted an analysis using Cox proportional-hazards model, excluding patients with dementia or mental disorders. All covariates were the same as the ones in the primary analysis except for dementia.

Ethical considerations

Ethical approval for the research protocol was granted by the ethical review board of the Graduate School of Nursing, Sapporo City University, Sapporo, Japan, (approval ID 2021-9-3) and the participating institution (approval ID 2020–44). The requirement for informed consent was waived because of the anonymous nature of the data.

Results

Participant characteristics

The patient flowchart is shown in Fig 2. Throughout the study period, 467 patients were admitted to the ICU. A total of 267 patients were excluded. Consequently, a total of 200 patients (100 patients from the before phase and 100 from the after phase) were included in this study (Fig 2). Patient characteristics are shown in Table 1. Patients from the after phase had significantly higher APACHE II scores, mortality rates, mechanical ventilator use rates, and longer duration of mechanical ventilation, compared to those from the before phase. No patients with COVID-19 were admitted in the ICU during the study period.

Fig 2

Patient recruitment flowchart.

Table 1

Patient characteristics before and after the no-visitation policy.

Variables	n = 200	Before phase n = 100	After phase n = 100	p-valuea
Age, median [IQR]	76.0 [68.8–84.2]	75.5 [67.8–84.2]	76.0 [69.0–84.2]	.841
Age ≧ 65 yr, n (%)	161 (80.5)	80 (80.0)	81 (81.0)	.858
Female, n (%)	76 (38.0)	40 (40.0)	36 (36.0)	.560
Pre-existing medical condition
Hypertension, n (%)	103 (51.5)	45 (45.0)	58 (58.0)	.066
Dementia, n (%)	28 (14.0)	10 (10.0)	18 (18.0)	.103
Mental disorder b , n (%)	21 (10.5)	12 (12.0)	9 (9.0)	.489
ICU admission type, n (%)
Medical	144 (72.0)	68 (68.0)	76 (76.0)	.367
Emergency surgery	19 (9.5)	12 (12.0)	7 (7.0)
Scheduled surgery	37 (18.5)	20 (20.0)	17 (17.0)
Primary reason for ICU admission, n (%)
Respiratory failure	53 (26.5)	30 (30.0)	23 (23.0)	.055
CHF/ACS/Arrhythmia	28 (14.0)	7 (7.0)	21 (21.0)
Sepsis	28 (14.0)	15 (15.0)	13 (13.0)
Cardiovascular surgery	25 (12.5)	16 (16.0)	9 (9.0)
Abdominal surgery	15 (7.5)	9 (9.0)	6 (6.0)
Other surgery	15 (7.5)	5 (5.0)	10 (10.0)
Others	36 (18.0)	18 (18.0)	18 (18.0)
ICU length of stay, median [IQR]	5.0 [4.0–8.2]	5.0 [4.0–7.2]	6.0 [4.0–10.0]	.209
Hospital length of stay, median [IQR]	24.0 [13.8–42.0]	22.5 [13.0–42.0]	25.5 [15.0–39.8]	.166
APACHE II, median [IQR]	18.0 [12.0–23.2]	17.0 [11.0–22.0]	19.5 [13.8–26.2]	.008
SOFA, median [IQR]	6.0 [4.0–9.0]	6.0 [3.8–9.0]	7.0 [4.0–9.0]	.105
Mechanical ventilation use, n (%)	117 (58.5)	50 (50.0)	67 (67.0)	.015
Duration of mechanical ventilation, median [IQR]	4.0 [2.0–8.0]	3.0 [2.0–6.8]	5.0 [3.0–10.0]	.013
Opioid use, n (%)	114 (57.0)	46 (46.0)	68 (68.0)	.002
Benzodiazepine use, n (%)	16 (8.0)	7 (7.0)	9 (9.0)	.602
Sedative use, n (%)	134 (67.0)	63 (63.0)	71 (71.0)	.229
CRRT, n (%)	28 (14.0)	11 (11.0)	17 (17.0)	.221
IABP, n (%)	10 (5.0)	5 (5.0)	5 (5.0)	>.999
ECMO, n (%)	5 (2.5)	2 (2.0)	3 (3.0)	>.999
Mortality, n (%)
Death in hospital, n(%)	27 (13.5)	7 (7.0)	20 (20.0)	.026
Death in ICU, n (%)	18 (9.0)	10 (10.0)	8 (8.0)

aWilcoxon rank sum test; Pearson’s chi-squared test; Fisher’s exact test.

bMental disorder; schizophrenia, depression, bipolar disorder, alcoholism, adjustment disorder, and panic disorder.

IQR, interquartile range; CHF/ACS, congestive heart failure/acute coronary syndrome; APACHE II, Acute Physiology and Chronic Health Evaluation II; SOFA, sepsis-related organ failure assessment; CRRT, continuous renal replacement therapy; IABP, intra-aortic balloon pumping; ECMO, extracorporeal membrane oxygenation.

Deficits in ICDSC data were observed in 2.4% of the patients and were only limited to the day of ICU admission or the day of ICU discharge. Therefore, missing values on the day of ICU admission were replaced by the average ICDSC score of the following day, and deficits on the day of ICU discharge were replaced by the average of the ICDSC score of the previous day. There were no missing data other than the ICDSC scores mentioned above.

Univariable analysis of outcome data

Of the 200 patients admitted to the ICU during the study period, 123 (61.5%) patients developed delirium. The difference in the incidence of delirium between the before and after phases (59% vs. 64%, p = 0.127) was not statistically significant. The number of visits per patient during ICU stay in each phase is showed in S1 Fig. The proportion of patients who were visited during the after phase was significantly lower than that during the before phase (19% vs. 92%, p<0.001).

The median number of days for onset of delirium among patients who developed delirium before and after the implementation of the no-visitation policy was not significantly different (2 [IQR], 2–3 vs 2 [IQR], 2–3, p = 0.696). This result does not take into account whether patients had been sedated or not. The Kaplan-Meier curve between the before and after phases for the development of delirium is shown in Fig 3. The log-rank test did not show a significant difference between the two phases (p = 0.61).

Fig 3

Kaplan-Meier curve: Time until the development of delirium during the ICU stay for the before and after phases.

Multivariable analysis

The results of the unadjusted and adjusted Cox regression models are presented in Table 2. The no-visitation policy was not significantly associated with the development of delirium after adjusting for covariates (HR 0.895, 95% CI, 0.613–1.306; p = 0.525). The presence of dementia, higher APACHE II score, and mechanical ventilation use were significantly associated with the development of delirium.

Table 2

Estimates of the hazard ratios of variables on development of delirium in the Cox proportional-hazards models.

Variable	unadjusted		adjusteda
	HR (95%CI)	p-value	HR (95%CI)	p-value
No-visitation policy	1.157 (0.810–1.652)	.421	0.895 (0.613–1.306)	.565
Age	1.004 (0.991–1.017)	.543	0.998 (0.984–1.012)	.778
Male	1.109 (0.765–1.607)	.585	1.118 (0.757–1.653)	.573
Dementia	2.176 (1.383–3.421)	< .001	2.078 (1.251–3.454)	.004
Emergency surgery	1.705 (0.990–2.935)	.054	1.512 (0.831–2.750)	.174
APACHE II b	1.048 (1.026–1.071)	< .001	1.039 (1.015–1.064)	.001
Benzodiazepine use	1.484 (0.849–2.593)	.166	1.071 (0.592–1.939)	.819
Mechanical ventilation use	2.317 (1.550–3.463)	< .001	1.735 (1.100–2.736)	.017

aThe Cox proportional-hazards model was used to adjust for eight variables: no-visitation policy, age, sex, dementia, emergency surgery, APACHEII, benzodiazepine use, and mechanical ventilation use.

bAPACHEII score was calculated without age related score.

HR, hazard ratio; CI, Confidence interval.

First, the multivariate logistic regression was performed to determine the outcome of the development of delirium and its results are presented in S1 Table. The results indicated that the no-visitation policy was not significantly associated with the development of delirium (OR 0.714, 95%CI 0.354–1.415). Second, the results of the Cox proportional-hazards model with a covariate changed from mechanical ventilation use to duration of mechanical ventilation are shown in S2 Table. The results showed no association between the no-visitation policy and the number of days until the development of delirium (HR 0.938, 95%CI 0.644–1.367). Third, the results of the Cox proportional-hazards model without the inclusion of patients with dementia or mental disorders are shown in S3 Table. The results showed no association between the no-visitation policy and the number of days until the development of delirium (HR 0.890, 95%CI 0.572–1.385).

Discussion

In this single-center before-after, comparative, and retrospective observational study, the no-visitation policy was not associated with the development of delirium in critically ill patients. The robustness of the findings is demonstrated in the sensitivity analysis.

Based on our findings, no visitation may not be associated with delirium in critically ill patients. The results of this study are consistent with the results of a previous RCT comparing the incidence of delirium in flexible visitation and restricted visitation [10]. However, in a previous observational before-after study comparing no visitation and restricted visitation in emergency patients, the incidence of delirium was higher in the no-visitation group [13]. There are several possible reasons for these different results. In the present study, we screened delirium three times a day using ICDSC by trained nurses; however, past studies did not screen every patient. They considered patients to be diagnosed with delirium by a psychiatrist based on consultation. As noted, detection bias may not be avoided during the COVID-19 pandemic; however, the number of consultations before and after visitation policy change has not been reported. In addition, the targeted patient population was different. In this study, critically ill patients were targeted, while in the previous study, emergency inpatients were targeted.

There are several possible reasons for the lack of association between the number of days until the development of delirium and the no visitation policy. First, there are many risk factors for delirium in critically ill patients. In the ICU, risk factors for delirium include drugs, severity of illness, emergency surgery, and invasive treatments such as mechanical ventilators [28]. Therefore, even if visitation is effective in preventing delirium, it may not lead to the prevention of delirium in ICU patients, given the iatrogenic factors that contribute to the development of delirium. This is probably the main reason for finding no relationship between the number of days until the development of delirium and the no visitation policy in this study. Second, the impaired level of consciousness of ICU patients may have contributed to the lack of association between the number of days until the development of delirium and the no visitation policy. In this study, 58% of the patients were on mechanical ventilators, and 67% were receiving sedatives. Therefore, it is likely that more than half of the patients had a period of poor consciousness. The incidence of delirium has been reduced in a before-after comparative study comparing restricted visitation with flexible visitation [7]. However, as compared to the patients in our study, the proportion of patients with mechanical ventilation use and sedative use in the previous study was less than half. The patients may not recognize the visitors as a result of poor consciousness. This may reduce the effectiveness of visits to prevent delirium.

Strengths of the study

This study has two strengths: First, it investigated the association between no-visitation policy and delirium in critically ill patients. No visitation cannot be implemented as an intervention due to ethical issues. Therefore, a study like this would not have been possible under normal circumstances and could only be conducted under special circumstances. Second, no-visitation policy was implemented as a measure against infectious diseases and not for the purpose of this study; hence, there was no performer bias.

Limitations of the study

This study has several limitations: First, as it was a before-and-after comparative study, unknown confounding factors may not have been controlled for. Second, this study was a single-center study; thus, external validity should be considered with caution. Third, even with a no-visitation policy, a few visitors stayed with the patients for a short time (i.e., a brief period of time just before the patient’s death); however, we evaluated the no-visitation policy, not no-visitation. Thus, we did not exclude the patients who met visitors. Given the paucity of visitation opportunities and the short time, we did not consider that visitation during the after period interfered with our findings. Fourth, there may be an Information bias regarding the presence of dementia or mental disorders of the variables used in the multivariate and sensitivity analyses. The presence of these diseases was determined by the medical records, which may have contributed to a bias because there might have been cases that were either not disclosed in the medical records or were documented as mild mental disorders. However, we considered that those cases occurred randomly in both phases and did not significantly affect the results. Fifth, the exact number of online communications between patients and family members during the no-visitation policy is unknown. However, we did not have online communication manual and structured, thus we considered the contribution of online communication on our findings to have been minimum.

Implications for clinical practice

We emphasize that the results of this study do not indicate that ICU patients do not need to have visitors. This is because delirium is only one indicator of the effectiveness of ICU visits. A previous study showed that flexible family visitation to critically ill patients reduce family anxiety and depression and increases satisfaction [10]. Another study showed a reduction in patients’ own anxiety symptoms under unrestricted visitation [29]. Therefore, visitation has the potential for a variety of positive effects on critically ill patients and their families. Above all, visitation is the right of patients and their families. However, the prohibition of visitation was not associated with the development of delirium, which is important for clarifying the mechanism of delirium.

Conclusion

This study showed that no visitation policy was not associated with the incidence of delirium and the number of days until the development of delirium in critically ill patients in the ICU.

Histograms of the number of visits per patient during ICU stay in each phase.

(TIF)

Click here for additional data file.

Estimates of the adjusted odds ratios of variables on the incidence of delirium in the multivariate logistic regression.

(DOCX)

Click here for additional data file.

Estimates of the adjusted hazard ratios of variables on the development of delirium in the Cox proportional-hazards models.

(DOCX)

Click here for additional data file.

Estimates of the adjusted hazard ratios of variables on the development of delirium in the Cox proportional-hazards models removing patients with dementia or mental disorders from the primary analysis.

(DOCX)

Click here for additional data file.

Dataset used for Kaplan-Meier curve showing time to delirium during ICU stay in each phase and used for histogram showing visitors per patient in each phase.

(XLSX)

Click here for additional data file.

29 Dec 2021

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Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

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Reviewer #1: In this study, the authors investigated the association between prohibited visitation policies and delirium in 200 intensive care unit (ICU) patients. They found that the adjusted HR of no-visitation policy for the number of days until the first development of delirium during the ICU stay was 0.883 (0.603–1.294). So they concluded that the no-visiting policy was not associated with development of delirium in ICU patients. It is an interesting study, focusing on an important issue and it provides informative conclusions. I offer the following comments:

It is not clear the study design. It seems that it is a case-control study rather than a before-after comparative study. 200 patients were enrolled: 100 before and 100 after; so it seems that the enrollment was not consecutive. Please, better clarify this point.

The paragraph “Bias” needs to be better explained. The authors quote: “Differences in characteristics before and after the implementation of the 168 no-visitation policy existed. Therefore, we used multivariate analysis to adjust 169 for known confounders associated with delirium”. This point should be clearly explained and better addressed in the statistical analysis paragraph and in the results section. Moreover, the authors report in the Statistical analysis: “The covariates were as follows: age, sex, APACHE-II, history of dementia, ICU, admission after emergency surgery, use of benzodiazepine, and use of 194 mechanical ventilation. To avoid multicollinearity, the APACHE II score was 195 calculated without using age as a covariate”. How were these variables chosen (step-wise selection? Univariate analysis”? This point is critical for the analysis. All these points might have influenced study results.

The paragraph “Sample size” is not clear and the sample size calculation should be better reported and more robustly based on statistical data (power of the analysis?)

Lines 249-251: The incidence of delirium was higher during 250 the no-visitation policy than during the usual visitation policy (64% vs. 59%, 251 p=0.127). This sentence should be rephrased as there is no difference in the incidence of delirium between the two groups.

Table 2. It is not clear whether these variables for adjusted for each others. Please, specify.

Figure is interesting but it should be improved from a graphical point of view.

Reviewer #2: Takeshi Unoki et al. Present a retrospective study on the impact of the no-visitation policy on patients admitted to ICU during Covid-19 pandemic. They concluded that the no visitation policy was not associated

to an higher incidence of delirium.

Anyway, I do have some comments.

1) The calculation of the sample size should be better defined

2) In the bias section, the authors declare to use multivariate analysis to adjust for known

confounders associated with delirium. Can the authors please state which are the

counfounders and how they were chosen?

3) In the “No visitation policy in the study” paragraph, the authors state that some patients had

access to online communications with the families. How many patients had the possibility? Do

you think this might be a bias?

4) Can the authors please explain what they mean with “medical ventilation”?

5) Can the authors define which were the psychiatric disorders taken into account (i.e.

depression/schizophrenia etc)?

6) How did the authors address the patients with dementia or psychiatric disorders in the ICDSC

scale? I wonder if those patients should be excluded from the analysis.

7) I wonder what is the real impact of the higher percentage of opioids use and the higher number

of mechanical ventilation days in the no visitation group. As the authors state it as a study

limitation, could it be possible to perform a subanalysis excluding such a difference?

8) In line 252-253, the authors talk about the median number of days for onset of delirium.

Among these days, do the authors take into account also the days the patients were sedated?

**********

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Reviewer #1: No

Reviewer #2: No

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

3 Feb 2022

Response to the Editor and Reviewers

Comment

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

Response

We have revised the description of the manuscript according to PLOS ONE's style requirements.

Comment

2. This is a retrospective study, as such, we do not feel that any conclusions on the intervention effects can be supported; thus, we ask that you revise the text (especially, but not limited to, the title) to avoid unsupported statements.

Response

We totally agree with your comments. We have revised the title and relooked through the entire manuscript to ensure that any terms indicating the intervention effects were not used.

------Revised Manuscript------

Modified title: Relationship between no-visitation policy and the development of delirium in patients admitted to the intensive care unit

Comment

3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Response

We have added the grant number for this study in the ‘Funding Information’ section.

Comment

4. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

"Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

Reply

We have submitted the required minimum data set as S1 Data.

Reviewer’s comments:

Reviewer’s Responses to Questions

Comment to the Author

Comment

Reviewer #1:

In this study, the authors investigated the association between prohibited visitation policies and delirium in 200 intensive care unit (ICU) patients. They found that the adjusted HR of no-visitation policy for the number of days until the first development of delirium during the ICU stay was 0.883 (0.603–1.294). So they concluded that the no-visiting policy was not associated with development of delirium in ICU patients. It is an interesting study, focusing on an important issue and it provides informative conclusions. I offer the following comments:

1. It is not clear the study design. It seems that it is a case-control study rather than a before-after comparative study. 200 patients were enrolled: 100 before and 100 after; so it seems that the enrollment was not consecutive. Please, better clarify this point.

Reply

We apologize for the confusion due to our disorganized description. We revised the description of the methods and added a new Fig1 that explains the study design to make it easier easily to understand the methods.

This study is not a case-controlled study, but a single-center before-after, comparative, and retrospective observational study. Before and after the implementation of the no-visitation policy, eligible patients were consecutively enrolled until their number reached 100, respectively. We have revised the description of the methods and Fig.2 and added a new Fig 1. The revised description in the manuscript is as below, with the changed parts in red.

------Revised Manuscript------

P8, Line117

The recruitment process is shown in Fig 1. First, patients who were admitted at the time when the no-visitation policy was began to be implemented were excluded because they had been exposed to both visitation policies. Next, patients who were admitted after the implementation of the no-visitation policy were consecutively screened and enrolled until this number reached 100, according to the sample size calculation. Subsequently, patients who were admitted before the implementation of the no-visitation policy were consecutively screened retrospectively from the time of implementation of the no-visitation policy and enrolled until this number reached 100.

Comment

2. The paragraph “Bias” needs to be better explained. The authors quote: “Differences in characteristics before and after the implementation of the 168 no-visitation policy existed. Therefore, we used multivariate analysis to adjust 169 for known confounders associated with delirium”. This point should be clearly explained and better addressed in the statistical analysis paragraph and in the results section. Moreover, the authors report in the Statistical analysis: “The covariates were as follows: age, sex, APACHE-II, history of dementia, ICU, admission after emergency surgery, use of benzodiazepine, and use of 194 mechanical ventilation. To avoid multicollinearity, the APACHE II score was 195 calculated without using age as a covariate”. How were these variables chosen (step-wise selection? Univariate analysis”? This point is critical for the analysis. All these points might have influenced study results.

Reply

We apologize for the confusion caused due to inappropriate wording.

We attempted to explain how we analyzed and how we choose the covariates. First, the bias section was removed and a description regarding the analysis was integrated into the “Statistical analysis” section.

We choose the covariates based on past research that described factors for delirium incidents in ICU settings and clinical expert knowledge. This method was recommended, whereas the selection of covariates based on statistical methods (i.e., stepwise method) was not recommended by the guideline (Lederer et al., 2019).

Reference

Lederer, D. J., Bell, S. C., Branson, R. D., Chalmers, J. D., Marshall, R., Maslove, D. M., Ost, D. E., Punjabi, N. M., Schatz, M., Smyth, A. R., Stewart, P. W., Suissa, S., Adjei, A. A., Akdis, C. A., Azoulay, É., Bakker, J., Ballas, Z. K., Bardin, P. G., Barreiro, E., … Vincent, J.-L. (2019). Control of confounding and reporting of results in causal inference studies. Guidance for authors from editors of respiratory, sleep, and critical care journals. Annals of the American Thoracic Society, 16(1), 22–28. doi: 10.1513/AnnalsATS.201808-564PS

------Revised Manuscript------

P11, Line 188

The patients were divided into two groups, before and after the implementation of the no-visitation policy, and were compared using Kaplan-Meier curves with the number of days until the development of delirium as the outcome. The log-rank test was used to compare the two groups. In the multivariate analysis, we used the Cox proportional-hazards models to analyze the association between the number of days until the onset of delirium as the objective variable and the visitation policies. We calculated the hazard ratio (HR) and 95% confidence interval (CI) for the development of delirium. We predefined covariates for multivariable analysis, based on past studies and clinical expert knowledge. We selected age [21-23], sex, APACHE-II [21], history of dementia [24], ICU admission after emergency surgery [22,23] , use of benzodiazepine [21,23,25] and mechanical ventilation use [26] for covariates. To avoid multicollinearity, the APACHE II score was calculated without using age as a covariate. Dose of opioids was not included in the model, because most patients receiving opioids were also receiving mechanical ventilation.

Comment

3. The paragraph “Sample size” is not clear and the sample size calculation should be better reported and more robustly based on statistical data (power of the analysis?)

Reply

We apologize that the description was incomplete and contained errors.

In fact, when we calculated the sample size, we used the rule that 10 is the required number of events per variable in a Cox proportional-hazards regression analysis (Peduzzi et al., 1995). We also pre-determined seven variables to be adjusted in the Cox proportional-hazards model to examine the association between the no visitation policy and delirium. In addition, based on the previous literature, we estimated the incidence of delirium was around 40%. Based on this assumption, a sample size of 200 was required. We revised the sample size section. The revised manuscript is as below, with the changed parts in red.

Reference

Peduzzi, P., Concato, J., Feinstein, A. R., & Holford, T. R. (1995). Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. Journal of Clinical Epidemiology, 48(12), 1503–1510. doi:

10.1016/0895-4356(95)00048-8

------Revised Manuscript------

P10 Line:174

Sample size

To analyze the association between the number of days until the development of delirium and visitation policies, the sample size was calculated as follows: the incidence of delirium as an event was assumed to be 40% based on previous literature [1-3]. The covariates to be adjusted in the Cox proportional-hazards model were set to 7. Based on these conditions, we used the rule that 10 events per variable are required to perform a Cox proportional-hazards regression and set the required sample size to 200 [19,20].

Comment

4.Lines 249-251: The incidence of delirium was higher during 250 the no-visitation policy than during the usual visitation policy (64% vs. 59%, 251 p=0.127). This sentence should be rephrased as there is no difference in the incidence of delirium between the two groups.

Reply

We totally agree with your comments and have revised the sentence accordingly. The revised description is below, with the changed parts in red.

------Revised Manuscript------

P18 Line:263

Univariable analysis of outcome data

Of the 200 patients admitted to the ICU during the study period, 123 (61.5%) patients developed delirium. The difference in the incidence of delirium between the before and after phases (59% vs. 64%, p=0.127) was not statistically significant.

Comment

5. Table 2. It is not clear whether these variables for adjusted for each others. Please, specify.

Reply

Thank you for pointing this out.

All covariates described in the statistical section were included in the multivariable analysis for multivariable adjustment. We have shown the variables used for adjustments in the footnote of Table 2.

------Revised Manuscript------

P20 Line:290

aThe Cox proportional-hazards model was used to adjust for eight variables: no-visitation policy, age, sex, dementia, emergency surgery, APACHEⅡ, benzodiazepine use, and mechanical ventilation use.

Comment

6.Figure is interesting but it should be improved from a graphical point of view.

Reply

Thank you for pointing this out.

The three figures have been completely revised to make them easier to understand.

Comment

Reviewer #2: Takeshi Unoki et al. Present a retrospective study on the impact of the no-visitation policy on patients admitted to ICU during Covid-19 pandemic. They concluded that the no visitation policy was not associated to an higher incidence of delirium. Anyway, I do have some comments.

1.The calculation of the sample size should be better defined

Reply

We apologize that the description was incomplete and contained errors.

In fact, when we calculated the sample size, we used the rule that 10 is the required number of events per variable in a Cox proportional-hazards regression analysis (Peduzzi et al., 1995). We also pre-determined seven variables to be adjusted in the Cox proportional-hazards model to examine the association between the no visitation policy and delirium. In addition, based on the previous literature, we estimated the incidence of delirium was around 40%. Based on this assumption, a sample size of 200 was required. We revised the sample size section. The revised manuscript is below, with the changed parts in red.

Reference

Peduzzi, P., Concato, J., Feinstein, A. R., & Holford, T. R. (1995). Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. Journal of Clinical Epidemiology, 48(12), 1503–1510. doi:

10.1016/0895-4356(95)00048-8

------Revised Manuscript------

P10 Line:174

Sample size

To analyze the association between the number of days until the development of delirium and visitation policies, the sample size was calculated as follows: the incidence of delirium as an event was assumed to be 40% based on previous literature [1-3]. The covariates to be adjusted in the Cox proportional-hazards model were set to 7. Based on these conditions, we used the rule that 10 events per variable are required to perform a Cox proportional-hazards regression and set the required sample size to 200 [19,20].

Comment

2. In the bias section, the authors declare to use multivariate analysis to adjust for known confounders associated with delirium. Can the authors please state which are the counfounders and how they were chosen?

Reply

We apologize for the confusion caused by our inappropriate wording.

We attempted to explain how we analyzed and chose the covariates. First, the bias section was removed and a description regarding the analysis was integrated into the “Statistical analysis” section. Second, we choose the covariates based on past research that described factors for delirium incidents in the ICU settings and clinical expert knowledge. This method was recommended by the guideline (Lederer et al., 2019). We attached a rationale for the research regarding the factors involved in the development of delirium to each of the covariates in the statistical analysis section. We show below the revised manuscript with the modified parts in red.

Reference

Lederer, D. J., Bell, S. C., Branson, R. D., Chalmers, J. D., Marshall, R., Maslove, D. M., Ost, D. E., Punjabi, N. M., Schatz, M., Smyth, A. R., Stewart, P. W., Suissa, S., Adjei, A. A., Akdis, C. A., Azoulay, É., Bakker, J., Ballas, Z. K., Bardin, P. G., Barreiro, E., … Vincent, J.-L. (2019). Control of confounding and reporting of results in causal inference studies. Guidance for authors from editors of respiratory, sleep, and critical care journals. Annals of the American Thoracic Society, 16(1), 22–28. doi: 10.1513/AnnalsATS.201808-564PS

------Revised Manuscript------

P11, Line 188

The patients were divided into two groups, before and after the implementation of the no-visitation policy, and were compared using Kaplan-Meier curves with the number of days until the development of delirium as the outcome. The log-rank test was used to compare the two groups. In the multivariate analysis, we used the Cox proportional-hazards models to analyze the association between the number of days until the onset of delirium as the objective variable and the visitation policies. We calculated the hazard ratio (HR) and 95% confidence interval (CI) for the development of delirium. We predefined covariates for multivariable analysis, based on past studies and clinical expert knowledge. We selected age [21-23], sex, APACHE-II [21], history of dementia [24], ICU admission after emergency surgery [22,23] , use of benzodiazepine [21,23,25] and mechanical ventilation use [26] for covariates. To avoid multicollinearity, the APACHE II score was calculated without using age as a covariate. Dose of opioids was not included in the model, because most patients receiving opioids were also receiving mechanical ventilation.

-------------------

Comment

3. In the “No visitation policy in the study” paragraph, the authors state that some patients had access to online communications with the families. How many patients had the possibility? Do you think this might be a bias?

Reply

Thank you for pointing this out.

Yes, we think bias may occur due to online communication in the no-visitation phase, as you indicated. However, we do not considered that this bias significantly affected our results. Firstly, there were no manuals, tablets, or other equipment for online communication at the hospital during the study period. We considered that this indicated that online communication was not frequent. Of course, If a family member brought a cell phone to the hospital and the patient could use it, they could call each other. Unfortunately, online communication was not recorded in the medical chart; therefore, we were not able to be quantify it. We have described the potential bias regarding online communication in the section on limitations of the study. We show below the revised manuscript with the modified parts in red.

------Revised Manuscript------

P24, Line 359

Limitations of the study

This study has several limitations: First, as it was a before-and-after comparative study, unknown confounding factors may not have been controlled for. Second, this study was a single-center study; thus, external validity should be considered with caution. Third, even with a no-visitation policy, a few visitors stayed with the patients for a short time (i.e., a brief period of time just before the patient’s death); however, we evaluated the no-visitation policy, not no-visitation. Thus, we did not exclude the patients who met visitors. Given the paucity of visitation opportunities and the short time, we did not consider that visitation during the after period interfered with our findings. Fourth, there may be an Information bias regarding the presence of dementia or mental disorders of the variables used in the multivariate and sensitivity analyses. The presence of these diseases was determined by the medical records, which may have contributed to a bias because there might have been cases that were either not disclosed in the medical records or were documented as mild mental disorders. However, we considered that those cases occurred randomly in both phases and did not significantly affect the results. Fifth, the exact number of online communications between patients and family members during the no-visitation policy is unknown. However, we did not have online communication manual and structured, thus we considered the contribution of online communication on our findings to have been minimum.

Comment

4. Can the authors please explain what they mean with “medical ventilation”?

Reply

We apologize for the typo. The correct term is “mechanical ventilation use.” We have corrected it throughout the manuscript.

Comment

5. Can the authors define which were the psychiatric disorders taken into account (i.e.depression/schizophrenia etc)?

Reply

Thank you for pointing this out.

We added the description of the definition of the mental disorders in this study. We show below the revised manuscript with the modified parts in red.

------Revised Manuscript------

P9 Line 144

Variable / Data collection

We retrospectively collected data from the electronic medical records for this study. We collected patients’ characteristics including age, sex, and past medical history, such as dementia and mental disorders. Clinical data, including the primary reason for ICU admission, the Acute Physiology and Chronic Health Evaluation II (APACHE II), and the Sequential Organ Failure Assessment (SOFA) within 24 hours of ICU admission were also collected. Additionally, duration of mechanical ventilation, ICU length of stay, hospital length of stay, opioid use, sedatives use, mortality, use of continuous renal replacement therapy, use of intra-aortic balloon pumping, use of extra corporeal oxygen exchange during ICU stay were recorded. Sepsis was defined as the presence of an infectious disease diagnosis and an elevated SOFA score of two or more points [15]. Benzodiazepines use was defined as continuous intravenous benzodiazepines for more than 24 hours. Mental disorders comprised any mental illness, including schizophrenia and depression. However, dementia was not considered as a mental disorder in this study because we used it as a covariate in the analysis.

P17, Line 256

Comment

6.How did the authors address the patients with dementia or psychiatric disorders in the ICDSC scale? I wonder if those patients should be excluded from the analysis.

Reply

Thank you for pointing this out.

As you mentioned, a past study using ICDSC indicated that false positives of delirium included dementia and mental disorders (Bergeron et al., 2001). However, a different reported high specificity of ICDSC in studies that investigated the detection of delirium (specificity:95%,95%CI:87~98%) (van Eijk et al., 2009). Therefore, we did not think we needed to exclude patients with dementia and mental disorders. Additionally, if similar specificity of ICDSC between before and after phase, the result would have unchanged.

However, as you pointed out, false positives of delirium may have occurred. Therefore, we added a sensitivity analysis excluding patients with dementia and mental disorders from the primary analysis to the supplementary. The results showed no association between the no-visitation policy and the number of days until the development of delirium (Hazard ratio 0.890, 95%Cl 0.572-1.385). Thank you to your suggestion, we have conducted additional analysis and gained new insights. We also show the revised manuscript below with the modified parts in red in the sensitivity analysis section.

References

Bergeron, N., Dubois, M. J., Dumont, M., Dial, S., & Skrobik, Y. (2001). Intensive care delirium screening checklist: Evaluation of a new screening tool. Intensive Care Medicine, 27(5), 859–864.doi:

10.1007/s001340100909

van Eijk, M. M. J., van Marum, R. J., Klijn, I. A. M., de Wit, N., Kesecioglu, J., & Slooter, A. J. C. (2009). Comparison of delirium assessment tools in a mixed intensive care unit. Critical Care Medicine, 37(6), 1881–1885. doi: 10.1097/CCM.0b013e3181a00118

------Revised Manuscript------

P13, Line 221

Third, a previous study reported the occurrence of false positives when the ICDSC was used to determine delirium in patients with dementia and mental disorders [16]. Therefore, we conducted an analysis using Cox proportional- hazards model, excluding patients with dementia or mental disorders. All covariates were the same as the ones in the primary analysis except for dementia.

Comment

7. I wonder what is the real impact of the higher percentage of opioids use and the higher number of mechanical ventilation days in the no visitation group. As the authors state it as a study limitation, could it be possible to perform a subanalysis excluding such a difference?

Reply

Thank you for pointing this out.

As you pointed out, the no-visitation group tended to have higher rates of opioid use and longer duration of mechanical ventilation. Our analysis has not been able to adjust for this difference. For this reason, we changed the variable used in the sensitivity analysis from the mechanical ventilation use to duration of mechanical ventilation. In addition, 84.6% of the patients on ventilators were on opioids. Contrastingly, 86.8% of the patients on opioids were on mechanical ventilators. Thus, we avoided including the opioid variable in our sensitivity analysis due to the possibility of multicollinearity.

When we performed the Cox proportional-hazards model by changing the covariate of mechanical ventilation use in the primary analysis to duration of mechanical ventilation, the results did not change significantly, with an AHR of 0.938 (95% CI: 0.644-1.367, p-value: 0.741) for the no-visitation policy. In other variables, dementia, APACHE II-age increased the risk of developing delirium. In addition, we agree with your comment and have performed a Cox proportional- hazards model by changing the covariate of mechanical ventilation use in the primary analysis to opioid use. The results did not change significantly, with an AHR of 0.883(95% CI: 0.604-1.291, p-value: 0.520) for the no-visitation policy. The results are shown below.

Thank you again for pointing this out; we have gained a new insight and confirmed the robustness of the results. We considered duration of mechanical ventilation to be an important variable as well. Therefore, we modified the section on sensitivity analysis and added the table of sensitivity analysis to the supplementary files. Below, we show the revised parts from the manuscript in red.

Estimates of the hazard ratios of variables on development of delirium in the Cox proportional hazards models include covariate as Opioid use

Variable Adjusted

hazard ratio 95% CI p-value

No-visitation policy 0.883 0.604-1.291 0.520

Age 0.998 0.985-1.013 0.876

Male 1.153 0.780-1.705 0.473

Dementia 1.941 1.164-3.238 0.010

Emergency surgery 1.346 0.717-2.529 0.354

APACHE IIa 1.036 1.011-1.063 0.004

Benzodiazepine

use 1.041 0.572-1.895 0.893

Opioid use 1.789 1.086-2.949 0.022

aAPACHEⅡ score was calculated without age related score

------Revised Manuscript------

P13, Line 221

Second, in order to remove the effects of duration of mechanical ventilation on our findings, we changed the covariate of mechanical ventilation use as binomial variable to the duration of mechanical ventilation, and conducted the Cox proportional-hazards model. All covariates included in the primary analysis were also included int the model, with the exception of mechanical ventilation use.

Comment

8. In line 252-253, the authors talk about the median number of days for onset of delirium.Among these days, do the authors take into account also the days the patients were sedated?

Reply

Thank you for pointing this out.

In the sections you mentioned, the median and interquartile range of the number of days until the onset of delirium among only patients who developed delirium were listed regardless of whether the patient had been sedated or not. As suggested, these points were difficult to understand. Below is the revised manuscript with the changed parts in red.

------Revised Manuscript------

P18, Line 270

The median number of days for onset of delirium among patients who developed delirium before and after the implementation of the no-visitation policy was not significantly different (2 [IQR], 2–3 vs 2 [IQR], 2–3, p=0.696). This result does not take into account whether patients had been sedated or not. The Kaplan-Meier curve between the before and after phases for the development of delirium is shown in Fig 2. The log-rank test did not show a significant difference between the two phases (p=0.61).

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

23 Feb 2022

Relationship between no-visitation policy and the development of delirium in patients admitted to the intensive care unit

PONE-D-21-25576R1

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Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: The authors have properly addressed my issues. Moreover, a detailed description of what the authors did has been provided. I have no more comments.

Reviewer #2: The Author extensively addressed my comments.

I would underline in the "Limitations of the study" section the fact that the patients of the after phase group had higher mechanical ventilation use rates and longer duration of mechanical ventilation (line 305) hence greater use of sedatives.

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Reviewer #1: Yes: Mario Mazza

Reviewer #2: No

28 Feb 2022

PONE-D-21-25576R1

Relationship between no-visitation policy and the development of delirium in patients admitted to the intensive care unit

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