Application of the whole-course care model (IWF/C Care) for postintensive care syndrome based on an early warning system in critically ill patients: a randomised controlled trial study protocol

Abstract

Introduction

Critically ill patients are at risk of developing postintensive care syndrome (PICS), which is manifested by physical, psychological and cognitive impairment. Currently, there are no programmes that combine early warning systems with interventions for PICS. We hypothesise that a comprehensive care model for PICS based on an early warning system would reduce medical costs and the incidence of PICS.

Methods and analysis

The Intensive Care Unit (ICU) -Ward-Family/Community whole-course care (IWF/C Care) trial will be a unicentric, randomised, controlled trial. A total of 138 ICU patients from two ICUs at a university hospital in Guizhou province, China, will be enrolled in February 2023. The inclusion criteria are an age of 18 years or older, an ICU stay of more than 48 hours, provide informed consent and the ability to communicate normally. Patients will be followed for 12 months and randomised in a 1:1:1 ratio to three groups.

Interventions

Patients in intervention group 1 will be assessed by the PICS early warning system within 24 hours of ICU discharge, and precise interventions will be carried out according to the results; that is, high-risk patients will receive care based on the IWF/C Care model and low-risk patients will receive routine care. All patients in intervention group 2 will receive care based on the IWF/C Care model. The control group will receive routine care. The primary endpoints are the incidence of PICS and quality of life. The secondary endpoints include the incidence of adverse events: the unplanned readmission rate, cost-effectiveness, and the experiences and feelings of patients receiving care based on the IWF/C Care model. The incidence of PICS will be measured at ICU discharge, general ward discharge, the home/community stage and 1 month and 3, 6, 9, and 12 months after discharge.

Ethics and dissemination

Ethics approval was obtained from Biomedical Research Ethics Committee of the Affiliated Hospital of Zunyi Medical University (approval number: KLL-2022-780). The results of this study will be distributed through peer-reviewed journals.

Trial registration number

ChiCTR2300068135.

Correspondence to Dr Rujun Hu; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• This randomised controlled trial will examine the effect of the whole-course care model (ICU-Ward-Family/Community Care) based on an early warning system on the incidence of postintensive care syndrome (PICS) and quality of life using an innovative and uniform modality.

• Based on the framework of Orem’s nursing system theory, this study will implement nursing care according to the characteristics of patients in each system and will conduct whole-course health service management.

• The ICU early warning system can accurately predict the risk of PICS in patients.

• Blinding of the patients or investigators will not be possible due to the nature of the intervention.

Introduction

Postintensive care syndrome (PICS) was first proposed by the American Society of Critical Care Medicine (SCCM) at the Global Critical Care Conference in 2010¹ and refers to the new or aggravated physical, psychological and cognitive dysfunction of critically ill patients after they are transferred out of the Intensive Care Unit (ICU). The main manifestations are physical disorders, such as ICU-acquired weakness (ICU-AW), disuse atrophy and fatigue²; psychological disorders, such as depression, anxiety and post-traumatic stress disorder (PTSD)³ and cognitive disorders, such as delirium, amnesia and inattention.¹ Studies have shown that within 1 year of transfer from the ICU, the incidence of symptoms in all dimensions of PICS is relatively high,^{4 5} and family members may also experience symptoms such as anxiety, depression and PTSD,⁶ which seriously affect the quality of life (QOL) for patients and their family caregivers.^{7 8} With the prevention and rehabilitation of PICS becoming a new research hotspot, increasing research has gradually focused on the early prevention and later rehabilitation of patients transferred from the ICU.⁹ However, there are large differences in early prevention in different ICU wards. For example, there are no uniform standards for early mobilisation, muscle strength assessment or delirium management.^10–12 Early intervention in the ICU has not been extended to the ward and the community, and the prevention and rehabilitation of patients have not been effectively connected. SCCM held the second global meeting in 2012, which focused on the hospitalisation and community rehabilitation of PICS patients. Simultaneously, the meeting submitted that PICS prevention and treatment should include the entire process of management during the ICU, the ward and after discharge.⁴ With the development of China’s public health, the next 10 years will be an important period of strategic opportunity to promote the construction of a healthy China. The whole-cycle and whole-course health service models will be gradually promoted, and the whole-course health service model for patients discharged from the ICU, which is in line with China’s national conditions, is worthy of attention. Therefore, based on the ICU-Ward-Family/Community Care (IWF/C Care), the operating mechanism of the PICS whole-course care model needs to be further studied.

In recent years, reducing the morbidity of PICS has become the focus of scholars studying the risks and influencing factors of PICS.^13–15 The back propagation artificial neural network (BP), the most widely used neural network, is a type of multilayer feed-forward neural network trained according to the error BP algorithm.¹⁶ It can automatically identify the characteristics and laws of the signal according to the situation of the input signal, and the stability of the model is good. Therefore, the research group used the BP neural network algorithm to construct the early prediction model of PICS in previous research, thereby allowing high-risk groups to be accurately screened out.¹⁷ The early warning model constructed by the research group can better predict the occurrence of post-ICU syndrome. This study will use computer information technology to develop a model-based early warning system that will provide an automated, intelligent and informative early warning platform for standardising the risk management of PICS patients. This will reduce the incidence of PICS and ensure patient safety.

The Orem’s nursing system theory was composed of nurses’ nursing behaviours when providing care for patients and patients’ self-care behaviours, including a wholly compensatory system, a partly compensatory system and a supportive education system (figure 1).¹⁸ Three different systems can help patients to face their self-care deficits in stages, thereby actively engaging patients and family members in decision-making and care planning. Combining the above-mentioned research with the Orem’s nursing system theory as a framework and the early risk warning system as a carrier, a whole-course care model for PICS patients based on the IWF/C Care model was constructed. The results of our study contribute to improving the self-management skills of PICS patients and play a positive role in promoting the full-cycle prevention and rehabilitation management of major diseases.

Figure 1. Nursing system theoretical framework.

Methods and analysis

Study design and setting

The IWF/C-Nursing trial, a three-arm, single-centre, parallel-group, randomised controlled trial, will develop a PICS early warning system on the basis of previous research (analysis of potential subtypes of PICS¹⁹ and the construction of a PICS early warning model¹⁷) to screen patients transferred from the ICU; a whole-course care programme based on the IWF/C Care method will be compared with standard care at 1, 3, 6, 9 and 12 months after ICU discharge. This protocol publication follows the Standard Protocol Items: Recommendation for Intenventional Trials (SPIRIT) guidelines.²⁰ Figure 2 shows the study flow chart and online supplemental file 1 shows the schedule of enrolment, interventions and assessments. This study will be conducted in two comprehensive ICUs of a tertiary general hospital in China. It is expected that the first subject will be enrolled on 15 February 2023, and the end of the study will be on 15 June 2024. Training on study procedures will be necessary for all participating staff members.

Figure 2. The IWF/C care study flow chart, interventions and assessments. ICU, Intensive Care Unit; FAI, fatigue assessment instrument; HADS, Hospital Anxiety and Depression Scale; IES-R, Impact of Event Scale-Revised; IWF/C, ICU-Ward-Family/Community; MMSE, Mini-Mental State Examination; PQSI, Pittsburgh Sleep Quality Index; SF-36, Short Form 36.

Participation and recruitment

The study population will include 138 patients from adult ICUs. The recruitment of research subjects is being carried out at two comprehensive ICUs and general wards of a tertiary general hospital in Guizhou Province, China. According to the inclusion and exclusion criteria, the ICU doctors or nurses are directly screening patients who meet the inclusion criteria. The researchers are interviewing the patients or their families face-to-face, obtaining informed consent and completing the baseline survey.

Inclusion criteria

Adult patients will be eligible if they:

• Are 18 years of age or older.

• Have an ICU length of stay ≥48 hours.

• Have the ability to communicate normally.

• Provide informed consent.

Exclusion criteria

Patients will be excluded from the trial if they:

• Have cerebrovascular sequelae or cognitive impairment and are unable to communicate.

• Have grade C hepatic dysfunction.

• Have daily contraindications, such as severe asthma, severe acute respiratory distress syndrome, hypertensive crisis and myocardial ischaemia, while awake.

• Have a history of ICU admission.

• Have a serious mental illness, such as anxiety, depression and suicidal tendencies, before admission.

• Have advanced‐stage cancer or an expected survival of less than 6 months.

These criteria have been established to exclude those who are unable to give their consent or follow the post-ICU programme. All patients will be screened for eligibility by ICU physicians before hospital discharge. The reasons for non-randomisation will be collected.

Dropout criteria

• Patients who die.

• Patients who experience obvious discomfort during the study period due to direct or indirect reasons related to the study and those who experience aggravated conditions for which emergency measures must be taken will be considered as having adverse reactions.

• Patients who withdrawal on their own, those who do not complete the entire course of treatment and follow-up as stipulated in the protocol, and those who do not cooperate with the treatment during the research process and are not discharged according to their doctor’s advice.

Randomisation

The Research Randomizer website (https://www.randomizer.org) was used to produce a sequence of random numbers 1–138. Randomisation to one of the three study arms will occur in a 1:1:1 manner. Randomisation will be performed by an unblinded study coordinator who does not perform any intervention or outcome assessments. Research staff, with no clinical involvement in the trial, will be responsible for keeping the random allocation list and preparing sealed, opaque sequentially numbered envelopes, each containing a random number denoting the allocated treatment.

Blinding

Due to the nature of this study, it will be impossible to blind patients and researchers. Therefore, this is a single-blind trial, where the statistician will be blinded. The intervention will be performed by multidisciplinary teams, and the team members will not be involved in the data collection or analysis. Outcome assessments will be conducted by an investigator who has received adequate training in questionnaire administration and is not involved in the intervention or evaluation of results. The statistician will also not participate in data collection or programme intervention.

Intervention

Intervention duration/termination

The length of the patient’s hospital stay will determine the period of the intervention. Participants will stop receiving the intervention if they withdraw, are discharged directly from the ICU or die.

Preintervention phase

Team building and training: set up a multidisciplinary cooperative intervention team, mainly including ICU managers, ICU medical staff, ward managers, ward medical staff, rehabilitation therapists, nutritionists, community hospital managers, community hospital medical staff, graduate students, ICU transfer patients and their families. Before the start of the project, the team members will be trained to know the purpose and role of this research, their role in the project and the work they undertake. The division of labour among the members is shown in table 1.

Table 1

Formation and division of labour in multidisciplinary teams

Personnel	Division of labour	Remark
ICU doctor and nurse	Responsible for the risk and symptom assessment of PICS during the ICU period of patients, ABCDE bundle nursing measures and implementer of sleep management	1 doctor and 2 nurses in each ICU
Ward doctor and nurse	Responsible for PICS symptom assessment and implementation of rehabilitation interventions during patient ward treatment	1 doctor and 2 nurses in each ward
Rehabilitation therapist	ICU-Ward-Family/Community three-stage rehabilitation guidance and implementation	2
Counsellor	ICU-Ward-Family/Community three-stage mental state assessment and psychological counselling of patients	1
Nutritionist	ICU-Ward-Family/Community three-stage assessment of the nutritional status of patients and support for the formulation of nutritional programmes	1
Family/patient	In the recovery process of self-care ability, assist medical staff or complete ICU-Ward-Family/Community rehabilitation interventions alone	Patients and their families were included in the study
ICU-Ward-Community Hospital Manager	Assist in formulating or improving relevant work systems and facilities to ensure the smooth implementation of the project	The study involved department directors and head nurses
Research assistant	Data collection, liaising with various departments for coordination and communication, tracking the whereabouts of patients, and ensuring the timely and effective implementation of intervention measures	2

ICU, Intensive Care Unit; PICS, postintensive care syndrome.

Intervention phase

Collection of early warning indicators

Patients who are transferred from the ICU will be screened according to the inclusion and exclusion criteria, and the presence of 21 early warning indicators will be determined and recorded on the early warning indicator collection form.¹⁷ PICS early warning indicators include sex, age, marital status, diagnostic classification, length of ICU stay (days), occupation, height (cm), weight (kg), body mass index, tobacco and alcohol habits, education level, history, exercise, residence mode, duration of mechanical ventilation (hour), duration of noninvasive ventilation (hour), with or without constraints, with or without delirium, and dosages of dexmedetomidine hydrochloride (mg) and midazolam (mg). The indicators will be assigned values: the continuous variables will be directly normalised, aiming to normalise the variable value to the interval 0, 1. Values will be assigned to categorical variables, as shown in online supplemental file 2 of this manuscript.

Intervention description

IWF/C care

ICU period

The ICU period will involve a comprehensive compensation system. Due to the seriousness of their conditions, critically ill patients are often treated with sedation, analgesia, bed rest and immobilisation, which puts them at high risk of developing PICS. Additionally, patient self-care abilities are often diminished during this time. Therefore, prevention should be the primary focus, with the goal of reducing the risk of PICS. During this stage, a multidisciplinary team will intervene using the ABCDEF cluster intervention strategy. This strategy includes awakening, breathing coordination, choice, delirium monitoring and management, early exercise/mobility and family support. Additionally, early psychological counselling and the creation of an ICU diary will be provided as supplementary measures. It is crucial to prioritise PICS screening and promptly initiate rehabilitation for symptomatic patients. Furthermore, a dual-track linkage plan will be established, with the prevention track during the ICU period serving as the primary recovery path and the rehabilitation track providing supplementary support.

Ward period

The general ward period will involve a partial compensation system in which the patient’s condition is typically stable, but there is still a chance of deterioration. Patients exhibiting PICS symptoms during this period will receive the rehabilitation track intervention, while those without such symptoms will be evaluated promptly. Preventive measures will be taken, and treatment will be provided based on the patient’s condition. To enhance patient care in the ICU, it is recommended to incorporate psychological counselling services, encourage reading of ICU diaries, and promote self-care capabilities alongside the continuation of ‘DEF’ and PICS assessments in the ‘ABCDEF’ strategy. It is important to prioritise both prevention and control measures, as well as the recovery process. Within 24 hours after transfer out of the ICU, the PICS early warning system will be used to screen patients and divide them into high-risk patients and low-risk patients. The ward intervention plan will be drawn up for each patient, and the intervention team will be contacted with the evaluation results and intervention plan.

Family/community period

The community/family period in the counselling-education system is a crucial time for patients as they recover physically, but they may lack the necessary knowledge for effective disease self-management. During this time, new rehabilitation problems may arise, which may exacerbate PICS symptoms and prolong recovery time. To address these issues, rehabilitation exercise will be an important intervention method for patients in this stage, serving as a continuation of the first two stages of this study. In order to provide effective care for patients with PICS, we will continue to focus on symptom assessment, rehabilitation, and increasing disease self-care knowledge and skills for both patients and their families. This approach will be supplemented by psychological support and efforts to reduce risk factors. Together, these components will form a comprehensive care model that integrates prevention and rehabilitation. The specific components of care will be tailored to meet the individual needs of each patient. The specific intervention plan can be found in online supplemental file 3.

Control treatment

Participants in the control group will receive the usual care without any additional information or consultation. ICU period: a multidisciplinary team composed of ICU doctors, nurses, and rehabilitation specialists will provide ‘ABCDE’ cluster interventions. Ward period: condition observation, specialised disease nursing, analgesic and sedative management, general life nursing, etc. Family/Community period: The patients will be followed up by telephone within 1 week after discharge.

Outcomes and measurements

Primary outcome

Primary outcome 1: incidence of PICS

The investigator will record the number of occurrences of PICS and calculate its incidence as (number of cases with PICS/total number of patients observed)×100%. At present, there is no uniform diagnostic tool for PICS when used clinically, but the diagnosis is made by assessing whether there is impairment of cognitive, psychological and physical functions.^{21 22} Patients will benefit from a standardised assessment, addressing their health-related QOL (Brief QOL scale Short Form 36, SF-36) and the three principal components of PICS: physical status (Barthel index (BI), PQSI and FAI), mental health (MH) disorders (Hospital Anxiety and Depression Scale (HADS) and Impact of Event Scale-Revised, IES-R) and cognitive impairment (Mini-Mental State Examination, MMSE). At present, there is no dedicated evaluation tool for PICS. Instead, general rating scales are used to determine if patients are experiencing cognitive, psychological or physical impairments. If any of these scales indicate a positive result, a diagnosis of PICS will be made.

Assessment of cognitive impairment

The Mini-Mental State Examination

The MMSE is currently one of the most commonly used cognitive function screening tools in the world that assesses orientation, attention, memory, language and visual-spatial skills.^{23 24} Items are easy to understand and highly operable. The maximum score on the scale is 30, of which scores of 27–30 are considered normal and scores <22 are classified as cognitive dysfunction.

Examination for mental disorders

Impact of Event Scale-Revised

The IES-R is a widely used instrument to assess psychological distress in ICU family members,^{25 26} which measures the presence and severity of symptoms associated with a traumatic event during the past week. It consists of three subscales that measure intrusion, avoidance and hyperarousal. The scores range from 0 to 88, and a score of greater than 22 is indicative of a diagnosis of PTSD.

Hospital Anxiety and Depression Scale

The HADS comprises 14 items and is commonly used to determine the levels of anxiety and depression. Seven of the items relate to anxiety, and seven relate to depression.²⁷ The HADS is scored on two subscales (anxiety and depression) and has thresholds for mild/baseness for depression and anxiety, respectively.²⁸

Assess for physical impairment

The Barthel Index

Rating scale is recognised worldwide as the most commonly used scale for assessing activities of daily living (ADL).^{29 30} The scale mainly evaluates 10 items, including eating, bathing, grooming, dressing, defecation control, urination control, toileting, bed and chair transfer, walking 45 cm on level ground, and going up and down stairs. The scale is 100, with higher scores indicating better independence and less dependence.

Fatigue assessment instrument

Mainly evaluates the fatigue status of daily activities in patients transferred out of the ICU.³¹ It is mainly used to evaluate fatigue status in the past 2 weeks. The table has 29 items, including 4 factors: factor 1 measures the severity of fatigue, factor 2 measures the sensitivity of fatigue to specific environments, factor 3 measures the psychological consequences that fatigue may cause and factor 4 measures whether fatigue affects rest or sleep. Response: A total of 1–7 points are used for evaluation. The total score of fatigue is the sum of the 29 item scores. According to the score of factor 1, fatigue was divided into no fatigue (factor 1: <4 points), mild fatigue (factor 1: ≥4 to <5), moderate fatigue (factor 1: ≥5 to <6) and severe fatigue (factor 1: 1 to ≥6).³²

Pittsburgh Sleep Quality Index

Includes 19 self-assessments and 5 other evaluation items, of which the 19th self-evaluation item and 5 other-evaluation items do not participate in scoring.³³ The PSQI mainly includes seven items, including sleep quality, time to fall asleep, sleep time, sleep efficiency, sleep disorders, hypnotics and daytime dysfunction.³⁴ Each item is rated from 0 to 3 points, from light to heavy, and the total score of the Pittsburgh Sleep Quality Index (PSQI) is the total score of 7 items. If the total PSQI score is ≥7 points, it indicates that there is sleep difficulty, and the higher the score is, the worse the sleep quality of the subject.

Primary outcome 2: QOL

SF-36³⁵ will be used to evaluate patient QOL, which includes physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional and MH in 8 dimensions and 36 items. The higher the score is, the better the QOL.³⁶

Secondary outcomes

Secondary outcome 1: unplanned readmission rate

Record the number of unplanned readmission patients and calculate the unplanned readmission rate, that is, (number of readmissions/total number of observed patients)×100%.

Secondary outcome 2: the frequency of adverse events

The number of cases of adverse events during the intervention process of the whole-course care model will be recorded, and the incidence of adverse events, including pressure injury, unplanned extubation, falls, medication error, aspiration, transfusion errors, etc, will be calculated. That is, (number of cases of adverse events/total number of observed patients)×100%.

Secondary outcome 3: cost-effectiveness

Intervention costs will be collected, including labour costs (researchers’ time spent on participating in the study), transportation costs (research subjects returning to the hospital for follow-up, intervention staff visiting patients' homes) and communication costs (patient telephone follow-up costs). From the payer’s point of view, the decision analysis model will be used for economic analysis, and incremental cost analysis will be used to evaluate the cost of the two intervention groups (1 and 2) and the control group. The results of the cost-effectiveness analysis will be expressed as the incremental cost per reduction in 1 case of PICS and can also be expressed as the cost per reduction in the incidence of PICS in 1% of patients.

Secondary outcome 4: the experience and feelings of patients participating in the ‘IWF/C’ whole-course care model

The qualitative interview outline created by the research group will be used to collect data through semistructured interviews. The researchers will conduct one-on-one, semistructured interviews with the patients in the intervention group within 1 week after the intervention to understand the patients' experiences and feelings about the ‘IWF/C’ whole-course care model.

Demographics, such as age, gender, body weight, length, preexisting comorbidities, previous ICU admissions and ICU readmissions; treatment-related characteristics, such as type of admission, ICU and hospital length of stay; mechanical ventilation-related characteristics; and episodes of sedative coma and delirium during ICU treatment will be assessed using the Richmond Agitation Sedation Scale and the Confusion Assessment Method for the ICU scale.

Data management and monitoring

Data management and monitoring will be provided by the coordinating investigator site’s clinical trial unit. The trial will follow national and international standards for good clinical practice and comply with regulatory and ethical requirements. Related or unrelated serious adverse events affecting the participants (including family members) will be collected and documented in source documents. The quality of the study and regulatory compliance will be monitored. The monitoring personnel will not participate in our research. The ethics committee has approved supervision to verify the qualifications of the investigators and research team members and to monitor sound and appropriate documents.

Sample size

The sample size was calculated based on two main outcome indicators (the incidence of PICS and QOL), with the larger sample size selected for this study. Assuming that the incidence of PICS in intervention group 2 is 39%³⁷ and a clinically relevant difference among the groups of 32%, for distribution of a tail with a type I error of 0.05, a power of 80%, a p- =0.55 and a $\stackrel{-}{q}$ =0.45, the sample size was calculated as 114 patients, with 38 in each arm. Assuming a lost to follow-up of 20%, the sample size needed is 138 patients (46 in each group). A clinically significant difference in SF-36 scores is defined as a difference of more than 5 points between the obtained sample scores and the normative scores for the general population.³⁸ Based on the published literature,^39–41 patients transferred from the ICU had a total SF-36 score of 59.44–71.45 before the intervention, which increased to 107.20–122.70 after the intervention. The SF-36 score includes a Physical Component Score (PCS) and a Mental Component Score (MCS). The PCS score before the intervention ranged from 40.08 to 49.06 and increased to 72.56–77.34 after the intervention. The MCS score before the intervention ranged from 40.24 to 50.67 and increased to 80.06–87.06 after the intervention. The sample size of 8–40 patients was calculated using the above method based on the mean difference between the two groups and a 20% lost to follow-up rate. Therefore, the sample size of this study was ultimately determined to be 138 patients.

Data analysis

Statistical analysis will be performed by using IBM SPSS V.22 software. Qualitative variables will be presented as proportions, while for quantitative variables, the mean (SD) or median (IQR), after checking for normality using the Shapiro-Wilk test, will be used. Independent sample t tests, χ² tests and Wilcoxon rank sum tests will be used for pairwise comparisons. Analysis of variance or repeated analysis of variance will be used to analyse the observation indicators of the three groups of patients at baseline, ICU, ward and postdischarge time points. Two-tailed p values will be presented, and a significance level of 0.05 will be used.

An intention-to-treat (ITT) approach will be followed.⁴² The principle of ITT will be used to analyse the impact of drop-out on the results; that is, all research objects entering the group will be included in the analysis, and multiple imputation methods will be used for missing values.

The decision analysis model will be used for economic analysis. The incremental cost analysis will evaluate the costs of the two interventions. The results of the cost-effectiveness analysis will be expressed as the incremental cost per reduction of 1 case of delirium or ICU-AW, per 1% reduction in the incidence of cognitive impairment, PTSD, anxiety and depression, or per 1% reduction in primary caregiver family anxiety and the cost of the incidence of depression.

Patient and public involvement

Patients and/or the public will not be involved in the design, conduct, reporting or dissemination of this research.

Discussion

IWF/C Care is a three-arm randomised clinical trial designed to evaluate the efficacy of an early warning system combined with the whole-course care model in improving QOL and reducing the incidence of PICS. Our protocol builds on strong prior research findings of the whole-course care model and the early warning model.^{17 43} The advantages of our programme include the blinding of the statistician; introducing a structural equation model to analyse the elements of the nursing model and the intervention effects at each stage, which is beneficial in analysing the influence of the elements of the nursing model on the operation, exploring the interrelationships between elements, linking the three stages of ‘IWF/C’, adopting the dual-track linkage of prevention and rehabilitation, and carrying out whole-course health service management according to the characteristics of the patients at each stage.

Ethics and dissemination

The study protocol (V.1.0, 7 December 2022) and applied informed consent forms have been approved by Biomedical Research Ethics Committee of the Affiliated Hospital of Zunyi Medical University. We plan to disseminate and publish the trial outcomes in a peer-reviewed journal.

We would like to thank our patients, caregivers, healthcare team, who without this work would not have been possible.

Ethics statements

Patient consent for publication

Not applicable.

Footnote

Contributors RH initiated the study conception and design of the IWF/C-Nursing trial, was responsible for the funding application, and acted as the sponsor and coordinating investigator. RH, HG and XL made substantial contributions to the conception and trial design and cowrote the funding application. XL, ZX, CJ and JL will be responsible for the implementation of the trial. CY designed the statistical analysis plan. XL and RH cowrote the manuscript. JL, CY, ZX, CJ and HG critically reviewed the manuscript for important intellectual content. All authors read and approved the final manuscript.

Funding This study was supported by grants from the Zunyi Science and Technology Bureau (Zunshi Kehe HZ Zi (2020) No. 256).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

References

¹ Needham DM, Davidson J, Cohen H, et al. Improving long-term outcomes after discharge from intensive care unit: report from a Stakeholders' conference. Crit Care Med 2012; 40: 502–9. doi:10.1097/CCM.0b013e318232da75

² van der Merwe E, Paruk F. Quantifying the burden of the post-ICU syndrome in South Africa: A Scoping review of evidence from the public health sector. South Afr J Crit Care 2022; 38: 82–7. doi:10.7196/SAJCC.2022.v38i2.527

³ Inoue S, Hatakeyama J, Kondo Y, et al. Post‐Intensive care syndrome: its pathophysiology, prevention, and future directions. Acute Med Surg 2019; 6: 233–46. doi:10.1002/ams2.415

⁴ Elliott D, Davidson JE, Harvey MA, et al. Exploring the scope of post–intensive care syndrome therapy and care: engagement of non–critical care providers and survivors in a second Stakeholders meeting. Crit Care Med 2014; 42: 2518–26. doi:10.1097/CCM.0000000000000525

⁵ Solverson KJ, Grant C, Doig CJ. Assessment and predictors of physical functioning post-hospital discharge in survivors of critical illness. Ann Intensive Care 2016; 6: 92. doi:10.1186/s13613-016-0187-8

⁶ Petrinec AB, Martin BR. Post-intensive care syndrome symptoms and health-related quality of life in family decision-makers of critically ill patients. Pall Supp Care 2018; 16: 719–24. doi:10.1017/S1478951517001043

⁷ Torres J, Carvalho D, Molinos E, et al. The impact of the patient post-intensive care syndrome components upon Caregiver burden. Med Intensiva 2017; 41: 454–60. doi:10.1016/j.medin.2016.12.005

⁸ Geense W, Zegers M, Vermeulen H, et al. MONITOR-IC study, a mixed methods prospective Multicentre controlled cohort study assessing 5-year outcomes of ICU survivors and related Healthcare costs: a study protocol. BMJ Open 2017; 7: e018006. doi:10.1136/bmjopen-2017-018006

⁹ Iwashyna TJ. Survivorship will be the defining challenge of critical care in the 21st century. Ann Intern Med 2010; 153: 204–5. doi:10.7326/0003-4819-153-3-201008030-00013

¹⁰ Costa DK, White MR, Ginier E, et al. Identifying barriers to delivering the awakening and breathing coordination, delirium, and early exercise/mobility bundle to minimize adverse outcomes for mechanically ventilated patients: A systematic review. Chest 2017; 152: 304–11. doi:10.1016/j.chest.2017.03.054

¹¹ Roberson AR, Starkweather A, Grossman C, et al. Influence of muscle strength on early mobility in critically ill adult patients: systematic literature review. Heart Lung 2018; 47: 1–9. doi:10.1016/j.hrtlng.2017.10.003

¹² Xing J, Sun Y, Jie Y, et al. Perceptions, attitudes, and current practices regards delirium in China: A survey of 917 critical care nurses and physicians in China. Medicine (Baltimore) 2017; 96: e8028. doi:10.1097/MD.0000000000008028

¹³ Yao L, Li Y, Yin R, et al. Incidence and influencing factors of post-intensive care cognitive impairment. Intensive Crit Care Nurs 2021; 67: 103106. doi:10.1016/j.iccn.2021.103106

¹⁴ Voiriot G, Oualha M, Pierre A, et al. Chronic critical illness and post-intensive care syndrome: from pathophysiology to clinical challenges. Ann Intensive Care 2022; 12: 58. doi:10.1186/s13613-022-01038-0

¹⁵ Ito Y, Tsubaki M, Kobayashi M, et al. Effect size estimates of risk factors for post-intensive care syndrome-family: A systematic review and meta-analysis. Heart Lung 2023; 59: 1–7. doi:10.1016/j.hrtlng.2023.01.005

¹⁶ Junjie W, Jingwu C. Application of BP neural network in disease prediction. Journal of Mathematical Medicine 2008; 21: 259–62.

¹⁷ Ying W, Zhixia J, Lu X, et al. Research on the construction of a prediction model for post-ICU syndrome based on BP neural network. Chinese Nursing Management 2021; 21: 1856–60.

¹⁸ Orem DE. Nursing concepts of practice. Totonto:Mosby, 1991.

¹⁹ Manman H, Zhixia J, Fang Z, et al. Latent category analysis of symptom characteristics in patients with post-ICU syndrome. Chinese Journal of Nursing 2021; 56: 1445–52.

²⁰ Chan A-W, Tetzlaff JM, Gøtzsche PC, et al. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ 2013; 346: e7586. doi:10.1136/bmj.e7586

²¹ Chu Y, Timmins F, Thompson D, et al. Instruments to measure Postintensive care syndrome: a Scoping review protocol. BMJ Open 2022; 12: e061048. doi:10.1136/bmjopen-2022-061048

²² Narváez-Martínez MA, Gómez Tovar LO, Henao-Castaño ÁM. Scales to measure post intensive care syndrome, a Scoping review. Enferm Clin (Engl Ed) 2022; 32: 440–50. doi:10.1016/j.enfcle.2022.07.003

²³ Creavin ST, Wisniewski S, Noel-Storr AH, et al. Mini‐Mental state examination (MMSE) for the detection of dementia in clinically Unevaluated people aged 65 and over in community and primary care populations. Cochrane Database Syst Rev 2016; 2016: CD011145. doi:10.1002/14651858.CD011145.pub2

²⁴ Folstein MF, Folstein SE, McHugh PR. Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189–98. doi:10.1016/0022-3956(75)90026-6

²⁵ Alfheim HB, Hofsø K, Småstuen MC, et al. Post-traumatic stress symptoms in family Caregivers of intensive care unit patients: A longitudinal study. Intensive Crit Care Nurs 2019; 50: 5–10. doi:10.1016/j.iccn.2018.05.007

²⁶ Kentish-Barnes N, Lemiale V, Chaize M, et al. Assessing burden in families of critical care patients. Crit Care Med 2009; 37 (10 Suppl): S448–56. doi:10.1097/CCM.0b013e3181b6e145

²⁷ Sukantarat KT, Williamson RCN, Brett SJ. Psychological assessment of ICU survivors: a comparison between the hospital anxiety and depression scale and the depression, anxiety and stress scale. Anaesthesia 2007; 62: 239–43. doi:10.1111/j.1365-2044.2006.04948.x

²⁸ McAdam JL, Puntillo K. Symptoms experienced by family members of patients in intensive care units. Am J Crit Care 2009; 18: 200–9; doi:10.4037/ajcc2009252

²⁹ MAHONEY FI, BARTHEL DW. Functional evaluation: the Barthel index. Md State Med J 1965; 14: 61–5.

³⁰ Wade DT, Collin C. The Barthel ADL index: a standard measure of physical disability Int Disabil Stud 1988; 10: 64–7. doi:10.3109/09638288809164105

³¹ Schwartz JE, Jandorf L, Krupp LB. The measurement of fatigue: a new instrument. J Psychosom Res 1993; 37: 753–62. doi:10.1016/0022-3999(93)90104-n

³² Dittner AJ, Wessely SC, Brown RG. The assessment of fatigue: a practical guide for Clinicians and researchers. J Psychosom Res 2004; 56: 157–70. doi:10.1016/S0022-3999(03)00371-4

³³ Hinz A, Glaesmer H, Brähler E, et al. Sleep quality in the general population: Psychometric properties of the Pittsburgh sleep quality index, derived from a German community sample of 9284 people. Sleep Med 2017; 30: 57–63. doi:10.1016/j.sleep.2016.03.008

³⁴ Manková D, Dudysová D, Novák J, et al. Reliability and validity of the Czech version of the Pittsburgh sleep quality index in patients with sleep disorders and healthy controls. BioMed Research International 2021; 2021: 1–9. doi:10.1155/2021/5576348

³⁵ Chonghua W. A comparative study on the use of MOS SF-36 scale in measuring the quality of life of drug addicts. Chinese Journal of Behavioral Medicine 1998.

³⁶ Wafa hamdi, Azzouz D, Ghannouchi MM, et al. Health-related quality of life assessment on 100 Tunisian patients with Ankylosing Spondylitis using the SF-36 survey. Oman Med J 2012; 27: 455–60. doi:10.5001/omj.2012.109

³⁷ Ying W, Zhixia J, Xiaoyun F, et al. Analysis of the status and influencing factors of post-ICU syndrome in a tertiary hospital in Zunyi city. Journal of Zunyi Medical University 2020; 43: 353–7.

³⁸ Griffith DM, Salisbury LG, Lee RJ, et al. Determinants of health-related quality of life after ICU: importance of patient demographics, previous Comorbidity, and severity of illness. Crit Care Med 2018; 46: 594–601. doi:10.1097/CCM.0000000000002952

³⁹ Kang J, Jeong YJ, Hong J. The effect of Postintensive care syndrome on the quality of life of intensive care unit survivors: A secondary analysis. Aust Crit Care 2021; 34: 246–53. doi:10.1016/j.aucc.2020.08.006

⁴⁰ Jun Z, Xinyang Z, Zhenggang L, et al. Effect of transitional nursing mode on the quality of life of patients with post-ICU syndrome. Chinese Journal of Integrated Traditional Chinese and Western Medicine First Aid 2022; 29: 218–21.

⁴¹ Fengxia W, Zhipeng X, Jianhua W, et al. The effect of early mobilization strategy on the prognosis of patients with post-ICU syndrome. Chinese Journal of Emergency and Critical Care Nursing 2021; 2: 216–20.

⁴² Ranganathan P, Pramesh CS, Aggarwal R. Common pitfalls in statistical analysis: intention-to-treat versus per-protocol analysis. Perspect Clin Res 2016; 7: 144–6. doi:10.4103/2229-3485.184823

⁴³ Min H, Zhixia J, Xingsong H, et al. Discussion on the whole-course management model of post-ICU syndrome based on Stakeholder theory. Nurs Res 2021; 35: 1532–8.