Fatigue in intensive care survivors one year after discharge

Fatigue, perceived by the individual as an overwhelming sense of tiredness at rest, is one of the symptoms most commonly reported by patients [1]. There are many causes of pathological fatigue, including both neurological and non-neurological diseases. Within the last group, cancer, infections, and drugs are factors associated with fatigue [1]. For many cancer patients, fatigue is the most distressing untreated symptom that causes the greatest amount of interference with daily life [2]. Cancer Related Fatigue affects quality of life adversely by reducing mental and physical functioning, disturbing mood, and interfering with usual activities [3]. A survey on Australian and Canadian haematological cancer survivors identified ‘Dealing with feeling tired’ as the highest concern of survivors [4]. Interestingly, fatigue continues to be a problem for breast carcinoma disease-free survivors, 5–10 years after the diagnosis, especially for women treated with both radiation and chemotherapy [5].

Some evidence suggest that patients who have been critically ill continue to face a multitude of physical, psychological, and social difficulties in the long term after discharge [6]. Fatigue has not been widely explored in Intensive Care Unit (ICU) patients but more than 50 % of ICU survivors reported lowered energy levels and fatigue in the first year after discharge [7]. More recently, an extensive survey on long-term complications reported by the General Practitioners who followed ICU survivors at one year showed that decreased exercise tolerance and chronic fatigue were among those most often reported [8], underlying the clinical relevance of chronic fatigue in ICU survivors. However, no study has specifically assessed fatigue among long-term ICU survivors through a validated instrument.

Many instruments to measure fatigue have been proposed in rheumatic conditions [9]. One of the most used is the Functional Assessment Chronic Illness Therapy-Fatigue (FACIT-F) scale. It was developed in 1997 to measure fatigue in oncology patients with anaemia [10], and has been validated in a sample of the general USA population [11], and in patients with rheumatic diseases [9, 12]. Recently, FACIT-F has been validated in patients with inflammatory bowel disease [13], Chronic Obstructive Pulmonary Disease (COPD) [14, 15] and iron deficiency anaemia [16], resulting in one of the most appropriate fatigue questionnaires [17].

Many studies on validation of fatigue questionnaires analysed the correlation between the FACIT-F and the Vitality domain (VT) of the general 36-item Short-Form Health Survey (SF-36) [9]. A strong correlation was found between FACIT-F scale and VT of SF-36, though FACIT-F items cover a wider range of fatigue than the VT items of SF-36 [9, 16].

The aim of the present study was to measure fatigue through a specific instrument (FACIT-F) administered to ICU survivors one year after discharge from the hospital. A secondary aim was to compare the findings of fatigue assessed by FACIT-F with those obtained by the VT of SF-36.

The study was conducted in a mixed medical-surgical 6-bed ICU of a university hospital of 710 beds located in the Northeast of Italy. This ICU serves all thoracic, vascular, and high-risk abdominal surgery patients and about half of the medical ward patients of the hospital.

All consecutive adult ICU patients discharged between March 2013 and October 2014 were considered for enrolment. We included patients aged more than 18 years, staying in ICU for at least 72 h, without pre-existing cognitive dysfunction or language barrier. One year after hospital discharge, we assessed the vital status of the patients through the Vital Statistics Offices. We excluded patients residing farther than 30 km from the hospital, and we contacted the ICU survivors by phone to ask them to participate in the study. Those who agreed received an appointment at the hospital for a date and time convenient for them.

The demographics and clinical data of the study patients were retrieved from the ICU database. The software for this (PROSAFE) is made available by the Italian GiViTI group, and has been used in the study ICU since 2008 for daily collection and storage of patient data. For each participant, the following information was retrieved: gender, age, Body Mass Index (BMI), pre-existing comorbidities (like hypertension, COPD, cardiac failure of NYHA class III or IV, and diabetes), reason for ICU admission, type of admission (elective surgery, emergency surgery, or medical admission), date of hospital and ICU admission, presence of severe sepsis or septic shock (at ICU admission or during ICU stay), main treatments received (administration of vasoactive amines, mechanical ventilation, renal replacement techniques), date of ICU and hospital discharge and vital status at hospital discharge. The following computed data were also retrieved: Simplified Acute Physiology Score (SAPS) II [18] and Sequential Organ Failure Assessment (SOFA) Score [19] which referred to the first 24 h in ICU, and Length Of Stay (LOS) referring to the number of days in ICU and in hospital after ICU discharge.

During the study period, 439 patients were discharged from the ICU alive (Fig. 1). Two hundred and forty of them, who stayed in ICU less than 72 h, as well as 6 patients with a pre-existing cognitive disorder and 4 patients with language barriers, were excluded. Of the remaining 189 patients, 25 died in hospital after ICU discharge, and 34 were dead at one year according to the Vital Statistics Offices. Of the 130 patients alive one year after ICU discharge, 15 refused to participate in the study, and no information about them was collected. Thirty-nine patients who lived farther than 30 km from the hospital, 12 patients who were not found despite multiple attempts to contact them, six patients hospitalized at one year, and two homeless people could not be interviewed. At one year, we directly interviewed 56 patients.

The mean raw FACIT-F score of the study patients was 39.1 (±10.1, median 41, Q1-Q3 34-47), and the FACIT-F-trans value was 66.4 (±12.4, median 66, Q1-Q3 59-74). Cronbach’s α of FACIT-F was 0.937. The correlation coefficient between the FACIT-F-trans and the VT of SF-36 was 0.660 (p < 0.001). The Bland Altman plot of FACIT-F-Trans vs VT showed a bias of -0.8 with 95 % limits of agreement from -34.1 to 35.7 (Fig. 2). The linear regression between differences and means was 0.639, suggesting a significant proportional bias.

The SF-36 data for the study group and the adjusted Italian population [24] are reported in Table 2. The radar chart for the study group and the adjusted Italian normal population is shown in Fig. 3.

		Study patients	Normative valuesa	Delta	p value *
SF-36b
PF	mean	65.89	68.95	-3.1	0.510
	SD	29.45	18.21
	Median	75
	Q1-Q3	44-90
RP	mean	48.66	64.61	-15.9**	0.006
	SD	39.14	15.47
	Median	50
	Q1-Q3	0-100
BP	mean	73.98	63.95	+10	0.021
	SD	29.81	11.37
	Median	84
	Q1-Q3	52-100
GH	mean	60.05	53.81	+6.2	0.074
	SD	23.19	11.38
	Median	67
	Q1-Q3	39-77
VT	mean	65.63	55.34	+10.3	0.001
	SD	20.45	8.14
	Median	68
	Q1-Q3	50-80
SF	mean	76.79	79.70	-2.9	0.435
	SD	26.91	6.61
	Median	88
	Q1-Q3	59-100
RE	mean	72.02	68.06	-4.0	0.496
	SD	42.06	10.16
	Median	100
	Q1-Q3	58-100
MH	mean	72.21	62.06	+10.1	0.001
	SD	20.14	5.92
	Median	76
	Q1-Q3	60-88

^a Data of the Italian normative sample collected by Apolone et al. [24] adjusted for gender and age

^b PF physical functioning, RP role limitation due to physical problems, BP bodily pain, GH general health, VT vitality, SF social functioning, RE role limitation due to emotional problems, MH mental health (range 0-100 with higher scores represent better functioning)

^* p value: statistical significance according to unpaired t test

** Delta value showing a minimum clinically significant difference of more than 5 points, consistent with quality of life worse than the adjusted normal population

Eighteen patients (32 %) reported a perceived breathlessness grade of one (normal value) on the MRCD Scale. Of the remaining patients, 17 (30 %) were in the second grade, 10 (18 %) in the third, 8 (14 %) in the fourth and 3 (6 %) in the fifth grade of the MRCD Scale. The correlation coefficient between the MRCD Scale and FACIT-F-Trans was -0.593 (p = 0.01), and that between the MRCD Scale and VT was -0.430 (p = 0.01).

Chronic fatigue is distressing and greatly interferes with daily activities. It may result from depression but can also cause it, and however worsens the quality of life of patients and their families. Assessing fatigue by a validated instrument is important because it may allow physicians to take care of the patients with chronic fatigue and their families.

Our study patients reported a value of fatigue, assessed by the FACIT-F scale, not too far from that of the general USA population (median 41 vs 47) [11]. The FACIT-F-trans values were significantly related to the VT of SF-36 (Spearman’s rho 0.660). The VT dimension of SF-36 reported by these patients was better than that of the adjusted Italian population (mean 65.6 vs 55.3), both statistically (p = 0.001), and clinically (because it was higher than 5 points [22]). The Bland-Altman plot of SF-36 VT versus FACIT-F-trans showed a small bias (-0.8), but wide limits of agreement and proportional bias.

This is the first study where the FACIT-F questionnaire was administered to former ICU patients. One year after hospital discharge, the mean raw FACIT-F score, which has a range 0-52, was 39.1 ± 10.1. The mean raw values reported in studies performed in different settings ranged from 29.1 [25] to 35.8 [12] in rheumatologic diseases, from 24 ± 11 in iron deficiency anaemia [16] to 23.9 ± 12.6 in anaemic cancer patients [11], and from 40.0 ± 9.8 in non-anaemic cancer patients [11] to 43.6 ± 9.4 in a sample of the general USA population [11]. Therefore, fatigue reported by our study patients was lower than that reported in studies performed in patients, and more similar to that of a normal USA population.

As far as validation of FACIT-F is concerned, Cronbach’s α of 0.937 for our patients was high, and similar to that reported by others [12, 13, 16]. This finding indicates good reliability of the questionnaire, whose questions are likely to measure the same construct. Moreover, the FACIT-F values did not show a floor or ceiling effect (data not shown). We also tested the construct validity considering that the grade of the MRCD scale should be related to fatigue, and we found that FACIT-F was significantly related to the MRCD scale. Therefore, we can conclude that the FACIT-F questionnaire is valid for ICU survivors assessed at one year.

The secondary aim of our study was to verify whether the VT domain of SF-36, which is widely used in the assessment of ICU patients at follow-up, could substitute the most specific FACIT-F questionnaire. We found a good correlation between FACIT-F-trans (range 0-100), and VT of SF-36 (rho 0.660, p < 0.001). The Bland Altman plot showed a bias of -0.8 with 95 % limits of agreement from -34.1 to 35.7. These wide limits of agreement, and the significant proportional bias found by the linear regression suggest that VT does not allow an accurate assessment of fatigue. The reason for this discrepancy between correlation and agreement of FACIT-F and VT may depend on the items assessed by each questionnaire. The FACIT-F consists of 13 items, assessing 11 negative and 2 positive aspects (An5 ‘I have energy’, and An7 ‘I am able to do my usual activities’), while the VT of SF-36 consists of 4 items, that assess 2 positive and 2 negative aspects. We can hypothesize that FACIT-F may grasp the negative aspects of fatigue better than VT.

The VT of SF-36 in our patients was clinically better than that of the adjusted Italian normal population [24]. In detail, values clinically worse (mean of study patients minus normative mean > 5) than that of the adjusted Italian normal population were found for RP, while clinically better values were found for BP, GH, and MH dimensions (Table 2). Many studies assessing quality of life at one year by SF-36, in mixed ICU patients of different countries, generally found values of SF-36 dimensions clinically lower than that of the adjusted normal population [26–31]. Hence, our patients experienced a relatively good quality of life one year after hospital discharge, comparable to that of the adjusted Italian normal population. We do not have an explanation for this finding. Nevertheless, Chiumello et al. [32], who evaluated 26 Italian ARDS patients ventilated in supine or prone position at the one-year stage, had similar results. Interestingly, the assessments of both our patients and those of Chiumello et al. [32] were performed by direct interview at the hospital, and the percentages of the eligible patients assessed were 43 % and 39 %, respectively. We excluded patients residing farther than 30 km from the hospital, and Chiumello et al. [32] excluded patients residing more than 40 km from the hospital. Of the 15 patients (11.5 %) who refused to participate, some claimed that they had difficulty in reaching the hospital. Therefore, the assessment of patients at the hospital may create a selection bias. An alternative hypothesis is that the Italian normative sample, collected in 1995 [24], may not be suitable for comparisons after 20 years. Indeed, the country with the world's second highest life expectancy in 2012 and 2013 [33], has a relatively healthy cuisine and diet, and a good healthcare system. Possibly, all these factors may have positively affected health-related quality of life over time, with better actual normal values than in the past.

This study has strengths and limitations. As far as the former are concerned, the comparison between the patients interviewed and those missing the interview showed no statistically significant differences, except for BMI and LOS in ICU, which were slightly different (Table 1). Therefore, our findings should be of general value although we cannot rule out any undetected selection bias. The exclusion of patients living over 30 km from the hospital is a limitation, and we do not know whether some refusals may mask any symptoms related to Post Traumatic Stress Disorder [34]. Collecting data by direct interview allowed us to have very little missing data (33 of 2744 items, 0.01 %), and guarantees the absence of interference from family members or other persons in the answers to the questionnaires. Moreover, it allowed all patients to give their written informed consent to the study, as required by the Ethics Committee.

This study validates the 13-item FACIT-F scale to assess fatigue in ICU survivors one year after hospital discharge. The Vitality dimension of SF-36 correlates with the FACIT-F scale, but consists of only four items assessing two positive and two negative aspects of vitality. FACIT-F grasps the negative aspects of fatigue better than the Vitality dimension of SF-36. Specific tools assess specific conditions better that general tools. This information should be useful for future studies designed to investigate fatigue in former ICU patients.