Abstract
Objective
To evaluate the ability of the Perme Score to detect changes in the level of mobility of patients with COVID-19 outside the intensive care unit.
Method
A retrospective cohort study was conducted in inpatient units of a private hospital. Patients older than 18, diagnosed with COVID-19, who were discharged from the intensive care unit and remained in the inpatient units were included. The variables collected included demographic characterization data, length of hospital stay, respiratory support, Perme Score values at admission to the inpatient unit and at hospital discharge and the mobilization phases performed during physical therapy.
Result
A total of 69 patients were included, 80% male and with a mean age of 61.9 years (SD=12.5 years). The comparison of the Perme Score between the times of admission to the inpatient unit and at hospital discharge shows significant variation, with a mean increase of 7.3 points (95%CI:5.7-8.8; p<0.001), with estimated mean values of Perme Score at admission of 17.5 (15.8; 19.3) and hospital discharge of 24.8 (23.3; 26.3). There was no association between Perme Score values and length of hospital stay (measure of effect and 95%CI 0.929 (0.861; 1.002; p=0.058)).
Conclusion
The Perme Score proved effective for assessing mobility in patients diagnosed with COVID-19 with prolonged hospitalization outside the intensive care setting. In addition, we demonstrated by the value of the Perme Score that the level of mobility increases significantly from the time of admission to inpatient units until hospital discharge. There was no association between the Perme Score value and length of hospital stay.
Keywords: humans, male, patient discharge, length of stay, inpatients, COVID-19, Physical therapy modalities
Introduction
In December 2019, a set of pneumonia cases, later proven to be caused by a new coronavirus (called “COVID-19”), appeared in Wuhan, Hubei Province, China.1 The World Health Organization (WHO) declared COVID-19 a pandemic in March 2020, raising an alert for an unprecedented public health emergency.2
Although most patients have a favourable outcome, approximately 5% have severe clinical manifestations with respiratory failure, septic shock and multiple organ failure.3 Prolonged intensive care unit (ICU) stay due to disease severity4,5 associated with intense inflammatory processes caused by COVID-19 infection6,7 may have potential effects on the musculoskeletal system, with decreased muscle mass and myopathies that predispose to muscle dysfunction that may contribute to loss of mobility, functional disability and decreased quality of life up to one year after hospital discharge.8
Thus, evaluating the patient’s functional status during the entire hospitalization, whether in the intensive care setting or not, becomes essential for advancing rehabilitation, which already starts during the hospitalization period. Several measuring instruments have been adapted to assess patients’ physical function in the ICU.9,10 All these assessment measures evaluate the physical function of patients, but only the Perme Score evaluates the barriers to mobilization in addition to patient-related factors.11,12
The Perme Score is an instrument that objectively measures the mobility status of patients admitted to the ICU. It comprises 15 items divided into seven categories, and the total Perme Score ranges from 0 to 32 points. Lower scores are associated with a lower level of mobility, and higher scores are associated with a higher level of mobility. In 2021, Timenetsky et al. used the Perme Score to describe the level of mobility of patients with COVID-19 admitted to the ICU and concluded that the level of mobility of patients was low on ICU admission and that most patients improved their level of mobility during the ICU stay.13 Continued assessment of functional status outside the intensive care setting ensures progress in the rehabilitation process. Thus, using the same instrument facilitates the comparison and evolution of the patient throughout hospitalization.
This study aims to evaluate the ability of the Perme Score to detect changes in the level of mobility of patients with COVID-19 outside the ICU and correlate the Perme Score value with length of stay.
Material and Methods
Type and location of the study
A retrospective cohort study was conducted in a private hospital’s inpatient unit medical clinic in São Paulo with data from February to October 2021.
Ethical Aspects
This study was submitted to and approved by the Ethics and Research Committee, and the Free and Informed Consent form was granted an exemption. This study is in accordance with the recently amended Declaration of Helsinki of 1975.
Data collection
Patients older than 18 years with a diagnosis of COVID-19 confirmed by reverse transcription polymerase chain reaction (RT–PCR) who were discharged from the ICU and remained in the inpatient units (IU) were included in the study.
All study data were retrieved from the electronic medical records by an independent research assistant from the Department of Clinical Medicine from February to October 2021. The data were tabulated in a REDCap database14 by the same research assistant, who did not participate as the author of this study. The data were made available to the authors completely anonymized.
Clinical variables
The variables collected included age, gender, length of stay in the ICU, date of intubation, date of extubation, time of invasive mechanical ventilation, date of hospitalization, date of hospitalization in the medical clinic, date of hospital discharge, Perme Score at admission to the inpatient unit and at hospital discharge, tracheostomy, tracheostomy date and tracheostomy decannulation date. In addition, the mobilization phases performed during physical therapy care ranging from 1 to 5 and following the institutional protocol were collected.15
The mobility level was evaluated using the “Perme Score of Mobility in the Intensive Care Unit” (Perme Score).11,12 This measurement instrument was developed and proposed to evaluate the mobility level of patients admitted to intensive care. It comprises 15 items divided into seven categories: mental status, potential mobility barriers, functional strength, bed mobility, transfers, gait, and endurance. The total score of the Perme ranges from 0 to 32 points (see Figure 1). The lowest scores are associated with a lower level of mobility, and the highest scores are associated with a higher level of mobility. The Perme Score was translated from the English language, adapted, and validated for use in the Portuguese language spoken in Brazil and is thus far considered the only ICU-specific measurement instrument to consider barriers to mobilization.12
Figure 1. Comparison between patients older than 65 and up to 65 years old and in relation to gender regarding the Perme Score at admission to the inpatient unit, and comparison in the Perme Score variation of patients with COVID-19 admitted to medical units after discharge from the ICU (N=69).

In all comparisons, there was no evidence of a significant difference (p>0.05). *P values were obtained using the Mann–Whitney test. The score was calculated by the inpatient unit reference physiotherapists, who were trained to apply the score. The Perme assessment was performed on the day of admission of the patient to the inpatient unit and in the 24 hours before hospital discharge.
Statistical analysis
The data were described as absolute and relative frequencies for the categorical variables, medians and quartiles, and minimum and maximum values for the numerical variables. The distributions of the numerical variables were studied using histograms, boxplots, and the Shapiro-Wilk normality test.
Comparisons between patients older than 65 and up to 65 years old and in relation to gender regarding the Perme Score at entry and the variation of the Perme Score were performed using nonparametric Mann–Whitney tests. Values are expressed as medians (1st quartile; 3rd quartile), minimum and maximum values.
The Perme Scores were compared between the time at admission to the IU and at hospital discharge using a mixed linear model, considering the dependence between the applications of the instrument in the same patient. The results of the model are presented as estimated mean values, 95% confidence intervals (95%CI) and p values.
A logistic model was applied to investigate the relationship of the Perme Score on admission to the IU with the length of stay in the IU. The length of stay is dichotomized into long stay (more than seven days) or not (up to seven days). The results are presented as measures of effect, 95%CI and p values. The analyses were performed using the SPSS statistical package, considering a significance level of 5%.
Results
The database contained 89 records of patients with COVID-19 admitted to medical units after discharge from the ICU. Twenty patients were excluded because they did not have data on the Perme Score at admission to the IU and/or the date of hospital discharge.
A total of 69 patients were included, of whom almost 80% were male and had a mean age of 61.9 years (SD=12.5 years). The sample was quite homogeneous in relation to age, with 53.6% up to 65 years old and 46.4% over 65 years old. The demographic characteristics and length of hospital stay and ventilatory support are described in Table 1.
Table 1. Sociodemographic and hospitalization characteristics of patients with COVID-19 admitted to medical units after discharge from the ICU (N=69).
| Mean (SD) | 61,9 (12,5) |
| Men | 55 (79,7%) |
| Women | 14 (20,3)% |
| Length of hospital stay (days) | 55,0 (33,0; 81,0) |
| Length of ICU stay (days) | 39,0 (21,0; 60,0) |
| Length of stay in the IU (days) | 12,0 (8,0; 19,0) |
| Tracheostomy | 33 (48,5%) |
| Decannulated | 23 (92,0%) |
| TQT time | 40,0 (28,0; 63,0) |
| Minimum; maximum | 15,0; 108,0 |
| Mechanical ventilation time (days) | 20,0 (11,0; 58,0) |
| Minimum; maximum | 3,0; 130,0 |
| Oxygen in IU | 56 (81,2%) |
| Oxygen after discharge to home | 17 (25,0%) |
| NIV in the IU | 36 (52,9%) |
| NIV after discharge to home | 4 (5,9%) |
Values are expressed as the median and interquartile range, except for age, which is expressed as the mean and standard deviation. SD: standard deviation Q1: first quartile; Q3: third quartile. ICU: Intensive care unit; TQT: tracheostomy; IU: inpatient unit; NIV: Noninvasive ventilation.
We investigated the differences between patients older than 65 years old and up to 65 years old and between men and women in relation to the Perme Score at admission to the IU and the variation in the Perme Score (difference between the Perme Score value at hospital discharge and upon admission to the IU). and the tests for the hypothesis of equality between the groups showed no evidence of differences (p> 0.05). See Figure 2.
Figure 2. Individual (dotted lines) and mean (continuous line) in the Perme Score variation between at admission to the inpatient unit and at hospital discharge of patients with COVID-19 hospitalized in medical units after discharge from the ICU (N=69).

The comparison of the Perme Score between admission to the IU and at hospital discharge shows significant variation (see Figure 3), with a mean increase of 7.3 points (95%CI: 5.7-8.8; p <0.001), with values of estimated mean of the Perme Score at admission to the inpatient unit of 17.5 (15.8; 19.3) and at hospital discharge of 24.8 (23.3; 26.3).
Figure 3. Percentage of patients included in each mobilization phase during physical therapy sessions.

Considering the ceiling effect in the Perme Score, only one (1.4%) patient had a maximum score at the entrance and at the exit, and we observed a total of 12 (17.9%) patients with a maximum score among the 69 evaluated.
The mobilization phases performed during physical therapy are shown in Figure 3.
The logistic model that analyzed the association between the entry Perme Score value and length of hospital stay did not show a significant association with an effect measure and 95%CI 0.929 (0.861; 1.002; p=0.058).
Discussion
In this study, we demonstrated the mobility status of patients diagnosed with SARS-CoV-2 upon arrival at inpatient units, i.e., after discharge from the ICU, and their progression to hospital discharge using the Perme Score.
Our patients were predominantly male (79.7%), and the mean age was 61.9 years. Other authors found an average age similar to ours, approximately 60 years; however, in terms of sex, the distribution of these studies was 57%, 82% and 58%, respectively.13,16,17 In addition, our patients had a hospitalization time of more than 30 days, and almost half required tracheostomy, reinforcing the characteristics of critically ill patients exposed to potential risk factors for loss of functional mobility. Argenzioano et al., describing the characteristics of a thousand COVID-19 patients, found a length of hospital stay similar to that of our study, with an average of 23 days of hospitalization.18
Our study found no age or gender difference in the Perme Score values upon admission to the IU or in the Perme Score variation; however, the heterogeneous distribution of our sample in terms of sex (79.1% male) may have influenced this result. In contrast, Timenetsky identified a significant difference in age between patients who showed improvement in the Perme Score values in the ICU versus those who showed no improvement.13 The group with an improved Perme Score was younger, with a mean age of 62.5 years, compared to a mean age of 79.5 years in the group without improvement. This same study found no difference in relation to gender. A higher prevalence of frailty in females has been described in critically ill and non-critically ill populations.19,20 Therefore, assessing the impact of sex on the condition and clinical evolution must be very careful.
The impact on mobility as a consequence of musculoskeletal changes associated with myopathies and loss of muscle mass in critically ill patients has been described by several authors,4,21,22 and these changes are also replicated in patients with COVID-19 due to the severity of the disease, disease alone or due to the characteristic of viral pathophysiology, which is still poorly understood.23
Our study used the Perme Score as an instrument to assess patient mobility during their stay in the inpatient units. The Perme Score is a scale developed to evaluate patient mobility in the intensive care setting, taking into account conditions extrinsic to the patient who interfere with their mobility in the bed, such as the presence of supplemental oxygen device, endotracheal tube, many types of intravenous and intraarterial access and catheters, gastrostomy, nasogastric tube, chest drains, which can be interpreted as a barrier to mobility.11,12 Until then, no functional assessment instrument had taken these factors into account. Although evaluated outside the intensive care setting, our patients met the inclusion characteristics of the patients for the use of the Perme Score since they could have intravenous or intraarterial access, gastrostomy, nasogastric tube and chest drains and noninvasive ventilation. These data were described in 52.9% of the patients included in our study.
Pereira et al. also used the Perme Score to assess the functionality of patients undergoing liver transplantation at the time of hospital discharge, i.e., outside the intensive care setting. In this study, the average Perme Score at admission to inpatient units was 28 and at discharge 31. This score is close but not reaching the Perme ceiling, which is 32 points.24 When compared to the study by Pereira, our patients had lower mobility because the Perme Score at admission to IU was 17 points, with a significant gain of 7 points (p <0.001) until the time of hospital discharge, guiding the importance of the rehabilitation process still in the in-hospital phase but also making clear the impact of COVID-19 on the loss of mobility of patients.
Finally, with respect to the floor and ceiling effect of the instruments, a floor and ceiling effect of up to 15% is considered acceptable.25 One of the limitations of using Perme is the floor effect: patients who score zero on the scale due to sedation due to clinical severity, common for critically ill patients; and ceiling effect: patients who score 32 on the scale for not having any mobility deficit or barrier to mobilization, very common in patients in inpatient units. For our patient profile, a ceiling effect would be expected, i.e., that the patients had maximum values of the Perme Score. In the evaluation of the entry Perme Score, only 1 (1.4%) patient had a maximum score of 32 points.
Our results, added to the results published by Pereira et al., reinforce the applicability of its use in inpatient units and encourage future studies to validate the Perme Score in this new scenario.
In the intensive care environment, studies demonstrate that early mobilization reduces the length of stay in the ICU and length of hospital stay, reduces the number of days on mechanical ventilation and prevents physical deconditioning.26–28 It is worth mentioning that the gains are not only motor and how much the removal of the patient from the bed influences the improvement of pulmonary ventilation, improves oxygenation, and consequently reduces the need for ventilatory support in general.29,30 In recent decades, we have had significant gains in terms of mobility in the ICU.28,31 However, little is known about how well these gains are maintained in the transition from ICU to inpatient units and how long it takes to regain the mobility levels they had before admission.
Undoubtedly, using a single instrument to assess the patient’s mobility throughout their hospitalization journey would make more sense for the continuity of care in all phases of the rehabilitation process.
There are several instruments that assess the functional status in the ICU,9,10,32 but none that are used during the entire period of hospitalization. The hospital environment offers challenges to the rehabilitation process because, in addition to motor changes inherent to the individual, there is a range of devices used that offer restrictions to them and that should be considered during the therapeutic program appropriate to the patient’s condition.
For most patients, discharge from the ICU means an improvement in the patient’s condition and the beginning of a return to baseline functionality. However, an initial lapse in mobility activity may indicate the existence of barriers that prevent patients from promptly continuing their mobility trajectory from their achievements in the ICU. In the only previous study focusing on mobility activity in IU, Hopkins and colleagues32 found a decrease in activity within the first 24 hours in IUs.
The performance of motor physical therapy in the recovery of patients with COVID-19 has an essential role in gaining mobility, restoring physical independence, and recovering functional capacity.33,34 The prevention of the negative effects of immobility is a priority in preventing the loss of functional status of patients who develop severe conditions associated with COVID-19. Improving patient mobility, as evidenced by the Perme Score, decreases the length of hospital stay.26–28 Thus, therapeutic planning may include behaviour that prioritizes patient mobility through postural changes, sitting, standing, and walking when possible.35
Our rehabilitation program has been following the recommendation of the literature that proposes mobilization protocols based on the Perme Score, which certainly favours its implementation in practice, associating the assessment instrument with activity levels.15,36 It is divided into 5 phases and is performed depending on the clinical conditions of the patient, ranging from passive mobilization (phase 1) to independent gait (phase 5). Our results demonstrate that the mobility gain evidenced by the Perme Score was accompanied by advancement in the phases of the rehabilitation process. There was a transition of 39% of patients from phases 1 to 3 to phases 4 and 5 during the IU stay.
Limitations
Our study has limitations. The first is that the data were retrieved using a database, which limited our access to the patient’s previous health condition and possible comorbidities and limited the interpretation of the value of the Perme Score in its entirety. It would help if we had the data for all domains. The second is the heterogeneity of the sample in terms of sex (79.1% male), which may have influenced the results of comparing the Perme Score in terms of sex. The third is our small sample size. The fourth is the use of a non-validated instrument, as is the case with the Perme Score in inpatient units; however, one of the objectives of the study is to demonstrate the effectiveness of the instrument in the inpatient units to stimulate a validation study that will probably take place with our group.
Conclusion
The Perme Score proved effective for assessing mobility in patients diagnosed with COVID-19 with prolonged hospitalization outside the intensive care setting. In addition, we demonstrated by the value of the Perme Score that the level of mobility increases significantly from the time of admission to inpatient units until hospital discharge. The continuity of the assessment of the mobility level outside the intensive care environment provides the guarantee of evolution in the rehabilitation process. Thus, using the same instrument provides the comparison and measurement of the patient’s evolution throughout the entire period of hospitalization.
Contributors
MSN made substantial contributions to study conception and design, data acquisition, analysis and interpretation of the data and has been involved in drafting the manuscript and revising it critically for important intellectual content; CT, RACE, SB, LLSG and FMS made substantial contributions to study conception and design and acquisition, analysis, and interpretation of the data and has been involved in drafting the manuscript and revising it critically for important intellectual content; FBT made substantial contributions to study conception and design and analysis and interpretation of the data and have been involved in drafting the manuscript and providing final approval of the version to be published.
Competing interest
All the authors declare no competing interests.
Ethics approval
This study was submitted to and approved by the Ethics and Research committee of the Hospital Israelita Albert Einstein, CAAE 5743322.2.0000.0071, and the Free and Informed Consent form was granted exemption. This study is in accordance with the recently amended Declaration of Helsinki of 1975.
Acknowledgments
Acknowledgments
We thank the statistics team, especially for the help of Sandra Regina Malagutti.
Funding Statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References
- A novel coronavirus from patients with pneumonia in China, 2019. Zhu Na, Zhang Dingyu, Wang Wenling, Li Xingwang, Yang Bo, Song Jingdong, Zhao Xiang, Huang Baoying, Shi Weifeng, Lu Roujian, Niu Peihua, Zhan Faxian, Ma Xuejun, Wang Dayan, Xu Wenbo, Wu Guizhen, Gao George F., Tan Wenjie. Feb 20;2020 New England Journal of Medicine. 382(8):727–733. doi: 10.1056/nejmoa2001017. doi: 10.1056/nejmoa2001017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- WHO Coronavirus disease 2019 (COVID-19): situation report. [2020-7-24]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019
- Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Huang Chaolin, Wang Yeming, Li Xingwang, Ren Lili, Zhao Jianping, Hu Yi, Zhang Li, Fan Guohui, Xu Jiuyang, Gu Xiaoying, Cheng Zhenshun, Yu Ting, Xia Jiaan, Wei Yuan, Wu Wenjuan, Xie Xuelei, Yin Wen, Li Hui, Liu Min, Xiao Yan, Gao Hong, Guo Li, Xie Jungang, Wang Guangfa, Jiang Rongmeng, Gao Zhancheng, Jin Qi, Wang Jianwei, Cao Bin. Feb;2020 The Lancet. 395(10223):497–506. doi: 10.1016/s0140-6736(20)30183-5. doi: 10.1016/s0140-6736(20)30183-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fredericks C.M. In: Pathophysiology of the motor systems: principles and clinical presentations. Fredericks C.M., Saladim L.K., editors. F.A. Davis Company; Philadelphia: Adverse effects of immobilization on the musculoskeletal system. [Google Scholar]
- Mobilizing patients in the intensive care unit: improving neuromuscular weakness and physical function. Needham Dale M. Oct 8;2008 JAMA. 300(14):1685–90. doi: 10.1001/jama.300.14.1685. doi: 10.1001/jama.300.14.1685. [DOI] [PubMed] [Google Scholar]
- Post-COVID-19 acute sarcopenia: physiopathology and management. Piotrowicz Karolina, Gąsowski Jerzy, Michel Jean-Pierre, Veronese Nicola. Jul 30;2021 Aging Clinical and Experimental Research. 33(10):2887–2898. doi: 10.1007/s40520-021-01942-8. doi: 10.1007/s40520-021-01942-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China. Mao Ling, Jin Huijuan, Wang Mengdie, Hu Yu, Chen Shengcai, He Quanwei, Chang Jiang, Hong Candong, Zhou Yifan, Wang David, Miao Xiaoping, Li Yanan, Hu Bo. Jun 1;2020 JAMA Neurology. 77(6):683–90. doi: 10.1001/jamaneurol.2020.1127. doi: 10.1001/jamaneurol.2020.1127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Functional disability 5 years after acute respiratory distress syndrome. Herridge Margaret S., Tansey Catherine M., Matté Andrea, Tomlinson George, Diaz-Granados Natalia, Cooper Andrew, Guest Cameron B., Mazer C. David, Mehta Sangeeta, Stewart Thomas E., Kudlow Paul, Cook Deborah, Slutsky Arthur S., Cheung Angela M. Apr 7;2011 New England Journal of Medicine. 364(14):1293–1304. doi: 10.1056/nejmoa1011802. doi: 10.1056/nejmoa1011802. [DOI] [PubMed] [Google Scholar]
- Assessment of impairment and activity limitations in the critically ill: a systematic review of measurement instruments and their clinimetric properties. Parry Selina M., Granger Catherine L., Berney Sue, Jones Jennifer, Beach Lisa, El-Ansary Doa, Koopman René, Denehy Linda. Feb 5;2015 Intensive Care Medicine. 41(5):744–762. doi: 10.1007/s00134-015-3672-x. doi: 10.1007/s00134-015-3672-x. [DOI] [PubMed] [Google Scholar]
- Versão brasileira da Escala de Estado Funcional em UTI: tradução e adaptação transcultural. Silva V.Z.M. da, Araújo J.A. de, Cipriano G., Pinedo M., Needham D.M., Zanni J.M., et al. 2017Rev. bras. ter. intensiva. 29(1):34–38. doi: 10.5935/0103-507X.20170006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- A tool to assess mobility status in critically ill patients: the Perme Intensive Care Unit Mobility Score. Perme Christiane, Nawa Ricardo Kenji, Winkelman Chris, Masud Faisal. Jan 1;2014 Methodist DeBakey Cardiovascular Journal. 10(1):41–9. doi: 10.14797/mdcj-10-1-41. doi: 10.14797/mdcj-10-1-41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Perme Intensive Care Unit Mobility Score and ICU Mobility Scale: translation into Portuguese and cross-cultural adaptation for use in Brazil. Kawaguchi Yurika Maria Fogaça, Nawa Ricardo Kenji, Figueiredo Thais Borgheti, Martins Lourdes, Pires-Neto Ruy Camargo. Dec;2016 Jornal Brasileiro de Pneumologia. 42(6):429–434. doi: 10.1590/s1806-37562015000000301. doi: 10.1590/s1806-37562015000000301. [DOI] [PMC free article] [PubMed] [Google Scholar]
- The Perme Mobility Index: A new concept to assess mobility level in patients with coronavirus (COVID-19) infection. Timenetsky Karina Tavares, Serpa Neto Ary, Lazarin Ana Carolina, Pardini Andreia, Moreira Carla Regina Sousa, Corrêa Thiago Domingos, Caserta Eid Raquel Afonso, Nawa Ricardo Kenji. Apr 21;2021 PLoS ONE. 16(4):e0250180. doi: 10.1371/journal.pone.0250180. doi: 10.1371/journal.pone.0250180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. Harris Paul A., Taylor Robert, Thielke Robert, Payne Jonathon, Gonzalez Nathaniel, Conde Jose G. Apr;2009 Journal of Biomedical Informatics. 42(2):377–381. doi: 10.1016/j.jbi.2008.08.010. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Protocolo fisioterapêutico com base na escala Perme Intensive Care Unit Mobility Score para doentes críticos. Thielo Luisa Farias, Quintana Luciana Dias, Rabuske Marilene. 2020ASSOBRAFIR Ciência. 11(1):e42249. doi: 10.47066/2177-9333.ac.2020.0009. doi: 10.47066/2177-9333.ac.2020.0009. [DOI] [Google Scholar]
- Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. Grasselli Giacomo, Zangrillo Alberto, Zanella Alberto, Antonelli Massimo, Cabrini Luca, Castelli Antonio, Cereda Danilo, Coluccello Antonio, Foti Giuseppe, Fumagalli Roberto, Iotti Giorgio, Latronico Nicola, Lorini Luca, Merler Stefano, Natalini Giuseppe, Piatti Alessandra, Ranieri Marco Vito, Scandroglio Anna Mara, Storti Enrico, Cecconi Maurizio, Pesenti Antonio, Agosteo Emiliano, Alaimo Valentina, Albano Giovanni, Albertin Andrea, Alborghetti Armando, Aldegheri Giorgio, Antonini Benvenuto, Barbara Enrico, Belgiorno Nicolangela, Belliato Mirko, Benini Annalisa, Beretta Enrico, Bianciardi Leonardo, Bonazzi Stefano, Borelli Massimo, Boselli Enrico, Bronzini Nicola, Capra Carlo, Carnevale Livio, Casella Giampaolo, Castelli Gianpaolo, Catena Emanuele, Cattaneo Sergio, Chiumello Davide, Cirri Silvia, Citerio Giuseppe, Colombo Sergio, Coppini Davide, Corona Alberto, Cortellazzi Paolo, Costantini Elena, Covello Remo Daniel, De Filippi Gianluca, Dei Poli Marco, Della Mura Federica, Evasi Giulia, Fernandez-Olmos Raquel, Forastieri Molinari Andrea, Galletti Marco, Gallioli Giorgio, Gemma Marco, Gnesin Paolo, Grazioli Lorenzo, Greco Stefano, Gritti Paolo, Grosso Paolo, Guatteri Luca, Guzzon Davide, Harizay Fabiola, Keim Roberto, Landoni Giovanni, Langer Thomas, Lombardo Andrea, Malara Annalisa, Malpetti Elena, Marino Francesco, Marino Giovanni, Mazzoni Maurizio Giovanni , Merli Guido, Micucci Antonio, Mojoli Francesco, Muttini Stefano, Nailescu Adriana, Panigada Mauro, Perazzo Paolo, Perego Giovanni Battista, Petrucci Nicola, Pezzi Angelo, Protti Alessandro, Radrizzani Danilo, Raimondi Maurizio, Ranucci Marco, Rasulo Frank, Riccio Mario, Rona Roberto, Roscitano Claudio, Ruggeri Patrizia, Sala Antonello, Sala Giuseppe, Salvi Luca, Sebastiano Pietro, Severgnini Paolo, Sforzini Ilaria, Sigurtà Francesco Donato, Subert Matteo, Tagliabue Paola, Troiano Carmine, Valsecchi Roberto, Viola Uberto, Vitale Giovanni, Zambon Massimo, Zoia Elena, COVID-19 Lombardy ICU Network Apr 28;2020 JAMA. 323(16):1574–81. doi: 10.1001/jama.2020.5394. doi: 10.1001/jama.2020.5394. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Clinical characteristics of coronavirus disease 2019 in China. Guan Wei-Jie, Ni Zheng-Yi, Hu Yu, Liang Wen-hua, Ou Chun-quan, He Jian-xing, Liu Lei, Shan Hong, Lei Chun-liang, Hui David S.C., Du Bin, Li Lan-juan, Zeng Guang, Yuen Kwok-Yung, Chen Ru-chong, Tang Chun-li, Wang Tao, Chen Ping-yan, Xiang Jie, Li Shi-yue, Wang Jin-lin, Liang Zi-jing, Peng Yi-xiang, Wei Li, Liu Yong, Hu Ya-hua, Peng Peng, Wang Jian-ming, Liu Ji-yang, Chen Zhong, Li Gang, Zheng Zhi-jian, Qiu Shao-qin, Luo Jie, Ye Chang-jiang, Zhu Shao-yong, Zhong Nan-shan. Apr 30;2020 New England Journal of Medicine. 382(18):1708–1720. doi: 10.1056/nejmoa2002032. doi: 10.1056/nejmoa2002032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series. Argenziano Michael G, Bruce Samuel L, Slater Cody L, Tiao Jonathan R, Baldwin Matthew R, Barr R Graham, Chang Bernard P, Chau Katherine H, Choi Justin J, Gavin Nicholas, Goyal Parag, Mills Angela M, Patel Ashmi A, Romney Marie-Laure S, Safford Monika M, Schluger Neil W, Sengupta Soumitra, Sobieszczyk Magdalena E, Zucker Jason E, Asadourian Paul A, Bell Fletcher M, Boyd Rebekah, Cohen Matthew F, Colquhoun MacAlistair I, Colville Lucy A, de Jonge Joseph H, Dershowitz Lyle B, Dey Shirin A, Eiseman Katherine A, Girvin Zachary P, Goni Daniella T, Harb Amro A, Herzik Nicholas, Householder Sarah, Karaaslan Lara E, Lee Heather, Lieberman Evan, Ling Andrew, Lu Ree, Shou Arthur Y, Sisti Alexander C, Snow Zachary E, Sperring Colin P, Xiong Yuqing, Zhou Henry W, Natarajan Karthik, Hripcsak George, Chen Ruijun. May 29;2020 BMJ. 369:m1996. doi: 10.1136/bmj.m1996. doi: 10.1136/bmj.m1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sex-specific prevalence and outcomes of frailty in critically ill patients. Hessey Erin, Montgomery Carmel, Zuege Danny J., Rolfson Darryl, Stelfox Henry T., Fiest Kirsten M., Bagshaw Sean M. Sep 29;2020 Journal of Intensive Care. 8(1):75–83. doi: 10.1186/s40560-020-00494-9. doi: 10.1186/s40560-020-00494-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sex Differences in Frailty. Hubbard Ruth E. 2015Frailty in Aging. 41:41–53. doi: 10.1159/000381161. doi: 10.1159/000381161. [DOI] [PubMed] [Google Scholar]
- Acute skeletal muscle wasting in critical illness. Puthucheary Zudin A., Rawal Jaikitry, McPhail Mark, Connolly Bronwen, Ratnayake Gamunu, Chan Pearl, Hopkinson Nicholas S., Padhke Rahul, Dew Tracy, Sidhu Paul S., Velloso Cristiana, Seymour John, Agley Chibeza C., Selby Anna, Limb Marie, Edwards Lindsay M., Smith Kenneth, Rowlerson Anthea, Rennie Michael John, Moxham John, Harridge Stephen D. R., Hart Nicholas, Montgomery Hugh E. Oct 16;2013 JAMA. 310(15):1591–1600. doi: 10.1001/jama.2013.278481. doi: 10.1001/jama.2013.278481. [DOI] [PubMed] [Google Scholar]
- Novel events in the molecular regulation of muscle mass in critically ill patients. Constantin Despina, McCullough Justine, Mahajan Ravi P., Greenhaff Paul L. Jul 28;2011 The Journal of Physiology. 589(15):3883–3895. doi: 10.1113/jphysiol.2011.206193. doi: 10.1113/jphysiol.2011.206193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Neuroinfection may contribute to pathophysiology and clinical manifestations of COVID-19. Steardo Luca, Steardo Luca Jr., Zorec Robert, Verkhratsky Alexei. Apr 11;2020 Acta Physiologica. 229(3):e13473. doi: 10.1111/apha.13473. doi: 10.1111/apha.13473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- The Perme scale score as a predictor of functional status and complications after discharge from the intensive care unit in patients undergoing liver transplantation. Pereira Camila Santos, Carvalho Alexandra Torres, Bosco Adriane Dal, Forgiarini Júnior Luiz Alberto. 2019Revista Brasileira de Terapia Intensiva. 31(1):57–62. doi: 10.5935/0103-507x.20190016. doi: 10.5935/0103-507x.20190016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Quality criteria were proposed for measurement properties of health status questionnaires. Terwee Caroline B., Bot Sandra D.M., de Boer Michael R., van der Windt Daniëlle A.W.M., Knol Dirk L., Dekker Joost, Bouter Lex M., de Vet Henrica C.W. Jan;2007 Journal of Clinical Epidemiology. 60(1):34–42. doi: 10.1016/j.jclinepi.2006.03.012. doi: 10.1016/j.jclinepi.2006.03.012. [DOI] [PubMed] [Google Scholar]
- ICU early mobilization: from recommendation to implementation at three medical centers. Engel Heidi J., Needham Dale M., Morris Peter E., Gropper Michael A. Sep;2013 Critical Care Medicine. 41:S69–S80. doi: 10.1097/ccm.0b013e3182a240d5. doi: 10.1097/ccm.0b013e3182a240d5. [DOI] [PubMed] [Google Scholar]
- Early intensive care unit mobility therapy in the treatment of acute respiratory failure. Morris Peter E., Goad Amanda, Thompson Clifton, Taylor Karen, Harry Bethany, Passmore Leah, Ross Amelia, Anderson Laura, Baker Shirley, Sanchez Mary, Penley Lauretta, Howard April, Dixon Luz, Leach Susan, Small Ronald, Hite R Duncan, Haponik Edward. Aug;2008 Critical Care Medicine. 36(8):2238–2243. doi: 10.1097/ccm.0b013e318180b90e. doi: 10.1097/ccm.0b013e318180b90e. [DOI] [PubMed] [Google Scholar]
- Effectiveness of an early mobilization protocol in a trauma and burns intensive care unit: a retrospective cohort study. Clark Diane E., Lowman John D., Griffin Russell L., Matthews Helen M., Reiff Donald A. Feb 1;2013 Physical Therapy. 93(2):186–196. doi: 10.2522/ptj.20110417. doi: 10.2522/ptj.20110417. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mobilization Started Within 2 Hours After Abdominal Surgery Improves Peripheral and Arterial Oxygenation: A Single-Center Randomized Controlled Trial. Svensson-Raskh Anna, Schandl Anna Regina, Ståhle Agneta, Nygren-Bonnier Malin, Fagevik Olsén Monika. Mar 20;2021 Physical Therapy. 101(5):pzab094. doi: 10.1093/ptj/pzab094. doi: 10.1093/ptj/pzab094. [DOI] [PMC free article] [PubMed] [Google Scholar]
- The effect of body position on pulmonary function: a systematic review. Katz Shikma, Arish Nissim, Rokach Ariel, Zaltzman Yacov, Marcus Esther-Lee. Oct 11;2018 BMC Pulmonary Medicine. 18(1):159. doi: 10.1186/s12890-018-0723-4. doi: 10.1186/s12890-018-0723-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Early intervention (mobilization or active exercise) for critically ill adults in the intensive care unit. Doiron Katherine A, Hoffmann Tammy C, Beller Elaine M. Mar 27;2018 Cochrane Database of Systematic Reviews. 2018(12):CD010754. doi: 10.1002/14651858.cd010754.pub2. doi: 10.1002/14651858.cd010754.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Physical therapy on the wards after early physical activity and mobility in the intensive care unit. Hopkins Ramona O., Miller Russell R., III, Rodriguez Larissa, Spuhler Vicki, Thomsen George E. Dec 1;2012 Physical Therapy. 92(12):1518–1523. doi: 10.2522/ptj.20110446. doi: 10.2522/ptj.20110446. [DOI] [PubMed] [Google Scholar]
- Physical rehabilitation in the ICU: a systematic review and meta-analysis. Wang Yi Tian, Lang Jenna K., Haines Kimberley J., Skinner Elizabeth H., Haines Terry P. Aug 18;2021 Critical Care Medicine. 50(3):375–388. doi: 10.1097/ccm.0000000000005285. doi: 10.1097/ccm.0000000000005285. [DOI] [PubMed] [Google Scholar]
- Physiotherapy for adult patients with critical illness: recommendations of the European Respiratory Society and European Society of Intensive Care Medicine Task Force on Physiotherapy for Critically Ill Patients. Gosselink R., Bott J., Johnson M., Dean E., Nava S., Norrenberg M., Schönhofer B., Stiller K., van de Leur H., Vincent J. L. Feb 19;2008 Intensive Care Medicine. 34(7):1188–1199. doi: 10.1007/s00134-008-1026-7. doi: 10.1007/s00134-008-1026-7. [DOI] [PubMed] [Google Scholar]
- Consideration of prevention and management of long-term consequences of post-acute respiratory distress syndrome in patients with COVID-19. Candan Sevim Acaroz, Elibol Nuray, Abdullahi Auwal. May 18;2020 Physiotherapy Theory and Practice. 36(6):663–668. doi: 10.1080/09593985.2020.1766181. doi: 10.1080/09593985.2020.1766181. [DOI] [PubMed] [Google Scholar]
- Effectiveness of structured early mobilization protocol on mobility status of patients in medical intensive care unit. Gatty A., Samuel Alaparthi SR, GK Prabhu, D Upadya, M Krishnan, S Amaravadi, S.K. 2020Physiother Theory Pract. 23:1–13. doi: 10.1080/09593985.2020.1840683. [DOI] [PubMed] [Google Scholar]
