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1.
Sci Rep ; 12(1): 7977, 2022 05 13.
Article in English | MEDLINE | ID: mdl-35562379

ABSTRACT

Coronavirus disease 19 (COVID-19) patients usually require long periods of mechanical ventilation and sedation, which added to steroid therapy, favours a predisposition to the development of delirium and subsequent mental health disorders, as well as physical and respiratory sequelae. The aim of this study was to determine the prevalence of post-intensive care syndrome (PICS) at 3 months after hospital discharge, in a cohort of mechanically ventilated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). An ambispective, observational study was conducted in three hospitals with intensive care unit (ICU) follow-up clinics. We studied adults who survived a critical illness due to SARS-CoV-2 infection requiring invasive mechanical ventilation. A physical (muscle strength and pulmonary function), functional [12-Item Short Form Health Survey (SF-12), and Barthel score], psychological [hospital anxiety and depression (HADS) and posttraumatic stress disorder symptom severity scales], and cognitive [Montreal cognitive assessment (MoCA) test] assessment were performed. A total of 186 patients were evaluated at 88 days (IQR 68-121) after hospital discharge. Mean age was 59 ± 12 years old, 126 (68%) patients were men, and median length of mechanical ventilation was 14 days (IQR 8-31). About 3 out of 4 patients (n = 139, 75%) met PICS criteria. Symptoms of cognitive and psychiatric disorders were found in 59 (32%) and 58 (31%) patients, respectively. Ninety-one (49%) patients had muscle weakness. Pulmonary function tests in patients with no respiratory comorbidities showed a normal pattern in 93 (50%) patients, and a restrictive disorder in 62 (33%) patients. Also, 69 patients (37%) were on sick leave, while 32 (17%) had resumed work at the time of assessment. In conclusion, survivors of critical illness due to SARS-CoV-2 infection requiring mechanical ventilation have a high prevalence of PICS. Physical domain is the most frequently damaged, followed by cognitive and psychiatric disorders. ICU follow-up clinics enable the assistance of this vulnerable population.


Subject(s)
COVID-19 , Adult , Aged , COVID-19/complications , COVID-19/epidemiology , COVID-19/therapy , Critical Illness/psychology , Female , Humans , Intensive Care Units , Male , Middle Aged , Prevalence , Respiration, Artificial , SARS-CoV-2
2.
J Crit Care ; 29(2): 188-93, 2014 Apr.
Article in English | MEDLINE | ID: mdl-24287174

ABSTRACT

PURPOSES: To evaluate the effects of a computerized physician order entry (CPOE) system in the cardiac intensive care unit by detecting prescription errors (PEs) and also to assess the impact on working conditions. METHODS: A longitudinal, prospective, before-after study was conducted during the periods before and after the implementation of the CPOE system. Clinical pharmacists were responsible for the registration, description and classification of PEs, and their causes and severity, according to an international taxonomy. Professionals were also surveyed for their opinion, concerns, and level of satisfaction. RESULTS: A total of 470 treatment orders containing 5729 prescriptions were evaluated. The CPOE resulted in a marked reduction in the number of PEs: error rate was 44.8% (819 errors among 1829 prescriptions) with handwritten orders and 0.8% (16 among 2094 prescriptions) at the final electronic phase (P < .001). Lapses were the main cause of error in both prescription methods. Most errors did not reach the patients. Errors related with the computerized system were scarce. Most users were satisfied with many aspects of this technology, although a higher workload was reported. CONCLUSIONS: Computerized physician order entry in the cardiac intensive care unit proved to be a safe and effective strategy in reducing PEs and was globally well received by professionals.


Subject(s)
Drug Prescriptions/statistics & numerical data , Intensive Care Units , Medical Order Entry Systems/statistics & numerical data , Medication Errors/statistics & numerical data , Workflow , Controlled Before-After Studies , Humans , Medication Errors/prevention & control , Prospective Studies , Spain
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