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1.
BMJ Open Qual ; 13(2)2024 Jun 03.
Artigo em Inglês | MEDLINE | ID: mdl-38830729

RESUMO

BACKGROUND: The demand for healthcare services during the COVID-19 pandemic was excessive for less-resourced settings, with intensive care units (ICUs) taking the heaviest toll. OBJECTIVE: The aim was to achieve adequate personal protective equipment (PPE) use in 90% of patient encounters, to reach 90% compliance with objectives of patient flow (OPF) and to provide emotional support tools to 90% of healthcare workers (HCWs). METHODS: We conducted a quasi-experimental study with an interrupted time-series design in 14 ICUs in Argentina. We randomly selected adult critically ill patients admitted from July 2020 to July 2021 and active HCWs in the same period. We implemented a quality improvement collaborative (QIC) with a baseline phase (BP) and an intervention phase (IP). The QIC included learning sessions, periods of action and improvement cycles (plan-do-study-act) virtually coached by experts via platform web-based activities. The main study outcomes encompassed the following elements: proper utilisation of PPE, compliance with nine specific OPF using daily goal sheets through direct observations and utilisation of a web-based tool for tracking emotional well-being among HCWs. RESULTS: We collected 7341 observations of PPE use (977 in BP and 6364 in IP) with an improvement in adequate use from 58.4% to 71.9% (RR 1.2, 95% CI 1.17 to 1.29, p<0.001). We observed 7428 patient encounters to evaluate compliance with 9 OPF (879 in BP and 6549 in IP) with an improvement in compliance from 53.9% to 67% (RR 1.24, 95% CI 1.17 to 1.32, p<0.001). The results showed that HCWs did not use the support tool for self-mental health evaluation as much as expected. CONCLUSION: A QIC was effective in improving healthcare processes and adequate PPE use, even in the context of a pandemic, indicating the possibility of expanding QIC networks nationwide to improve overall healthcare delivery. The limited reception of emotional support tools requires further analyses.


Assuntos
COVID-19 , Unidades de Terapia Intensiva , Melhoria de Qualidade , SARS-CoV-2 , Humanos , COVID-19/prevenção & controle , COVID-19/epidemiologia , Argentina , Unidades de Terapia Intensiva/organização & administração , Unidades de Terapia Intensiva/estatística & dados numéricos , Masculino , Feminino , Equipamento de Proteção Individual/estatística & dados numéricos , Pessoa de Meia-Idade , Pandemias/prevenção & controle , Atenção à Saúde/normas , Adulto , Saúde Pública/métodos , Pessoal de Saúde/estatística & dados numéricos , Pessoal de Saúde/psicologia , Análise de Séries Temporais Interrompida/métodos
2.
J Infect Dev Ctries ; 6(7): 555-62, 2012 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-22842942

RESUMO

INTRODUCTION: A patient's response to sepsis is influenced by their genetic background. Our objective was to use plasma markers, such as protein C (PC), D-dimer, Plasminogen Activator Inhibitor-1 (PAI-1) levels, and the PAI-1 rs1799889 4G/5G and  Tumor Necrosis Factor-α rs1800629 G/A  polymorphisms to improve classical intensive care unit (ICU) scores. METHODOLOGY: We studied 380 subjects, 166 with sepsis. We performed coagulation tests: plasma PAI-1 and PC levels were evaluated by chromogenic methods; and D-dimer was evaluated by immunoturbidimetric assay. Polymorphisms were performed using for polymerase chain reactions followed by digest with specific restriction enzyme. We acquired the APACHE and SOFA scores (time zero), sex, age, body mass index, associated co-morbidities, length of ICU stay (days), the severity of sepsis (sepsis, severe sepsis or septic shock), the HIV status and the ICU outcome (survival or death). RESULTS: We found significant differences between patients who died (n=80) and those who survived (n=86) in terms of the ICU length of stay (6 vs. 10 days), septic shock (64 versus 24%), age (51 versus 38 years old), HIV+ condition (34 versus 16%), SOFA (7 versus 4), APACHE (19 versus 13), D-dimer (4.32 versus 2.88 mg/ml), PC (46.0 versus 63.5 %) and PAI-1 (33.0 versus 16.5 UA/l). When we used a regression analysis with dichotomized variables, only the SOFA4, PAI-116, HIV status and the PAI-1 4G allele proved to be predictors of death at time zero. CONCLUSIONS: In the future, ICU scores may be further improved by adding certain genomic or plasma data. 


Assuntos
Biomarcadores/sangue , Plasma/química , Inibidor 1 de Ativador de Plasminogênio/genética , Sepse/diagnóstico , Sepse/genética , Fator de Necrose Tumoral alfa/genética , APACHE , Adulto , Argentina , Técnicas de Laboratório Clínico , Medicina Clínica/métodos , Predisposição Genética para Doença , Humanos , Unidades de Terapia Intensiva , Pessoa de Meia-Idade , Reação em Cadeia da Polimerase , Polimorfismo Genético , Polimorfismo de Fragmento de Restrição , Fatores de Tempo
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