RESUMO
RATIONALE: The positive end-expiratory pressure (PEEP) strategy in patients with coronavirus 2019 (COVID-19) acute respiratory distress syndrome (ARDS) remains debated. Most studies originate from the initial waves of the pandemic. Here we aimed to assess the impact of high PEEP/low FiO2 ventilation on outcomes during the second wave in the Netherlands. METHODS: Retrospective observational study of invasively ventilated COVID-19 patients during the second wave. Patients were categorized based on whether they received high PEEP or low PEEP ventilation according to the ARDS Network tables. The primary outcome was ICU mortality, and secondary outcomes included hospital and 90-day mortality, duration of ventilation and length of stay, and the occurrence of kidney injury. Propensity matching was performed to correct for factors with a known relationship to ICU mortality. RESULTS: This analysis included 790 COVID-ARDS patients. At ICU discharge, 32 (22.5%) out of 142 high PEEP patients and 254 (39.2%) out of 848 low PEEP patients had died (HR 0.66 [0.46-0.96]; P = 0.03). High PEEP was linked to improved secondary outcomes. Matched analysis did not change findings. CONCLUSIONS: High PEEP ventilation was associated with improved ICU survival in patients with COVID-ARDS.
Assuntos
COVID-19 , Mortalidade Hospitalar , Respiração com Pressão Positiva , Síndrome do Desconforto Respiratório , Humanos , COVID-19/mortalidade , COVID-19/terapia , Estudos Retrospectivos , Respiração com Pressão Positiva/métodos , Masculino , Feminino , Pessoa de Meia-Idade , Países Baixos/epidemiologia , Idoso , Síndrome do Desconforto Respiratório/terapia , Síndrome do Desconforto Respiratório/mortalidade , Unidades de Terapia Intensiva , SARS-CoV-2 , Tempo de Internação/estatística & dados numéricos , Respiração Artificial/métodos , Respiração Artificial/estatística & dados numéricosRESUMO
Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.
Assuntos
Cuidados Críticos , Unidades de Terapia Intensiva , Medicina de Precisão , Humanos , Medicina de Precisão/métodos , Cuidados Críticos/métodos , Cuidados Críticos/normas , Consenso , Síndrome , Estado Terminal/terapia , Fenótipo , Síndrome do Desconforto Respiratório/terapia , Síndrome do Desconforto Respiratório/diagnóstico , Síndrome do Desconforto Respiratório/classificaçãoRESUMO
End-of-life care (EOLC) exemplifies the joint mission of intensive and palliative care (PC) in their human-centeredness. The explosion of technological advances in medicine must be balanced with the culture of holistic care. Inevitably, it brings together the science and the art of medicine in their full expression. High-quality EOLC in the ICU is grounded in evidence, ethical principles, and professionalism within the framework of the Law. Expert professional statements over the last two decades in India were developed while the law was evolving. Recent landmark Supreme Court judgments have necessitated a review of the clinical pathway for EOLC outlined in the previous statements. Much empirical and interventional evidence has accumulated since the position statement in 2014. This iteration of the joint Indian Society of Critical Care Medicine-Indian Association of Palliative Care (ISCCM-IAPC) Position Statement for EOLC combines contemporary evidence, ethics, and law for decision support by the bedside in Indian ICUs. How to cite this article: Mani RK, Bhatnagar S, Butola S, Gursahani R, Mehta D, Simha S, et al. Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit. Indian J Crit Care Med 2024;28(3):200-250.
RESUMO
BACKGROUND: Catheter-Associated Urinary Tract Infections (CAUTIs) frequently occur in the intensive care unit (ICU) and are correlated with a significant burden. METHODS: We implemented a strategy involving a 9-element bundle, education, surveillance of CAUTI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CAUTI rates and performance feedback. This was executed in 299 ICUs across 32 low- and middle-income countries. The dependent variable was CAUTI per 1,000 UC days, assessed at baseline and throughout the intervention, in the second month, third month, 4 to 15 months, 16 to 27 months, and 28 to 39 months. Comparisons were made using a 2-sample t test, and the exposure-outcome relationship was explored using a generalized linear mixed model with a Poisson distribution. RESULTS: Over the course of 978,364 patient days, 150,258 patients utilized 652,053 UC-days. The rates of CAUTI per 1,000 UC days were measured. The rates decreased from 14.89 during the baseline period to 5.51 in the second month (risk ratio [RR] = 0.37; 95% confidence interval [CI] = 0.34-0.39; P < .001), 3.79 in the third month (RR = 0.25; 95% CI = 0.23-0.28; P < .001), 2.98 in the 4 to 15 months (RR = 0.21; 95% CI = 0.18-0.22; P < .001), 1.86 in the 16 to 27 months (RR = 0.12; 95% CI = 0.11-0.14; P < .001), and 1.71 in the 28 to 39 months (RR = 0.11; 95% CI = 0.09-0.13; P < .001). CONCLUSIONS: Our intervention, without substantial costs or additional staffing, achieved an 89% reduction in CAUTI incidence in ICUs across 32 countries, demonstrating feasibility in ICUs of low- and middle-income countries.
Assuntos
Infecções Relacionadas a Cateter , Unidades de Terapia Intensiva , Infecções Urinárias , Humanos , Infecções Relacionadas a Cateter/epidemiologia , Infecções Relacionadas a Cateter/prevenção & controle , Infecções Urinárias/epidemiologia , Infecções Urinárias/prevenção & controle , Ásia/epidemiologia , América Latina/epidemiologia , Oriente Médio/epidemiologia , Masculino , Feminino , Europa Oriental/epidemiologia , Controle de Infecções/métodos , Pessoa de Meia-Idade , Infecção Hospitalar/prevenção & controle , Infecção Hospitalar/epidemiologia , IdosoRESUMO
This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWSTM and CircEWS-lite TM showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety.
RESUMO
BACKGROUND: Reporting on the International Nosocomial Infection Control Consortium study results from 2015 to 2020, conducted in 630 intensive care units across 123 cities in 45 countries spanning Africa, Asia, Eastern Europe, Latin America, and the Middle East. METHODS: Prospective intensive care unit patient data collected via International Nosocomial Infection Control Consortium Surveillance Online System. Centers for Disease Control and Prevention/National Health Care Safety Network definitions applied for device-associated health care-associated infections (DA-HAI). RESULTS: We gathered data from 204,770 patients, 1,480,620 patient days, 936,976 central line (CL)-days, 637,850 mechanical ventilators (MV)-days, and 1,005,589 urinary catheter (UC)-days. Our results showed 4,270 CL-associated bloodstream infections, 7,635 ventilator-associated pneumonia, and 3,005 UC-associated urinary tract infections. The combined rates of DA-HAIs were 7.28%, and 10.07 DA-HAIs per 1,000 patient days. CL-associated bloodstream infections occurred at 4.55 per 1,000 CL-days, ventilator-associated pneumonias at 11.96 per 1,000 MV-days, and UC-associated urinary tract infections at 2.91 per 1,000 UC days. In terms of resistance, Pseudomonas aeruginosa showed 50.73% resistance to imipenem, 44.99% to ceftazidime, 37.95% to ciprofloxacin, and 34.05% to amikacin. Meanwhile, Klebsiella spp had resistance rates of 48.29% to imipenem, 72.03% to ceftazidime, 61.78% to ciprofloxacin, and 40.32% to amikacin. Coagulase-negative Staphylococci and Staphylococcus aureus displayed oxacillin resistance in 81.33% and 53.83% of cases, respectively. CONCLUSIONS: The high rates of DA-HAI and bacterial resistance emphasize the ongoing need for continued efforts to control them.
Assuntos
Infecções Relacionadas a Cateter , Infecção Hospitalar , Humanos , Infecção Hospitalar/epidemiologia , Infecção Hospitalar/prevenção & controle , Infecções Relacionadas a Cateter/epidemiologia , Infecções Relacionadas a Cateter/microbiologia , Estudos Prospectivos , Unidades de Terapia Intensiva , Adulto , Pneumonia Associada à Ventilação Mecânica/epidemiologia , Pneumonia Associada à Ventilação Mecânica/microbiologia , Masculino , Criança , Feminino , Infecções Urinárias/epidemiologia , Infecções Urinárias/microbiologia , Pessoa de Meia-Idade , Controle de Infecções/métodos , Lactente , Pré-Escolar , Ásia/epidemiologiaRESUMO
Background: In the COVID-STEROID 2 trial there was suggestion of heterogeneity of treatment effects (HTE) between patients enrolled from Europe vs. India on the primary outcome. Whether there was HTE for the remaining patient-centred outcomes is unclear. Methods: In this post hoc analysis of the COVID-STEROID 2 trial, which compared 12 mg vs. 6 mg dexamethasone in adults with COVID-19 and severe hypoxemia, we evaluated HTE by geographical region (Europe vs. India) for secondary outcomes with analyses adjusted for stratification variables. Results are presented as risk differences (RDs) or mean differences (MDs) with 99% confidence intervals (CIs) and P-values from interaction tests. Findings: There were differences in mortality at day 28 (RD for Europe -8.3% (99% CI: -17.7 to 1.0) vs. India 0.1% (99% CI: -10.0 to 10.0)), mortality at day 90 (RD for Europe -7.4% (99% CI: -17.1 to 2.0) vs. India -1.4% (99% CI: -12.8 to 9.8)), mortality at day 180 (RD for Europe -6.7% (99% CI: -16.4 to 2.9) vs. India -1.0% (99% CI: -12.3 to 10.3)), and number of days alive without life support at day 90 (MD for Europe 6.1 days (99% CI: -1.3 to 13.4) vs. India 1.7 days (99% CI: -8.4 to 11.8)). For serious adverse reactions, the direction was reversed (RD for Europe -1.0% (99% CI: -7.1 to 5.2) vs. India -5.3% (99% CI: -16.2 to 5.0). Interpretation: Our analysis suggests higher dose dexamethasone may have less beneficial effects for patients in India as compared with those in Europe; however, the evidence is weak, and this could represent a chance finding. Funding: None for this analysis. The COVID STEROID 2 trial was funded by The Novo Nordisk Foundation and supported by Rigshospitalet's Research Council.
RESUMO
BACKGROUND: Central line (CL)-associated bloodstream infections (CLABSIs) occurring in the intensive care unit (ICU) are common and associated with a high burden. METHODS: We implemented a multidimensional approach, incorporating an 11-element bundle, education, surveillance of CLABSI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CLABSI rates and clinical outcomes, and performance feedback in 316 ICUs across 30 low- and middle-income countries. Our dependent variables were CLABSI per 1,000-CL-days and in-ICU all-cause mortality rates. These variables were measured at baseline and during the intervention, specifically during the second month, third month, 4 to 16 months, and 17 to 29 months. Comparisons were conducted using a two-sample t test. To explore the exposure-outcome relationship, we used a generalized linear mixed model with a Poisson distribution to model the number of CLABSIs. RESULTS: During 1,837,750 patient-days, 283,087 patients, used 1,218,882 CL-days. CLABSI per 1,000 CL-days rates decreased from 15.34 at the baseline period to 7.97 in the 2nd month (relative risk (RR) = 0.52; 95% confidence interval [CI] = 0.48-0.56; P < .001), 5.34 in the 3rd month (RR = 0.35; 95% CI = 0.32-0.38; P < .001), and 2.23 in the 17 to 29 months (RR = 0.15; 95% CI = 0.13-0.17; P < .001). In-ICU all-cause mortality rate decreased from 16.17% at baseline to 13.68% (RR = 0.84; P = .0013) at 17 to 29 months. CONCLUSIONS: The implemented approach was effective, and a similar intervention could be applied in other ICUs of low- and middle-income countries to reduce CLABSI and in-ICU all-cause mortality rates.