Effects of pain, sedation and delirium monitoring on clinical and economic outcome: A retrospective study

Optimal strategies for assessing and managing pain, agitation, and delirium in the critically ill surgical patient: What you need to know

ABSTRACT

Pain, agitation, and delirium (PAD) are primary drivers of outcome in the ICU, and expertise in managing these entities successfully is crucial to the intensivist's toolbox. In addition, there are unique aspects of surgical patients that impact assessment and management of PAD. In this review, we address the continuous spectrum of assessment, and management of critically ill surgical patients, with a focus on limiting PAD, particularly incorporating mobility as an anchor to ICU liberation. Finally, we touch on the impact of PAD in specific populations, including opioid use disorder, traumatic brain injury, pregnancy, obesity, alcohol withdrawal, and geriatric patients. The goal of the review is to provide rapid access to information regarding PAD and tools to assess and manage these important elements of critical care of surgical patients.

Effectiveness of an intensive care telehealth programme to improve process quality (ERIC): a multicentre stepped wedge cluster randomised controlled trial

PURPOSE

Supporting the provision of intensive care medicine through telehealth potentially improves process quality. This may improve patient recovery and long-term outcomes. We investigated the effectiveness of a multifaceted telemedical programme on the adherence to German quality indicators (QIs) in a regional network of intensive care units (ICUs) in Germany.

METHODS

We conducted an investigator-initiated, large-scale, open-label, stepped-wedge cluster randomised controlled trial enrolling adult ICU patients with an expected ICU stay of ≥ 24 h. Twelve ICU clusters in Berlin and Brandenburg were randomly assigned to three sequence groups to transition from control (standard care) to the intervention condition (telemedicine). The quality improvement intervention consisted of daily telemedical rounds guided by eight German acute ICU care QIs and expert consultations. Co-primary effectiveness outcomes were patient-specific daily adherence (fulfilled yes/no) to QIs, assessed by a central end point adjudication committee. Analyses used mixed-effects logistic modelling adjusted for time. This study is completed and registered with ClinicalTrials.gov (NCT03671447).

RESULTS

Between September 4, 2018, and March 31, 2020, 1463 patients (414 treated on control, 1049 on intervention condition) were enrolled at ten clusters, resulting in 14,783 evaluated days. Two randomised clusters recruited no patients (one withdrew informed consent; one dropped out). The intervention, as implemented, significantly increased QI performance for "sedation, analgesia and delirium" (adjusted odds ratio (99.375% confidence interval [CI]) 5.328, 3.395-8.358), "ventilation" (OR 2.248, 1.198-4.217), "weaning from ventilation" (OR 9.049, 2.707-30.247), "infection management" (OR 4.397, 1.482-13.037), "enteral nutrition" (OR 1.579, 1.032-2.416), "patient and family communication" (OR 6.787, 3.976-11.589), and "early mobilisation" (OR 3.161, 2.160-4.624). No evidence for a difference in adherence to "daily multi-professional and interdisciplinary clinical visits" between both conditions was found (OR 1.606, 0.780-3.309). Temporal trends related and unrelated to the intervention were detected. 149 patients died during their index ICU stay (45 treated on control, 104 on intervention condition).

CONCLUSION

A telemedical quality improvement program increased adherence to seven evidence-based German performance indicators in acute ICU care. These results need further confirmation in a broader setting of regional, non-academic community hospitals and other healthcare systems.

Delirium in elderly patients with COPD combined with respiratory failure undergoing mechanical ventilation: a prospective cohort study

Background

COPD combined with respiratory failure is very common in intensive care unit (ICU). We aimed to evaluate the current status and influencing factors of delirium in elderly COPD patients with undergoing mechanical ventilation.

Methods

Patients with COPD combined with respiratory failure and mechanically ventilated who were admitted to the ICU of our hospital were selected. The characteristics of included patients were assessed. Pearson correlation analysis was performed to evaluate the characteristics of patients and delirium. Logistic regression analysis was conducted to identify the risk factors of delirium in elderly patients with COPD combined with respiratory failure undergoing mechanical ventilation.

Results

A total of 237 COPD combined with respiratory failure patients were included, the incidence of delirium was 21.94%. Pearson correlation analysis indicated that age (r = 0.784), BMI (r = 0.709), hypertension (r = 0.696), APACHE II score (r = 0.801), CPOT (r = 0.513), sedation(r = 0.626) and PaO₂ (r = 0.611) were all correlated with the occurrence of delirium (all p < 0.05). Logistic regression analysis indicated that age ≥ 75y (OR 3.112, 95% CI 2.144–4.602), BMI ≤ 19 kg/m² (OR 2.742, 95% CI 1.801–3.355), hypertension(OR 1.909, 95% CI 1.415–2.421), APACHE II score ≥ 15 (OR 2.087, 95% CI 1.724–2.615), CPOT ≥ 5 (OR 1.778, 95% CI 1.206–2.641), sedation(OR 3.147, 95% CI 2.714–3.758), PaO₂ ≤ 75 mmHg(OR 2.196, 95%CI 1.875–3.088) were the risk factors of delirium in elderly patients with COPD combined with respiratory failure undergoing mechanical ventilation (all p < 0.05).

Conclusions

Delirium is common in patients with COPD and respiratory failure undergoing mechanical ventilation, and there are many related influencing factors. Medical staff should pay more attention to patients with risk factors and take intervention measures as soon as possible to reduce the incidence of delirium.

Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature

BACKGROUND

The term "data science" encompasses several methods, many of which are considered cutting edge and are being used to influence care processes across the world. Nursing is an applied science and a key discipline in health care systems in both clinical and administrative areas, making the profession increasingly influenced by the latest advances in data science. The greater informatics community should be aware of current trends regarding the intersection of nursing and data science, as developments in nursing practice have cross-professional implications.

OBJECTIVES

This study aimed to summarize the latest (calendar year 2020) research and applications of nursing-relevant patient outcomes and clinical processes in the data science literature.

METHODS

We conducted a rapid review of the literature to identify relevant research published during the year 2020. We explored the following 16 topics: (1) artificial intelligence/machine learning credibility and acceptance, (2) burnout, (3) complex care (outpatient), (4) emergency department visits, (5) falls, (6) health care-acquired infections, (7) health care utilization and costs, (8) hospitalization, (9) in-hospital mortality, (10) length of stay, (11) pain, (12) patient safety, (13) pressure injuries, (14) readmissions, (15) staffing, and (16) unit culture.

RESULTS

Of 16,589 articles, 244 were included in the review. All topics were represented by literature published in 2020, ranging from 1 article to 59 articles. Numerous contemporary data science methods were represented in the literature including the use of machine learning, neural networks, and natural language processing.

CONCLUSION

This review provides an overview of the data science trends that were relevant to nursing practice in 2020. Examinations of such literature are important to monitor the status of data science's influence in nursing practice.

Adult sedation and analgesia in a resource limited intensive care unit - A Systematic Review and evidence based guideline

Background

Sedation and analgesia are essential in the intensive care unit in order to promote control of pain, anxiety, prevent loss of materials, accidental extubation and improve the synchrony of patients with ventilator. However, excess of these medications leads to an increased morbidity and mortality, and thus demands protocol.

Methods

Preferred Reporting Items for Systematic Reviews and the Meta-Analysis Protocol have been used to undertake this review. Pub Med, Cochrane Library, and Google Scholar search engines were used to find up-to-date evidence that helps to draw recommendations and conclusions.

Results

In this Guideline and Systematic Review, we have used 16 Systemic Review and Meta-Analysis, 3 Evidence-Based Guidelines and 10 RCT Meta-Analysis, 6 Systemic Reviews of Non-randomized Studies, 8 Randomized Clinical Trials, 11 Cohort Studies, 5 Cross-Sectional Studies and 1 Case Report with their respective study descriptions.

Discussion

Analgesia, which as a sedation basement can reduce sedative use, is key aspect of treatment in ICU patients, and we can also conclude that an analgesic sedation regimen can reduce the occurrence of delirium by reducing sedatives. The aim of this guideline and the systematic review is to write up and formulate analgesia-based sedation for limited resource settings.

Conclusions

Analgesia and sedation are effective in critically ill patients; however, too much sedation is associated with longer periods of mechanical ventilation and longer duration of ICU stay. Poorly managed ICU patients have a delirium rate of up to 80%, increased mortality, longer hospital stays, higher hospital costs and bad long-term outcomes.

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Critically ill patients shall be awake, alert without pain, anxiety and delirium.

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Analgesia and sedation in the ICU shall be given as per needed after determined they are in need of.

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Sedation breaks are paramount important as equal as spontaneous breathing trials.

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Unnecessary deep sedations will increase hospital and personnel costs by increasing length of ICU stay.