Background: Pain, sedation, delirium, and iatrogenic withdrawal syndrome are conditions that often coexist, algorithms can be used to assist healthcare professionals in decision making. However, a comprehensive review is lacking. This systematic review aimed to assess the effectiveness, quality, and implementation of algorithms for the management of pain, sedation, delirium, and iatrogenic withdrawal syndrome in all pediatric intensive care settings. Methods: A literature search was conducted on November 29, 2022, in PubMed, Embase, CINAHL and Cochrane Library, ProQuest Dissertations & Theses, and Google Scholar to identify algorithms implemented in pediatric intensive care and published since 2005. Three reviewers independently screened the records for inclusion, verified and extracted data. Included studies were assessed for risk of bias using the JBI checklists, and algorithm quality was assessed using the PROFILE tool (higher % = higher quality). Meta-analyses were performed to compare algorithms to usual care on various outcomes (length of stay, duration and cumulative dose of analgesics and sedatives, length of mechanical ventilation, and incidence of withdrawal). Results: From 6,779 records, 32 studies, including 28 algorithms, were included. The majority of algorithms (68%) focused on sedation in combination with other conditions. Risk of bias was low in 28 studies. The average overall quality score of the algorithm was 54%, with 11 (39%) scoring as high quality. Four algorithms used clinical practice guidelines during development. The use of algorithms was found to be effective in reducing length of stay (intensive care and hospital), length of mechanical ventilation, duration of analgesic and sedative medications, cumulative dose of analgesics and sedatives, and incidence of withdrawal. Implementation strategies included education and distribution of materials (95%). Supportive determinants of algorithm implementation included leadership support and buy-in, staff training, and integration into electronic health records. The fidelity to algorithm varied from 8.2% to 100%. Conclusions: The review suggests that algorithm-based management of pain, sedation and withdrawal is more effective than usual care in pediatric intensive care settings. There is a need for more rigorous use of evidence in the development of algorithms and the provision of details on the implementation process. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021276053, PROSPERO [CRD42021276053].

Background: Pain, sedation, delirium, and iatrogenic withdrawal syndrome are conditions that often coexist, algorithms can be used to assist healthcare professionals in decision making. However, a comprehensive review is lacking. This systematic review aimed to assess the effectiveness, quality, and implementation of algorithms for the management of pain, sedation, delirium, and iatrogenic withdrawal syndrome in all pediatric intensive care settings. Methods: A literature search was conducted on November 29, 2022, in PubMed, Embase, CINAHL and Cochrane Library, ProQuest Dissertations & Theses, and Google Scholar to identify algorithms implemented in pediatric intensive care and published since 2005. Three reviewers independently screened the records for inclusion, verified and extracted data. Included studies were assessed for risk of bias using the JBI checklists, and algorithm quality was assessed using the PROFILE tool (higher % = higher quality). Meta-analyses were performed to compare algorithms to usual care on various outcomes (length of stay, duration and cumulative dose of analgesics and sedatives, length of mechanical ventilation, and incidence of withdrawal). Results: From 6,779 records, 32 studies, including 28 algorithms, were included. The majority of algorithms (68%) focused on sedation in combination with other conditions. Risk of bias was low in 28 studies. The average overall quality score of the algorithm was 54%, with 11 (39%) scoring as high quality. Four algorithms used clinical practice guidelines during development. The use of algorithms was found to be effective in reducing length of stay (intensive care and hospital), length of mechanical ventilation, duration of analgesic and sedative medications, cumulative dose of analgesics and sedatives, and incidence of withdrawal. Implementation strategies included education and distribution of materials (95%). Supportive determinants of algorithm implementation included leadership support and buy-in, staff training, and integration into electronic health records. The fidelity to algorithm varied from 8.2% to 100%. Conclusions: The review suggests that algorithm-based management of pain, sedation and withdrawal is more effective than usual care in pediatric intensive care settings. There is a need for more rigorous use of evidence in the development of algorithms and the provision of details on the implementation process. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021276053, PROSPERO [CRD42021276053].

Introduction: Despite common, serious, costly, and often fatal conditions affecting up to 50 % of older patients, delirium is often unrecognized and overlooked. We examine the accuracy of the 4AT for detecting older patients with delirium.Methods: We performed a systematic search of PubMed, Web of Science, PsycINFO, and EMBASE databases from inception to April 2020 and updated to January 2022. Four independently reviewers extracted study data and assessed the methodological quality using the revised quality assessment of diagnostic accuracy studies tool (QUADAS-2). Pooled estimates of sensitivity and specificity were generated using a bivariate random effects model. All statistical analyses were performed with STATA version 15.1 and Meta-DiSc version 1.4 software. Results: Eleven studies with 2789 participants were included. The pooled sensitivity and specificity were 0.87 (95 % CI: 0.81-0.91) and 0.87 (95 % CI: 0.79-0.92), respectively, and the positive and negative likelihood ratios were 6.66 (95 % CI: 4.12-10.74) and 0.15 (95 % CI: 0.10-0.23), respectively. Deeks' test indicated no significant publication bias (t = 0.83, P = 0.43). Univariable meta-regression showed that patient selection and flow and timing significantly influenced the pooled sensitivity (P < 0.05), settings significantly influenced the pooled specificity (P < 0.05).Conclusion: Our meta-analysis demonstrates that 4AT is a sensitive and specific screening tool for delirium in older patients. Its brevity and simplicity support its use in routine clinical practice, particularly in time-poor settings. Clinicians should come to a conclusion based largely on the 4AT findings in conjunction with clinical judgment.

Aim To compare the safety and effects of unrestricted visiting policies (UVPs) and restricted visiting policies (RVPs) in intensive care units (ICUs) with respect to outcomes related to delirium, infection, and mortality. Methods MEDLINE, Cochrane Library, Embase, Web of Science, CINAHL, CBMdisc, CNKI, Wanfang, and VIP database records generated from their inception to 22 January 2022 were searched. Randomized controlled trials and quasi-experimental studies were included. The main outcomes investigated were delirium, ICU-acquired infection, ICU mortality, and length of ICU stay. Two reviewers independently screened studies, extracted data, and assessed risks of bias. Random-effects and fixed-effects meta-analyses were conducted to obtain pooled estimates, due to heterogeneity. Meta-analyses were performed using RevMan 5.3 software. The results were analyzed using odds ratios (ORs), 95% confidence intervals (CIs), and standardized mean differences (SMDs). Results Eleven studies including a total of 3741 patients that compared UVPs and RVPs in ICUs were included in the analyses. Random effects modeling indicated that UVPs were associated with a reduced incidence of delirium (OR = 0.4, 95% CI 0.25-0.63, I-2 = 71%, p = 0.0005). Fixed-effects modeling indicated that UVPs did not increase the incidences of ICU-acquired infections, including ventilator-associated pneumonia (OR = 0.96, 95% CI 0.71-1.30, I-2 = 0%, p = 0.49), catheter-associated urinary tract infection (OR 0.97, 95% CI 0.52-1.80, I-2 = 0%, p = 0.55), and catheter-related blood stream infection (OR = 1.15, 95% CI 0.72-1.84, I-2 = 0%, p = 0.66), or ICU mortality (OR = 1.03, 95% CI 0.83-1.28, I-2 = 49%, p = 0.12). Forest plotting indicated that UVPs could reduce the lengths of ICU stays (SMD = - 0.97, 95% CI - 1.61 to 0.32, p = 0.003). Conclusion The current meta-analysis indicates that adopting a UVP may significantly reduce the incidence of delirium in ICU patients, without increasing the risks of ICU-acquired infection or mortality. Further large-scale, multicenter studies are needed to confirm these indications.