Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial.

CONTEXT: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge. OBJECTIVES: To assess the effectiveness on clinical outcomes of an artificial intelligence (AI)/machine learning (ML) decision support tool for predicting patient need for palliative care services in the hospital. METHODS: The study design was a pragmatic, cluster-randomized, stepped-wedge clinical trial in 12 nursing units at two hospitals over a 15-month period between August 19, 2019, and November 17, 2020. Eligible patients were randomly assigned to either a medical service consultation recommendation triggered by an AI/ML tool predicting the need for palliative care services or usual care. The primary outcome was palliative care consultation note. Secondary outcomes included: hospital readmissions, length of stay, transfer to intensive care and palliative care consultation note by unit. RESULTS: A total of 3183 patient hospitalizations were enrolled. Of eligible patients, A total of 2544 patients were randomized to the decision support tool (1212; 48%) and usual care (1332; 52%). Of these, 1717 patients (67%) were retained for analyses. Patients randomized to the intervention had a statistically significant higher incidence rate of palliative care consultation compared to the control group (IRR, 1.44 [95% CI, 1.11-1.92]). Exploratory evidence suggested that the decision support tool group reduced 60-day and 90-day hospital readmissions (OR, 0.75 [95% CI, 0.57, 0.97]) and (OR, 0.72 [95% CI, 0.55-0.93]) respectively. CONCLUSION: A decision support tool integrated into palliative care practice and leveraging AI/ML demonstrated an increased palliative care consultation rate among hospitalized patients and reductions in hospitalizations.

Alternative splicing of METTL3 explains apparently METTL3-independent m6A modifications in mRNA.

N6-methyladenosine (m6A) is a highly prevalent mRNA modification that promotes degradation of transcripts encoding proteins that have roles in cell development, differentiation, and other pathways. METTL3 is the major methyltransferase that catalyzes the formation of m6A in mRNA. As 30% to 80% of m6A can remain in mRNA after METTL3 depletion by CRISPR/Cas9-based methods, other enzymes are thought to catalyze a sizable fraction of m6A. Here, we reexamined the source of m6A in the mRNA transcriptome. We characterized mouse embryonic stem cell lines that continue to have m6A in their mRNA after Mettl3 knockout. We show that these cells express alternatively spliced Mettl3 transcript isoforms that bypass the CRISPR/Cas9 mutations and produce functionally active methyltransferases. We similarly show that other reported METTL3 knockout cell lines express altered METTL3 proteins. We find that gene dependency datasets show that most cell lines fail to proliferate after METTL3 deletion, suggesting that reported METTL3 knockout cell lines express altered METTL3 proteins rather than have full knockout. Finally, we reassessed METTL3's role in synthesizing m6A using an exon 4 deletion of Mettl3 and found that METTL3 is responsible for >95% of m6A in mRNA. Overall, these studies suggest that METTL3 is responsible for the vast majority of m6A in the transcriptome, and that remaining m6A in putative METTL3 knockout cell lines is due to the expression of altered but functional METTL3 isoforms.

Improving time to palliative care review with predictive modeling in an inpatient adult population: study protocol for a stepped-wedge, pragmatic randomized controlled trial.

BACKGROUND: Palliative care is a medical specialty centered on improving the quality of life (QOL) of patients with complex or life-threatening illnesses. The need for palliative care is increasing and with that the rigorous testing of triage tools that can be used quickly and reliably to identify patients that may benefit from palliative care. METHODS: To that aim, we will conduct a two-armed stepped-wedge cluster randomized trial rolled out to two inpatient hospitals to evaluate whether a machine learning algorithm accurately identifies patients who may benefit from a comprehensive review by a palliative care specialist and decreases time to receiving a palliative care consult in hospital. This is a single-center study which will be conducted from August 2019 to November 2020 at Saint Mary's Hospital & Methodist Hospital both within Mayo Clinic Rochester in Minnesota. Clusters will be nursing units which will be chosen to be a mix of complex patients from Cardiology, Critical Care, and Oncology and had previously established relationships with palliative medicine. The stepped wedge design will have 12 units allocated to a design matrix of 5 treatment wedges. Each wedge will last 75 days resulting in a study period of 12 months of recruitment unless otherwise specified. Data will be analyzed with Bayesian hierarchical models with credible intervals denoting statistical significance. DISCUSSION: This intervention offers a pragmatic approach to delivering specialty palliative care to hospital patients in need using machine learning, thereby leading to high value care and improved outcomes. It is not enough for AI to be utilized by simply publishing research showing predictive performance; clinical trials demonstrating better outcomes are critically needed. Furthermore, the deployment of an AI algorithm is a complex process that requires multiple teams with varying skill sets. To evaluate a deployed AI, a pragmatic clinical trial can accommodate the difficulties of clinical practice while retaining scientific rigor. TRIAL REGISTRATION: ClinicalTrials.gov NCT03976297 . Registered on 6 June 2019, prior to trial start.

N6-Methyladenosine on mRNA facilitates a phase-separated nuclear body that suppresses myeloid leukemic differentiation.

N6-Methyladenosine (m6A) on mRNAs mediates different biological processes and its dysregulation contributes to tumorigenesis. How m6A dictates its diverse molecular and cellular effects in leukemias remains unknown. We found that YTHDC1 is the essential m6A reader in myeloid leukemia from a genome-wide CRISPR screen and that m6A is required for YTHDC1 to undergo liquid-liquid phase separation and form nuclear YTHDC1-m6A condensates (nYACs). The number of nYACs increases in acute myeloid leukemia (AML) cells compared with normal hematopoietic stem and progenitor cells. AML cells require the nYACs to maintain cell survival and the undifferentiated state that is critical for leukemia maintenance. Furthermore, nYACs enable YTHDC1 to protect m6A-mRNAs from the PAXT complex and exosome-associated RNA degradation. Collectively, m6A is required for the formation of a nuclear body mediated by phase separation that maintains mRNA stability and control cancer cell survival and differentiation.

mTORC1 promotes cell growth via m6A-dependent mRNA degradation.

Dysregulated mTORC1 signaling alters a wide range of cellular processes, contributing to metabolic disorders and cancer. Defining the molecular details of downstream effectors is thus critical for uncovering selective therapeutic targets. We report that mTORC1 and its downstream kinase S6K enhance eIF4A/4B-mediated translation of Wilms' tumor 1-associated protein (WTAP), an adaptor for the N6-methyladenosine (m6A) RNA methyltransferase complex. This regulation is mediated by 5' UTR of WTAP mRNA that is targeted by eIF4A/4B. Single-nucleotide-resolution m6A mapping revealed that MAX dimerization protein 2 (MXD2) mRNA contains m6A, and increased m6A modification enhances its degradation. WTAP induces cMyc-MAX association by suppressing MXD2 expression, which promotes cMyc transcriptional activity and proliferation of mTORC1-activated cancer cells. These results elucidate a mechanism whereby mTORC1 stimulates oncogenic signaling via m6A RNA modification and illuminates the WTAP-MXD2-cMyc axis as a potential therapeutic target for mTORC1-driven cancers.

Improving the delivery of palliative care through predictive modeling and healthcare informatics.

OBJECTIVE: Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address this problem by building a predictive model into a comprehensive clinical framework with the aims to (i) identify in-hospital patients likely to benefit from a PC consult, and (ii) intervene on such patients by contacting their care team. MATERIALS AND METHODS: Electronic health record data for 68 349 inpatient encounters in 2017 at a large hospital were used to train a model to predict the need for PC consult. This model was published as a web service, connected to institutional data pipelines, and consumed by a downstream display application monitored by the PC team. For those patients that the PC team deems appropriate, a team member then contacts the patient's corresponding care team. RESULTS: Training performance AUC based on a 20% holdout validation set was 0.90. The most influential variables were previous palliative care, hospital unit, Albumin, Troponin, and metastatic cancer. The model has been successfully integrated into the clinical workflow making real-time predictions on hundreds of patients per day. The model had an "in-production" AUC of 0.91. A clinical trial is currently underway to assess the effect on clinical outcomes. CONCLUSIONS: A machine learning model can effectively predict the need for an inpatient PC consult and has been successfully integrated into practice to refer new patients to PC.

GM-CSF Neutralization With Lenzilumab in Severe COVID-19 Pneumonia: A Case-Cohort Study.

OBJECTIVE: To assess the efficacy and safety of lenzilumab in patients with severe coronavirus disease 2019 (COVID-19) pneumonia. METHODS: Hospitalized patients with COVID-19 pneumonia and risk factors for poor outcomes were treated with lenzilumab 600 mg intravenously for three doses through an emergency single-use investigational new drug application. Patient characteristics, clinical and laboratory outcomes, and adverse events were recorded. We also identified a cohort of patients matched to the lenzilumab patients for age, sex, and disease severity. Study dates were March 13, 2020, to June 18, 2020. All patients were followed through hospital discharge or death. RESULTS: Twelve patients were treated with lenzilumab; 27 patients comprised the matched control cohort (untreated). Clinical improvement, defined as improvement of at least 2 points on the 8-point ordinal clinical endpoints scale, was observed in 11 of 12 (91.7%) patients treated with lenzilumab and 22 of 27 (81.5%) untreated patients. The time to clinical improvement was significantly shorter for the lenzilumab-treated group compared with the untreated cohort with a median of 5 days versus 11 days (P=.006). Similarly, the proportion of patients with acute respiratory distress syndrome (oxygen saturation/fraction of inspired oxygen<315 mm Hg) was significantly reduced over time when treated with lenzilumab compared with untreated (P<.001). Significant improvement in inflammatory markers (C-reactive protein and interleukin 6) and markers of disease severity (absolute lymphocyte count) were observed in patients who received lenzilumab, but not in untreated patients. Cytokine analysis showed a reduction in inflammatory myeloid cells 2 days after lenzilumab treatment. There were no treatment-emergent adverse events attributable to lenzilumab. CONCLUSION: In high-risk COVID-19 patients with severe pneumonia, granulocyte-macrophage colony-stimulating factor neutralization with lenzilumab was safe and associated with faster improvement in clinical outcomes, including oxygenation, and greater reductions in inflammatory markers compared with a matched control cohort of patients hospitalized with severe COVID-19 pneumonia. A randomized, placebo-controlled clinical trial to validate these findings is ongoing (NCT04351152).

m6A RNA Methylation Maintains Hematopoietic Stem Cell Identity and Symmetric Commitment.

Stem cells balance cellular fates through asymmetric and symmetric divisions in order to self-renew or to generate downstream progenitors. Symmetric commitment divisions in stem cells are required for rapid regeneration during tissue damage and stress. The control of symmetric commitment remains poorly defined. Using single-cell RNA sequencing (scRNA-seq) in combination with transcriptomic profiling of HSPCs (hematopoietic stem and progenitor cells) from control and m6A methyltransferase Mettl3 conditional knockout mice, we found that m6A-deficient hematopoietic stem cells (HSCs) fail to symmetrically differentiate. Dividing HSCs are expanded and are blocked in an intermediate state that molecularly and functionally resembles multipotent progenitors. Mechanistically, RNA methylation controls Myc mRNA abundance in differentiating HSCs. We identified MYC as a marker for HSC asymmetric and symmetric commitment. Overall, our results indicate that RNA methylation controls symmetric commitment and cell identity of HSCs and may provide a general mechanism for how stem cells regulate differentiation fate choice.

m6A enhances the phase separation potential of mRNA.

N6-methyladenosine (m6A) is the most prevalent modified nucleotide in mRNA1,2, with around 25% of mRNAs containing at least one m6A. Methylation of mRNA to form m6A is required for diverse cellular and physiological processes3. Although the presence of m6A in an mRNA can affect its fate in different ways, it is unclear how m6A directs this process and why the effects of m6A can vary in different cellular contexts. Here we show that the cytosolic m6A-binding proteins-YTHDF1, YTHDF2 and YTHDF3-undergo liquid-liquid phase separation in vitro and in cells. This phase separation is markedly enhanced by mRNAs that contain multiple, but not single, m6A residues. Polymethylated mRNAs act as a multivalent scaffold for the binding of YTHDF proteins, juxtaposing their low-complexity domains and thereby leading to phase separation. The resulting mRNA-YTHDF complexes then partition into different endogenous phase-separated compartments, such as P-bodies, stress granules or neuronal RNA granules. m6A-mRNA is subject to compartment-specific regulation, including a reduction in the stability and translation of mRNA. These studies reveal that the number and distribution of m6A sites in cellular mRNAs can regulate and influence the composition of the phase-separated transcriptome, and suggest that the cellular properties of m6A-modified mRNAs are governed by liquid-liquid phase separation principles.

Ketamine/propofol admixture vs etomidate for intubation in the critically ill: KEEP PACE Randomized clinical trial.

BACKGROUND: Periintubation hypotension is associated with poor outcomes in the critically ill. We aimed to determine if an admixture of ketamine and propofol for emergent endotracheal intubation in critically ill patients was superior to etomidate. Primary endpoint was the change in mean arterial pressure from baseline to 5 minutes postdrug administration. METHODS: Emergent-use, stratified (shock status and unit type), multiunit, randomized, parallel-group superiority clinical trial was conducted at a tertiary academic medical center. Adult medical/surgical and transplant/oncologic intensive care unit patients undergoing emergent intubation were assigned randomly to receive either ketamine/propofol admixture (0.5 mg/kg of ketamine and propofol each) or reduced dose etomidate (0.15 mg/kg) for emergent intubation. RESULTS: One hundred sixty participants were randomized, and 152 (79 ketamine/propofol admixture, 73 etomidate) were included in the intention-to-treat analysis. There was no statistically significant difference in mean arterial pressure change from baseline to 5 minutes postdrug administration (treatment difference [ketamine/propofol admixture-etomidate]: -2.1 mm Hg; 95% confidence interval, -6.9 mm Hg to +2.7 mm Hg; p = 0.385). In addition, no statistically significant difference was demonstrated in the change of mean arterial pressure from baseline at 10 minutes and 15 minutes postdrug administration, no statistical difference in the use of new-onset vasoactive agents or difficulty of intubation between groups. More patients in the etomidate group required non-red blood cell transfusions (16 [22%] vs. 8 [10%], p = 0.046). For patients who had adrenal testing performed, more patients in the etomidate group developed immediate adrenal insufficiency (13 [81%] of 16 vs. 5 [38%] of 13, p = 0.027). Serious adverse events were rare, 2 (3%) (cardiac arrest, hypotension) in ketamine/propofol admixture and 4 (5%) (hypertension, hypotension) in etomidate (p = 0.430). CONCLUSION: In a heterogeneous critically ill population, ketamine/propofol admixture was not superior to a reduced dose of etomidate at preserving per-intubation hemodynamics and appears to be a safe alternative induction agent in the critically ill. LEVEL OF EVIDENCE: Therapeutic/Care Management, level II. TRIAL REGISTRY: ClinicalTrials.gov, NCT02105415, Ketamine/Propofol Admixture "Ketofol" at Induction in the Critically Ill Against Etomidate: KEEP PACE Trial, IRB 13-000506, Trial Registration: March 31, 2014.

Clinical impact of intraoperative electronic health record downtime on surgical patients.

OBJECTIVE: Despite increased use of electronic health records (EHRs), the clinical impact of system downtime is unknown. MATERIALS AND METHODS: This retrospective matched cohort study evaluated the impact of EHR downtime episodes lasting more than 60 minutes over a 6-year study period. Patients age 18 years or older who underwent surgical procedures at least 60 minutes in duration with an inpatient stay exceeding 24 hours within the study period were eligible for inclusion. Out of 4115 patients exposed to 1 of 176 EHR downtime episodes, 4103 patients were matched to an unexposed cohort in a 1:1 ratio. Multivariable regression analysis, as well as trend analysis for effect of duration of downtime on outcomes, was performed. RESULTS: Downtime-exposed patients had operating room duration 1.1 times longer (p < .001) and postoperative length of stay 1.04 times longer (p = .007) compared to unexposed patients. The 30-day mortality rates were similar between these groups (odds ratio 1.26, p > .05). In trend analysis, there was no association between duration of downtime with respect to evaluated outcomes, postoperative length of stay, and 30-day mortality. CONCLUSION: EHR downtime had no impact on 30-day mortality. Potential associations for increased postoperative length of stay and duration of time spent in the operating room were observed among downtime-exposed patients. No trend effect was observed with respect to duration of downtime and postoperative length of stay and 30-day mortality rates.

Reading m6A in the Transcriptome: m6A-Binding Proteins.

N6-Methyladenosine (m6A) is the most prevalent post-transcriptional modification of eukaryotic mRNA and long noncoding RNA. m6A mediates its effects primarily by recruiting proteins, including the multiprotein eukaryotic initiation factor 3 complex and a set of proteins that contain the YTH domain. Here we describe the mechanisms by which YTH domain-containing proteins bind m6A and influence the fate of m6A-containing RNA in mammalian cells. We discuss the diverse, and occasionally contradictory, functions ascribed to these proteins and the emerging concepts that are influencing our understanding of these proteins and their effects on the epitranscriptome.

The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells.

N6-methyladenosine (m6A) is an abundant nucleotide modification in mRNA that is required for the differentiation of mouse embryonic stem cells. However, it remains unknown whether the m6A modification controls the differentiation of normal and/or malignant myeloid hematopoietic cells. Here we show that shRNA-mediated depletion of the m6A-forming enzyme METTL3 in human hematopoietic stem/progenitor cells (HSPCs) promotes cell differentiation, coupled with reduced cell proliferation. Conversely, overexpression of wild-type METTL3, but not of a catalytically inactive form of METTL3, inhibits cell differentiation and increases cell growth. METTL3 mRNA and protein are expressed more abundantly in acute myeloid leukemia (AML) cells than in healthy HSPCs or other types of tumor cells. Furthermore, METTL3 depletion in human myeloid leukemia cell lines induces cell differentiation and apoptosis and delays leukemia progression in recipient mice in vivo. Single-nucleotide-resolution mapping of m6A coupled with ribosome profiling reveals that m6A promotes the translation of c-MYC, BCL2 and PTEN mRNAs in the human acute myeloid leukemia MOLM-13 cell line. Moreover, loss of METTL3 leads to increased levels of phosphorylated AKT, which contributes to the differentiation-promoting effects of METTL3 depletion. Overall, these results provide a rationale for the therapeutic targeting of METTL3 in myeloid leukemia.

14-3-3ζ loss impedes oncogene-induced mammary tumorigenesis and metastasis by attenuating oncogenic signaling.

The 14-3-3ζ protein belongs to the 14-3-3 family of regulatory eukaryotic proteins that modulate signaling by binding to wide variety of signaling molecules. 14-3-3ζ expression is amplified in over 40% breast cancer patients and is associated with a poor prognosis. Various in vitro and xenograft models have suggested that attenuating 14-3-3ζ expression may provide therapeutic benefits but there has been no study looking at tumor onset and metastasis in breast cancer mouse models with a targeted deletion of 14-3-3ζ. We generated a 14-3-3ζ knockout mouse model to characterize the role of 14-3-3ζ in breast cancer progression. Crossing 14-3-3ζ-/- mice with MMTV-PyMT and MMTV-Neu transgenic mice revealed that loss of 14-3-3ζ prolonged tumor latency and reduced lung metastasis as compared to MMTV-PyMT and MMTV-Neu mice. Mechanistically, loss of 14-3-3ζ suppressed tumor proliferation and angiogenesis and promoted apoptosis by suppressing the Akt and Erk pathway and upregulated the expression of the tumor suppressor p53. Our results provide evidence showing that attenuating 14-3-3ζ expression/activity in mammary tumors can provide a therapeutic benefit.

Reversible methylation of m6Am in the 5' cap controls mRNA stability.

Internal bases in mRNA can be subjected to modifications that influence the fate of mRNA in cells. One of the most prevalent modified bases is found at the 5' end of mRNA, at the first encoded nucleotide adjacent to the 7-methylguanosine cap. Here we show that this nucleotide, N6,2'-O-dimethyladenosine (m6Am), is a reversible modification that influences cellular mRNA fate. Using a transcriptome-wide map of m6Am we find that m6Am-initiated transcripts are markedly more stable than mRNAs that begin with other nucleotides. We show that the enhanced stability of m6Am-initiated transcripts is due to resistance to the mRNA-decapping enzyme DCP2. Moreover, we find that m6Am is selectively demethylated by fat mass and obesity-associated protein (FTO). FTO preferentially demethylates m6Am rather than N6-methyladenosine (m6A), and reduces the stability of m6Am mRNAs. Together, these findings show that the methylation status of m6Am in the 5' cap is a dynamic and reversible epitranscriptomic modification that determines mRNA stability.

Decision Support Tool to Improve Glucose Control Compliance After Cardiac Surgery.

Hyperglycemia control is associated with improved outcomes in patients undergoing cardiac surgery. The Surgical Care Improvement Project metric (SCIP-inf-4) was introduced as a performance measure in surgical patients and included hyperglycemia control. Compliance with the SCIP-inf-4 metric remains suboptimal. A novel real-time decision support tool (DST) with guaranteed feedback that is based on the existing electronic medical record system was developed at a tertiary academic center. Implementation of the DST increased the compliance rate with the SCIP-inf-4 from 87.3% to 96.5%. Changes in tested clinical outcomes were not observed with improved metric compliance. This new framework can serve as a backbone for development of quality control processes for other metrics. Further and, ideally, multicenter studies are required to test if implementation of electronic DSTs will translate into improved resource utilization and outcomes for patients.

m(6)A RNA methylation promotes XIST-mediated transcriptional repression.

The long non-coding RNA X-inactive specific transcript (XIST) mediates the transcriptional silencing of genes on the X chromosome. Here we show that, in human cells, XIST is highly methylated with at least 78 N6-methyladenosine (m6A) residues-a reversible base modification of unknown function in long non-coding RNAs. We show that m6A formation in XIST, as well as in cellular mRNAs, is mediated by RNA-binding motif protein 15 (RBM15) and its paralogue RBM15B, which bind the m6A-methylation complex and recruit it to specific sites in RNA. This results in the methylation of adenosine nucleotides in adjacent m6A consensus motifs. Furthermore, we show that knockdown of RBM15 and RBM15B, or knockdown of methyltransferase like 3 (METTL3), an m6A methyltransferase, impairs XIST-mediated gene silencing. A systematic comparison of m6A-binding proteins shows that YTH domain containing 1 (YTHDC1) preferentially recognizes m6A residues on XIST and is required for XIST function. Additionally, artificial tethering of YTHDC1 to XIST rescues XIST-mediated silencing upon loss of m6A. These data reveal a pathway of m6A formation and recognition required for XIST-mediated transcriptional repression.

The Effect of an Electronic Checklist on Critical Care Provider Workload, Errors, and Performance.

PURPOSE: The strategy used to improve effective checklist use in intensive care unit (ICU) setting is essential for checklist success. This study aimed to test the hypothesis that an electronic checklist could reduce ICU provider workload, errors, and time to checklist completion, as compared to a paper checklist. METHODS: This was a simulation-based study conducted at an academic tertiary hospital. All participants completed checklists for 6 ICU patients: 3 using an electronic checklist and 3 using an identical paper checklist. In both scenarios, participants had full access to the existing electronic medical record system. The outcomes measured were workload (defined using the National Aeronautics and Space Association task load index [NASA-TLX]), the number of checklist errors, and time to checklist completion. Two independent clinician reviewers, blinded to participant results, served as the reference standard for checklist error calculation. RESULTS: Twenty-one ICU providers participated in this study. This resulted in the generation of 63 simulated electronic checklists and 63 simulated paper checklists. The median NASA-TLX score was 39 for the electronic checklist and 50 for the paper checklist (P = .005). The median number of checklist errors for the electronic checklist was 5, while the median number of checklist errors for the paper checklist was 8 (P = .003). The time to checklist completion was not significantly different between the 2 checklist formats (P = .76). CONCLUSION: The electronic checklist significantly reduced provider workload and errors without any measurable difference in the amount of time required for checklist completion. This demonstrates that electronic checklists are feasible and desirable in the ICU setting.

Adverse in-hospital events are associated with increased in-hospital mortality and length of stay in patients with or at risk of acute respiratory distress syndrome.

OBJECTIVE: To explore the effect of various adverse hospital events on short- and long-term outcomes in a cohort of acutely ill hospitalized patients. PATIENTS AND METHODS: In a secondary analysis of a retrospective cohort of acutely ill hospitalized patients with sepsis, shock, or pneumonia or undergoing high-risk surgery who were at risk for or had developed acute respiratory distress syndrome between 2001 and 2010, the effects of potentially preventable hospital exposures and adverse events (AEs) on in-hospital and intensive care unit (ICU) mortality, length of stay, and long-term survival were analyzed. Adverse effects chosen for inclusion were inadequate empiric antimicrobial coverage, hospital-acquired aspiration, medical or surgical misadventure, inappropriate blood product transfusion, and injurious tidal volume while on mechanical ventilation. RESULTS: In 828 patients analyzed, the distribution of 0, 1, 2, and 3 or more cumulative AEs was 521 (63%), 126 (15%), 135 (16%), and 46 (6%) patients, respectively. The adjusted odds ratios (95% CI) for in-hospital mortality in patients who had 1, 2, and 3 or more AEs were 0.9 (0.5-1.7), 0.9 (0.5-1.6), and 1.4 (0.6-3.3), respectively. One AE increased the length of stay, difference between means (95% CI), in the hospital by 8.7 (3.8-13.7) days and in the ICU by 2.4 (0.6-4.2) days. CONCLUSION: Potentially preventable hospital exposure to AEs is associated with prolonged ICU and hospital lengths of stay. Implementation of effective patient safety interventions is of utmost priority in acute care hospitals.

Outcome of adverse events and medical errors in the intensive care unit: a systematic review and meta-analysis.

Adverse events and medical errors (AEs/MEs) are more likely to occur in the intensive care unit (ICU). Information about the incidence and outcomes of such events is conflicting. A systematic review and meta-analysis were conducted to examine the effects of MEs/AEs on mortality and hospital and ICU lengths of stay among ICU patients. Potentially eligible studies were identified from 4 major databases. Of 902 studies screened, 12 met the inclusion criteria, 10 of which are included in the quantitative analysis. Patients with 1 or more MEs/AEs (vs no MEs/AEs) had a nonsignificant increase in mortality (odds ratio = 1.5; 95% confidence interval [CI] = 0.98-2.14) but significantly longer hospital and ICU stays; the mean difference (95% CI) was 8.9 (3.3-14.7) days for hospital stay and 6.8 (0.2-13.4) days for ICU. The ICU environment is associated with a substantial incidence of MEs/AEs, and patients with MEs/AEs have worse outcomes than those with no MEs/AEs.