ObjectivesThe objective of this study was to examine the association between admission time and in-hospital mortality in patients with severe community-acquired pneumonia.Research DesignThe study population consisted of individuals who were enrolled between January 2019 and December 2023. These individuals were divided into two groups based on the time of admission: daytime admission from 8:00 am to 6:00 pm and nighttime admission from 6:00 pm to 8:00 am The primary endpoint of the study was in-hospital mortality. Binary logistic regression was employed to assess the association between admission time and in-hospital mortality.ResultsA total of 307 patients with severe community-acquired pneumonia were ultimately enrolled in the study. Of the total number of patients, 57% (175 patients) were admitted at night. A comparative analysis of the clinical outcomes in the two groups revealed that the mortality rate for patients admitted at night was 28%, which was not significantly different from that of patients admitted during the day, which was 35.6% (P = .155). The findings from binary logistic regression analyses revealed no statistically significant correlation between nighttime admissions and in-hospital mortality.ConclusionsThis study's findings indicate that nighttime admission for patients diagnosed with severe community-acquired pneumonia is not associated with an elevated risk of mortality. Conversely, there may be a reduced mortality rate for patients admitted during nighttime hours. However, further prospective multicenter studies are required in the future to confirm this.

Incidents related to patient safety are a problem of great impact in Intensive Care Medicine (ICM). Multiple strategies have been developed to identify them, analyze, and develop policies aim at reducing their incidence and minimizing their effects and consequences. The development of a safety culture, an adequate organizational and structural design of the ICM, which contemplates the implementation of effective safe practices, with a provision of human resources adjusted to the care activity carried out and the periodic analysis of the different events and their factors, will allow us to bring the risk of critical patient care closer to zero, as would be desirable.

Providers vary in their impact on clinical outcomes, but this is rarely accounted for in healthcare research. By failing to identify the provider responsible for a patient's care, investigators miss an opportunity to account for nonrandom variation in outcomes. Prior methods of identifying responsible providers have relied on manual chart review, which is time-consuming and expensive, or analysis of claims data, which has been demonstrated to be inaccurate. To address these gaps, we sought to develop an algorithm using electronic health record (EHR) data to identify the responsible provider for each day of a patient's hospitalization.

A multicenter retrospective cohort study.

Midwest healthcare system.

Hospitalized patients and their providers.

None.

We first confirmed high inter-rater reliability of manual chart review to identify the responsible provider. Using manual chart review as the gold standard, we then assessed the accuracy of an automated algorithm in a set of randomly selected patients. The agreement between two independent physicians in their determination of the responsible provider by chart review was 100%. Among 200 randomly selected patients, the algorithm identified the same responsible provider as the physician chart reviewer on 93% (3372/3626; 95% CI, 92-94%) of patient-days.

Readily available EHR data can be used to assign patients to providers daily with a high degree of accuracy. This methodology could be applied in healthcare research to identify sources of variation other than the intervention being studied.

Measuring and assessing the relationship between inpatient nurse staffing and workload across a national health system is difficult because of challenges in systematically observing inpatient workload at the unit level.

The objective of this study was to apply a novel measure of inpatient nurse workload to estimate the relationship between inpatient nurse staffing and nurse workload at the unit level during a key nursing activity: the peak-time medication pass.

A retrospective observational study was conducted in the Veterans Health Administration, the largest employer of nurses in the United States. The sample included all patients ( n = 1,578,399 patient days) admitted to 311 non-intensive care unit inpatient acute care units in 112 hospitals in 2019 (104,588 unit days). Staffing was measured as the unit-level, nurse-to-patient ratio, and workload was measured using average time (duration) for RNs to complete the peak-time medication pass.

We found a negative relationship between the RN-to-patient ratio and average peak-time medication pass duration after adjusting for unit-level patient volume and average patient severity of illness and other unit-level factors. This relationship was nonlinear: The marginal effect of staffing on workload decreased as staffing increased.

As unit-level nurse staffing increased, average RN workload decreased. This result suggests that interventions to improve nurse staffing may have larger nonlinear effects for units with lower staffing levels. Understanding the effect of differing staffing decisions on variations in nursing workload is critical for adopting models of care that effectively use scarce staffing resources and contribute to retaining nurses in the inpatient workforce. This work provides evidence that peak-time medication pass duration is a valid process-based measure of workload and highlights the potential diminishing returns to increasing staffing.

Handgrip strength (HGS) is a non-invasive and reliable biomarker of overall health, physical function, mobility, and mortality. This study aimed to investigate the possible relationship between HGS and mortality in older adult patients hospitalized with COVID-19 in the intensive care unit (ICU) by Alpha (B.1.1.7) and Delta (B.1.617.2) variants. This retrospective cohort study was conducted on 472 COVID-19 patients (222 female and 250 male) aged 60-85 years admitted to the ICU. Demographic data, underlying comorbidities, COVID-19-related symptoms, as well as laboratory and computed tomography (CT) findings were obtained from the patient's medical records. Using a JAMAR® hydraulic dynamometer, the average grip strength value (kg) after three measurements on the dominant side was recorded for subsequent analysis. Low grip strength (LGS) was defined as an arbitrary cut-off of two standard deviations below the gender-specific peak mean value of normative HGS in Iranian healthy population, i.e. < 26 kg in males and < 14 kg in females. The findings showed lower mean grip strength and high frequency of LGS in the non-survivors patients versus survivors group and in the Delta (B.1.617.2) variant vs. Alpha (B.1.1.7) variant, respectively (both p < 0.01). The binary logistic regression analysis showed that chronic obstructive pulmonary disease (COPD) (adjusted odds ratio [OR] 5.125, 95% CI 1.425-25.330), LGS (OR 4.805, 95% CI 1.624-10.776), SaO2 (OR - 3.501, 95% CI 2.452-1.268), C-reactive protein (CRP) level (OR 2.625, 95% CI 1.256-7.356), and age (OR 1.118, 95% CI 1.045-1.092) were found to be independent predictors for mortality of patients with Alpha (B.1.1.7) variant (all p < 0.05). However, only four independent predictors including COPD (OR 6.728, 95% CI 1.683-28.635), LGS (OR 5.405, 95% CI 1.461-11.768), SaO2 (OR - 4.120, 95% CI 2.924-1.428), and CRP level (OR 1.893, 95% CI 1.127-8.692) can be predicted the mortality of patients with Delta (B.1.617.2) variant (p < 0.05). Along with the well-known and common risk factors (i.e. COPD, CRP, and SaO2), handgrip strength can be a quick and low-cost prognostic tool in predicting chances of mortality in older adults who are afflicted with COVID-19 variants.

Despite the high workload of cardiac intensive care unit (ICU), there is a paucity of evidence on the association between nurse workforce and mortality in patients with cardiogenic shock (CS). This study aimed to evaluate the prognostic impact of the ICU nursing grade on mortality and cost-effectiveness in CS.

A nationwide analysis was performed using the K-NHIS database. Patients diagnosed with CS and admitted to the ICU at tertiary hospitals were enrolled. ICU nursing grade was defined according to the bed-to-nurse ratio: grade1 (bed-to-nurse ratio < 0.5), grade2 (0.5 ≤ bed-to-nurse ratio < 0.63), and grade3 (0.63 ≤ bed-to-nurse ratio < 0.77) or above. The primary endpoint was in-hospital mortality. Cost-effective analysis was also performed.

Of the 72,950 patients with CS, 27,216 (37.3%) were in ICU nursing grade 1, 29,710 (40.7%) in grade 2, and 16,024 (22.0%) in grade ≥ 3. The adjusted-OR for in-hospital mortality was significantly higher in patients with grade 2 (grade 1 vs. grade 2, 30.6% vs. 37.5%, adjusted-OR 1.14, 95% CI1.09-1.19) and grade ≥ 3 (40.6%) with an adjusted-OR of 1.29 (95% CI 1.23-1.36) than those with grade 1. The incremental cost-effectiveness ratio of grade1 compared with grade 2 and ≥ 3 was $25,047/year and $42,888/year for hospitalization and $5151/year and $5269/year for 1-year follow-up, suggesting that grade 1 was cost-effective. In subgroup analysis, the beneficial effects of the high-intensity nursing grade on mortality were more prominent in patients who received CPR or multiple vasopressors usage.

For patients with CS, ICU grade 1 with a high-intensity nursing staff was associated with reduced mortality and more cost-effectiveness during hospitalization compared to grade 2 and grade ≥ 3, and its beneficial effects were more pronounced in subjects at high risk of CS.

(1) To assess mental workloads of intensive care unit (ICU) nurses in 12-hour working shifts (days and nights) using eye movement data; (2) to explore the impact of stress on the ocular metrics of nurses performing patient care in the ICU.

Prior studies have employed workload scoring systems or accelerometer data to assess ICU nurses' workload. This is the first naturalistic attempt to explore nurses' mental workload using eye movement data.

Tobii Pro Glasses 2 eye-tracking and Empatica E4 devices were used to collect eye movement and physiological data from 15 nurses during 12-hour shifts (252 observation hours). We used mixed-effect models and an ordinal regression model with a random effect to analyze the changes in eye movement metrics during high stress episodes.

While the cadence and characteristics of nurse workload can vary between day shift and night shift, no significant difference in eye movement values was detected. However, eye movement metrics showed that the initial handoff period of nursing shifts has a higher mental workload compared with other times. Analysis of ocular metrics showed that stress is positively associated with an increase in number of eye fixations and gaze entropy, but negatively correlated with the duration of saccades and pupil diameter.

Eye-tracking technology can be used to assess the temporal variation of stress and associated changes with mental workload in the ICU environment. A real-time system could be developed for monitoring stress and workload for intervention development.

Among patients with severe acute kidney injury (AKI) admitted to the ICU in high-income countries, regional practice variations for fluid balance (FB) management, timing, and choice of renal replacement therapy (RRT) modality may be significant.

Secondary post hoc analysis of the STandard vs. Accelerated initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial (ClinicalTrials.gov number NCT02568722).

One hundred-fifty-three ICUs in 13 countries.

Altogether 2693 critically ill patients with AKI, of whom 994 were North American, 1143 European, and 556 from Australia and New Zealand (ANZ).

None.

Total mean FB to a maximum of 14 days was +7199 mL in North America, +5641 mL in Europe, and +2211 mL in ANZ (p < 0.001). The median time to RRT initiation among patients allocated to the standard strategy was longest in Europe compared with North America and ANZ (p < 0.001; p < 0.001). Continuous RRT was the initial RRT modality in 60.8% of patients in North America and 56.8% of patients in Europe, compared with 96.4% of patients in ANZ (p < 0.001). After adjustment for predefined baseline characteristics, compared with North American and European patients, those in ANZ were more likely to survive to ICU (p < 0.001) and hospital discharge (p < 0.001) and to 90 days (for ANZ vs. Europe: risk difference [RD], -11.3%; 95% CI, -17.7% to -4.8%; p < 0.001 and for ANZ vs. North America: RD, -10.3%; 95% CI, -17.5% to -3.1%; p = 0.007).

Among STARRT-AKI trial centers, significant regional practice variation exists regarding FB, timing of initiation of RRT, and initial use of continuous RRT. After adjustment, such practice variation was associated with lower ICU and hospital stay and 90-day mortality among ANZ patients compared with other regions.