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ObjectivesThe main aim of the study was (1) to assess digital literacy among acutely admitted patients in an ED, (2) to provide quantitative data relating to the ‘inverse information law’. We hypothesised that a large proportion of acutely admitted patients are digitally incapable, and there is a link between age, frailty, hospital admittances and digital incapability.DesignThis study is a single-centre, cross-sectional, prospective case-controlled questionnaire study. Clinical Frailty Scale (CFS), gender and age were collected from the patients’ electronic medical reports. Information regarding smartphone usage, ability to access public mail/communication, educational level, living situation and number of admittances the last year were patient-reported bedside. Subsequently, ability to use a digital platform was tested.SettingA secondary care ED in Denmark, with a high level of broadband penetration, allows easy digital access.ParticipantsA total of 588 patients were assessed for eligibility, hereof 468 patients were included. Inclusion criteria were age above 18 years, admitted for treatment of an internal medicine or surgical problem, triaged non-emergent in a stable condition, informed oral and written consent.Main outcome measuresThe proportions of acutely admitted patients who were digitally capable versus incapable whether there is a link between age, frailty, hospital admittances and digital incapability.ResultsAmong patients included, 57% (n=265) had high digital literacy, while 43% (n=203) had low literacy Δ%=14. The high digital capability group was significantly younger by 23% (15.3, 20.5) p<0.001 and had lower CFS than the low digital capability group 2.3 versus 4.2 (1.7, 2.3) p<0.001. The low digital capability group had 1.6-fold more admittances the previous year (0.5, 1.2) p<0.001.ConclusionsThe proportion of digitally illiterate patients is high (43%), and they are older, frailer and have more hospital admittances and less high education than digitally literate patients. There is a significant digital divide that needs to be considered in health care.

Acute kidney injury (AKI) is a syndrome with high mortality and morbidity in part due to delayed recognition based on changes in creatinine. A marker for AKI based on a single measurement is needed and therefore the performance of a single measurement of plasma neutrophil gelatinase-associated lipocalin (pNGAL) to predict AKI in patients admitted to the emergency department was tested. Samples from the Triage study which included 6005 consecutive adult patients admitted to the emergency department were tested for pNGAL. The optimal cutoff for pNGAL was determined by the AUC and compared to AKI based on creatinine using different estimations of the premorbid kidney function. In 4833 patients, two or more plasma creatinine (pCr) measurements were available allowing the detection of AKI. The highest prevalence of AKI (10%) was found when defining AKI as an increase in pCr ≥26.5 μmol/L from the prior year's mean pCr. At these conditions the AUC for pNGAL to predict AKI was 85% giving an optimal cutoff of 142.5 ng/mL with a negative predictive value of 0.96, a positive predictive value of 0.35, a specificity of 0.87 and a sensitivity of 0.70. The study illustrates that the value of a single measurement of pNGAL is primarily in excluding AKI whereas it`s poorer in predicting the presence of AKI. When diagnosing AKI with pCr the optimal baseline pCr level is the mean of available pCr (mb-pCr) measurements from up to a year prior to the current event.

Background and hypothesis Acute kidney injury (AKI) and chronic kidney disease (CKD) are associated with high morbidity. Current diagnostic markers, e.g., creatinine (Cr) and estimated glomerular filtration rate (eGFR), lack precision in early kidney disease detection. Neutrophil gelatinase-associated lipocalin (NGAL) has been proposed as a more sensitive biomarker for kidney injury. This study examined the effectiveness of plasma NGAL (pNGAL) as biomarker for CKD and AKI prediction in an emergency department (ED) setting and for predicting the presence of CKD and AKI in future admissions (readmission). The performance was compared to that of C-reactive protein (CRP). Methods A prospective longitudinal study was conducted at North Zealand University Hospital in Denmark, including 925 patients admitted to the ED. pNGAL and CRP were measured at admission, with follow-up pNGAL measurements for hospitalized patients. CKD and AKI were defined according to KDIGO guidelines. Receiver operating characteristic (ROC) analyses assessed the sensitivity, specificity, and predictive value of pNGAL and CRP, for AKI and CKD, at both admission and readmission. Results and conclusion pNGAL is useful for ruling out AKI and CKD, especially at admission, but its low PPV limit its diagnostic accuracy, particularly at readmission. It is more effective as a screening tool rather than a standalone diagnostic marker. Higher predictive performance was observed for pNGAL compared to CRP. For serial pNGAL measurements, CKD patients exhibited higher initial levels at admission, but these differences diminished by day four, with considerable variability observed thereafter.

Background Emergency department (ED) crowding is a major patient safety concern and has a negative impact on healthcare systems and healthcare providers. We hypothesized that it would be feasible to control crowding by employing a multifaceted approach consisting of systematically fast-tracking patients who are mostly not in need of a hospital stay as assessed by an initial nurse and treated by decision competent physicians. Methods Data from 120,901 patients registered in a secondary care ED from the 4t th quarter of 2021 to the 1st quarter of 2024 was drawn from the electronic health record’s data warehouse using the SAP Web Intelligence tool and processed in the Python programming language. Crowding was compared before and after ED transformation from a uniform department into a high flow (α) and a low flow (β) section with patient placement in gurneys/chairs or beds, respectively. Patients putatively not in need of hospitalization were identified by nurse, placed in in the α setting and assessed and treated by decision competent physicians. Incidence of crowding, number of patients admitted per day and readmittances within 72 h following ED admission before and after changes were determined. Values are number of patients, mean ± SEM and mean differences with 95% CIs. Statistical significance was ascertained using Student’s two tailed t-test for unpaired values. Results Before and after ED changes crowding of 130% amounted to 123.8 h and 19.3 h in the latter. This is a difference of -104.6 ± 23.9 h with a 95% CI of -159.9 to -49.3, Δ% -84 ( p  = 0.002). There was the same amount of patients / day amounting to 135.8 and 133.5 patients / day Δ% = -1.7 patients 95% CI -6.3 to 1.6 ( p  = 0.21). There was no change in readmittances within 72 h before and after changes amounting to 9.0% versus 9.5%, Δ% = 0.5, 95%, CI -0.007 to 1.0 ( p  > 0.052). Conclusion It appears feasible to abate crowding with unchanged patient admission and without an increase in readmittances by fast-track assessment and treatment of patients who are not in need of hospitalization.

Background Setting the dry weight and maintaining fluid balance is still a difficult challenge in dialysis patients. Overhydration is common and associated with increased cardiac morbidity and mortality. Pulmonary hypertension is associated with volume overload in end-stage renal dysfunction patients. Thus, monitoring pulmonary pressure by a CardioMEMS device could potentially be of guidance to physicians in the difficult task of assessing fluid overload in hemodialysis patients. Case presentation 61-year old male with known congestive heart failure deteriorated over 3 months’ time from a state with congestive heart failure and diuresis to a state of chronic kidney disease and anuria. He began a thrice/week in-hospital hemodialysis regime. As he already had implanted a CardioMEMS device due to his heart condition, we were able to monitor invasive pulmonary artery pressure during the course of dialysis sessions. To compare, we estimated overhydration by both bioimpedance and clinical assessment. Pulmonary artery pressure correlated closely with fluid drainage during dialysis and inter-dialytic weight gain. The patient reached prescribed dry weight but remained pulmonary hypertensive by definition. During two episodes of intradialytic systemic hypotension, the patient still had pulmonary hypertension by current definition. Conclusion This case report observes a close correlation between pulmonary artery pressure and fluid overload in a limited amount of observations. In this case we found pulmonary artery pressure to be more sensitive towards fluid overload than bioimpedance. The patient remained pulmonary hypertensive both as he reached prescribed dry weight and experienced intradialytic hypotensive symptoms. Monitoring pulmonary artery pressure via CardioMEMS could hold great potential as a real-time guidance for fluid balance during hemodialysis, though adjusted cut-off values for pulmonary pressure for anuric patients may be needed. Further studies are needed to confirm the findings of this case report and the applicability of pulmonary pressure in assessing optimal fluid balance.

Infectious diseases are major health care challenges globally and a prevalent cause of admission to emergency departments. Epidemiologic characteristics and outcomes based on population level data are limited. The Database of Community Acquired Infections in Eastern Denmark (DCAIED) 2018-2021 was established with the aim to explore and estimate the population characteristics, and outcomes of patients suffering from community acquired infections at the emergency departments in the Capital Region and the Zealand Region of Denmark using data from electronic medical records. Adult patients ([greater than or equal to]18 years) presenting to the emergency department with suspected or confirmed infection are included in the cohort. Presence of sepsis and organ failure are assessed using modified criteria from the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). During the inclusion period from January 2018 to January 2022, 2,241,652 adult emergency department visits have been registered. Of these, 451,825 were unique encounters of which 60,316 fulfilled criteria of suspected infection and 28,472 fulfilled sepsis criteria and 8,027 were defined as septic shock. The database covers the entire Capital and Zealand Region of Denmark with an uptake area of 2.6 million inhabitants and includes demographic, laboratory and outcome indicators, with complete follow-up. The database is well-suited for epidemiological research for future national and international collaborations. Keywords: emergency department, infectious diseases, sepsis, shock, database, epidemiology, community acquired

Background/Objectives: Acute kidney injury (AKI) is a significant global health issue with a high morbidity and mortality. The Kidney Disease: Improving Global Outcomes (KDIGO) guidelines identify various exposures and susceptibilities as risk factors for AKI. However, the predictive significance of these factors in heterogeneous emergency department (ED) populations remains unclear. We hypothesized that assessing KDIGO-listed exposures and susceptibilities for AKI, alone and in combination, would provide an insight into their predictive value for AKI. Furthermore, we investigated whether adding biomarkers, plasma neutrophil gelatinase-associated lipocalin (pNGAL) and C-reactive protein (CRP), could enhance AKI risk prediction. Methods: Data were analyzed from the prospective longitudinal “NGAL study” conducted at North Zealand University Hospital in Denmark. A total of 344 ED patients were included, with AKI diagnosed using KDIGO’s creatinine-based criteria. Patient data, including medical history, exposures, and susceptibilities, were extracted and analyzed. Predictive performance was evaluated using a receiver operating characteristic (ROC) analysis on individual and combined risk factors. Additional models incorporated pNGAL and CRP to assess their impact on prediction accuracy. Results: Individual exposures and susceptibilities showed a poor predictive performance, with nephrotoxic drugs and advanced age demonstrating the highest sensitivity but a low positive predictive value (PPV). Combining multiple risk factors improved AKI prediction, with models clustering into those optimizing sensitivity or PPV. The inclusion of pNGAL significantly enhanced predictive performance, achieving the highest combined sensitivity and PPV. Although less than pNGAL, CRP also improved prediction, while requiring fewer variables than pNGAL-inclusive models. Conclusions: No individual KDIGO-listed exposure or susceptibility could reliably predict AKI in the ED setting. Combining multiple exposures and susceptibilities improved the predictive accuracy, but the models excelled either at screening or confirmation, not both. The addition of pNGAL and CRP significantly enhanced AKI prediction, emphasizing the need for biomarker integration in risk stratification models. These findings highlight the limitations of clinical parameters alone and underscore the importance of a multifaceted approach to AKI risk assessment.

Diagnosis of acute kidney injury (AKI) based on plasma creatinine often lags behind actual changes in renal function. Here, we investigated early detection of AKI using the plasma soluble urokinase plasminogen activator receptor (suPAR) and neutrophil gelatinase-sssociated lipocalin (NGAL) and observed the impact of early detection on prescribing recommendations for renally-eliminated medications. This study is a secondary analysis of data from the DISABLMENT cohort on acutely admitted older (≥65 years) medical patients (n = 339). Presence of AKI according to kidney disease: improving global outcomes (KDIGO) criteria was identified from inclusion to 48 h after inclusion. Discriminatory power of suPAR and NGAL was determined by receiver-operating characteristic (ROC). Selected medications that are contraindicated in AKI were identified in Renbase®. A total of 33 (9.7%) patients developed AKI. Discriminatory power for suPAR and NGAL was 0.69 and 0.78, respectively, at a cutoff of 4.26 ng/mL and 139.5 ng/mL, respectively. The interaction of suPAR and NGAL yielded a discriminatory power of 0.80, which was significantly higher than for suPAR alone (p = 0.0059). Among patients with AKI, 22 (60.6%) used at least one medication that should be avoided in AKI. Overall, suPAR and NGAL levels were independently associated with incident AKI and their combination yielded excellent discriminatory power for risk determination of AKI.

Background Older people have the highest incidence of acute medical admissions. Old age and acute hospital admissions are associated with a high risk of adverse health outcomes after discharge, such as reduced physical performance, readmissions and mortality. Hospitalisations in this population are often by acute admission and through the emergency department. This, along with the rapidly increasing proportion of older people, warrants the need for clinically feasible tools that can systematically assess vulnerability in older medical patients upon acute hospital admission. These are essential for prioritising treatment during hospitalisation and after discharge. Here we explore whether an abbreviated form of the FI-Lab frailty index, calculated as the number of admission laboratory test results outside of the reference interval (FI-OutRef) was associated with long term mortality among acutely admitted older medical patients. Secondly, we investigate other markers of aging (age, total number of chronic diagnoses, new chronic diagnoses, and new acute admissions) and their associations with long-term mortality. Methods A cohort study of acutely admitted medical patients aged 65 or older. Survival time within a 3 years post-discharge follow up period was used as the outcome. The associations between the markers and survival time were investigated by Cox regression analyses. For analyses, all markers were grouped by quartiles. Results A total of 4,005 patients were included. Among the 3,172 patients without a cancer diagnosis, mortality within 3 years was 39.9%. Univariate and multiple regression analyses for each marker showed that all were significantly associated with post-discharge survival. The changes between the estimates for the FI-OutRef quartiles in the univariate- and the multiple analyses were negligible. Among all the markers investigated, FI-OutRef had the highest hazard ratio of the fourth quartile versus the first quartile: 3.45 (95% CI: 2.83-s4.22, P < 0.001). Conclusion Among acutely admitted older medical patients, FI-OutRef was strongly associated with long-term mortality. This association was independent of age, sex, and number of chronic diagnoses, new chronic diagnoses, and new acute admissions. Hence FI-OutRef could be a biomarker of advancement of aging within the acute care setting.