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Background

A major barrier to the analysis of ventilation waveform data collected during CPR is the presence of artefacts caused by chest compressions. This study describes the development and evaluation of an algorithm to extract parameters regarding ventilation volume, pressure, and frequency from pneumotachography waveform data collected during ongoing simulated CPR.

Method

Ventilation waveform data was collected from a pneumotachograph connected to the respiratory circuit of a ventilator and a test lung. Both regular ventilation and ventilation during simulated CPR were used to develop the algorithm. A grid search was employed to optimize the algorithm parameters compared to the ventilator settings. The parameters were then manually tuned using clinical data from ventilation during CPR. The performance of the algorithm was described in terms of the median error vs. the known ventilator settings in the simulated data.

Results

Compared to the ventilator settings, the largest systematic errors of the algorithm was an overestimation of peak pressures during asynchronous CPR (median error of 3 (IQR 0.3–5.8) cmH₂O), and an underestimation of inspiratory volumes during synchronous CPR (median error 46 (IQR −76 to 10) ml).

Conclusion

In an experimental setting, the developed algorithm provides a novel solution to measure ventilation parameters during ongoing chest compressions. The algorithm is freely available under an open-source licence for use and further development. Further studies will be needed to validate the algorithm.

Background 

Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more patients requiring an ambulance than there are available ambulances are common. Machine Learning (ML) techniques offer a promising but largely untested approach to assessing relative risks among these patients. The study aims to establish whether the provision of ML-based risk scores predicting patient outcomes improves the ability of dispatchers to identify patients at high risk for deterioration in RCS and dispatch the first available ambulance to them.

Methods and findings 

We performed a parallel-group, randomized trial of adult patients assessed by a dispatch nurse at two study sites in Sweden as requiring a low-priority ambulance response in RCS. Patients were randomized 1:1 to be prioritized with the aid of an ML-based risk assessment tool, or per current clinical practice. The primary outcome was defined in terms of whether the first available ambulance was sent to the patient with the highest National Early Warning Score (NEWS 2) based on subsequently collected vital signs. A total of 1,245 RCS were included in the study. In the intervention arm, 68.3% of RCS were assessed correctly per the primary outcome versus 62.5% in the control group, corresponding to an odds ratio of 1.28 (95% CI [1.00, 1.63], p = 0.047). This study was limited to only patients determined to require a low-priority ambulance response in two Swedish regions, and was underpowered for the primary outcome due to a smaller than expected sample size.

Conclusion 

This study suggests that clinical ML-based decision support tools may have the ability to influence care provider decisions and improve their capacity to rapidly differentiate between high- and low-risk patients at dispatch. Further research should establish the suitability of these tools in larger cohorts, for patients with both higher- and lower-levels of priority, and in other settings. The trial was registered at ClinicalTrials.gov (NCT04757194).

Background: Clinical feedback is often lacking in prehospital care, and while performance data is increasingly available to clinical and operational leadership, it is seldom made available to care providers themselves. In this study, we investigate the impact of a simple intervention consisting of the provision of monthly feedback reports via email to emergency medical dispatch nurses in three Swedish regions.

Method: Individualised reports consisting of 14 measures divided into descriptive (eg, priority-setting and call times), process (eg, dispatch times and documentation completeness) and outcome (eg, over/under triage rate) categories were developed with staff and management input. Report delivery was implemented using a stepped-wedge design, and effects were evaluated using a hierarchical regression-based interrupted time series analysis.

Results: 40 dispatchers were included in the study between March 2020 and October 2023, who handled a total of 246 353 incidents. Some impacts on documentation-related process measures were identified, with the odds of complete documentation increasing by 7.5% (95% CI 5.1 to 9.9) and the odds of having a documented contact reason increasing by 3.8% (1.5-5.9). These effects remained robust over the post-intervention period. Weaker impacts on outcome measures were identified which could be explained by a higher priority given to emergency medical dispatches overall.

Conclusion: Providing performance data can influence care providers to adjust their behaviour to improve process-related quality metrics under their direct control. The intervention may also have induced nurses to more often upgrade the priority of their patients. Improving outcome metrics may however require more intensive, multifaceted interventions.

Background

At emergency medical dispatch centres (EMDCs) telephone triage takes place in three steps: identifying the event, assessing the callers' need for support, and prioritizing the response. Some calls are considered to be more difficult to handle than others, and decision support systems may in these situations be of limited help. The aim of this study was to describe and characterize difficult calls to EMDCs.

Methods

Retrospective call data from 2022 to 2023 was extracted for Registered Nurse (RN) dispatchers at three EMDCs in Sweden agreeing to participate in this mixed-method study. Categories of difficult calls were identified based on prior research and operationalized as key-word searches in the free text call notes or as indicators based on structured data. A purposeful selection of calls meeting these criteria were extracted, anonymized, and data regarding categories and the phase on the call in which they occurred then coded. A descriptive quantitative analysis was performed, and logistic regression was used to estimate the association between demographics and the likelihood of high-priority ambulance dispatch.

Results

Over the two-year study period, 14 included RNs handled 27,805 calls. Of these, 4888 calls (17.6%) were identified as potentially difficult calls based on free-text notes and structured data, from which 123 calls were selected for further analysis. The median age of callers were 49 years, and 49% were female. Median call duration was 5.6 min, compared to 5.1 min in the full dataset, and 39.5% of calls resulted in a lights and sirens response.Vague or unclear symptoms and psychiatric problems were the most common difficulties. These could occur in all three phases of the calls and in several of the phases in one single call, with a combination of "assessing and prioritizing" being the most common. Male sex was found to be associated with a higher likelihood of receiving an ambulance with high priority.

Conclusions

Difficult calls, mainly with vague or unclear symptoms and psychiatric problems, are common at EMDCs. The reason for the tendency to prioritize young males higher are seen in other contexts but not in truly high priority cases at dispatch and needs further investigation.

Prehospital care involves increasingly complex decision-making processes, necessitating commensurate advances in the methods used to assess and improve the quality of patient triage processes. This doctoral project aimed to advance the measurement of patient outcomes in the evaluation of prehospital decision-making and develop interventions to improve those outcomes. In study I, a set of outcome definitions for evaluating referrals to non-emergency care by dispatch nurses was validated, confirming the ability of systematic data abstraction processes to identify patient harms missed by traditional incident reporting systems. In study II, an intervention delivering feedback on process and outcome metrics to dispatch nurses was evaluated, identifying improvements in some process metrics, while impacts on outcomes remained elusive. In study III a machine learning-based approach to estimating composite risk scores was validated internally for use in prehospital contexts. In study IV, similar models for use in Ambulance care were externally validated in a dataset collected from six Swedish regions, finding that model performance remained superior to traditional rule-based risk assessment instruments even when the models were applied in novel settings. Study V is a randomized controlled trial whereby a clinical decision support tool based on these models was found to enhance the ability of dispatchers to identify and prioritize high-risk patients in resource constrained situations. Future directions for study include the incorporation of additional structured and unstructured data in the prediction models, and efforts to evaluate and enhance their fairness and alignment with human assessments of care need. Open-source software packages implementing these tools are available to enhance the transparency of the work and stimulate further development.

Background

Heart failure patients tend to experience higher rates of hospital readmissions compared to other ambulatory care-sensitive conditions. In Sweden, the nationwide Care Coordination Act (CCA) was introduced in January 2018 with the goal of improving care coordination resulting in a reduction of readmissions and length of stay. There is insufficient knowledge regarding the effect of this reform on heart failure patients.

Methods

We studied the association of implementing CCA on all cause 30-day readmissions and length of stay for patients over 65 years of age with ICD-50 heart failure. The dataset included all admissions with a primary diagnosis of heart failure among elderly, multimorbid patients between 2015 and 2019. An interrupted time series analysis using hierarchical mixed models with random effects clustered at the hospital ward level was conducted.

Results

A total of 111 414 admissions were included. The average readmission rate for heart failure patients was 26.8 % before and 26.7 % after the CCA. The average length of stay (LOS) was 8.4 days before the CCA and 8.1 days after. Mortality within 30 days was 7.3 % before the CCA and 7.5 % after. There were no significant differences between the periods before and after. In an analysis assessing the overall linear time trend 2 of 21 regions showed a reduction in readmissions and 10 in length of stay.

Conclusions

After the introducing the CCA, no detectable impact was found on readmissions or mortality for heart failure patients, which is in line with previous studies such as those studying the US Hospital Readmission Reduction Program. While no overall association on length of stay could be identified, it was reduced in a number of the Swedish regions. The heterogeneity between regions could be used to understand the specific components needed to achieve reduction of readmissions in future studies.

Background

Nursing homes have limited capacity to provide medical care to clinically frail residents and therefore rely on transferring residents to hospital-based emergency departments when acute medical needs arise. The utilization of emergency department care varies between nursing homes but the extent of this variation is unexplored. Further, the effect of organizational characteristics of nursing homes on emergency department utilization is unknown. This study aims to characterize the variation in emergency department visit rates between nursing homes, and to identify contextual and organizational characteristics that contribute to this variation.

Study design

Population-based cohort study of individuals living in nursing homes during 2019 and 2020 in Sweden.

Methods

National registry data on nursing home residents were linked to nursing homes based on civil- and business registration addresses. Emergency department visits were identified for each resident in the national patient registry and measured as incidence rates per nursing home. Multi-level analysis was performed to investigate the association between emergency department visit rates, and contextual and organizational characteristics of nursing homes.

Results

The median incidence rate of emergency department visits from nursing homes was 5.2 per 100 person-months in 2019 (IQR = 3.7–6.9) and 4.4 per 100 person-months in 2020 (IQR = 3.0–5.7). Individuals living in nursing homes in the most rural locations had lower odds of emergency department visits (OR 0.51, 95% CI 0.41–0.61 versus the most urban locations). Moreover, individuals in nursing homes specialized in dementia care had lower odds of emergency department visits (OR 0.90, 95% CI 0.87–0.94 versus somatic care).

Conclusion

The results suggest that the location and organizational characteristics of nursing homes may have an impact on the utilization of medical services by the nursing home resident population. Further research is warranted to investigate any ensuing health inequities.

Background An increasing number of patients receive ambulance care without being conveyed to a definitive care provider. This process has been described as complex, challenging, and lacking in guideline support by EMS clinicians. The use of quality- and outcome measures among non-conveyed patients is an understudied phenomenon.Aim To identify current quality- and outcome measures for the general population of non-conveyed patients in order to describe major trends and knowledge gaps.Methods A scoping review of peer-reviewed original articles was conducted to identify quality- and outcome measures for non-conveyance within emergency medical services. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews statement (PRISMA-ScR) was followed. The PROSPERO and OSF database were checked for pending reviews or protocols. PubMed, CINAHL, Scopus, Web of Science and the Cochrane Library database were searched for relevant articles. Searches were performed in November 2023.Results Thirty-six studies fulfilled the inclusion criteria and were included in the review. Mortality was the most used outcome measure, reported in 24 (67%) of the articles. Emergency department attendance and hospital admission were the following most used outcome measures. Follow-up durations varied substantially between both measures and studies. Mortality rates were found to have the longest follow-up times, with a median follow-up duration a little bit over one week.Conclusions This scoping review shows that studies report a wide range of quality and outcome measures in the ambulance setting to measure non-conveyance. Reported quality and outcome measures were also heterogeneous with regard to their follow-up timeframe. The variety of approaches to evaluate non-conveyance poses challenges for future research and quality improvement. A more uniform approach to reporting and measuring non-conveyance is needed to enable comparisons between contexts and formal meta-analysis.

BACKGROUND: Ventilation during cardiopulmonary resuscitation (CPR) has long been a part of the standard treatment during cardiac arrests. Ventilation is usually given either during continuous chest compressions (CCC) or during a short pause after every 30 chest compressions (30:2). There is limited knowledge of how ventilation is delivered if it effects the hemodynamics and if it plays a role in the occurrence of lung injuries. The aim of this study was to compare ventilation parameters, hemodynamics, blood gases and lung injuries during experimental CPR given with CCC and 30:2 in a porcine model.

METHODS: Sixteen pigs weighing approximately 33 kg were randomized to either receive CPR with CCC or 30:2. Ventricular fibrillation was induced by passing an electrical current through the heart. CPR was started after 3 min and given for 20 min. Chest compressions were provided mechanically with a chest compression device and ventilations were delivered manually with a self-inflating bag and 12 l/min of oxygen. During the experiment, ventilation parameters and hemodynamics were sampled continuously, and arterial blood gases were taken every five minutes. After euthanasia and cessation of CPR, the lungs and heart were removed in block and visually examined followed by sampling of lung tissue which were examined using microscopy.

RESULTS: In the CCC group and the 30:2 group, peak inspiratory pressure (PIP) was 58.6 and 35.1 cmH₂O (p < 0.001), minute volume (MV) 2189.6 and 1267.1 ml (p < 0.001), peak expired carbon dioxide (PECO₂) 28.6 and 39.4 mmHg (p = 0.020), partial pressure of carbon dioxide (PaCO₂) 50.2 and 61.1 mmHg (p = 0.013) and pH 7.3 and 7.2 (p = 0.029), respectively. Central venous pressure (CVP) decreased more over time in the 30:2 group (p = 0.023). All lungs were injured, but there were no differences between the groups.

CONCLUSIONS: Ventilation during CCC resulted in a higher PIP, MV and pH and lower PECO₂ and PaCO₂, showing that ventilation mode during CPR can affect ventilation parameters and blood gases.

Carcinoembryonic antigen (CEA) has emerged as an attractive target for theranostic applications in colorectal cancers (CRCs). In the present study, the humanized anti-CEA antibody hT84.66-M5A (M5A) was labeled with ¹⁷⁷Lu for potential CRC therapy. Moreover, the novel combination of ¹⁷⁷Lu-DOTA-M5A with the heat shock protein 90 inhibitor onalespib, suggested to mediate radiosensitizing properties, was assessed in vivo for the first time. M5A antibody uptake and therapeutic effects, alone or in combination with onalespib, were assessed in human CRC xenografts and visualized using SPECT/CT imaging. Although both ¹⁷⁷Lu-DOTA-M5A and onalespib monotherapies effectively reduced tumor growth rates, the combination therapy demonstrated the most substantial impact, achieving a fourfold reduction in tumor growth compared to the control group. Median survival increased by 33% compared to ¹⁷⁷Lu-DOTA-M5A alone, and tripled compared to control and onalespib groups. Importantly, combination therapy yielded comparable or superior effects to the double dose of ¹⁷⁷Lu-DOTA-M5A monotherapy. ¹⁷⁷Lu-DOTA-M5A increased apoptotic cell levels, indicating its potential to induce tumor cell death. These findings show promise for ¹⁷⁷Lu-DOTA-M5A as a CRC therapeutic agent, and its combination with onalespib could significantly enhance treatment efficacy. Further in vivo studies are warranted to validate these findings fully and explore the treatment’s potential for clinical use.

Simple summary

Cancer treatment is hampered by the limitations of individual therapy modalities and the intricate nature of the disease. The administration of maximal monotherapy doses often leads to undesirable side effects and/or therapy resistance. As a result, there is a growing recognition of the importance of investigating combination therapy to effectively address these obstacles. In the present in vivo study, the therapeutic effects of combination therapy with the heat shock protein 90 inhibitor onalespib, a potential radiosensitizer, and ¹⁷⁷Lu-DOTA-M5A for colorectal cancer (CRC) treatment were explored for the first time. The results demonstrated that the combination treatment was so effective that retained or even superior therapeutic effects could be achieved with only half the dose of administered ¹⁷⁷Lu-DOTA-M5A, showing enhanced tumor growth suppression and increased apoptosis. Consequently, the combination therapy involving ¹⁷⁷Lu-DOTA-M5A and onalespib constitutes a promising approach for treating metastatic CRCs. By enhancing therapeutic effects, minimizing therapy resistance, and reducing side effects, this approach has the potential to expand the patient population that can benefit from targeted treatment.