Automated and app-based activation of first responders for prehospital cardiac arrest: an analysis of 16.500 activations of the KATRETTER system in Berlin

BACKGROUND

Bystander CPR is one of the main independent factors contributing to better survival after out-of-hospital cardiac arrest. Simultaneously, the rate of bystander CPR in Germany is below the European average. First responder applications (apps) contribute to reducing the time period without CPR (no-flow time) until professional help can arrive on-scene.

METHODS

The KATRETTER app was introduced in Berlin as one of the first apps in Europe which do not require any medical qualifications to register as a first responder. The activation of volunteer first responders for suspected cardiac arrest cases through the Berlin Emergency Medical Services integrated control center was evaluated based on data collected between 16 Oct 2020 and 16 Oct 2022. Our descriptive analysis includes the number of registered first responders, number of activations, the number and percentages of accepted activations, as well as all reports where first responders arrived at the scene.

RESULTS

As of 15 Oct 2022, a total of 10,102 first responders were registered in the state of Berlin. During this specified period, there were 16.505 activations of the system for suspected out-of-hospital cardiac arrest. In 38.4% of the accepted cases, first responders documented patient contact, and in 34.6% of cases with patient contact, CPR was performed. Only 2% of registered first responders did not have any medical qualifications.

CONCLUSIONS

Smartphone-based first responder applications should not be understood as a means of alerting professional help, but rather like a digitally amplified "call for help" in the vicinity of an emergency location. A large number of first responders can be recruited within 24 months, without large-scale public relations work necessary. No qualifications were required to become a first responder, contributing to a low-threshold registration process with the effect of a more widespread distribution of the app and cost reduction during implementation.

[Prehospital perimortem cesarean section during cardiopulmonary resuscitation for traumatic cardiac arrest : Case report and lessons learned]

The following case report discusses the resuscitation of a pregnant woman in traumatic cardiac arrest after a fall from a height with consecutive resuscitative hysterotomy for maternal and fetal salvage. The report illustrates all lessons learned from critical appraisal amid new guideline recommendations and gives an overview of the published literature on the matter. Despite extensive resuscitation efforts, ultimately both the mother and the newborn were pronounced life extinct at the scene. Prehospital treatment of (traumatic) cardiac arrest in a pregnant patient as well as performing a perimortem cesarean section remain infrequent but challenging scenarios.

Präklinische Notfallthorakotomie in der Berliner Notfallrettung – Darstellung der Umsetzung im Land Berlin und Diskussion erster Erkenntnisse

Im Jahr 2015 fand das Thema „traumatisch bedingter Herz-Kreislauf-Stillstand“ erstmalig Einzug in die aktualisierten Reanimationsleitlinien des European Resuscitation Council. Neben dem speziell anzuwendenden Maßnahmenbündel mit Atemwegsmanagement, Therapie der Hypovolämie, externer Blutungskontrolle und beidseitiger Thoraxentlastung sollte auch eine Notfallthorakotomie bei geeigneten Patienten erwogen werden. Um dieses Vorgehen systematisch in der Berliner Notfallrettung zu etablieren und standardisieren, hat die Ärztliche Leitung Rettungsdienst der Berliner Feuerwehr verschiedene Maßnahmen unternommen, um die optimale Ausnutzung der Schlüsselfaktoren Expertise, „elapsed time“, Equipment und „environment“ sicherzustellen. Dabei konnten im Laufe der ersten 2,5 Jahre auch bereits wichtige Erfahrungen aus der neuen Versorgungsstruktur dieser schwerstverletzten Patienten gewonnen werden.

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scores

The implementation of Artificial Intelligence (AI) still faces significant hurdles and one key factor is the access to data. One approach that could support that is federated machine learning (FL) since it allows for privacy preserving data access. For this proof of concept, a prediction model for coronary artery calcification scores (CACS) has been applied. The FL was trained based on the data in the different institutions, while the centralized machine learning model was trained on one allocation of data. Both algorithms predict patients with risk scores ≥5 based on age, biological sex, waist circumference, dyslipidemia and HbA1c. The centralized model yields a sensitivity of c. 66% and a specificity of c. 70%. The FL slightly outperforms that with a sensitivity of 67% while slightly underperforming it with a specificity of 69%. It could be demonstrated that CACS prediction is feasible via both, a centralized and an FL approach, and that both show very comparable accuracy. In order to increase accuracy, additional and a higher volume of patient data is required and for that FL is utterly necessary. The developed "CACulator" serves as proof of concept, is available as research tool and shall support future research to facilitate AI implementation.

263 INFORMING INTERVENTION DESIGN IN COGNITIVELY IMPAIRED POPULATIONS: LESSONS LEARNED FROM THE OPTIMIZE DEPRESCRIBING INTERVENTION

Background

Polypharmacy is common in older adults with cognitive impairment and multiple chronic conditions increasing their risks of adverse drug events, hospitalization, further cognitive decline and death and leading to higher health care costs. Deprescribing, the process of reducing or stopping potentially inappropriate medications may improve outcomes. The OPTIMIZE trial examined whether educating and activating patients, family and clinicians about deprescribing reduces number of medications for older adults with cognitive impairment and multiple chronic conditions. Acceptability and challenges of intervention delivery in this vulnerable population are not well understood.

Methods

We explored mechanisms of intervention effectiveness through post hoc qualitative interviews and surveys with 15 patients, 7 family caregivers, and 28 clinicians. We assessed accessibility and delivery of materials as well as the ability of the materials to facilitate conversations and influence decisions around deprescribing.

Results

Acceptance of the intervention was affected by contextual factors including cognition and prior knowledge of deprescribing. Positive effects of the intervention included patients scheduling specific appointments to discuss deprescribing and providers being prompted to consider deprescribing. Recollection of intervention materials by patients was inconsistent but highest shortly after intervention delivery. Short clinic visit times remained the largest clinician barrier to deprescribing.

Conclusion

Our work identifies key learnings in intervention roll out which can guide future scaling of our intervention and other pragmatic deprescribing intervention studies in patients with cognitive impairment. We highlight the critical roles of both timing and repetition in intervention delivery to cognitively impaired populations as well as the barrier to deprescribing posed by short clinic consultation time. Our success in activating deprescribing conversations in this population highlights the need to incentivize medical professionals and health systems to incorporate deprescribing into routine clinical practice and expand proven interventions to other vulnerable populations.

Forecasting admissions in psychiatric hospitals before and during Covid-19: a retrospective study with routine data

The COVID-19 pandemic has strong effects on most health care systems. Forecasting of admissions can help for the efficient organisation of hospital care. We aimed to forecast the number of admissions to psychiatric hospitals before and during the COVID-19 pandemic and we compared the performance of machine learning models and time series models. This would eventually allow to support timely resource allocation for optimal treatment of patients. We used admission data from 9 psychiatric hospitals in Germany between 2017 and 2020. We compared machine learning models with time series models in weekly, monthly and yearly forecasting before and during the COVID-19 pandemic. A total of 90,686 admissions were analysed. The models explained up to 90% of variance in hospital admissions in 2019 and 75% in 2020 with the effects of the COVID-19 pandemic. The best models substantially outperformed a one-step seasonal naïve forecast (seasonal mean absolute scaled error (sMASE) 2019: 0.59, 2020: 0.76). The best model in 2019 was a machine learning model (elastic net, mean absolute error (MAE): 7.25). The best model in 2020 was a time series model (exponential smoothing state space model with Box-Cox transformation, ARMA errors and trend and seasonal components, MAE: 10.44). Models forecasting admissions one week in advance did not perform better than monthly and yearly models in 2019 but they did in 2020. The most important features for the machine learning models were calendrical variables. Model performance did not vary much between different modelling approaches before the COVID-19 pandemic and established forecasts were substantially better than one-step seasonal naïve forecasts. However, weekly time series models adjusted quicker to the COVID-19 related shock effects. In practice, multiple individual forecast horizons could be used simultaneously, such as a yearly model to achieve early forecasts for a long planning period and weekly models to adjust quicker to sudden changes.

[Quo vadis joint emergency dispatch system?]

The call volume in emergency medical service (EMS) dispatch centers has seen a drastic increase for many years now, especially looking at urban regions of Germany. In this context, the control mechanisms of the EMS dispatch center can be utilized to break new ground regarding the handling of emergency calls and dispatch practice in order to manage incoming calls as efficiently as possible. This article clearly explains standardized protocol-based emergency medical call taking, internal structuring of control centers and pathways, also during the COVID-19 pandemic, using the Berlin EMS dispatch center as an example. The terms structured and standardized protocol-based emergency medical call taking should be differentiated, whereby the standardized call taking process is more binding and based on international standards with high reliability. Quality management measures ensure that the protocol is applied in accordance with the regulations. Improved collaboration and automated transfer of data between EMS dispatch centers and the control centers for non-life-threatening physician on-call services enable low-priority calls to be forwarded on a regular basis. Interprofessional teams in EMS can improve the care of specific patient groups in a targeted manner and avoid transport to emergency departments. Standardized protocol-based and software-based emergency call taking currently represents best practice according to medical science, supporting a nationwide implementation. Furthermore, an intensive collaboration between EMS control centers and control centers for non-life-threatening physician on-call services is recommended as well as the introduction of specialized EMS resources and app-based alerting of first responders.

Success Factors of Artificial Intelligence Implementation in Healthcare

Background: Artificial Intelligence (AI) in healthcare has demonstrated high efficiency in academic research, while only few, and predominantly small, real-world AI applications exist in the preventive, diagnostic and therapeutic contexts. Our identification and analysis of success factors for the implementation of AI aims to close the gap between recent years' significant academic AI advancements and the comparably low level of practical application in healthcare. Methods: A literature and real life cases analysis was conducted in Scopus and OpacPlus as well as the Google advanced search database. The according search queries have been defined based on success factor categories for AI implementation derived from a prior World Health Organization survey about barriers of adoption of Big Data within 125 countries. The eligible publications and real life cases were identified through a catalog of in- and exclusion criteria focused on concrete AI application cases. These were then analyzed to deduct and discuss success factors that facilitate or inhibit a broad-scale implementation of AI in healthcare. Results: The analysis revealed three categories of success factors, namely (1) policy setting, (2) technological implementation, and (3) medical and economic impact measurement. For each of them a set of recommendations has been deducted: First, a risk adjusted policy frame is required that distinguishes between precautionary and permissionless principles, and differentiates among accountability, liability, and culpability. Second, a "privacy by design" centered technology infrastructure shall be applied that enables practical and legally compliant data access. Third, the medical and economic impact need to be quantified, e.g., through the measurement of quality-adjusted life years while applying the CHEERS and PRISMA reporting criteria. Conclusions: Private and public institutions can already today leverage AI implementation based on the identified results and thus drive the translation from scientific development to real world application. Additional success factors could include trust-building measures, data categorization guidelines, and risk level assessments and as the success factors are interlinked, future research should elaborate on their optimal interaction to utilize the full potential of AI in real world application.

228 Outcomes of Gallstone Complications During the COVID Pandemic

Background

The Intercollegiate General Surgery Guidance on COVID-19 recommended either non-surgical management or cholecystostomy drains for the management of acute biliary disease replacing gold standard practice of early laparoscopic cholecystectomy within 1 week of index admission with drainage reserved for high-risk patients where surgery is not appropriate.

Method

This is the retrospective study presenting the impact of gallstone disease in our unit during five months of the COVID- 19 pandemic (March 2020-August 2020) compared with the equivalent period in 2019.

Results

Patients presenting to the HPB unit with a coded diagnosis of gallstones were included and during the study period 1447 patients presented compared with 1413 in 2019. In 2020 compared with 2019 there was a significant decrease in patients presenting with cholecystitis (240 vs 313; p = 0.031) but no significant difference in patients presenting due to gallbladder perforation (44 vs 51). Interestingly the numbers of cholecystostomies were comparable, with 11 in 2020 and 15 in 2019 representing significantly less than the 7.2% figure published by Peckham-Cooper et al.

Conclusions

In our study there was a decrease in patients with cholecystitis and perforation and there was an increase in patients with gallstone pancreatitis, increase waiting lists with increase in the incidence of serious complications. In our trust we currently have 656 patients awaiting cholecystectomy compared to 280 in august 2019. With the recent elevation of the alert level to 4 and increased government restrictions, a consistent National approach is required to mitigate these risks.

[Prioritization of intensive medical treatment places - Concept proposal]

In the situation of a shortage of ventilation beds, ethically justifiable, transparent and comprehensible decisions must be made. This concept proposes that all patients are first intubated depending on necessity and then assessed by a triage team afterwards. In this situation newly admitted COVID patients compete with newly admitted Non-COVID patients as well as patients already treated in intensive care units for a ventilator. The combination of short-term and long-term prognoses should enable the interprofessional triage team to make comprehensible decisions. The aim of the prioritization concept is to save as many human lives as possible and to relieve the treatment team of the difficult decision on prioritization.

Outcomes of gallstone complications during the COVID pandemic

As data and metadata from the SARS-CoV-2 pandemic mature, the true impact on non-cancer, non-emergency surgical practice is becoming apparent. The authors present data on the impact of gallstone disease in their unit during 5 months of the COVID-19 pandemic (March 2020 to August 2020) compared with the equivalent period in 2019. Although the total number of patients presenting with gallstone disease was comparable, there was a decrease in patients with cholecystitis and perforation (although it is possibly too early for these to have presented), and there was a small but worrying increase in patients with gallstone pancreatitis. With the recent increase in alert level to 4 and increased government restrictions in an attempt to avoid a second national lockdown, a consistent national approach is required to mitigate these risks.

Predicting the risk of drug-drug interactions in psychiatric hospitals

Introduction

The most common medical decision is the prescription of medicines. More than 130 different drugs with proven efficacy are currently available for the treatment of patients with mental disorders.

Objectives

The aim was to use routine data available at a patient’s admission to the hospital to predict polypharmacy and drug-drug interactions (DDI).

Methods

The study used data obtained from a large clinical pharmacovigilance study sponsored by the Innovations Funds of the German Federal Joint Committee. It included all inpatient episodes admitted to eight psychiatric hospitals in Hesse, Germany, over two years. We used gradient boosting to predict respective outcomes. We tested the performance of our final models in unseen patients from another calendar year and separated the study sites used for training from the study sites used for performance testing.

Results

A total of 53,909 episodes were included in the study. The models’ performance, as measured by the area under the ROC, was “excellent” (0.83) and “acceptable” (0.72) compared to common benchmarks for the prediction of polypharmacy and DDI, respectively. Both models were substantially better than a naive prediction based solely on basic diagnostic grouping.

Conclusions

This study has shown that polypharmacy and DDI at a psychiatric hospital can be predicted from routine data at patient admission. These predictions could support an efficient management of benefits and risks of hospital prescriptions, for instance by including pharmaceutical supervision early after admission for patients at risk before pharmacological treatment is established

Disclosure

This work was supported by the Innovations Funds of the German Federal Joint Committee (grant number: 01VSF16009). The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscrip

The Economic Impact of Artificial Intelligence in Health Care: Systematic Review

Background

Positive economic impact is a key decision factor in making the case for or against investing in an artificial intelligence (AI) solution in the health care industry. It is most relevant for the care provider and insurer as well as for the pharmaceutical and medical technology sectors. Although the broad economic impact of digital health solutions in general has been assessed many times in literature and the benefit for patients and society has also been analyzed, the specific economic impact of AI in health care has been addressed only sporadically.

Objective

This study aimed to systematically review and summarize the cost-effectiveness studies dedicated to AI in health care and to assess whether they meet the established quality criteria.

Methods

In a first step, the quality criteria for economic impact studies were defined based on the established and adapted criteria schemes for cost impact assessments. In a second step, a systematic literature review based on qualitative and quantitative inclusion and exclusion criteria was conducted to identify relevant publications for an in-depth analysis of the economic impact assessment. In a final step, the quality of the identified economic impact studies was evaluated based on the defined quality criteria for cost-effectiveness studies.

Results

Very few publications have thoroughly addressed the economic impact assessment, and the economic assessment quality of the reviewed publications on AI shows severe methodological deficits. Only 6 out of 66 publications could be included in the second step of the analysis based on the inclusion criteria. Out of these 6 studies, none comprised a methodologically complete cost impact analysis. There are two areas for improvement in future studies. First, the initial investment and operational costs for the AI infrastructure and service need to be included. Second, alternatives to achieve similar impact must be evaluated to provide a comprehensive comparison.

Conclusions

This systematic literature analysis proved that the existing impact assessments show methodological deficits and that upcoming evaluations require more comprehensive economic analyses to enable economic decisions for or against implementing AI technology in health care.

Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach

BACKGROUND

A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects relevant to the organization of psychiatric hospital care. A further aim was to compare the results of a machine learning approach with those obtained through a traditional method and those obtained through a naive baseline classifier.

METHODS

The study included consecutively discharged patients between 1st of January 2017 and 31st of December 2018 from nine psychiatric hospitals in Hesse, Germany. We compared the predictive performance achieved by stochastic gradient boosting (GBM) with multiple logistic regression and a naive baseline classifier. We tested the performance of our final models on unseen patients from another calendar year and from different hospitals.

RESULTS

The study included 45,388 inpatient episodes. The models' performance, as measured by the area under the Receiver Operating Characteristic curve, varied strongly between the predicted outcomes, with relatively high performance in the prediction of coercive treatment (area under the curve: 0.83) and 1:1 observations (0.80) and relatively poor performance in the prediction of short length of stay (0.69) and non-response to treatment (0.65). The GBM performed slightly better than logistic regression. Both approaches were substantially better than a naive prediction based solely on basic diagnostic grouping.

CONCLUSION

The present study has shown that administrative routine data can be used to predict aspects relevant to the organisation of psychiatric hospital care. Future research should investigate the predictive performance that is necessary to provide effective assistance in clinical practice for the benefit of both staff and patients.

Tooth loss in Sjögren's syndrome patients compared to age and gender matched controls

BACKGROUND

To analyze the prevalence and location of tooth loss in Sjögren's syndrome (SS) patients and compare them with an age- and gender-matched control group.

MATERIAL AND METHODS

Dental charts and x-rays of 108 (SS) patients were retrieved from an academic dental center and special care dentistry department. For each SS patient, an age- and gender-matched non-SS patient was randomly selected. Medication, number of extractions and date and location of extractions were assessed. Differences between SS and non-SS patients were analyzed using Mann-Whitney U tests, Chi-square tests and Fisher's exact tests.

RESULTS

Significantly more SS patients were edentulous compared to the non-SS group (14.8% versus 1.9%, p = 0.001). SS patients had a 61% higher risk to have experienced one or more extractions than control patients. In the SS group, there was a non-significant tendency for more maxillary teeth to have been extracted than mandibular teeth (42:34). In the control group, the number of extractions in the maxilla and mandible were comparable (21:20). When divided into sextants, the number of SS patients with one or more extractions was significantly higher than for non-SS patients for each sextant (p = 0.001 to p = 0.032). The largest difference in the proportion of patients with one or more extractions between the SS and non-SS patients occurred in the upper anterior sextant (3.4 times more frequent).

CONCLUSIONS

SS patients are more prone to experience dental extractions compared to patients without SS. It could be speculated that this is related to a decreased salivary secretion.

The Epidemiology, treatment, and complication of ameloblastoma in East-Indonesia: 6 years retrospective study

Background

Ameloblastoma is a neoplasm classified as a benign epithelial odontogenic tumor of the jaws, grow slowly and are locally invasive. The aim of the present study was to investigate the incidence, treatment, and complication of patients with ameloblastoma in East-Indonesia during six years retrospective study.

Material and Methods

This retrospective study included 84 patients who were diagnosed with ameloblastoma from 2011 to 2016. There were 56 patients with treatment data available. Data from each patient, including gender, age, histologic type, the size of the tumor, radiologic form, tumor location, type of treatment, and complication were reviewed and analyzed retrospectively.

Results

Fourteen patients were diagnosed with unicystic ameloblastoma (25%), thirty two patients with multicystic follicular ameloblastoma (57%) and ten patients with an unspecified multicystic ameloblastoma (18%). A total of about 35 patients were treated conservatively (62.5%) and 21 patients were treated radically (37.5%). Swelling was present as a pre-operative complication in all 56 cases (100%). There were no complaints concerning speech.

Conclusions

The majority findings of the histologic type were multicystic ameloblastoma and their location were in the mandible. Most ameloblastoma were treated conservatively and reconstructions were made with only titanium plates and not bone graft.

Key words:Ameloblastoma, epidemiology, east Indonesia.

FBXO10 deficiency and BTK activation upregulate BCL2 expression in mantle cell lymphoma

Targeting Bruton tyrosine kinase (BTK) by ibrutinib is an effective treatment for patients with relapsed/refractory mantle cell lymphoma (MCL). However, both primary and acquired resistance to ibrutinib have developed in a significant number of these patients. A combinatory strategy targeting multiple oncogenic pathways is critical to enhance the efficacy of ibrutinib. Here, we focus on the BCL2 anti-apoptotic pathway. In a tissue microarray of 62 MCL samples, BCL2 expression positively correlated with BTK expression. Increased levels of BCL2 were shown to be due to a defect in protein degradation because of no or little expression of the E3 ubiquitin ligase FBXO10, as well as transcriptional upregulation through BTK-mediated canonical nuclear factor-κB activation. RNA-seq analysis confirmed that a set of anti-apoptotic genes (for example, BCL2, BCL-XL and DAD1) was downregulated by BTK short hairpin RNA. The downregulated genes also included those that are critical for B-cell growth and proliferation, such as BCL6, MYC, PIK3CA and BAFF-R. Targeting BCL2 by the specific inhibitor ABT-199 synergized with ibrutinib in inhibiting growth of both ibrutinib-sensitive and -resistant cancer cells in vitro and in vivo. These results suggest co-targeting of BTK and BCL2 as a new therapeutic strategy in MCL, especially for patients with primary resistance to ibrutinib.

[Resource use and financing of guideline-adherent psychotherapeutic inpatient care]

BACKGROUND

The financing of psychiatric psychotherapeutic care in Germany is determined by the German psychiatric staffing regulations which are unchanged since 1991. Psychotherapy was established after 1991 as an effective and indispensable treatment of mental and behavioral disorders.

AIMS AND OBJECTIVES

The aim of this study was to empirically investigate the use of psychiatrists' and psychologists' working time for psychotherapy in guideline-adherent hospital care. A further aim was to compare these results to the resources defined by the German psychiatric staffing regulations and in the new prospective payment system for psychiatry and psychosomatics in Germany.

MATERIAL AND METHODS

University hospitals for psychiatry and psychotherapy were asked to retrospectively provide data of patients for which guideline-adherent care was possible. Participating institutions provided both data describing the staff time utilization of psychotherapeutic services provided by psychiatrists and psychologists and patient classifications according to the German psychiatric staffing regulations and the new prospective payment system for psychiatry and psychosomatics.

RESULTS

Resources defined by the German psychiatric staffing regulations covered a mean of only 71 min of psychotherapy per patient and week while the actual mean intensity of psychotherapeutic care provided by the participating hospitals was 194 min per patient and week. The associated use of staff time was 102 min per patient and week. Both figures increased during an inpatient episode. The resources defined by the German psychiatric staffing regulations covered only 70 % of medical and psychological personnel. The current configuration of the new prospective payment system for psychiatry and psychosomatics covered only 59 % of staff time.

CONCLUSION

The results of this study provide another unambiguous recommendation to adjust the out-dated German psychiatric staffing regulations to the current evidence and S3 guidelines for psychiatric psychotherapeutic hospital care. In particular, more resources are required for the provision of psychotherapeutic care.

3D Orbital Reconstruction in a Patient with Microphthalmos and a Large Orbital Cyst-A Case Report

BACKGROUND

Orbital cysts are rare developmental anomalies that can occur in microphthalmic and anophthalmic patients. Such cysts can promote orbital growth and subsequently markedly increase the size of the orbit, which is commonly underdeveloped in these patients. Cyst removal is therefore generally dissuaded (at least) in the first 5 years.

CLINICAL CASE

A 6-year-old boy with a microphthalmos and a cyst developed protrusion of his prosthetic eye and a swelling of the lower eyelid. MRI showed a large cyst causing distortion of the right orbit. Due to the expansive orbital growth and subsequent misfitting of the prosthesis, cystectomy and orbital floor reconstruction was performed using 3D technology.

CONCLUSION

3D imaging and printing enables exact delineation of orbital cysts and the adjacent bony structures. Furthermore it offers the possibility to plan an individual surgical approach and to design and fabricate a custom fit orbital floor implant.

Cost drivers of inpatient mental health care: a systematic review

Aims. New reimbursement schemes for inpatient mental health care are imminent in the UK and Germany. The shared intention is to reflect cost differences between patients in reimbursement rates. This requires understanding of patient characteristics that influence hospital resource use. The aim of this review was to show which associations between mental health care per diem hospital costs and patient characteristics are supported by current evidence. Methods. A systematic review of the literature published between 1980 and 2012 was carried out. The search strategy included electronic databases and hand-searching. Furthermore, reference lists, citing articles and related publications were screened and experts were contacted. Results. The search found eight studies. Dispersion in per diem costs was moderate, as was the ability to explain it with patient characteristics. Six patient characteristics were identified as the most relevant variables. These were (1) age, (2) major diagnostic group, (3) risk, (4) legal problems, (5) the ability to perform activities of daily living and (6) presence of psychotic or affective symptoms. Two non-patient-related factors were identified. These were (1) day of stay and (2) treatment site. Conclusions. Idiosyncrasies of mental health care complicated the prediction of per diem hospital costs. More research is required in European settings since transferability of results is unlikely.

Effective dose assessment in the maxillofacial region using thermoluminescent (TLD) and metal oxide semiconductor field-effect transistor (MOSFET) dosemeters: a comparative study

OBJECTIVES

The objective of this study was to compare the performance of metal oxide semiconductor field-effect transistor (MOSFET) technology dosemeters with thermoluminescent dosemeters (TLDs) (TLD 100; Thermo Fisher Scientific, Waltham, MA) in the maxillofacial area.

METHODS

Organ and effective dose measurements were performed using 40 TLD and 20 MOSFET dosemeters that were alternately placed in 20 different locations in 1 anthropomorphic RANDO(®) head phantom (the Phantom Laboratory, Salem, NY). The phantom was exposed to four different CBCT default maxillofacial protocols using small (4 × 5 cm) to full face (20 × 17 cm) fields of view (FOVs).

RESULTS

The TLD effective doses ranged between 7.0 and 158.0 µSv and the MOSFET doses between 6.1 and 175.0 µSv. The MOSFET and TLD effective doses acquired using four different (FOV) protocols were as follows: face maxillofacial (FOV 20 × 17 cm) (MOSFET, 83.4 µSv; TLD, 87.6 µSv; -5%); teeth, upper jaw (FOV, 8.5 × 5.0 cm) (MOSFET, 6.1 µSv; TLD, 7.0 µSv; -14%); tooth, mandible and left molar (FOV, 4 × 5 cm) (MOSFET, 10.3 µSv; TLD, 12.3 µSv; -16%) and teeth, both jaws (FOV, 10 × 10 cm) (MOSFET, 175 µSv; TLD, 158 µSv; +11%). The largest variation in organ and effective dose was recorded in the small FOV protocols.

CONCLUSIONS

Taking into account the uncertainties of both measurement methods and the results of the statistical analysis, the effective doses acquired using MOSFET dosemeters were found to be in good agreement with those obtained using TLD dosemeters. The MOSFET dosemeters constitute a feasible alternative for TLDs for the effective dose assessment of CBCT devices in the maxillofacial region.

[Value of intermittent androgen deprivation in the context of the current data situation]

Androgen deprivation therapy is an integral part of the treatment of advanced and progressive prostate cancer. Various prospective randomised trials have investigated whether or not temporary suspension of androgen deprivation might delay the emergence of castration resistant prostate cancer and concomitantly improve quality of life. Until now, no phase III trial has been able to prove that intermittent androgen deprivation might delay the development of castration resistant tumours. Data from previous trials, except for one study, did at least not show adverse effects on survival. Data on quality of life are inconsistent, showing a trend towards improved quality of life with IAD. German as well as European guidelines reflect IAD as an established constituent of day-to-day medical practice. This review is intended to provide a code of practice for an individualised treatment as based on recently published studies.

Assessment of radiation exposure in dental cone-beam computerized tomography with the use of metal-oxide semiconductor field-effect transistor (MOSFET) dosimeters and Monte Carlo simulations

OBJECTIVES

The aims of this study were to assess the organ and effective dose (International Commission on Radiological Protection (ICRP) 103) resulting from dental cone-beam computerized tomography (CBCT) imaging using a novel metal-oxide semiconductor field-effect transistor (MOSFET) dosimeter device, and to assess the reliability of the MOSFET measurements by comparing the results with Monte Carlo PCXMC simulations.

STUDY DESIGN

Organ dose measurements were performed using 20 MOSFET dosimeters that were embedded in the 8 most radiosensitive organs in the maxillofacial and neck area. The dose-area product (DAP) values attained from CBCT scans were used for PCXMC simulations. The acquired MOSFET doses were then compared with the Monte Carlo simulations.

RESULTS

The effective dose measurements using MOSFET dosimeters yielded, using 0.5-cm steps, a value of 153 μSv and the PCXMC simulations resulted in a value of 136 μSv.

CONCLUSIONS

The MOSFET dosimeters placed in a head phantom gave results similar to Monte Carlo simulations. Minor vertical changes in the positioning of the phantom had a substantial affect on the overall effective dose. Therefore, the MOSFET dosimeters constitute a feasible method for dose assessment of CBCT units in the maxillofacial region.