Incidence and predictors of thermal oesophageal and vagus nerve injuries in Ablation Index-guided high-power-short-duration ablation of atrial fibrillation: a prospective study

AIMS

High-power-short-duration (HPSD) ablation is an effective treatment for atrial fibrillation but poses risks of thermal injuries to the oesophagus and vagus nerve. This study aims to investigate incidence and predictors of thermal injuries, employing machine learning.

METHODS AND RESULTS

A prospective observational study was conducted at Leipzig Heart Centre, Germany, excluding patients with multiple prior ablations. All patients received Ablation Index-guided HPSD ablation and subsequent oesophagogastroduodenoscopy. A machine learning algorithm categorized ablation points by atrial location and analysed ablation data, including Ablation Index, focusing on the posterior wall. The study is registered in clinicaltrials.gov (NCT05709756). Between February 2021 and August 2023, 238 patients were enrolled, of whom 18 (7.6%; nine oesophagus, eight vagus nerve, one both) developed thermal injuries, including eight oesophageal erythemata, two ulcers, and no fistula. Higher mean force (15.8 ± 3.9 g vs. 13.6 ± 3.9 g, P = 0.022), ablation point quantity (61.50 ± 20.45 vs. 48.16 ± 19.60, P = 0.007), and total and maximum Ablation Index (24 114 ± 8765 vs. 18 894 ± 7863, P = 0.008; 499 ± 95 vs. 473 ± 44, P = 0.04, respectively) at the posterior wall, but not oesophagus location, correlated significantly with thermal injury occurrence. Patients with thermal injuries had significantly lower distances between left atrium and oesophagus (3.0 ± 1.5 mm vs. 4.4 ± 2.1 mm, P = 0.012) and smaller atrial surface areas (24.9 ± 6.5 cm2 vs. 29.5 ± 7.5 cm2, P = 0.032).

CONCLUSION

The low thermal lesion's rate (7.6%) during Ablation Index-guided HPSD ablation for atrial fibrillation is noteworthy. Machine learning based ablation data analysis identified several potential predictors of thermal injuries. The correlation between machine learning output and injury development suggests the potential for a clinical tool to enhance procedural safety.

Biomechanical performance of dental implants inserted in different mandible locations and at different angles: A finite element study

STATEMENT OF PROBLEM

Accurate implant placement is essential for the success of dental implants. This placement influences osseointegration and occlusal forces. The freehand technique, despite its cost-effectiveness and time efficiency, may result in significant angular deviations compared with guided implantation, but the effect of angular deviations on the stress-strain state of peri-implant bone is unclear.

PURPOSE

The purpose of this finite element analysis (FEA) study was to examine the effects of angular deviations on stress-strain states in peri-implant bone.

MATERIAL AND METHODS

Computational modeling was used to investigate 4 different configurations of dental implant positions, each with 3 angles of insertion. The model was developed using computed tomography images, and typical mastication forces were considered. Strains were analyzed using the mechanostat hypothesis.

RESULTS

The location of the implant had a significant impact on bone strain intensity. An angular deviation of ±5 degrees from the planned inclination did not significantly affect cancellous bone strains, which primarily support the implant. However, it had a substantial effect on strains in the cortical bone near the implant. Such deviations also significantly influenced implant stresses, especially when the support from the cortical bone was uneven or poorly localized.

CONCLUSIONS

In extreme situations, angular deviations can lead to overstraining the cortical bone, risking implant failure from unfavorable interaction with the implant. Accurate implant placement is essential to mitigate these risks.

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.

Dental students' attitudes on cardiopulmonary resuscitation training via virtual reality: an exploratory study

Purpose Resuscitation guidelines have advocated the use of virtual learning as a form of pre-course e-learning. Virtual reality (VR) has been identified to provide a method of constructive learning with instant feedback. There are increasing publications of VR use in cardiopulmonary resuscitation (CPR) training; however, there is a dearth from the dental profession. Therefore, the aim of this exploratory study was to investigate dental students' opinions in CPR training using VR.Methods In total, 120 dental students undertook both conventional (manikin) and VR CPR training in a cross-over design. The VR scenario was in a hospital setting. Following, students completed a questionnaire evaluating their experiences.Results The majority of students (n = 88) reported that this was the first time that they had utilised VR. The experience of using VR in CPR training was rated as very good. Most students felt that the inclusion of VR in CPR training created a better learning experience and had a high learning potential. However, the hospital setting was not entirely relevant.Conclusion Dental students recommended that VR CPR training should be used as an adjunct to conventional training in dental education, but the VR scenario would benefit being a virtual dental environment.

How to measure staff continuity in intensive psychiatric home treatment: a routine data and single case analysis

Background

Intensive forms of outreach mental health care (IOC) such as crisis resolution or home treatment teams are increasingly implemented as alternatives to inpatient admission, providing recovery-oriented treatment at home at comparable costs and outcomes. However, one issue with IOC is the lack of continuity regarding staff members who provide home visits, complicating relationship building and meaningful therapeutic exchange. The aim of this study is to validate existing primarily qualitative findings using performance data and to explore a possible correlation between the number of staff involved within IOC treatment and the service users' length of stay (LOS).

Methods

Routine data from an IOC team in a catchment area in Eastern Germany were analyzed. Basic parameters of service delivery were calculated and an in-depth descriptive analysis regarding staff continuity was performed. Further, an exploratory single case analysis was conducted, presenting the exact sequence of all treatment contacts for one case with low and one with high staff continuity.

Results

We analyzed 10.598 face-to-face treatment contacts based on 178 IOC users. The mean LOS was 30.99 days. About 75% of all home visits were conducted by two or more staff members simultaneously. Service users saw an average of 10.24 different staff per treatment episode. On 11% of the care days, only unknown staff, and on 34% of the care days at least one unknown staff member conducted the home visit. 83% of the contacts were performed by the same three staff members and 51% were made by one and the same staff member. A significant positive correlation (p = 0.0007) was found between the number of different practitioners seen by a service user in the first seven days of care and the LOS.

Conclusion

Our results suggest that a high number of different staff in the early period of IOC episodes correlates with an extended LOS. Future research must clarify the exact mechanisms of this correlation. Furthermore, it should be investigated how the multiple professions within IOC teams influence the LOS and the quality of treatment and what quality indicators may be suitable to ensure treatment processes.

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.

Off-label use of antidepressants, antipsychotics, and mood-stabilizers in psychiatry

Off-label drug prescribing in psychiatry is increasing. Many psychotropic drugs are approved for psychopathologic syndromes rather than based on international standard diagnostic classification systems which might facilitate the clinical decision for off-label prescriptions. The objective of this study was to analyze the prevalence and category of off-label use of psychotropic drugs. The study was conducted in 10 psychiatric hospitals in Germany over a period of 2 years. Prescription data of all patients were retrospectively analyzed after identification of antidepressants, antipsychotics, and mood-stabilizers, which were classified as off-label according to the German prescribing information and diagnostic classification according to ICD-10. In total, 53,909 patient cases (46% female) with a mean age of 46.8 (SD: 18) years were included in the study. 30.2% of the cases received at least one off-label prescription of a psychotropic drug during hospital stay. Off-label prevalence rates differed markedly between different diagnostic groups (ICD-10 F0/G3: 47%, F1: 33%, F2: 25%, F3: 21%, F4: 27%, F6: 46%, F7: 84%). The most often off-label prescribed drugs were quetiapine and mirtazapine for organic mental disorders (F0/G3), valproate and quetiapine in patients with disorders due to psychoactive substance use (F1), valproate in patients with psychotic disorders (F2), and risperidone and olanzapine in patients with affective disorders (F3). The prevalence rate of psychotropic off-label prescriptions is high if restricted to product description and ICD-10 diagnosis. Therefore, current psychiatric guidelines should drug-specifically issue this problem by defining psychiatric off-label indications based on a clear benefit-risk assessment.

Influence of head positioning during cone-beam CT imaging on the accuracy of virtual 3D models

OBJECTIVE

Cone beam computed tomography (CBCT) images are being increasingly used to acquire three-dimensional (3D) models of the skull for additive manufacturing purposes. However, the accuracy of such models remains a challenge, especially in the orbital area. The aim of this study is to assess the impact of four different CBCT imaging positions on the accuracy of the resulting 3D models in the orbital area.

METHODS

An anthropomorphic head phantom was manufactured by submerging a dry human skull in silicon to mimic the soft tissue attenuation and scattering properties of the human head. The phantom was scanned on a ProMax 3D MAX CBCT scanner using 90 and 120 kV for four different field of view positions: standard; elevated; backwards tilted; and forward tilted. All CBCT images were subsequently converted into 3D models and geometrically compared with a "gold-standard" optical scan of the dry skull.

RESULTS

Mean absolute deviations of the 3D models ranged between 0.15 ± 0.11 mm and 0.56 ± 0.28 mm. The elevated imaging position in combination with 120 kV tube voltage resulted in an improved representation of the orbital walls in the resulting 3D model without compromising the accuracy.

CONCLUSIONS

Head positioning during CBCT imaging can influence the accuracy of the resulting 3D model. The accuracy of such models may be improved by positioning the region of interest (e.g. the orbital area) in the focal plane (Figure 2a) of the CBCT X-ray beam.

A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery

Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventions and has therefore become an increasingly popular treatment modality in maxillofacial surgery. The current maxillofacial CAS consists of three main steps: (1) CT image reconstruction, (2) bone segmentation, and (3) surgical planning. However, each of these three steps can introduce errors that can heavily affect the treatment outcome. As a consequence, tedious and time-consuming manual post-processing is often necessary to ensure that each step is performed adequately. One way to overcome this issue is by developing and implementing neural networks (NNs) within the maxillofacial CAS workflow. These learning algorithms can be trained to perform specific tasks without the need for explicitly defined rules. In recent years, an extremely large number of novel NN approaches have been proposed for a wide variety of applications, which makes it a difficult task to keep up with all relevant developments. This study therefore aimed to summarize and review all relevant NN approaches applied for CT image reconstruction, bone segmentation, and surgical planning. After full text screening, 76 publications were identified: 32 focusing on CT image reconstruction, 33 focusing on bone segmentation and 11 focusing on surgical planning. Generally, convolutional NNs were most widely used in the identified studies, although the multilayer perceptron was most commonly applied in surgical planning tasks. Moreover, the drawbacks of current approaches and promising research avenues are discussed.

Soil phosphorus status and P nutrition strategies of European beech forests on carbonate compared to silicate parent material

Sustainable forest management requires understanding of ecosystem phosphorus (P) cycling. Lang et al. (2017) [Biogeochemistry, https://doi.org/10.1007/s10533-017-0375-0] introduced the concept of P-acquiring vs. P-recycling nutrition strategies for European beech (Fagus sylvatica L.) forests on silicate parent material, and demonstrated a change from P-acquiring to P-recycling nutrition from P-rich to P-poor sites. The present study extends this silicate rock-based assessment to forest sites with soils formed from carbonate bedrock. For all sites, it presents a large set of general soil and bedrock chemistry data. It thoroughly describes the soil P status and generates a comprehensive concept on forest ecosystem P nutrition covering the majority of Central European forest soils. For this purpose, an Ecosystem P Nutrition Index (ENI _P ) was developed, which enabled the comparison of forest P nutrition strategies at the carbonate sites in our study among each other and also with those of the silicate sites investigated by Lang et al. (2017). The P status of forest soils on carbonate substrates was characterized by low soil P stocks and a large fraction of organic Ca-bound P (probably largely Ca phytate) during early stages of pedogenesis. Soil P stocks, particularly those in the mineral soil and of inorganic P forms, including Al- and Fe-bound P, became more abundant with progressing pedogenesis and accumulation of carbonate rock dissolution residue. Phosphorus-rich impure, silicate-enriched carbonate bedrock promoted the accumulation of dissolution residue and supported larger soil P stocks, mainly bound to Fe and Al minerals. In carbonate-derived soils, only low P amounts were bioavailable during early stages of pedogenesis, and, similar to P-poor silicate sites, P nutrition of beech forests depended on tight (re)cycling of P bound in forest floor soil organic matter (SOM). In contrast to P-poor silicate sites, where the ecosystem P nutrition strategy is direct biotic recycling of SOM-bound organic P, recycling during early stages of pedogenesis on carbonate substrates also involves the dissolution of stable Ca-P_org precipitates formed from phosphate released during SOM decomposition. In contrast to silicate sites, progressing pedogenesis and accumulation of P-enriched carbonate bedrock dissolution residue at the carbonate sites promote again P-acquiring mechanisms for ecosystem P nutrition.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10533-021-00884-7.

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.

Comparison of convolutional neural network training strategies for cone-beam CT image segmentation

BACKGROUND AND OBJECTIVE

Over the past decade, convolutional neural networks (CNNs) have revolutionized the field of medical image segmentation. Prompted by the developments in computational resources and the availability of large datasets, a wide variety of different two-dimensional (2D) and three-dimensional (3D) CNN training strategies have been proposed. However, a systematic comparison of the impact of these strategies on the image segmentation performance is still lacking. Therefore, this study aimed to compare eight different CNN training strategies, namely 2D (axial, sagittal and coronal slices), 2.5D (3 and 5 adjacent slices), majority voting, randomly oriented 2D cross-sections and 3D patches.

METHODS

These eight strategies were used to train a U-Net and an MS-D network for the segmentation of simulated cone-beam computed tomography (CBCT) images comprising randomly-placed non-overlapping cylinders and experimental CBCT images of anthropomorphic phantom heads. The resulting segmentation performances were quantitatively compared by calculating Dice similarity coefficients. In addition, all segmented and gold standard experimental CBCT images were converted into virtual 3D models and compared using orientation-based surface comparisons.

RESULTS

The CNN training strategy that generally resulted in the best performances on both simulated and experimental CBCT images was majority voting. When employing 2D training strategies, the segmentation performance can be optimized by training on image slices that are perpendicular to the predominant orientation of the anatomical structure of interest. Such spatial features should be taken into account when choosing or developing novel CNN training strategies for medical image segmentation.

CONCLUSIONS

The results of this study will help clinicians and engineers to choose the most-suited CNN training strategy for CBCT image segmentation.

Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders

Introduction

The aim of this study was to describe the number and type of drugs used to treat depressive disorders in inpatient psychiatry and to analyse the determinants of potential drug-drug interactions (pDDI) and potentially inappropriate medication (PIM).

Methods

Our study was part of a larger pharmacovigilance project funded by the German Innovation Funds. It included all inpatients with a main diagnosis in the group of depressive episodes (F32, ICD-10) or recurrent depressive disorders (F33) discharged from eight psychiatric hospitals in Germany between 1 October 2017 and 30 September 2018 or between 1 January and 31 December 2019.

Results

The study included 14,418 inpatient cases. The mean number of drugs per day was 3.7 (psychotropic drugs = 1.7; others = 2.0). Thirty-one percent of cases received at least five drugs simultaneously (polypharmacy). Almost one half of all cases received a combination of multiple antidepressant drugs (24.8%, 95% CI 24.1%–25.5%) or a treatment with antidepressant drugs augmented by antipsychotic drugs (21.9%, 95% CI 21.3%–22.6%). The most frequently used antidepressants were selective serotonin reuptake inhibitors, followed by serotonin and norepinephrine reuptake inhibitors and tetracyclic antidepressants. In multivariate analyses, cases with recurrent depressive disorders and cases with severe depression were more likely to receive a combination of multiple antidepressant drugs (Odds ratio recurrent depressive disorder: 1.56, 95% CI 1.41–1.70, severe depression 1.33, 95% CI 1.18–1.48). The risk of any pDDI and PIM in elderly patients increased substantially with each additional drug (Odds Ratio: pDDI 1.32, 95% CI: 1.27–1.38, PIM 1.18, 95% CI: 1.14–1.22) and severity of disease (Odds Ratio per point on CGI-Scale: pDDI 1.29, 95% CI: 1.11–1.46, PIM 1.27, 95% CI: 1.11–1.44), respectively.

Conclusion

This study identified potential sources and determinants of safety risks in pharmacotherapy of depressive disorders and provided additional data which were previously unavailable. Most inpatients with depressive disorders receive multiple psychotropic and non-psychotropic drugs and pDDI and PIM are relatively frequent. Patients with a high number of different drugs must be intensively monitored in the management of their individual drug-related risk-benefit profiles.

Efficient high cone-angle artifact reduction in circular cone-beam CT using deep learning with geometry-aware dimension reduction

High cone-angle artifacts (HCAAs) appear frequently in circular cone-beam computed tomography (CBCT) images and can heavily affect diagnosis and treatment planning. To reduce HCAAs in CBCT scans, we propose a novel deep learning approach that reduces the three-dimensional (3D) nature of HCAAs to two-dimensional (2D) problems in an efficient way. Specifically, we exploit the relationship between HCAAs and the rotational scanning geometry by training a convolutional neural network (CNN) using image slices that were radially sampled from CBCT scans. We evaluated this novel approach using a dataset of input CBCT scans affected by HCAAs and high-quality artifact-free target CBCT scans. Two different CNN architectures were employed, namely U-Net and a mixed-scale dense CNN (MS-D Net). The artifact reduction performance of the proposed approach was compared to that of a Cartesian slice-based artifact reduction deep learning approach in which a CNN was trained to remove the HCAAs from Cartesian slices. In addition, all processed CBCT scans were segmented to investigate the impact of HCAAs reduction on the quality of CBCT image segmentation. We demonstrate that the proposed deep learning approach with geometry-aware dimension reduction greatly reduces HCAAs in CBCT scans and outperforms the Cartesian slice-based deep learning approach. Moreover, the proposed artifact reduction approach markedly improves the accuracy of the subsequent segmentation task compared to the Cartesian slice-based workflow.

Polypharmacy and the risk of drug-drug interactions and potentially inappropriate medications in hospital psychiatry

PURPOSE

The aim of this study was to analyze the epidemiology of polypharmacy in hospital psychiatry. Another aim was to investigate predictors of the number of drugs taken and the associated risks of drug-drug interactions and potentially inappropriate medications in the elderly.

METHODS

Daily prescription data were obtained from a pharmacovigilance project sponsored by the Innovations Funds of the German Federal Joint Committee.

RESULTS

The study included 47 071 inpatient hospital cases from eight different study centers. The mean number of different drugs during the entire stay was 6.1 (psychotropic drugs = 2.7; others = 3.4). The mean number of drugs per day was 3.8 (psychotropic drugs = 1.6; others = 2.2). One third of cases received at least five different drugs per day on average during their hospital stay (polypharmacy). Fifty-one percent of patients received more than one psychotropic drug simultaneously. Hospital cases with polypharmacy were 18 years older (p < 0.001), more likely to be female (52% vs. 40%, p < 0.001) and had more comorbidities (5 vs. 2, p < 0.001) than hospital cases without polypharmacy. The risks of drug-drug interactions (OR = 3.7; 95% CI = 3.5-3.9) and potentially inappropriate medication use in the elderly (OR = 2.2; CI = 1.9-2.5) substantially increased in patients that received polypharmacy.

CONCLUSION

Polypharmacy is frequent in clinical care. The number of used drugs is a proven risk factor of adverse drug reactions due to drug-drug interactions and potentially inappropriate medication use in the elderly. The potential interactions and the specific pharmacokinetics and -dynamics of older patients should always be considered when multiple drugs are used.

Comparative dosimetry of radiography device, MSCT device and two CBCT devices in the elbow region

The aim of the study was to estimate and to compare effective doses in the elbow region resulting from four different x-ray imaging modalities. Absorbed organ doses were measured using 11 metal oxide field effect transistor (MOSFET) dosimeters that were placed in a custom-made anthropomorphic elbow RANDO phantom. Examinations were performed using Shimadzu FH-21 HR radiography device, Siemens Sensation Open 24-slice MSCT-device, NewTom 5G CBCT device, and Planmed Verity CBCT device, and the effective doses were calculated according to ICRP 103 recommendations. The effective dose for the conventional radiographic device was 1.5 µSv. The effective dose for the NewTom 5G CBCT ranged between 2.0 and 6.7 µSv, for the Planmed Verity CBCT device 2.6 µSv and for the Siemens Sensation MSCT device 37.4 µSv. Compared with conventional 2D radiography, this study demonstrated a 1.4-4.6 fold increase in effective dose for CBCT and 25-fold dose for standard MSCT protocols. When compared with 3D CBCT protocols, the study showed a 6-19 fold increase in effective dose using a standard MSCT protocol. CBCT devices offer a feasible low-dose alternative for elbow 3D imaging when compared to MSCT.

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: a retrospective longitudinal pharmacovigilance study

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) and to evaluate the prediction performance with regard to its usefulness to support the efficient management of benefits and risks of drug prescriptions.

DESIGN

Retrospective, longitudinal study.

SETTING

We used data from a large multicentred pharmacovigilance project carried out in eight psychiatric hospitals in Hesse, Germany.

PARTICIPANTS

Inpatient episodes consecutively discharged between 1 October 2017 and 30 September 2018 (year 1) or 1 January 2019 and 31 December 2019 (year 2).

OUTCOME MEASURES

The proportion of rightly classified hospital episodes.

METHODS

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 receiver operating characteristic, was 'excellent' (0.83) and 'acceptable' (0.72) compared with 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.

CONCLUSION

This study has shown that polypharmacy and DDI 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.

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

[Outsourcing of nursing staff costs in psychiatry? : A secondary data analysis of possible effects on the remuneration system in psychiatry]

BACKGROUND

Nursing staff were excluded from the German DRG system for somatic hospital treatment and will be funded separately in the future. In psychiatry and psychosomatic medicine, binding personnel requirements have been defined but there has been no regulation of how these personnel requirements are adequately financed.

OBJECTIVE

The objective of this study was to analyze the costs of inpatient psychiatry and psychosomatic medicine and to evaluate possible effects of funding nursing staff separately.

MATERIAL AND METHODS

This analysis is based on aggregated daily treatment costs of selected hospitals (data year 2018), which annually submit their performance and cost data to the Institute for the Hospital Remuneration System (InEK) for the empirical further development of the remuneration system.

RESULTS

Nursing staff represent the largest cost factor in inpatient psychiatry and psychosomatic medicine. Excluding nursing staff drastically reduces the variance of psychiatric DRG renumeration and even exceeds its proportion of the total costs. After outsourcing nursing costs, psychiatric DRGs achieve only a very limited cost separation.

CONCLUSION

The binding personnel requirements necessitate adequate financing of nursing staff. This raises the debate about the further development of psychiatric remuneration. The question arises as to whether the effort associated with using the psychiatric DRG system justifies its usefulness as an instrument for budgeting when core functions such as cost separation are only given to a limited extent. Alternative approaches to budgeting should also be examined for putting costs and benefits in a better ratio.

On the limits of finite element models created from (micro)CT datasets and used in studies of bone-implant-related biomechanical problems

Patient-specific approach is gaining a wide popularity in computational simulations of biomechanical systems. Simulations (most often based on the finite element method) are to date routinely created using data from imaging devices such as computed tomography which makes the models seemingly very complex and sophisticated. However, using a computed tomography in finite element calculations does not necessarily enhance the quality or even credibility of the models as these depend on the quality of the input images. Low-resolution (medical-)CT datasets do not always offer detailed representation of trabecular bone in FE models and thus might lead to incorrect calculation of mechanical response to external loading. The effect of image resolution on mechanical simulations of bone-implant interaction has not been thoroughly studied yet. In this study, the effect of image resolution on the modeling procedure and resulting mechanical strains in bone was analyzed on the example of cranial implant. For this purpose, several finite element models of bone interacting with fixation-screws were generated using seven computed tomography datasets of a bone specimen but with different image resolutions (ranging from micro-CT resolution of 25 μm to medical-CT resolution of 1250 μm). The comparative analysis revealed that FE models created from images of low resolution (obtained from medical computed tomography) can produce biased results. There are two main reasons: 1. Medical computed tomography images do not allow generating models with complex trabecular architecture which leads to substituting of the intertrabecular pores with a fictitious mass; 2. Image gray value distribution can be distorted resulting in incorrect mechanical properties of the bone and thus in unrealistic or even completely fictitious mechanical strains. The biased results of calculated mechanical strains can lead to incorrect conclusion, especially when bone-implant interaction is investigated. The image resolution was observed not to significantly affect stresses in the fixation screw itself; however, selection of bone material representation might result in significantly different stresses in the screw.

Current use of anticholinergic medications in a large naturalistic sample of psychiatric patients

Due to the high number of psychotropic drugs with anticholinergic potential, patients taking psychotropic drugs are at high risk for anticholinergic adverse drug reactions (ADRs). The aim of this study was to analyze the prevalence and type of pharmacodynamic anticholinergic drug-drug interactions in psychiatric patients. The retrospective longitudinal analysis used data from a large pharmacovigilance study conducted in ten German psychiatric hospitals. Anticholinergic burden of drugs was defined as "strong" or "moderate" based on current literature. Number and type of anticholinergic drugs were assessed. In total, 27,396 patient cases (45.6% female) with a mean age of 47.3 ± 18.3 years were included. 17.4% (n = 4760) of patients were ≥ 64 years. 35.4% of the patients received between one and four anticholinergic drugs simultaneously. A combination of drugs with anticholinergic potential was detected in 1738 cases (6.3%). Most prescribed drugs were promethazine (n = 2996), olanzapine (n = 2561), biperiden (n = 1074), and doxepin (n = 963). Patients receiving anticholinergic combinations were younger (45.7 vs. 47.4 years, p < 0.01) and had a longer inpatient stay (median 18 vs. 26.5 days, p < 0.001). The prevalence of anticholinergic drug use in psychiatry is high. Further efforts need to focus on reducing the rate of anticholinergics and inappropriate medication especially in the elderly. Anticholinergic ADRs can be prevented by avoiding high-risk drug combinations. Replacing tricyclic antidepressants and first-generation antihistamines with drugs with lower anticholinergic potential and avoiding biperiden could reduce 59.3% of anticholinergic drug application.

Pharmacodynamic Drug-Drug interactions of QT-prolonging drugs in hospitalized psychiatric patients

At least 170 approved drugs are linked to QT prolongation, which can lead to serious adverse drug reactions (ADRs), such as Torsade de Pointes (TdP). The aim of this study was to analyze the prevalence and type of pharmacodynamic drug-drug interactions (DDIs) between QT-prolonging drugs in psychiatry. The present retrospective analysis used data from a large pharmacovigilance study, conducted in 10 psychiatric hospitals in Germany. Patients medication lists were screened for QT-prolonging drugs, classified according to the Arizona Center for Education and Research on Therapeutics (AZCERT). In total, 27,396 patient cases (46% female) with a mean (± standard deviation) age of 47 ± 18 years were included in the study. Altogether, 83% of the cases received at least one and up to eight QT-prolonging drugs at the same time. Combination of drugs with a known or possible risk for TdP (according to the AZCERT) was detected in 13,670 cases (50%). Most frequently prescribed psychotropic high-risk drugs (n = 48,995) were the antipsychotics pipamperone (n = 6202), quetiapine (n = 5718), prothipendyl (n = 4298), and risperidone (n = 4265). The replacement of high-risk drugs such as tricyclic antidepressants, levomepromazine, melperone, and promethazine with more tolerable drugs could avoid 11% of QT-prolonging drugs and increase the tolerability of psychopharmacological treatment. More than 80% of psychiatric patients receive at least one QT-prolonging drug during their hospital stay, and almost 50% of these drugs are combined in clinical practice. For the prevention of cardiac ADRs, the physician should evaluate the risk for QT prolongation for each drug and patient-specific risk factors before prescribing these drugs or drug combinations.

Bioavailability and -accessibility of subsoil allocated 33P-labelled hydroxyapatite to wheat under different moisture supply

Information on the bioavailability and -accessibility of subsoil phosphorus (P) and how soil moisture affects its utilization by plants is scarce. The current study examined whether and to which degree wheat acquires P from subsoil allocated hydroxyapatite and how this could be affected by soil moisture. We investigated the 33P uptake by growing wheat in two rhizotron trials (soil and sand) with integrated 33P-labelled hydroxyapatite hotspots over a period of 44 days using digital autoradiography imaging and liquid scintillation counting. We applied two irrigation scenarios, mimicking either rainfall via topsoil watering or subsoil water storage. The plants showed similar biomass development when grown in soil, but a reduced growth in sand rhizotrons. Total plant P(tot) stocks were significantly larger in plants grown under improved subsoil moisture supply, further evidenced by enhanced P stocks in the ears of wheat in the sand treatment due to an earlier grain filling. This P uptake is accompanied by larger 33P signals, indicating that the plants accessed the hydroxyapatite because subsoil irrigation also promoted root proliferation within and around the hotspots. We conclude that even within a single season plants access subsoil mineral P sources, and this process is influenced by water management.

Hospital costs associated with post-traumatic stress disorder in somatic patients: a retrospective study

BACKGROUND

Post-traumatic stress disorder is likely to affect clinical courses in the somatic hospital ward when appearing as comorbidity. Thus, this study aimed to assess the costs associated with comorbid post-traumatic stress disorder in a somatic hospital and to analyze if reimbursement appropriately compensated additional costs.

METHODS

The study used data from a German university hospital between 2011 and 2014, analyzing 198,819 inpatient episodes. Inpatient's episodes were included for analysis if they had a somatic primary diagnosis and a secondary diagnosis of post-traumatic stress disorder. Costs were calculated based on resource use and compared to reimbursement. Analyses were adjusted for sex, age and somatic comorbidities.

RESULTS

N = 219 Inpatient's episode were found with primary somatic disorder and a comorbid post-traumatic stress disorder. Inpatients episodes with comorbid post-traumatic stress disorder were compared to 34,229 control episodes, which were hospitalized with the same main diagnosis. Post-traumatic stress disorder was associated with additional hospital costs of €2311 [95%CI €1268 - €3355], while reimbursement rose by €1387 [€563 - €2212]. Results indicate that extra costs associated with post-traumatic stress disorder are not fully reimbursed. Male patients showed higher hospital costs associated with post-traumatic stress disorder. On average, post-traumatic stress disorder was associated with an extra length of stay of 3.4 days [2.1-4.6 days].

CONCLUSION

Costs associated with post-traumatic stress disorder were substantial and exceeded reimbursement, indicating an inadequate reimbursement for somatic patients with comorbid post-traumatic stress disorder.

Three-Dimensional Optical Scanning in Post-kala-azar Dermal Leishmaniasis (PKDL)

Post–kala-azar dermal leishmaniasis may occur after successful treatment of visceral leishmaniasis and is characterized by macules, papules, or nodules in the skin, with varying size. The response to antileishmanial therapy remains difficult to assess because there are presently no reliable biomarkers. To date, skin lesions are clinically assessed for decrease in size or change in color, which is invariably subjective. Novel 3-dimensional optical scanning devices offer safe and field-adapted methods to objectively assess skin lesions for changes over time in size and color that can be quantified with great accuracy.

Mechanical ventilation and the daily cost of ICU care

Background

Intensive care units represent one of the largest clinical cost centers in hospitals. Mechanical ventilation accounts for a significant share of this cost. There is a relative dearth of information quantifying the impact of ventilation on daily ICU cost. We thus determine daily costs of ICU care, incremental cost of mechanical ventilation per ICU day, and further differentiate cost by underlying diseases.

Methods

Total ICU costs, length of ICU stay, and duration of mechanical ventilation of all 10,637 adult patients treated in ICUs at a German hospital in 2013 were analyzed for never-ventilated patients (N = 9181), patients ventilated at least 1 day, (N = 1455) and all patients (N = 10,637). Total ICU costs were regressed on the number of ICU days. Finally, costs were analyzed separately by ICD-10 chapter of main diagnosis.

Results

Daily non-ventilated costs were €999 (95%CI €924 - €1074), and ventilated costs were €1590 (95%CI €1524 - €1657), a 59% increase. Costs per non-ventilated ICU day differed substantially and were lowest for endocrine, nutritional or metabolic diseases (€844), and highest for musculoskeletal diseases (€1357). Costs per ventilated ICU day were lowest for diseases of the circulatory system (€1439) and highest for cancer patients (€1594). The relative cost increase due to ventilation was highest for diseases of the respiratory system (94%) and even non-systematic for patients with musculoskeletal diseases (13%, p = 0.634).

Conclusions

Results show substantial variability of ICU costs for different underlying diseases and underline mechanical ventilation as an important driver of ICU costs.

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.

[Disorder-related case groups for needs-based hospital care]

BACKGROUND

The individual needs of patients are central to hospital care. Due to the resulting complexity grouping of patients with similar therapeutic needs seems to facilitate an efficient organization of processes and the required treatment resources in hospital care.

OBJECTIVE

The aim of this study was to develop a system of disorder-related, treatment-oriented case groups as a possible tool for the efficient and needs-based organization of hospital care.

MATERIAL AND METHODS

The disorder-related groups were developed in a multistage, mixed-methods design. The technical content and quantitative description of the case groups and the extent of treatment included all consecutive inpatient treatment cases discharged between 1 January 2017 and 31 December 2017 from 9 psychiatric hospitals in Hesse, Germany.

RESULTS

All diagnoses in chapter F of the German modification of the International Statistical Classification of Diseases 10 (ICD-10-GM) were grouped into a total of 10 disorder-related groups. Analyses included 20,252 inpatient hospital treatment cases. Substantial management-relevant differences between the case groups could be identified and the various case group-specific configurations of clinically relevant comorbidities could be demonstrated.

DISCUSSION

The presented disorder-related grouping system and configuration of comorbidities suggest a modular organization of therapeutic measures and constitute a promising basis for needs-based management of patient care. Future work will show to what degree the disorder-related groups can facilitate a needs-specific treatment and align economic and therapeutic interests of psychiatric care.

Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network

PURPOSE

In order to attain anatomical models, surgical guides and implants for computer-assisted surgery, accurate segmentation of bony structures in cone-beam computed tomography (CBCT) scans is required. However, this image segmentation step is often impeded by metal artifacts. Therefore, this study aimed to develop a mixed-scale dense convolutional neural network (MS-D network) for bone segmentation in CBCT scans affected by metal artifacts.

METHOD

Training data were acquired from 20 dental CBCT scans affected by metal artifacts. An experienced medical engineer segmented the bony structures in all CBCT scans using global thresholding and manually removed all remaining noise and metal artifacts. The resulting gold standard segmentations were used to train an MS-D network comprising 100 convolutional layers using far fewer trainable parameters than alternative convolutional neural network (CNN) architectures. The bone segmentation performance of the MS-D network was evaluated using a leave-2-out scheme and compared with a clinical snake evolution algorithm and two state-of-the-art CNN architectures (U-Net and ResNet). All segmented CBCT scans were subsequently converted into standard tessellation language (STL) models and geometrically compared with the gold standard.

RESULTS

CBCT scans segmented using the MS-D network, U-Net, ResNet and the snake evolution algorithm demonstrated mean Dice similarity coefficients of 0.87 ± 0.06, 0.87 ± 0.07, 0.86 ± 0.05, and 0.78 ± 0.07, respectively. The STL models acquired using the MS-D network, U-Net, ResNet and the snake evolution algorithm demonstrated mean absolute deviations of 0.44 mm ± 0.13 mm, 0.43 mm ± 0.16 mm, 0.40 mm ± 0.12 mm and 0.57 mm ± 0.22 mm, respectively. In contrast to the MS-D network, the ResNet introduced wave-like artifacts in the STL models, whereas the U-Net incorrectly labeled background voxels as bone around the vertebrae in 4 of the 9 CBCT scans containing vertebrae.

CONCLUSION

The MS-D network was able to accurately segment bony structures in CBCT scans affected by metal artifacts.

Costs of hospital-acquired Clostridium difficile infections: an analysis on the effect of time-dependent exposures using routine and surveillance data

Background

Hospital-acquired infections have not only gained increasing attention clinically, but also methodologically, as a time-varying exposure. While methods to appropriately estimate extra length of stay (LOS) have been established and are increasingly used in the literature, proper estimation of cost figures has lagged behind.

Methods

Analysing the additional costs and reimbursements of Clostridium difficile-infections (CDI), we use a within-main-diagnosis-time-to-exposure stratification approach to incorporate time-varying exposures in a regression model, while at the same time accounting for cost clustering within diagnosis groups.

Results

We find that CDI is associated with €9000 of extra costs, €7800 of higher reimbursements, and 6.4 days extra length of stay. Using a conventional method, which suffers from time-dependent bias, we derive estimates more than three times as high (€23,000, €8000, 21 days respectively). We discuss our method in the context of recent methodological advances in the estimation of the costs of hospital-acquired infections.

Conclusions

CDI is associated with sizeable in-hospital costs. Neglecting the methodological particularities of hospital-acquired infections can however substantially bias results. As the data needed for an appropriate analysis are collected routinely in most hospitals, we recommend our approach as a feasible way for estimating the economic impact of time-varying adverse events during hospital stay.

Use of neuron-specific enolase to predict mild brain injury in motorcycle crash patients with maxillofacial fractures: A pilot study

PURPOSE

Mild traumatic brain injury (TBI) is common but accurate diagnosis and its clinical consequences have been a problem. Maxillofacial trauma does have an association with TBI. Neuron-specific enolase (NSE) has been developed to evaluate neuronal damage. The objective of this study was to investigate the accuracy of NSE serum levels to detect mild brain injury of patients with sustained maxillofacial fractures during motor vehicle accidents.

METHODS

Blood samples were drawn from 40 healthy people (control group) and 48 trauma patients who had sustained isolated maxillofacial fractures and mild brain injury in motor vehicle accidents. Brain injuries were graded by Glasgow Coma Scale. In the trauma group, correlations between the NSE serum value and different facial fracture sites were also assessed.

RESULTS

The NSE serum level (mean ± SD, ng/ml) in the 48 patients with maxillofacial fractures and mild TBI was 13.12 ± 9.68, significantly higher than that measured in the healthy control group (7.72 ± 1.82, p < 0.001). The mean NSE serum level (ng/ml) in the lower part of the facial skeleton (15.44 with SD 15.34) was higher than that in the upper facial part (12.42 with SD 7.68); and the mean NSE level (ng/ml) in the middle-and lower part (11.97 with SD 5.63) was higher than in the middle part (7.88 with SD 2.64).

CONCLUSION

An increase in NSE serum levels can be observed in patients sustained maxillofacial fractures and mild brain injury.

Wound dehiscences following pre-implant bone augmentation with autogenous iliac crest bone grafts: A retrospective cohort study

PURPOSE

To evaluate possible risk factors associated with wound dehiscences following pre-implant alveolar bone augmentation with autologous anterior iliac crest bone grafts covered with resorbable collagen membranes or human demineralised bone laminae.

MATERIALS AND METHODS

Data of 161 patients who underwent bone augmentation prior to the insertion of dental implants were analysed. The preoperative dental status, locations of alveolar bone augmentation sites and location of wound dehiscences were recorded. Gender, age, smoking, alcohol exposure, and dental and medical histories were reviewed. Information was also collected on the surgeons, augmentation technique, application of a collagen membrane, fixation screw type and suture material. Univariate logistic regression analysis was used to evaluate pre- and perioperative variables as predictors of dehiscences.

RESULTS

A total of 42 (26.1%) of the 161 augmented patients developed a wound dehiscence following surgery. Most commonly affected sites were the anterior maxilla, followed by the anterior mandible. Males developed wound dehiscences with higher probability than females (odds ratio female = 0.444; P = 0.025; 95% CI: 0.214 to 0.903). Furthermore, marginal associations (P < 0.10) are found for smoking and an anterior location of the augmentation. Smokers were found to have higher probability of a wound dehiscence (odds ratio 2.089; P = 0.064; 95% CI: 0.957 to 4.500) compared to non-smokers. A posterior location of the augmentation was associated with lower probability of a wound dehiscence (odds ratio 0.188; P = 0.076; 95% CI: 0.035 to 0.802) compared to an anterior location.

CONCLUSIONS

Based on this study population, smoking in males seems to be the most important risk factor for the development of wound dehiscences after pre-implant alveolar bone augmentation procedures.

In-hospital costs of community-acquired colonization with multidrug-resistant organisms at a German teaching hospital

Background

Antibiotic resistance is a challenge in the management of infectious diseases and can cause substantial cost. Even without the onset of infection, measures must be taken, as patients colonized with multi-drug resistant (MDR) pathogens may transmit the pathogen. We aim to quantify the cost of community-acquired MDR colonizations using routine data from a German teaching hospital.

Methods

All 2006 cases of documented MDR colonization at hospital admission recorded from 2011 to 2014 are matched to 7917 unexposed controls with the same primary diagnosis. Cases with an onset MDR infection are excluded from the analysis. Routine data on costs per case is analysed for three groups of MDR bacteria: Methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococcus (VRE), and multidrug-resistant gram-negative bacteria (MDR-GN). Multivariate analyses are conducted to adjust for potential confounders.

Results

After controlling for main diagnosis group, age, sex, and Charlson Comorbidity Index, MDR colonization is associated with substantial additional costs from the healthcare perspective (€1480.9, 95%CI €1286.4–€1675.5). Heterogeneity between pathogens remains. Colonization with MDR-GN leads to the largest cost increase (€1966.0, 95%CI €1634.6–€2297.4), followed by MRSA with €1651.3 (95%CI €1279.1–€2023.6), and VRE with €879.2 (95%CI €604.1–€1154.2). At the same time, MDR-GN is associated with additional reimbursements of €887.8 (95%CI €722.1–€1053.6), i.e. costs associated with MDR-colonization exceed reimbursement.

Conclusions

Even without the onset of invasive infection, documented MDR-colonization at hospital admission is associated with increased hospital costs, which are not fully covered within the German DRG-based hospital payment system.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3549-0) contains supplementary material, which is available to authorized users.

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.

Effective Radiation Dose in the Wrist Resulting from a Radiographic Device, Two CBCT Devices and One MSCT Device: A Comparative Study

The objective of the present study was to assess and compare the effective doses in the wrist region resulting from conventional radiography device, multislice computed tomography (MSCT) device and two cone beam computed tomography (CBCT) devices using MOSFET dosemeters and a custom made anthropomorphic RANDO phantom according to the ICRP 103 recommendation. The effective dose for the conventional radiography was 1.0 μSv. The effective doses for the NewTom 5 G CBCT ranged between 0.7 μSv and 1.6 μSv, for the Planmed Verity CBCT 2.4 μSv and for the MSCT 8.6 μSv. When compared with the effective dose for AP- and LAT projections of a conventional radiographic device, this study showed an 8.6-fold effective dose for standard MSCT protocol and between 0.7 and 2.4-fold effective dose for standard CBCT protocols. When compared to the MSCT device, the CBCT devices offer a 3D view of the wrist at significantly lower effective doses.

Dental Stem Cells Harvested from Third Molars Combined with Bioactive Glass Can Induce Signs of Bone Formation In Vitro

Objectives

The aim of this study was to assess the interaction of a bioactive glass scaffold with cells derived from dental pulp, dental follicle and periodontal ligament.

Material and Methods

Impacted third molars were surgically removed from three young donors. Cells from the dental pulp, follicle and periodontal ligament tissues were isolated and expanded. Different cell populations were characterised using specific CD markers. Expanded pulp, follicle and periodontal cells were then seeded onto bioactive glass scaffolds and cultured in osteogenic medium or basic medium. Cell attachment, viability, proliferation and alkaline phosphatase activity were assessed.

Results

This study revealed good biocompatibility of the specific bioactive glass configuration tested and the osteogenic induction of cells derived from dental pulp, dental follicle and periodontal ligament. Osteogenic medium seemed to increase the differentiation pattern and dental pulp stem cells showed the most positive results compared to periodontal ligament and dental follicle stem cells.

Conclusions

Dental pulp stem cells combined with a bioactive glass scaffold and exposed to osteogenic medium in vitro represent a promising combination for future study of hard tissue regeneration in the cranio-maxillofacial skeleton.

Micro finite element analysis of dental implants under different loading conditions

Osseointegration is paramount for the longevity of dental implants and is significantly influenced by biomechanical stimuli. The aim of the present study was to assess the micro-strain and displacement induced by loaded dental implants at different stages of osseointegration using finite element analysis (FEA). Computational models of two mandible segments with different trabecular densities were constructed using microCT data. Three different implant loading directions and two osseointegration stages were considered in the stress-strain analysis of the bone-implant assembly. The bony segments were analyzed using two approaches. The first approach was based on Mechanostat strain intervals and the second approach was based on tensile/compression yield strains. The results of this study revealed that bone surrounding dental implants is critically strained in cases when only a partial osseointegration is present and when an implant is loaded by buccolingual forces. In such cases, implants also encounter high stresses. Displacements of partially-osseointegrated implant are significantly larger than those of fully-osseointegrated implants. It can be concluded that the partial osseointegration is a potential risk in terms of implant longevity.