Collaborative nowcasting of COVID-19 hospitalization incidences in Germany.

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges.

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.

BACKGROUND: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. METHODS: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. RESULTS: We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. CONCLUSIONS: Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

We compare forecasts of weekly case and death numbers for COVID-19 in Germany and Poland based on 15 different modelling approaches. These cover the period from January to April 2021 and address numbers of cases and deaths one and two weeks into the future, along with the respective uncertainties. We find that combining different forecasts into one forecast can enable better predictions. However, case numbers over longer periods were challenging to predict. Additional data sources, such as information about different versions of the SARS-CoV-2 virus present in the population, might improve forecasts in the future.

Multiscale DNA partitioning: statistical evidence for segments.

MOTIVATION: DNA segmentation, i.e. the partitioning of DNA in compositionally homogeneous segments, is a basic task in bioinformatics. Different algorithms have been proposed for various partitioning criteria such as Guanine/Cytosine (GC) content, local ancestry in population genetics or copy number variation. A critical component of any such method is the choice of an appropriate number of segments. Some methods use model selection criteria and do not provide a suitable error control. Other methods that are based on simulating a statistic under a null model provide suitable error control only if the correct null model is chosen. RESULTS: Here, we focus on partitioning with respect to GC content and propose a new approach that provides statistical error control: as in statistical hypothesis testing, it guarantees with a user-specified probability [Formula: see text] that the number of identified segments does not exceed the number of actually present segments. The method is based on a statistical multiscale criterion, rendering this as a segmentation method that searches segments of any length (on all scales) simultaneously. It is also accurate in localizing segments: under benchmark scenarios, our approach leads to a segmentation that is more accurate than the approaches discussed in the comparative review of Elhaik et al. In our real data examples, we find segments that often correspond well to features taken from standard University of California at Santa Cruz (UCSC) genome annotation tracks. AVAILABILITY AND IMPLEMENTATION: Our method is implemented in function smuceR of the R-package stepR available at http://www.stochastik.math.uni-goettingen.de/smuce.

Idealizing ion channel recordings by a jump segmentation multiresolution filter.

Based on a combination of jump segmentation and statistical multiresolution analysis for dependent data, a new approach called J-SMURF to idealize ion channel recordings has been developed. It is model-free in the sense that no a-priori assumptions about the channel's characteristics have to be made; it thus complements existing methods which assume a model for the channel's dynamics, like hidden Markov models. The method accounts for the effect of an analog filter being applied before the data analysis, which results in colored noise, by adapting existing muliresolution statistics to this situation. J-SMURF's ability to denoise the signal without missing events even when the signal-to-noise ratio is low is demonstrated on simulations as well as on ion current traces obtained from gramicidin A channels reconstituted into solvent-free planar membranes. When analyzing a newly synthesized acylated system of a fatty acid modified gramicidin channel, we are able to give statistical evidence for unknown gating characteristics such as subgating.

What is special about patients with lung cancer and pulmonary metastases in palliative care? Results from a nationwide survey.

BACKGROUND: Patients with advanced lung cancer constitute a special focus in palliative care not only for epidemiological or prognostic reasons, but also because their symptom burden is felt to be widespread and difficult to treat. This study describes disease-specific characteristics and the symptom burden of patients with advanced incurable lung cancer, comparing them with patients suffering from other diseaseentities. METHODS: A secondary analysis of the nationwide Hospice and Palliative Care Evaluation (HOPE) was performed, by focussing on inpatient hospice and palliative care unit patients and by using descriptive methods. RESULTS: From 2006 to 2008, 5487 inpatients were registered, 874 of which were diagnosed with lung cancer and 1884 with pulmonary metastases. Symptoms such as weakness, tiredness, or pain were most prevalent in all subgroups. Dyspnea was significantly more prevalent in all patients with different kinds of pulmonary tumor manifestations; confusion was significantly more prevalent in patients with lung cancer. Dyspnea could not be treated as effectively as pain or nausea. Confusion and nursing problems worsened during the observation period. Dyspnea and confusion were associated with increased risk of death during the observational period. CONCLUSION: The symptom pattern of patients with lung cancer is characterized by dyspnea and confusion--symptoms that are difficult to treat until discharge and that imply a worse prognosis. Therefore, increased research on the pathophysiology and treatment of dyspnea and confusion is required, and efforts in advance care planning and anticipation of dyspnea and confusion as a critical symptom in patients with lung cancer should be reinforced.

Drift estimation for single marker switching based imaging schemes.

In recent years, the diffraction barrier in fluorescence imaging has been broken and optical nanoscopes now routinely image with resolutions of down to 20 nm, an improvement of more than 10 fold. Because this allows imaging much smaller features and because all super-resolution approaches trade off speed for spatial resolution, mechanical instabilities of the microscopes become a limiting factor. Here, we propose a fully data-driven statistical registration method for drift detection and drift correction for single marker switching (SMS) imaging schemes, including a guideline for parameter choice and quality checks of the drift analysis. The necessary assumptions about the drift are minimal, allowing a model-free approach, but more specific models can easily be integrated. We determine the resulting performance on standard SMS measurements and show that the drift determination can be routinely brought to the range of precision achievable by fiducial marker-tracking methods.

Central head perforation, or "cut through," caused by the helical blade of the proximal femoral nail antirotation.

OBJECTIVE: This study was designed to investigate the specific type and incidence of implant failure in patients with a proximal femur fracture treated with a proximal femoral nail antirotation. This device has a helical-shaped blade as a neck-head holding device, instead of the lag screw used in other intramedullary nails. The advantage of the blade is believed to originate from bone impaction and a larger bone-implant interface in comparison with the lag screw design, with consequential greater mechanical resistance to torsion in the cancellous bone. PATIENTS AND METHODS: This is a retrospective cohort study conducted at the state hospital of Winterthur, Switzerland. From December 2006 until November 2008, 210 consecutive patients were treated with a pertrochanteric femur fracture (OTA type 31-A1, 31-A2, and 31-A3) using a proximal femoral nail antirotation. One hundred and twelve patients were followed up clinically for a minimum of 12 months after discharge. Clinical and radiologic assessment of fracture healing and/or implant failure was investigated. RESULTS: We report 7 cases of implant failure with a "Cut Through," defined as a postoperative central perforation of the spiral blade into the hip joint, without any displacement of the neck-head fragment. CONCLUSIONS: Cut through needs to be distinguished from the well-known anterocranial perforation combined with a varus displacement of the neck-head fragment, known as "Cut Out," seen with intramedullary nails utilizing lag screws. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Anatomic reconstruction of unstable lateral clavicular fractures.

BACKGROUND: Fractures of the lateral clavicle result in a high rate of nonunion compared with midshaft fractures. Many operative treatment methods of unstable lateral clavicle fractures have been described, but no single method has become generally accepted. This study reports our experience treating unstable lateral clavicle fractures with coracoclavicular ligament rupture. METHODS: Within 7 years, 19 patients with acute unstable lateral clavicle fractures were treated using a 2.4-mm T-plate and a coracoclavicular polydioxanone cord. The follow-up averaged 5.3 years (range, 2.0-8.8). Shoulder function was assessed using the Constant score and Disabilities of the Arm, Shoulder and Hand score. General health of the patients was evaluated according to the Short Form 36 questionnaire. RESULTS: Eighteen of the 19 patients treated with our method achieved union at 8.8 weeks (range, 6-14), a Constant Murley score of 91.5 (range, 72-100) on the injured side versus 93.5 (range, 80-100) on the contralateral side, a Disabilities of the Arm, Shoulder and Hand score of 1.4 (range, 0-9.2), and a Short Form 36 Health Score of 85 (range, 89-100). One patient showed breakage of the plate and a delayed union at the radiologic follow-up 4 months after surgery. CONCLUSION: This study shows that treatment of unstable lateral clavicular fractures with an angular stable locking plate together with a polydioxanone cord ligament augmentation leads to excellent results with a 95% union rate. Additional coracoclavicular augmentation next to plate fixation of the clavicle may partially solve the problem of uncertain plate fixation if the lateral fragment is small and multifragmented, as often observed.

Osteosynthesis of traumatic manubriosternal dislocations and sternal fractures with a 3.5/4.0 mm fixed-angle plate (LCP).

INTRODUCTION: We present a case series of three patients with manubriosternal dislocation and/or sternal fractures. METHOD: We describe our experiences of invasive surgical treatment with 3.5/4.0 mm fixed-angle plate (Locking compression plate, LCP) in this group of patients. Recommended nonoperative treatment options, e.g. correction tape or plaster bandage, symptomatic pain treatment, application of ice, and several weeks without sports are associated with a not inconsiderable rate of subluxations or reluxations with an increased risk of pseudarthrosis and chronic pain syndrome. RESULTS: Due to a small number of cases and the lack of controlled studies, a standardized operative procedure could, therefore, so far not been established. CONCLUSION: Our positive experiences with the operative treatment using 3.5/4.0 mm fixed-angle plate (LCP) may help to establish the operative procedure of first choice in this group of patients.

Successful removal of a 3.6-cm long metal band used as a penile constriction ring.

INTRODUCTION: Penile constriction rings are either used for autoerotic stimulus or to increase sexual performance. Potentially, they can become irremovable and cause urologic emergencies. AIM: We describe the successful removal of a 3.6-cm long piece of heavy metal tubing used as a penile constriction ring. METHODS: An angel grinder was used to open the metal tubing on both lateral sides. During the cutting procedure, the soft tissue parts were protected by two metal spatulas. Wet towels and cool running water prevented thermal injury. RESULTS: After removal of the band, no iatrogenic injury was visible and the further recovery of the patient remained uneventful. Postoperatively, one of the surgeons suffered from conjunctivitis of the left eye possibly due to metal sparks. CONCLUSION: Depending on the constricting object, heavy-duty technical equipment might become necessary for their removal. In such cases, special care should be taken to avoid injury to the patient and the medical crew.

Intrinsic MANOVA for Riemannian manifolds with an application to Kendall's space of planar shapes.

We propose an intrinsic multifactorial model for data on Riemannian manifolds that typically occur in the statistical analysis of shape. Due to the lack of a linear structure, linear models cannot be defined in general; to date only one-way MANOVA is available. For a general multifactorial model, we assume that variation not explained by the model is concentrated near elements defining the effects. By determining the asymptotic distributions of respective sample covariances under parallel transport, we show that they can be compared by standard MANOVA. Often in applications manifolds are only implicitly given as quotients, where the bottom space parallel transport can be expressed through a differential equation. For Kendall's space of planar shapes, we provide an explicit solution. We illustrate our method by an intrinsic two-way MANOVA for a set of leaf shapes. While biologists can identify genotype effects by sight, we can detect height effects that are otherwise not identifiable.

Global models for the orientation field of fingerprints: an approach based on quadratic differentials.

Quadratic differentials naturally define analytic orientation fields on planar surfaces. We propose to model orientation fields of fingerprints by specifying quadratic differentials. Models for all fingerprint classes such as arches, loops and whorls are laid out. These models are parametrised by few, geometrically interpretable parameters which are invariant under Euclidean motions. We demonstrate their ability in adapting to given, observed orientation fields, and we compare them to existing models using the fingerprint images of the NIST Special Database 4. We also illustrate that these model allow for extrapolation into unobserved regions. This goes beyond the scope of earlier models for the orientation field as those are restricted to the observed planar fingerprint region. Within the framework of quadratic differentials we are able to verify analytically Penrose's formula for the singularities on a palm. Potential applications of these models are the use of their parameters as indices of large fingerprint databases, as well as the definition of intrinsic coordinates for single fingerprint images.

Open and laparoscopic treatment of nonparasitic splenic cysts.

BACKGROUND: Nonparasitic splenic cysts are rare. Therefore, there is no 'evidence-based' information regarding their optimal surgical management. In the last years the laparoscopic approach has gained increasing acceptance in splenic surgery. The aim of this study is to present our experience with the laparoscopic management of splenic cysts. METHODS: The medical records of 7 patients with splenic cysts were reviewed retrospectively. RESULTS: One patient had an open partial splenic resection. Five patients, 3 of them with a posttraumatic and 2 with an epidermoid splenic cyst, underwent laparoscopic unroofing of the cyst. In 4 of these cases the postoperative course was uneventful, whereas in 1 case the patient developed a cyst relapse soon postoperatively. Later on this patient successfully underwent an open partial splenic resection. The 7th patient had an explorative laparoscopy. The cyst was located intrasplenically, entirely covered with unaffected splenic parenchyma, and reached the splenic hilus. Therefore, a conversion to open partial splenectomy was performed. CONCLUSION: Open partial splenectomy and laparoscopic cyst wall unroofing are both effective tools in the management of splenic nonparasitic cysts. Surgeons must master both techniques as nowadays spleen-preserving techniques should be attempted in every case of splenic nonparasitic cyst.