Community venue exposure risk estimator for the COVID-19 pandemic

Complexities of virus genotypes and the stochastic contacts in human society create a big challenge for estimating the potential risks of exposure to a widely spreading virus such as COVID-19. To increase public awareness of exposure risks in daily activities, we propose a birthday-paradox-based probability model to implement in a web-based system, named COSRE (community social risk estimator) and make in-time community exposure risk estimation during the ongoing COVID-19 pandemic. We define exposure risk to mean the probability of people meeting potential cases in public places such as grocery stores, gyms, libraries, restaurants, coffee shops, offices, etc. Our model has three inputs: the real-time number of active and asymptomatic cases, the population in local communities, and the customer counts in the room. With COSRE, possible impacts of the pandemic can be explored through spatiotemporal analysis, e.g., a variable number of people may be projected into public places through time to assess changes of risk as the pandemic unfolds. The system has potential to advance understanding of the true exposure risks in various communities. It introduces an objective element to plan, prepare and respond during a pandemic. Spatial analysis tools are used to draw county-level exposure risks of the United States from April 1 to July 15, 2020. The correlation experiment with the new cases in the next two weeks shows that the risk estimation model offers promise in assisting people to be more precise about their personal safety and control of daily routine and social interaction. It can inform business and municipal COVID-19 policy to accelerate recovery.     

Use of efficacy probability maps for the post-operative programming of deep brain stimulation in essential tremor

IntroductionPost-operative programming of deep brain stimulation for movement disorders can be both time consuming and difficult, which can delay the optimal symptom control for the patient. Probabilistic maps of stimulation response could improve programming efficiency and optimization.MethodsThe clinically selected contacts of patients who had undergone ventral intermediate nucleus deep brain stimulation for the treatment of essential tremor at our institution were compared against contacts selected based on a probability map of symptom reduction built by populating data from a number of patients using non-rigid image registration. A subgroup of patients whose clinical contacts did not match the map-based selections prospectively underwent a tremor rating scale evaluation to compare the symptom relief achieved by the two options. Both the patient and video reviewer were blinded to the selection.Results54% of the map-based and clinical contacts were an exact match retrospectively and were within one contact 83% of the time. In 5 of the 8 mismatched leads that were evaluated prospectively in a double blind fashion, the map-based contact showed equivalent or better tremor improvement than the clinically active contact.ConclusionsThis study suggests that probability maps of stimulation responses can assist in selecting the clinically optimal contact and increase the efficiency of programming.     

Does C-reactive Protein Add Prognostic Value to GRACE Score in Acute Coronary Syndromes?

Background

The incremental prognostic value of plasma levels of C-reactive protein (CRP) in relation to GRACE score has not been established in patients with acute coronary syndrome (ACS) with non-ST segment elevation.

Objective

To test the hypothesis that CRP measurements at admission increases the prognostic value of GRACE score in patients with ACS.

Methods

A total of 290 subjects, consecutively admitted for ACS, with plasma material obtained upon admission CRP measurement using a high-sensitivity method (nephelometry) were studied. Cardiovascular outcomes during hospitalization were defined by the combination of death, nonfatal myocardial infarction or nonfatal refractory angina.

Results

The incidence of cardiovascular events during hospitalization was 15% (18 deaths, 11 myocardial infarctions, 13 angina episodes) with CRP showing C-statistics of 0.60 (95% CI = 0.51-0.70, p = 0.034) in predicting these outcomes. After adjustment for the GRACE score, elevated CRP (defined as the best cutoff point) tended to be associated with hospital events (OR = 1.89, 95% CI = 0.92 to 3.88, p = 0.08). However, the addition of the variable elevated CRP in the GRACE model did not result in significant increase in C-statistics, which ranged from 0.705 to 0.718 (p = 0.46). Similarly, there was no significant reclassification of risk with the addition of CRP in the predictor model (net reclassification = 5.7 %, p = 0.15).

Conclusion

Although CRP is associated with hospital outcomes, this inflammatory marker does not increase the prognostic value of the GRACE score.     

The why,where, and how clinical reasoning model for the evaluation and treatment of patients with low back pain

BackgroundThere is considerable overlap between pain referral patterns from the lumbar disc, lumbar facets, the sacroiliac joint (SIJ), and the hip. Additionally, sciatic like symptoms may originate from the lumbar spine or secondary to extra-spinal sources such as deep gluteal syndrome (GPS). Given that there are several overlapping potential anatomic sources of symptoms that may be synchronous in patients who have low back pain (LBP), it may not be realistic that a linear deductive approach can be used to establish a diagnosis and direct treatment in this group of patients.ObjectiveThe objective of this theoretical clinical reasoning model is to provide a framework to help clinicians integrate linear and non-linear clinical reasoning approaches to minimize clinical reasoning errors related to logically fallacious thinking and cognitive biases.MethodsThis masterclass proposes a hypothesis-driven and probabilistic approach that uses clinical reasoning for managing LBP that seeks to eliminate the challenges related to using any single diagnostic paradigm.ConclusionsThis model integrates the why (mechanism of primary symptoms), where (location of the primary driver of symptoms), and how (impact of mechanical input and how it may or may not modulate the patient's primary complaint). The integration of these components individually, in serial, or simultaneously may help to develop clinical reasoning through reflection on and in action. A better understanding of what these concepts are and how they are related through the proposed model may help to improve the clinical conversation, academic application of clinical reasoning, and clinical outcomes.     

Detection of radioactive hot particles in environmental samples by repeated mixing

When a bulky environmental sample with radioactive hot particles, as e.g. soil, is repeatedly mixed in the counting bottle and its gamma-ray emission rate counted each time subsequently, the resulting frequency distribution of the counts is no longer symmetric but strongly skewed to the right. For this reason, it is possible to detect the presence of one or more hot particles in such samples simply by testing at a given level of significance whether the total number of counts observed after each mixing belong to the same Poisson distribution. It is shown by Monte Carlo calculations that if (i) the height of the counting bottle is about 5 cm, (ii) the total number of counts collected each time is around 1000, and (iii) the background activity of the sample matrix is not exceeding that of all hot particles in the sample, about 4 mixings will be sufficient to detect in this way the presence of up to 4 hot particles with a probability >95%. This probability is even higher if more than 1000 counts are collected, the hot particles have different activities, the height of the counting bottle is increased, or self attenuation of the gamma radiation in the sample is present. An efficiency calibration for the counting geometry used is not required. An experimental example is given.     

同名牙病理性对称的临床分析

目的 探讨牙列两侧同名牙的病理性对称，帮助提高对牙齿疾病的预防、诊断和治疗效果。方法 选择300例曾先后（或同时）接受2颗牙以上诊治的患者（指成年人）进行临床分析。结果 有58例患者两侧同名牙都有病理性对称的表现。结论 同名牙出现病理性对称有一定的概率。     

探讨肿瘤控制概率模型中各参数的取值变化对结果的影响

目的 探讨肿瘤控制概率（TCP）计算模型中各参数的取值变化对计算结果的影响。方法 在假设某一参数取不同的值，而其他参数取假设的参考值的情况下，利用TCP计算模型进行计算并画出TCP与肿瘤半径的关系曲线，然后分析参数取值的变化对计算结果产生的影响。结果 在对TCP计算结果产生影响的参数中，吸收剂量，肿瘤体积，辐射敏感性，肿瘤中克隆源性细胞的潜在倍增时间的变化对TCP计算结果影响较大，而细胞密度，DNA单链断裂修复速率与再敏感化速率对结果的影响较小。结论 使用TCP评估治疗效果时必须注意肿瘤生物学参数的准确性，否则会导致结果评估的失误。     

Estimating nutrient deficiencies in a population from dietary records: The use of probability analyses

The objective of this report is to describe a probability approach, and to compare approaches, to evaluating dietary intake data. The nutrient intake data used were calculated from seven-day food records obtained from 83 Ontario teenagers and the adequacy of the estimated nutrient intakes was assessed by three approaches. First, mean nutrient intakes were compared to the recommended daily nutrient intakes (RDNI). Second, the proportion of the population not meeting the RDNI was calculated. Third, the distribution of nutrient intakes below the RDNI was determined, and combined with probability statistics to calculate the number of subjects likely to have intakes below their own individual requirements. This latter approach recognizes that the RDNI overestimates the nutrient requirement of almost all individuals in the population. The first approach was found to underestimate, whereas the second approach overestimated, possible problems. The third analysis appears to predict an incidence of nutrient inadequacy which is more in agreement with biochemical evidence. Therefore. given an adequate estimate of usual daily nutrient intakes of the individual, dietary data may be effectively used to identify nutrient problems in a population.     

Survival prediction algorithms miss significant opportunities for improvement if used for case selection in trauma quality improvement programs

BackgroundQuality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were ‘expected to survive’. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as ‘expected’. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement.MethodsWe conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator.ResultsOver 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care.ConclusionsTRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs.