Immunologic and Targeted Molecular Therapies for Chordomas: A Narrative Review.

Chordomas are rare sarcomas arising from notochordal tissue and occur most commonly in the spine. The standard of care for chordomas without evidence of metastatic disease generally consists of en bloc resection followed by adjuvant radiotherapy. However, long-term (20-year) survival rates are approximately 30%. Chordomas are generally considered as chemo resistant. Therefore, systemic therapies have rarely been employed. Novel immunotherapies, including antibody therapy and tumor vaccines, have shown promise in early trials, leading to extended progression-free survival and symptom relief. However, the outcomes of larger trials using these vectors are heterogeneous. The aim of this review is to summarize novel chordoma treatments in immune-targeted therapies. The current merits, trial outcomes, and toxicities of these novel immune and targeted therapies, including those targeting vascular endothelial growth factor receptor (VEGFR) targets and the epidermal growth factor receptor (EGFR), will be discussed.

Right Information, Right Care, Right Patient, Right Time: Community Preferences to Inform a Self-Management Support Tool for Upper Respiratory Symptoms.

INTRODUCTION: During and after the COVID-19 pandemic, communities must cope with several conditions that cause similar upper-respiratory symptoms but are managed differently. We describe community reactions to a self-management toolkit for patients with upper respiratory symptoms to inform mobile e-health app development. The toolkit is based on the '4R' (Right Information, Right Care, Right Patient, Right Time) care planning and management model. METHODS: The 4R Cold, Flu and COVID-19 Information Tool (4R-Toolkit) along with a brief evaluation survey were distributed in three ways: through a Bronx NY Allergy/Asthma clinic, through the Bronx Borough President's Office listserv, and through peer recruitment. The survey assessed respondents' perceptions of the 4R-Toolkit's accessibility, preferences for sharing symptoms with clinicians, social media use, and e-health literacy. RESULTS: We obtained a diverse sample of 106 Bronx residents, with 83% reporting personal or a social contact with symptoms suggestive of COVID-19. Respondents varied in the information sources they preferred: computer (39%); smart phone (28%); paper (11%) and no preference (22%). Most (67%) reported that social media had at least some impact on their healthcare decisions. Regardless of media preferences, respondents were positive about the 4R-Toolkit. Out of 106 respondents, 91% believed the 4R-Toolkit would help people self-manage upper respiratory symptoms and 85% found it easy to understand. Respondents strongly endorsed retention of all 4R-Toolkit content domains with 81% indicating that they would be willing to share symptoms with providers using a 4R-Toolkit smartphone app. CONCLUSION: The 4R-Toolkit can offer patients and community members accurate and up-to-date information on COVID-19, the common cold, and the flu. The user-friendly tool is accessible to diverse individuals, including those with limited e-health literacy. It has potential to support self-management of upper respiratory symptoms and promote patient engagement with providers.

Efficacy of an allograft cellular bone matrix as an alternative to autograft in anterior cervical discectomy and fusion: radiological results & safety.

Background: The predominant surgical procedure employed for patients with symptomatic cervical radiculopathy is anterior cervical discectomy and fusion (ACDF). ACDF typically involves the use of an interbody cage augmented with iliac crest bone graft (ICBG) or local autograft to enhance fusion rate. Substantial complications can arise from autograft use, including donor site morbidity, difficulties with ambulation, and diminished quality of life. This study aims to evaluate the effectiveness and safety of an allograft cellular bone matrix (ACBM) as an osteopromotive bone, in ACDF procedures. Methods: This retrospective, single-center, consecutive case series included 73 patients who underwent an ACDF procedure. The surgical procedure involved the placement of an interbody cage supplemented with anterior plate fixation and an ACBM within the interbody spacer. Patient charts were reviewed to gather demographic information, radiographic findings, as well as perioperative and post-operative complications. Radiographic fusion was assessed at 6 and 12 months by a blinded, musculoskeletal-trained radiologist and a board-certified spinal surgeon reviewer. Any discrepancies were settled by a third, senior reviewer. Complete fusion was defined as: evidence of bridging bone across the disc space on CT, angular motion <3 degrees, and translational motion <2 mm on lateral radiographs. Complications were analyzed at 6, 12, and 15+ months post-operatively to assess clinical outcomes and device performance. Results: A total of 73 patients (50 males, 23 females) with an average age of 54.6 (range, 31-77) years underwent an ACDF procedure between C3-T1 with an ACBM. The breakdown of levels operated on was 26%, 32%, 34%, and 8% for one, two, three, and four level procedures, respectively. There were three patients who received spinal injections for pain within the first year post-operatively. There were two patients who required secondary surgery within the first 12 months where supplemental posterior hardware was needed. Notably, there were no instances of cage subsidence, cage migration, cage/graft removal, or reoperation. There were no cases of chronic dysphasia. At 6 months, 45% of patients with available imaging demonstrated complete fusion, while 97.4% of patients with available imaging demonstrated complete fusion at 12 months. Conclusions: At the 12-month follow-up, our study demonstrates a high fusion rate in a real-world population of up to 4 operative levels. There were no bone graft related complications or incidences of cage migration/subsidence. It is noteworthy that the study involved a significant number of multilevel cases (74% of cases). Despite this, our results align with historical fusion rates and provide support for the utilization of ACBMs as a fusion adjunct in ACDF procedures up to 4 levels.

Development of a natural language processing algorithm for the detection of spinal metastasis based on magnetic resonance imaging reports.

Background: Metastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system to identify and refer patients with spinal metastases can help overcome barriers to timely treatment. We describe the training, optimization and validation of a natural language processing algorithm to identify the presence of vertebral metastasis and metastatic epidural cord compression (MECC) from radiology reports of spinal MRIs. Methods: Reports from patients with spine MRI studies performed between January 1, 2008 and April 14, 2019 were reviewed by a team of radiologists to assess for the presence of cancer and generate a labeled dataset for model training. Using regular expression, impression sections were extracted from the reports and converted to all lower-case letters with all nonalphabetic characters removed. The reports were then tokenized and vectorized using the doc2vec algorithm. These were then used to train a neural network to predict the likelihood of spinal tumor or MECC. For each report, the model provided a number from 0 to 1 corresponding to its impression. We then obtained 111 MRI reports from outside the test set, 92 manually labeled negative and 19 with MECC to test the model's performance. Results: About 37,579 radiology reports were reviewed. About 36,676 were labeled negative, and 903 with MECC. We chose a cutoff of 0.02 as a positive result to optimize for a low false negative rate. At this threshold we found a 100% sensitivity rate with a low false positive rate of 2.2%. Conclusions: The NLP model described predicts the presence of spinal tumor and MECC in spine MRI reports with high accuracy. We plan to implement the algorithm into our EMR to allow for faster referral of these patients to appropriate specialists, allowing for reduced morbidity and increased survival.

Area Socioeconomic Status is Associated with Refusal of Recommended Surgery in Patients with Metastatic Bone and Joint Disease.

BACKGROUND: This study sought to identify associations between the Yost Index, a geocoded area neighborhood socioeconomic status (nSES) score, and race/ethnicity with patient refusal of recommended surgery for metastatic bone disease. METHODS: Patients with metastatic bone disease were extracted from the Surveillance, Epidemiology, and End Results database. The Yost Index was geocoded using factor analysis and categorized into quintiles using census tract-level American Community Service (ACS) 5-year estimates and seven nSES measures. Multivariable logistic regression models calculated odds ratios (ORs) of refusal of recommended surgery and 95% confidence intervals (CIs), adjusting for clinical covariates. RESULTS: A total of 138,257 patients were included, of which 14,943 (10.8%) were recommended for surgical resection. Patients in the lowest nSES quintile had 57% higher odds of refusing surgical treatment than those in the highest quintile (aOR = 1.57, 95% CI 1.30-1.91, p < 0.001). Patients in the lowest nSES quintile also had a 31.2% higher age-adjusted incidence rate of not being recommended for surgery compared with those in the highest quintile (186.4 vs. 142.1 per 1 million, p < 0.001). Black patients had 34% higher odds of refusing treatment compared with White patients (aOR = 1.34, 95% CI 1.14-1.58, p = 0.003). Advanced age, unmarried status, and patients with aggressive cancer subtypes were associated with higher odds of refusing surgery (p < 0.001). CONCLUSIONS: nSES and race/ethnicity are independent predictors of a patient refusing surgery for metastatic cancer to bone, even after adjusting for various clinical covariates. Effective strategies for addressing these inequalities and improving the access and quality of care of patients with a lower nSES and minority backgrounds are needed.

Projections of Single-level and Multilevel Spinal Instrumentation Procedure Volume and Associated Costs for Medicare Patients to 2050.

BACKGROUND: Instrumented spinal fusions can be used in the treatment of vertebral fractures, spinal instability, and scoliosis or kyphosis. Construct-level selection has notable implications on postoperative recovery, alignment, and mobility. This study sought to project future trends in the implementation rates and associated costs of single-level versus multilevel instrumentation procedures in US Medicare patients aged older than 65 years in the United States. METHODS: Data were acquired from the Centers for Medicare & Medicaid Services from January 1, 2000, to December 31, 2019. Procedure costs and counts were abstracted using Current Procedural Terminology codes to identify spinal level involvement. The Prophet machine learning algorithm was used, using a Bayesian Inference framework, to generate point forecasts for 2020 to 2050 and 95% forecast intervals (FIs). Sensitivity analyses were done by comparing projections from linear, log-linear, Poisson and negative-binomial, and autoregressive integrated moving average models. Costs were adjusted for inflation using the 2019 US Bureau of Labor Statistics' Consumer Price Index. RESULTS: Between 2000 and 2019, the annual spinal instrumentation volume increased by 776% (from 7,342 to 64,350 cases) for single level, by 329% (from 20,319 to 87,253 cases) for two-four levels, by 1049% (from 1,218 to 14,000 cases) for five-seven levels, and by 739% (from 193 to 1,620 cases) for eight-twelve levels (P < 0.0001). The inflation-adjusted reimbursement for single-level instrumentation procedures decreased 45.6% from $1,148.15 to $788.62 between 2000 and 2019, which is markedly lower than for other prevalent orthopaedic procedures: total shoulder arthroplasty (-23.1%), total hip arthroplasty (-39.2%), and total knee arthroplasty (-42.4%). By 2050, the number of single-level spinal instrumentation procedures performed yearly is projected to be 124,061 (95% FI, 87,027 to 142,907), with associated costs of $93,900,672 (95% FI, $80,281,788 to $108,220,932). CONCLUSIONS: The number of single-level instrumentation procedures is projected to double by 2050, while the number of two-four level procedures will double by 2040. These projections offer a measurable basis for resource allocation and procedural distribution.

A population-based study of COVID-19 mortality risk in US cancer patients.

BACKGROUND: In this study, we provide the largest analysis to date of a US-based cancer cohort to characterize death from COVID-19. METHODS: A total of 4 020 669 patients across 15 subtypes living with cancer in 2020 and included in the National Cancer Institute's Surveillance, Epidemiology, and End Results database were abstracted. We investigated prognostic factors for death due to COVID-19 using a Cox proportional hazards model and calculated hazard ratios (HRs). Standardized mortality ratios were calculated using observed mortality counts from Surveillance, Epidemiology, and End Results and expected mortality based on US mortality rates. RESULTS: A total of 291 323 patients died, with 14 821 (5.1%) deaths attributed to COVID-19 infection. The COVID-19 disease-specific mortality rate was 11.81/10 000-persons years, and the standardized mortality ratio of COVID-19 was 2.30 (95% confidence interval [CI] = 2.26 to 2.34; P < .0001). COVID-19 ranked as the second leading cause of death following ischemic heart disease (5.2%) among 26 noncancer causes of death. Patients who are older (80 years and older vs 49 years and younger: HR = 21.47, 95% CI = 19.34 to 23.83), male (vs female: HR = 1.46, 95% CI = 1.40 to 1.51), unmarried (vs married: HR = 1.47, 95% CI = 1.42 to 1.53), and Hispanic or non-Hispanic African American (vs non-Hispanic White: HR = 2.04, 95% CI = 1.94 to 2.14 and HR = 2.03, 95% CI = 1.94 to 2.14, respectively) were at greatest risk of COVID-19 mortality. CONCLUSIONS: We observed that people living with cancer are at 2 times greater risk of dying from COVID-19 compared with the general US population. This work may be used by physicians and public health officials in the creation of survivorship programs that mitigate the risk of COVID-19 mortality.

Association of Socioeconomic Status With Worse Overall Survival in Patients With Bone and Joint Cancer.

BACKGROUND: The effect of socioeconomic status (SES) on the outcomes of patients with metastatic cancer to bone has not been adequately studied. We analyzed the association between the Yost Index, a composite geocoded SES score, and overall survival among patients who underwent nonprimary surgical resection for bone metastases. METHODS: This population-based study used data from the National Cancer Institute's Surveillance, Epidemiology, and End Results database (2010 to 2018). We categorized bone and joint sites using International Classification of Disease-O-3 recodes. The Yost Index was geocoded using a factor analysis and categorized into quintiles using census tract-level American Community Service 5-year estimates and seven measures: median household income, median house value, median rent, percent below 150% of the poverty line, education index, percent working class, and percent unemployed. Multivariate Cox regression models were used to calculate adjusted hazard ratios of overall survival and 95% confidence intervals. RESULTS: A total of 138,158 patients were included. Patients with the lowest SES had 34% higher risk of mortality compared with those with the highest SES (adjusted hazard ratio of 1.34, 95% confidence interval: 1.32 to 1.37, P < 0.001). Among patients who underwent nonprimary surgery of the distant bone tumor (n = 11,984), the age-adjusted mortality rate was 31.3% higher in the lowest SES patients compared with the highest SES patients (9.9 versus 6.8 per 100,000, P < 0.001). Patients in the lowest SES group showed more racial heterogeneity (63.0% White, 33.5% Black, 3.1% AAPI) compared with the highest SES group (83.9% White, 4.0% Black, 11.8% AAPI, P < 0.001). Higher SES patients are more likely to be married (77.5% versus 59.0%, P < 0.0001) and to live in metropolitan areas (99.6% versus 73.6%, P < 0.0001) compared with lower SES patients. DISCUSSION: Our results may have implications for developing interventions to improve access and quality of care for patients from lower SES backgrounds, ultimately reducing disparities in orthopaedic surgery.

Causes of death among people living with metastatic cancer.

Studying survivorship and causes of death in patients with advanced or metastatic cancer remains an important task. We characterize the causes of death among patients with metastatic cancer, across 13 cancer types and 25 non-cancer causes and predict the risk of death after diagnosis from the diagnosed cancer versus other causes (e.g., stroke, heart disease, etc.). Among 1,030,937 US (1992-2019) metastatic cancer survivors, 82.6% of patients (n = 688,529) died due to the diagnosed cancer, while 17.4% (n = 145,006) died of competing causes. Patients with lung, pancreas, esophagus, and stomach tumors are the most likely to die of their metastatic cancer, while those with prostate and breast cancer have the lowest likelihood. The median survival time among patients living with metastases is 10 months; our Fine and Gray competing risk model predicts 1 year survival with area under the receiver operating characteristic curve of 0.754 (95% CI [0.754, 0.754]). Leading non-cancer deaths are heart disease (32.4%), chronic obstructive and pulmonary disease (7.9%), cerebrovascular disease (6.1%), and infection (4.1%).

Using K-Means Clustering to Identify Physician Clusters by Electronic Health Record Burden and Efficiency.

Objectives: Electronic health records (EHRs) have transformed the way modern medicine is practiced, but they remain a major source of documentation burden among physicians. This study aims to use data from Signal, a tool provided by the Epic EHR, to analyze physician metadata in the Montefiore Health System via cluster analysis to assess EHR burden and efficiency. Methods: Data were obtained for a one-month period (July 2020) representing a return to normal operation post-telemedicine implementation. Six metrics from Signal were used to phenotype physicians: time on unscheduled days, pajama time, time outside of 7 AM to 7 PM, turnaround time, proficiency score, and visits closed the same day. k-Means clustering was employed to group physicians, and the clusters were assessed overall and by sex and specialty. Results: Our results demonstrate the partitioning of physicians into a higher-efficiency, lower-time outside of scheduled hours (TOSH) cluster and a lower-efficiency, higher-TOSH cluster even when stratified by sex and specialty. Intra-cluster comparisons showed general homogeneity of physician metrics with the exception of the higher-efficiency, lower-TOSH cluster when stratified by sex. Conclusions: Taken together, the clusters uniquely reflect the EHR efficiency-burden of the Montefiore Health System. Applying k-means clustering to readily available EHR data allows for a scalable, efficient, and adaptable approach of assessing physician EHR burden and efficiency, allowing health systems to examine documentation trends and target wellness interventions.

Reirradiation with stereotactic body radiotherapy for primary or secondary lung malignancies: Tumor control probability and safety analyses.

BACKGROUND: Reirradiation with stereotactic body radiotherapy (SBRT) for patients with primary or secondary lung malignancies represents an appealing definitive approach, but its feasibility and safety are not well defined. The purpose of this study was to investigate the tumor control probability (TCP) and toxicity for patients receiving reirradiation with SBRT. PATIENTS AND METHODS: Eligible patients with recurrence of primary or secondary lung malignancies from our hospital were subjected to reirradiation with SBRT, and PubMed- and Embase-indexed articles were reviewed. The patient characteristics, pertinent SBRT dosimetric details, local tumor control, and toxicities were extracted. The logistic dose-response models were compared for TCP and overall survival (OS) in terms of the physical dose and three-, four-, and five-fraction equivalent doses. RESULTS: The data of 17 patients from our hospital and 195 patients extracted from 12 articles were summarized. Reirradiation with SBRT yielded 2-year estimates of 80% TCP for doses of 50.10 Gy, 55.85 Gy, and 60.54 Gy in three, four, and five fractions, respectively. The estimated TCP with common fractionation schemes were 50%, 60%, and 70% for 42.04 Gy, 47.44 Gy, and 53.32 Gy in five fractions, respectively. Similarly, the 2-year estimated OS was 50%, 60%, and 70% for 41.62 Gy, 46.88 Gy, and 52.55 Gy in five fractions, respectively. Central tumor localization may be associated with severe toxicity. CONCLUSIONS: Reirradiation with SBRT doses of 50-60 Gy in 3-5 fractions is feasible for appropriately selected patients with recurrence of peripheral primary or secondary lung malignancies, but should be carefully considered for centrally-located tumors due to potentially severe toxicity. Further studies are warranted for optimal dose/fractionation schedules and more accurate selection of patients suitable for reirradiation with SBRT.

Future trends in incidence and long-term survival of metastatic cancer in the United States.

BACKGROUND: Previous studies have demonstrated epidemiological trends in individual metastatic cancer subtypes; however, research forecasting long-term incidence trends and projected survivorship of metastatic cancers is lacking. We assess the burden of metastatic cancer to 2040 by (1) characterizing past, current, and forecasted incidence trends, and (2) estimating odds of long-term (5-year) survivorship. METHODS: This retrospective, serial cross-sectional, population-based study used registry data from the Surveillance, Epidemiology, and End Results (SEER 9) database. Average annual percentage change (AAPC) was calculated to describe cancer incidence trends from 1988 to 2018. Autoregressive integrating moving average (ARIMA) models were used to forecast the distribution of primary metastatic cancer and metastatic cancer to specific sites from 2019 to 2040 and JoinPoint models were fitted to estimate mean projected annual percentage change (APC). RESULTS: The average annual percent change (AAPC) in incidence of metastatic cancer decreased by 0.80 per 100,000 individuals (1988-2018) and we forecast an APC decrease by 0.70 per 100,000 individuals (2018-2040). Analyses predict a decrease in metastases to liver (APC = -3.40, 95% CI [-3.50, -3.30]), lung (APC (2019-2030) = -1.90, 95% CI [-2.90, -1.00]); (2030-2040) = -3.70, 95% CI [-4.60, -2.80]), bone (APC = -4.00, 95% CI [-4.30, -3.70]), and brain (APC = -2.30, 95% CI [-2.60, -2.00]). By 2040, patients with metastatic cancer are predicted to have 46.7% greater odds of long-term survivorship, driven by increasing plurality of patients with more indolent forms of metastatic disease. CONCLUSIONS: By 2040, the distribution of metastatic cancer patients is predicted to shift in predominance from invariably fatal to indolent cancers subtypes. Continued research on metastatic cancers is important to guide health policy and clinical intervention efforts, and direct allocations of healthcare resources.

Cancer that has spread beyond the area where it originated and into different organs is called metastatic cancer. This study analyzed trends in metastatic cancer incidence, the proportion of those with metastatic cancer surviving 5 years after diagnosis and the locations in the body each cancer had spread to. The incidence of metastatic cancer decreased between 1988 and 2018 and is expected to continue to decrease until 2040. Some of the most common locations cancer spreads to is the lung, liver, brain, and bone. Metastatic cancer incidence to these areas is predicted to decrease. Also, the likelihood of surviving for more than 5 years after diagnosis with metastatic cancer is predicted to increase by 2040. This research should facilitate optimal planning of future healthcare resources and policy.

Unknown Causes of Death in Cancer Patients.

OBJECTIVES: Deaths from an unknown cause are difficult to adjudicate and oncologic studies of comparative effectiveness often demonstrate inconsistencies in incorporating these deaths and competing events (eg, heart disease and stroke) in their analyses. In this study, we identify cancer patients most at risk for death of an unknown cause. METHODS: This retrospective, population-based study used cancer registry data from the Surveillance, Epidemiology, and End Results database (1992-2015). The absolute rate of unknown causes of death (COD) cases stratified by sex, marital status, race, treatment, and cancer site were calculated and a multivariable logistic regression model was applied to obtain adjusted odds ratios with 95% CIs. RESULTS: Out of 7,154,779 cancer patients across 22 cancer subtypes extracted from Surveillance, Epidemiology, and End Results, 3,448,927 died during follow-up and 276,068 (7.4%) of these deaths were from unknown causes. Patients with an unknown COD had a shorter mean survival time compared with patients with known COD (36.3 vs 65.7 mo, P < 0.001). The contribution of unknown COD to total mortality was highest in patients with more indolent cancers (eg, prostate [12.7%], thyroid [12.3%], breast [10.7%]) and longer follow-up (eg, >5 to 10 y). One, 3, and 5-year cancer-specific survival (CSS) calculations including unknown COD were significantly decreased compared with CSS estimates excluding cancer patients with unknown COD. CONCLUSION: Of the patients, 7.4% died of unknown causes during follow-up and the proportion of death was higher with longer follow-up and among more indolent cancers. The attribution of high percentages of unknown COD to cancer or non-cancer causes could impact population-based cancer registry studies or clinical trial outcomes with respect to measures involving CSS and mortality.

Cyclic electron flow around photosystem II in silico: How it works and functions in vivo.

To date, cyclic electron flow around PSI (PSI-CEF) has been considered the primary (if not the only) mechanism accepted to adjust the ratio of linear vs cyclic electron flow that is essential to adjust the ratio of ATP/NADPH production needed for CO2 carboxylation. Here we provide a kinetic model showing that cyclic electron flow within PSII (PSII-CEF) is essential to account for the accelerating rate of decay in flash-induced oscillations of O2 yield as the PQ pool progressively reduces to PQH2. Previously, PSII-CEF was modeled by backward transitions using empirical Markov models like Joliot-Kok (J-K) type. Here, we adapted an ordinary differential equation methodology denoted RODE1 to identify which microstates within PSII are responsible for branching between PSII-CEF and Linear Electron Flow (LEF). We applied it to simulate the oscillations of O2 yield from both Chlorella ohadii, an alga that shows strong PSII-CEF attributed to high backward transitions, and Synechococcus elongatus sp. 7002, a widely studied model cyanobacterium. RODE2 simulations reveal that backward transitions occur in microstates that possess a QB- semiquinone prior to the flash. Following a flash that forms microstates populating (QAQB)2-, PSII-CEF redirects these two electrons to the donor side of PSII only when in the oxidized S2 and S3 states. We show that this backward transition pathway is the origin of the observed period-2 oscillations of flash O2 yield and contributes to the accelerated decay of period-4 oscillations. This newly added pathway improved RODE1 fits for cells of both S. elongatus and C. ohadii. RODE2 simulations show that cellular adaptation to high light intensity growth is due to a decrease in QB availability (empty or blocked by Q2-B), or equivalently due to a decrease in the difference in reduction potential relative to QA/QA-. PSII-CEF provides an alternative mechanism for rebalancing the NADPH:ATP ratio that occurs rapidly by adjusting the redox level of the PQ:PQH2 pool and is a necessary process for energy metabolism in aquatic phototrophs.

Effect of Telemedicine and the COVID-19 Pandemic on Medical Trainees' Usage of the Electronic Health Record in the Outpatient Setting.

OBJECTIVES: This study aimed to (1) determine the impact of COVID-19 (coronavirus disease 2019) and the corresponding increase in use of telemedicine on volume, efficiency, and burden of electronic health record (EHR) usage by residents and fellows; and (2) to compare these metrics with those of attending physicians. METHODS: We analyzed 11 metrics from Epic's Signal database of outpatient physician user logs for active residents/fellows at our institution across three 1-month time periods: August 2019 (prepandemic/pre-telehealth), May 2020 (mid-pandemic/post-telehealth implementation), and July 2020 (follow-up period) and compared these metrics between trainees and attending physicians. We also assessed how the metrics varied for medical trainees in primary care as compared with subspecialties. RESULTS: Analysis of 141 residents/fellows and 495 attendings showed that after telehealth implementation, overall patient volume, Time in In Basket per day, Time outside of 7 a.m. to 7 p.m., and Time in notes decreased significantly compared with the pre-telehealth period. Female residents, fellows, and attendings had a lower same day note closure rate before and during the post-telehealth implementation period and spent greater time working outside of 7 a.m. to 7 p.m. compared with male residents, fellows, and attendings (p < 0.01) compared with the pre-telehealth period. Attending physicians had a greater patient volume, spent more time, and were more efficient in the EHR compared with trainees (p < 0.01) in both the post-telehealth and follow-up periods as compared with the pre-telehealth period. CONCLUSION: The dramatic change in clinical operations during the pandemic serves as an inflection point to study changes in physician practice patterns in the EHR. We observed that (1) female physicians closed fewer notes the same day and spent more time in the EHR outside of normal working hours compared with male physicians, and (2) attending physicians had higher patient volumes and also higher efficiency in the EHR compared with resident physicians.

Trends in seasonal pollen and asthma-related morbidity among adults and children in a U.S. high-density urban center, 2001-2020.

OBJECTIVE: To analyze the long-term trends in pollen counts and asthma-related emergency department visits (AREDV) in adult and pediatric populations in the Bronx. METHODS: Daily values of adult and pediatric AREDV were retrospectively obtained from three major Bronx hospitals using ICD-10 codes and pollen counts were obtained from the Armonk station from 2001-2020. Wilcoxon Ranked Sum was applied to compare median values, while Spearman correlation was employed to examine the association between these variables, for both decades and each season. RESULTS: The median value of pediatric AREDV increased by 200% from the 1st to 2nd decade (p < 0.001) and AREDV peak shifted from predominantly the spring season in the 1st decade to the fall and winter seasons in the 2nd decade. Seasonal patterns were consistent over 20 years with summer AREDV lower than all other seasons (9 vs. 17 per day) (p < 0.001). Spring tree pollen peaks were correlated with AREDV peaks (rho = 0.34) (p < 0.001). Tree pollen exceeding 100 grains/m3 corresponded to a median of 19.0 AREDVs while all other tree pollen (0 - 99 grains/m3) corresponded to a median of 15.0 AREDVs (p < 0.001). AREDVs sharply declined in 2020, coinciding with the emergence of COVID-19. CONCLUSIONS: Pollen and AREDVs peak earlier in the spring and are more strongly interconnected, while asthma rates among children are rapidly rising, particularly in the fall and winter. These findings can advise targeted awareness campaigns for better management of asthma related morbidity.

Bridging the gap between Kok-type and kinetic models of photosynthetic electron transport within Photosystem II.

Historically, two modeling approaches have been developed independently to describe photosynthetic electron transport (PET) from water to plastoquinone within Photosystem II (PSII): Markov models account for losses from finite redox transition probabilities but predict no reaction kinetics, and ordinary differential equation (ODE) models account for kinetics but not for redox inefficiencies. We have developed an ODE mathematical framework to calculate Markov inefficiencies of transition probabilities as defined in Joliot-Kok-type catalytic cycles. We adapted a previously published ODE model for PET within PSII that accounts for 238 individual steps to enable calculation of the four photochemical inefficiency parameters (miss, double hit, inactivation, backward transition) and the four redox accumulation states (S-states) that are predicted by the most advanced of the Joliot-Kok-type models (VZAD). Using only reaction kinetic parameters without other assumptions, the RODE-calculated time-averaged (e.g., equilibrium) inefficiency parameters and equilibrium S-state populations agree with those calculated by time-independent Joliot-Kok models. RODE also predicts their time-dependent values during transient photochemical steps for all 96 microstates involving PSII redox cofactors. We illustrate applications to two cyanobacteria, Arthrospira maxima and Synechococcus sp. 7002, where experimental data exists for the inefficiency parameters and the S-state populations, and historical data for plant chloroplasts as benchmarks. Significant findings: RODE predicts the microstates responsible for period-4 and period-2 oscillations of O2 and fluorescence yields and the four inefficiency parameters; the latter parameters are not constant for each S state nor in time, in contrast to predictions from Joliot-Kok models; some of the recombination pathways that contribute to the backward transition parameter are identified and found to contribute when their rates exceed the oxidation rate of the terminal acceptor pool (PQH2); prior reports based on the assumptions of Joliot-Kok parameters may require reinterpretation.