Observable variations in human sex ratio at birth

The human sex ratio at birth (SRB), defined as the ratio between the number of newborn boys to the total number of newborns, is typically slightly greater than 1/2 (more boys than girls) and tends to vary across different geographical regions and time periods. In this large-scale study, we sought to validate previously-reported associations and test new hypotheses using statistical analysis of two very large datasets incorporating electronic medical records (EMRs). One of the datasets represents over half (∼ 150 million) of the US population for over 8 years (IBM Watson Health MarketScan insurance claims) while another covers the entire Swedish population (∼ 9 million) for over 30 years (the Swedish National Patient Register). After testing more than 100 hypotheses, we showed that neither dataset supported models in which the SRB changed seasonally or in response to variations in ambient temperature. However, increased levels of a diverse array of air and water pollutants, were associated with lower SRBs, including increased levels of industrial and agricultural activity, which served as proxies for water pollution. Moreover, some exogenous factors generally considered to be environmental toxins turned out to induce higher SRBs. Finally, we identified new factors with signals for either higher or lower SRBs. In all cases, the effect sizes were modest but highly statistically significant owing to the large sizes of the two datasets. We suggest that while it was unlikely that the associations have arisen from sex-specific selection mechanisms, they are still useful for the purpose of public health surveillance if they can be corroborated by empirical evidences.

New Time-Related Insights into an Old Laboratory Parameter: Early CRP Discovered by IBM Watson Trauma Pathway Explorer© as a Predictor for Sepsis in Polytrauma Patients

The University Hospital Zurich together with IBM® invented an outcome prediction tool based on the IBM Watson technology, the Watson Trauma Pathway Explorer®. This tool is an artificial intelligence to predict three outcome scenarios in polytrauma patients: the Systemic Inflammatory Response Syndrome (SIRS) and sepsis within 21 days as well as death within 72 h. The knowledge of a patient’s future under standardized trauma treatment might be of utmost importance. Here, new time-related insights on the C-reactive protein (CRP) and sepsis are presented. Meanwhile, the validated IBM Watson Trauma Pathway Explorer® offers a time-related insight into the most frequent laboratory parameters. In total, 3653 patients were included in the databank used by the application, and ongoing admissions are constantly implemented. The patients were grouped according to sepsis, and the CRP was analyzed according to the point of time at which the value was acquired (1, 2, 3, 4, 6, 8, 12, 24, and 48 h and 3, 4, 5, 7, 10, 14, and 21 days). The differences were analyzed using the Mann–Whitney U-Test; binary logistic regression was used to determine the dependency of prediction, and the Closest Top-left Threshold Method presented time-specific thresholds at which CRP is predictive for sepsis. The data were considered as significant at p < 0.05, all analyses were performed in R. The differences in the CRP value of the non-sepsis and sepsis groups are starting to be significant between 6 and 8 h (p < 0.05) after admission inclusive of post hoc analysis, and the binary logistic regression depicts a similar picture. The level of significance is reached between 6 and 8 h (p < 0.05) after admission. The knowledge of the outcome reflected by the CRP in polytrauma patients improves the surgeon’s tactical position to indicate operations to reduce antigenic load and avoid an infectious adverse outcome.

Productivity Loss and Indirect Costs Among Non-Hodgkin Lymphoma Patients and Their Caregivers

Introduction: The impact of cancer care and management beyond treatment is significantly high for cancer patients. Due to the complexities of cancer treatment, patients are heavily reliant upon ancillary support often rendered by friends and family. One significant yet unquantifiable impact of cancer on society is productivity loss of both patients and their caregivers. Non-Hodgkin lymphoma is considered largely incurable with a protracted clinical course punctuated with multiple remission and relapses, warranting repeated treatment and intensive clinical testing, which necessitates significant engagement of patients and caregivers. Many patients are members of the workforce at the age of diagnosis. Both working patients and caregivers need time for medical care, which translates to indirect economic impact due to lost productivity. The objectives of this analysis were to evaluate the productivity loss and indirect costs in patients with chronic lymphocytic leukemia (CLL), mantle cell lymphoma (MCL), marginal zone lymphoma (MZL), or Waldenström macroglobulinemia (WM) and their caregivers. Methods: The MarketScan Commercial and Health and Productivity Management databases were used to identify patients with CLL, MCL, MZL, and WM (using ICD-9/ICD-10 codes) who were continuously enrolled for ≥6 months pre- and ≥1 month post-diagnosis (index date) from 1/1/2010 to 12/31/2019. The final study cohort included patients aged 18-64 who were full-time workers with eligibility of absentee, or short-/long-term disability on index date and for ≥1 month in follow-up. Those who were pregnant during the study period were excluded. Adult, full-time employed caregivers, defined as family members covered under the same health plan as the patient, and continuously enrolled ≥6 months pre- and ≥1 month post-index, were also identified. Among those with eligibility, the percentage with a claim of absentee, short- or long-term disability (patients only), and associated productivity time loss and indirect costs during follow-up were examined. Lost wages were calculated using the US Bureau of Labor Statistics 2019 report. For short- or long-term disabilities, mean daily wages were reduced to 70% of typical wages. Productivity time loss and costs were reported per-patient-per-month (PPPM) for each lymphoma. Results: The final patient cohort included 3,450 CLL, 448 MCL, 1,052 MZL and 394 WM patients; the caregiver cohort included 1,435 CLL, 171 MCL, 437 MZL and 190 WM caregivers. Among eligible patients, there were higher proportions of patients that had absentee claims (CLL, 76%; MCL, 72%; MZL, 72%; WM, 82%), followed by short-term disability (CLL, 16%; MCL, 36%; MZL, 18%; WM, 17%) and long-term disability (CLL, 3%; MCL, 10%; MZL, 3%; WM, 3%) (Figure 1A). The proportions of caregivers with absentee claims (CLL, 78%; MCL, 90%; MZL, 69%; WM, 75%) were also higher than those with short-term disability (CLL, 7%; MCL, 10%; MZL, 4%; WM, 8%) (Figure 1B). For all 4 lymphoma types, average illness-related absentee hours were higher in patients than caregivers (CLL, 9.5 vs 6.9; MCL, 44.5 vs 3.6; MZL, 17.0 vs 5.0; WM, 18.2 vs 8.1). A similar pattern was observed for short-term disability days (CLL, 6.9 vs 4.2; MCL, 10.8 vs 3.4; MZL, 7.0 vs 2.2; WM, 6.7 vs 4.8). Average PPPM indirect costs were higher for patients with long-term disability (CLL, $1,433; MCL, $1,233; MZL, $1,302; WM, $2,056) than with short-term disability (CLL, $1,203; MCL, $1,950; MZL, $1,145; WM. $1,177) or absentee claims (CLL, $365; MCL, $1,606; MZL, $612; WM, $662), except for patients with MCL (Figure 2A). Similar trends were observed among caregivers, though the indirect costs due to absenteeism and short-term disability were higher in patients than caregivers (Figure 2B). Conclusions: This real-world evidence study uncovered patients with CLL, MCL, MZL and WM and their caregivers incur substantial disease burden as shown by their productivity loss and indirect costs. Effective treatments that can offer a cure or better remission rates and shorter duration with less toxicity may not only enhance the patients and caregivers' quality of life but also reduce work loss. The availability of oral, targeted therapies has resulted in higher remission rates, durable responses, manageable toxicities and improved quality of life in trials. Future studies are needed to understand the impact of these oral, targeted therapies on patients' and caregivers' productivity. Figure 1 Figure 1. Disclosures Yang: BeiGene, Ltd.: Current Employment. Liu: BeiGene, Ltd.: Current Employment. Irwin: IBM Watson Health: Current Employment; BeiGene, Ltd.: Consultancy. Packnett: IBM Watson Health: Current Employment; BeiGene, Ltd.: Consultancy. Lew: BeiGene, Ltd.: Consultancy; IBM Watson Health: Current Employment. Noxon: BeiGene, Ltd.: Consultancy; IBM Watson Health: Current Employment. Tang: BeiGene, Ltd.: Current Employment. Chanan-Khan: BieGene, Jansen, Ascentage: Consultancy; BeiGene, Jansen, Ascentage: Honoraria; Alpha2 Pharmaceuticals: Patents & Royalties: Tabi; Cellectar: Current equity holder in publicly-traded company; Ascentage, Starton, Cellectar, NonoDev, Alpha2 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Alpha2 Pharmaceuticals, NonoDev, Starton: Current holder of stock options in a privately-held company; Ascentage: Research Funding.

1337. Medically Attended (MA) Illness Due to Respiratory Syncytial Virus (RSV) Infection among Infants in the United States during the 2016–17, 2017–18, 2018–19, and 2019–20 RSV Seasons: The Need for All-Infant Protection

Background RSV-associated lower respiratory tract infection (LRTI) is the leading cause of infant hospitalization. Most studies of RSV have focused on infants with underlying comorbidities, including prematurity. The purpose of this analysis is to describe the burden of RSV LRTI across all medical settings and in all infants experiencing their first RSV season. Methods Using de-identified claims data from two commercial (MarketScan Commercial, MSC; Optum Clinformatics, OC) and one public (MarketScan Medicaid, MSM) insurance database, we estimated the prevalence of MA RSV LRTI among infants born between April 1, 2016 and June 30, 2019 in their first RSV season. Estimates were made by gestational age, presence/absence of comorbidities, and setting (inpatient, emergency department and outpatient). Due to limited laboratory testing, we defined MA RSV LRTI using two sets of ICD-10-CM diagnosis codes: a specific definition (identifying RSV explicitly) and a sensitive definition that included unspecified bronchiolitis. The first specific diagnosis triggered a search for another MA RSV LRTI diagnosis (either specific or sensitive) within the next 7 days. In the sensitive analysis, the first diagnosis was allowed to meet the sensitive definition. Setting was recorded as the highest level of care attached to a MA RSV LRTI diagnosis within this 7-day period. Results Using the specific (sensitive) definitions, 4.2% (12.2%), 6.8% (16.8%), and 2.7% (7.2%) of newborns had an MA RSV LRTI diagnosis during their first respiratory season across the MSC, MSM, and OC datasets (Table 1). Term infants without comorbidities accounted for 77% (83%), 79% (86%), and 80 (81%) of all MA RSV LRTI, and 21% (10%), 19% (10%), and 21% (10%) of all infants with MA RSV LRTI had an inpatient hospital stay (Table 2). Term infants without comorbidities accounted for 69% (68%), 67% (79%), and 73% (73%) of all MA RSV LRTI inpatients (Table 2). Conclusion In commercial and public claims data, during their first RSV season, term infants without comorbidities accounted for a sizable majority of inpatient, emergency room, and outpatient encounters for RSV LRTI in the US. To address the burden of RSV LRTI, future RSV prevention efforts should target all infants. Funding Sanofi Pasteur, AstraZeneca Disclosures Jason Gantenberg, MPH, Sanofi Pasteur (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Nicole Zimmerman, MS, IBM Watson Health (Employee, Nicole Zimmerman is an employee of IBM, which was compensated by Sanofi to complete this work.)Sanofi (Other Financial or Material Support, Nicole Zimmerman is an employee of IBM, which was compensated by Sanofi to complete this work.) Andrew R. Zullo, PharmD, PhD, ScM, Sanofi Pasteur (Grant/Research Support, Research Grant or Support) Brendan Limone, PharmD, PharmD, Sanofi Pasteur (Other Financial or Material Support, IBM was contracted by Sanofi to perform analysis) Clarisse Demont, n/a, Sanofi Pasteur (Employee, Shareholder) Sandra S. Chaves, MD, MSc, Sanofi Pasteur (Employee) William V. La Via, MD, AstraZeneca (Shareholder)Sanofi Pasteur (Employee) Christopher Nelson, PhD, Epidemiology, Sanofi Pasteur (Employee) Christopher Rizzo, MD, Sanofi (Employee) David A. Savitz, PhD, Sanofi Pasteur (Grant/Research Support) Robertus Van Aalst, MSc, Sanofi Pasteur (Employee, Shareholder)

1439. Epidemiology and 12- Month Antibiotic Use in the Outpatient Setting among Adult Patients with Complicated Urinary Tract Infections: A Retrospective Database Analysis

Background Complicated urinary tract infections (cUTI) are one of the most common bacterial infections and represent substantial burden to the health care system. Here, we examine the epidemiology and treatment patterns associated with cUTI in a large US database containing longitudinal inpatient (IP) and outpatient (OP) patient-level data. Methods We conducted a retrospective cohort study of adult patients in the IBM MarketScan® Commercial or Medicare Supplemental Databases with at least 1 IP or non-diagnostic OP claim with a diagnosis for cUTI between January 1, 2017 and June 30, 2019. Patients meeting the following criteria were included for analysis: (1) ≥18 years of age on the index date, (2) ≥6 months of continuous enrollment (CE) with medical and pharmacy benefits prior to the index date, (3) ≥12 months of CE following the index date or evidence of death, and (4) no evidence of a prior cUTI during the 6-month baseline period. Demographics and clinical characteristics were quantified. Patients were classified as IP if they were hospitalized during 30-day post index date; remaining patients were classified as OP. Antibiotics received in the OP setting in the 12-months post index date were examined. Results 95,423 patients met study criteria. Most (86.4%) patients were Commercially insured, mean (SD) age was 53.6 (18.1) and 70.4% were female. Mean baseline Charlson Comorbidity Index was 0.77. During the 30-day post index date, 22.2% were treated as IP and 77.8% were strictly treated as OP. In the 12-month OP follow-up period among index IP, 78.2% required ≥ 2 antibiotics, 38.2% required ≥4 antibiotics, and 41.6% received an IV antibiotic. In the 12-month OP follow-up period among index OP, 81.8% required ≥2 antibiotics, 38.2% required ≥4 antibiotics, and 46.8% received an IV antibiotic. For both IP and OP, fluoroquinolones were the most common oral antibiotic class (57.7%), followed by cephalosporins (39.2%), penicillins (30.3%), trimethoprim-sulfamethoxazole (29.8%), and nitrofurantoin (25.2%). Cephalosporins were the most common IV antibiotic class (38.5%). Conclusion Regardless of index treatment setting, approximately 40% of all cUTI patients required ≥4 antibiotic therapy and almost half with receive an IV antibiotic in the outpatient setting in the 12-months post index date. Disclosures Thomas Lodise, Jr., PharmD, PhD, Astra-Zeneca (Consultant)Bayer (Consultant)DoseMe (Consultant, Advisor or Review Panel member)ferring (Consultant)genentech (Consultant)GSK (Consultant)Melinta (Consultant)merck (Consultant, Independent Contractor)nabriva (Consultant)paratek (Consultant, Advisor or Review Panel member, Speaker’s Bureau)shionogi (Consultant, Advisor or Review Panel member, Speaker’s Bureau)Spero (Consultant)tetraphase (Consultant)Venatrox (Consultant) Thomas Lodise, Jr., PharmD, PhD, Melinta Therapeutics (Individual(s) Involved: Self): Consultant; Merck (Individual(s) Involved: Self): Consultant, Scientific Research Study Investigator; Paratek (Individual(s) Involved: Self): Consultant; Shionogi (Individual(s) Involved: Self): Consultant, Speakers’ bureau; Spero (Individual(s) Involved: Self): Consultant; Tetraphase Pharmaceuticals Inc. (Individual(s) Involved: Self): Consultant Janna Manjelievskaia, PhD, MPH, IBM Watson Health (Employee)Spero Therapeutics (Consultant) Matthew Brouillette, MPH, Spero Therapeutics, Inc. (Other Financial or Material Support, I am an employee of IBM Watson Health, who received funds from Spero Therapeutics, Inc. to conduct this analysis.) Kate Sulham, MPH, Spero Therapeutics (Consultant)

Artificial Intelligence, Robots and Bioethical Challenges

"The arrival of digital research, where the object of research is transformed into numerical data, makes it possible to study the world and medicine, using new epistemological paradigms. What matters now is only the correlation between two quantities of data, with no concern for any consistent theory that explains such correlation. Today these correlations are used to predict with acceptable accuracy. What seems to be the outcome of this new revolution is the dominance of information, a conceptual labyrinth whose most common definition is based on an equally problematic category-data. The technological evolution of information and of the world seen as a series of data takes its concrete form in artificial intelligence (AI) and in robots. We are now able to construct machines that can make autonomous decisions and coexist with human beings. And in the context of healthcare it is possible to develop diagnostic approach, prescribe medication (see IBM Watson Program) or offer radiosurgery systems like Cyberknife. Contemporary society presents extremely delicate challenges where the most important variable is not intelligence but rather the little time available in which to make a decision. Here, cognitive mechanisms can have important applications. A series of anthropological and bioethical reflections can help to understand the challenges in the healthcare field: “Is it clear how this logic of hyper-individualization, governed by the use of artificial intelligence, will undermine the humanistic need for solidarity in this in deeds and mindset, in favor of private relationships between individuals and organizations?” (E. Sadin). "

How to Appropriate Value from General-Purpose Technology by Applying Open Innovation

Artificial intelligence increasingly attracts attention and investments. However, appropriating value from this general-purpose technology (GPT) can be difficult. To understand these challenges, this article analyzes why IBM failed to generate significant profits from IBM Watson Health despite its promising starting points. The findings suggest that, considering the characteristics of GPT, an overly closed approach for taking it to market contributed to the failure. Furthermore, conditions such as the immaturity and the complexity of the application field intensified the challenges. This study suggests that using a strong appropriability regime in open innovation can enhance the appropriation of value from a GPT.

The Effect of Misalignment of CEO Personality and Corporate Governance Structures on Firm Performance

We utilize the IBM Watson Personality Insights service to analyze CEOs’ verbal communication during conference calls to infer CEOs’ Big Five personality traits, which we employ to estimate their risk tolerance levels. We then explore whether the misalignment of CEO risk tolerance and governance structures is associated with company performance. Using a two-stage contingency approach, we test two hypotheses: (1) CEO risk tolerance and corporate governance structures are associated; and (2) misalignment of these structures with risk tolerance is negatively associated with financial performance. Based on a sample of 8208 firm-year observations during 2002–2013, we find support for both predictions. Our results support upper echelons theory and suggest that knowledge about CEOs’ inherent personality traits is important and relevant for governance mechanisms to work effectively.