Noninvasive, MultiOmic, and Multicompartmental Biomarkers of Reflux Disease: A Systematic Review.

BACKGROUND AND AIMS: Gastroesophageal reflux disease (GERD) is a prevalent gastrointestinal disorder that may complicate conditions such as obstructive airway disease. Our group has identified predictive biomarkers of GERD in particulate exposed first responders with obstructive airway disease. In addition, GERD diagnosis and treatment is costly and invasive. In light of these clinical concerns, we aimed to systematically review studies identifying noninvasive, multiOmic, and multicompartmental biomarkers of GERD. METHODS: A systematic review of PubMed and Embase was performed using keywords focusing on reflux disease and biomarkers and registered with PROSPERO. We included original human studies in English, articles focusing on noninvasive biomarkers of GERD published after December 31, 2009. GERD subtypes (non-erosive reflux disease and erosive esophagitis) and related conditions (Barrett's Esophagus [BE] and Esophageal Adenocarcinoma). Predictive measures were synthesized and risk of bias assessed (Newcastle-Ottawa Scale). RESULTS: Initial search identified n = 238 studies andn 13 articles remained after applying inclusion/exclusion criteria. Salivary pepsin was the most studied biomarker with significant sensitivity and specificity for GERD. Serum assessment showed elevated levels of Tumor Necrosis Factor-alpha in both GERD and Barrett's. Exhaled breath volatile sulfur compounds and acetic acid were associated with GERD. Oral Microbiome: Models with Lautropia, Streptococcus, and Bacteroidetes showed the greatest discrimination between BE and controls vs Lautropia; ROCAUC 0.94 (95% confidence interval; 0.85-1.00). CONCLUSION: Prior studies identified significant multiOmic, multicompartmental noninvasive biomarker risks for GERD and BE. However, studies have a high risk of bias and the reliability and accuracy of the biomarkers identified are greatly limited, which further highlights the need to discover and validate clinically relevant noninvasive biomarkers of GERD.

Selective adaptation of SARS-CoV-2 Omicron under booster vaccine pressure: a multicentre observational study.

BACKGROUND: High rates of vaccination and natural infection drive immunity and redirect selective viral adaptation. Updated boosters are installed to cope with drifted viruses, yet data on adaptive evolution under increasing immune pressure in a real-world situation are lacking. METHODS: Cross-sectional study to characterise SARS-CoV-2 mutational dynamics and selective adaptation over >1 year in relation to vaccine status, viral phylogenetics, and associated clinical and demographic variables. FINDINGS: The study of >5400 SARS-CoV-2 infections between July 2021 and August 2022 in metropolitan New York portrayed the evolutionary transition from Delta to Omicron BA.1-BA.5 variants. Booster vaccinations were implemented during the Delta wave, yet booster breakthrough infections and SARS-CoV-2 re-infections were almost exclusive to Omicron. In adjusted logistic regression analyses, BA.1, BA.2, and BA.5 had a significant growth advantage over co-occurring lineages in the boosted population, unlike BA.2.12.1 or BA.4. Selection pressure by booster shots translated into diffuse adaptive evolution in Delta spike, contrasting with strong, receptor-binding motif-focused adaptive evolution in BA.2-BA.5 spike (Fisher Exact tests; non-synonymous/synonymous mutation rates per site). Convergent evolution has become common in Omicron, engaging spike positions crucial for immune escape, receptor binding, or cleavage. INTERPRETATION: Booster shots are required to cope with gaps in immunity. Their discriminative immune pressure contributes to their effectiveness but also requires monitoring of selective viral adaptation processes. Omicron BA.2 and BA.5 had a selective advantage under booster vaccination pressure, contributing to the evolution of BA.2 and BA.5 sublineages and recombinant forms that predominate in 2023. FUNDING: The study was supported by NYU institutional funds and partly by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center.

Roadmap for embedding health equity research into learning health systems.

BACKGROUND: Achieving health equity is vital to fulfil the quadruple aim for optimal healthcare system performance. Traditionally, academic medicine and healthcare systems have focused their efforts on addressing health inequities with an emphasis on improving workforce diversity. Although this approach is an important requisite, a diverse workforce alone is not sufficient; rather holistic health equity should be established as the anchoring principal mission of all academic medical centres, residing at the intersection of clinical care, education, research and community. METHODS: NYU Langone Health (NYULH) has embarked on significant institutional changes to position itself as an equity-focused learning health system. One-way NYULH accomplishes this is through the establishment of a health equity research roadmap, which serves as the organising framework through which we conduct embedded pragmatic research in our healthcare delivery system to target and eliminate health inequities across our tripartite mission of patient care, medical education and research. RESULTS: This article outlines each of the six elements of the NYULH roadmap. These elements include: (1) developing processes for collecting accurate disaggregate data on race, ethnicity and language, sexual orientation and gender identity and disability; (2) using a data-driven approach to identify health equity gaps; (3) creating performance and metric-based quality improvement goals to measure progress toward elimination of health equity gaps; (4) investigating the root cause of the identified health equity gap; (5) developing and evaluating evidence-based solutions to address and resolve the inequities; and (6) continuous monitoring and feedback for system improvements. CONCLUSION: Application of each element of the roadmap can provide a model for how academic medical centres can use pragmatic research to embed a culture of health equity into their health system.

Rethinking Surge Preparedness After COVID-19: Effective Patient Load Balancing Within Health Systems and Beyond.

Within weeks of New York State's first confirmed case of COVID-19, New York City became the epicenter of the nation's COVID-19 pandemic. With more than 80,000 COVID-19 hospitalizations during the first wave alone, hospitals in downstate New York were forced to adapt existing procedures to manage the surge and care for patients facing a novel disease. Given the unprecedented surge, effective patient load balancing-moving patients from a hospital with diminishing capacity to another hospital within the same health system with relatively greater capacity-became chief among the capabilities required of New York health systems. The Greater New York Hospital Association invited members of downstate New York's 6 largest health systems to talk about how each of their systems evolved their patient load balancing procedures throughout the pandemic. Informed by their insights, experiences, lessons learned, and collaboration, we collectively present a set of consensus recommendations and best practices for patient load balancing at the facility and health system level, which may inform regional approaches to patient load balancing.

The impact of COVID-19 monoclonal antibodies on clinical outcomes: A retrospective cohort study.

PURPOSE: Despite progress in the treatment of coronavirus disease 2019 (COVID-19), including the development of monoclonal antibodies (mAbs), more clinical data to support the use of mAbs in outpatients with COVID-19 is needed. This study is designed to determine the impact of bamlanivimab, bamlanivimab/etesevimab, or casirivimab/imdevimab on clinical outcomes within 30 days of COVID-19 diagnosis. METHODS: A retrospective cohort study was conducted at a single academic medical center with 3 campuses in Manhattan, Brooklyn, and Long Island, NY. Patients 12 years of age or older who tested positive for COVID-19 or were treated with a COVID-19-specific therapy, including COVID-19 mAb therapies, at the study site between November 24, 2020, and May 15, 2021, were included. The primary outcomes included rates of emergency department (ED) visit, inpatient admission, intensive care unit (ICU) admission, or death within 30 days from the date of COVID-19 diagnosis. RESULTS: A total of 1,344 mAb-treated patients were propensity matched to 1,344 patients with COVID-19 patients who were not treated with mAb therapy. Within 30 days of diagnosis, among the patients who received mAb therapy, 101 (7.5%) presented to the ED and 79 (5.9%) were admitted. Among the patients who did not receive mAb therapy, 165 (12.3%) presented to the ED and 156 (11.6%) were admitted (relative risk [RR], 0.61 [95% CI, 0.50-0.75] and 0.51 [95% CI, 0.40-0.64], respectively). Four mAb patients (0.3%) and 2.64 control patients (0.2%) were admitted to the ICU (RR, 01.51; 95% CI, 0.45-5.09). Six mAb-treated patients (0.4%) and 3.37 controls (0.3%) died and/or were admitted to hospice (RR, 1.61; 95% CI, 0.54-4.83). mAb therapy in ambulatory patients with COVID-19 decreases the risk of ED presentation and hospital admission within 30 days of diagnosis.

Clinical and genomic signatures of SARS-CoV-2 Delta breakthrough infections in New York.

BACKGROUND: In 2021, Delta became the predominant SARS-CoV-2 variant worldwide. While vaccines have effectively prevented COVID-19 hospitalization and death, vaccine breakthrough infections increasingly occurred. The precise role of clinical and genomic determinants in Delta infections is not known, and whether they contributed to increased rates of breakthrough infections compared to unvaccinated controls. METHODS: We studied SARS-CoV-2 variant distribution, dynamics, and adaptive selection over time in relation to vaccine status, phylogenetic relatedness of viruses, full genome mutation profiles, and associated clinical and demographic parameters. FINDINGS: We show a steep and near-complete replacement of circulating variants with Delta between May and August 2021 in metropolitan New York. We observed an increase of the Delta sublineage AY.25 (14% in vaccinated, 7% in unvaccinated), its spike mutation S112L, and AY.44 (8% in vaccinated, 2% in unvaccinated) with its nsp12 mutation F192V in breakthroughs. Delta infections were associated with younger age and lower hospitalization rates than Alpha. Delta breakthrough infections increased significantly with time since vaccination, and, after adjusting for confounders, they rose at similar rates as in unvaccinated individuals. INTERPRETATION: We observed a modest adaptation of Delta genomes in breakthrough infections in New York, suggesting an improved genomic framework to support Delta's epidemic growth in times of waning vaccine protection despite limited impact on vaccine escape. FUNDING: The study was supported by NYU institutional funds. The NYULH Genome Technology Center is partially supported by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center.

Progressive dysbiosis of human orodigestive microbiota along the sequence of gastroesophageal reflux, Barrett's esophagus and esophageal adenocarcinoma.

The incidence of esophageal adenocarcinoma (EA) has drastically increased in the United States since 1970s for unclear reasons. We hypothesized that the widespread usage of antibiotics has increased the procarcinogenic potential of the orodigestive microbiota along the sequence of gastroesophageal reflux (GR), Barrett's esophagus (BE) and EA phenotypes. This case control study included normal controls (NC) and three disease phenotypes GR, BE and EA. Microbiota in the mouth, esophagus, and stomach, and rectum were analyzed using 16S rRNA gene sequencing. Overall, we discovered 44 significant pairwise differences in abundance of microbial taxa between the four phenotypes, with 12 differences in the mouth, 21 in the esophagus, two in the stomach, and nine in the rectum. Along the GR→BE→EA sequence, oral and esophageal microbiota were more diversified, the dominant genus Streptococcus was progressively depleted while six other genera Atopobium, Actinomyces, Veillonella, Ralstonia, Burkholderia and Lautropia progressively enriched. In NC, Streptococcus appeared to control populations of other genera in the foregut via numerous negative and positive connections, while in disease states, the rich network was markedly simplified. Inferred gene functional content showed a progressive enrichment through the stages of EA development in genes encoding antibiotic resistance, ligands of Toll-like and NOD-like receptors, nitrate-nitrite-nitric oxide pathway and acetaldehyde metabolism. The orodigestive microbiota is in a progressive dysbiotic state along the GR-BE-EA sequence. The increasing dysbiosis and antibiotic and procarcinogenic genes in the disease states warrants further study to define their roles in EA pathogenesis.

Oral and gastric microbiome in relation to gastric intestinal metaplasia.

Evidence suggests that Helicobacter pylori plays a role in gastric cancer (GC) initiation. However, epidemiologic studies on the specific role of other bacteria in the development of GC are lacking. We conducted a case-control study of 89 cases with gastric intestinal metaplasia (IM) and 89 matched controls who underwent upper gastrointestinal endoscopy at three sites affiliated with NYU Langone Health. We performed shotgun metagenomic sequencing using oral wash samples from 89 case-control pairs and antral mucosal brushing samples from 55 case-control pairs. We examined the associations of relative abundances of bacterial taxa and functional pathways with IM using conditional logistic regression with and without elastic-net penalty. Compared with controls, oral species Peptostreptococcus stomatis, Johnsonella ignava, Neisseria elongata and Neisseria flavescens were enriched in cases (odds ratios [ORs] = 1.29-1.50, P = .004-.01) while Lactobacillus gasseri, Streptococcus mutans, S parasanguinis and S sanguinis were under-represented (ORs = 0.66-0.76, P = .006-.042) in cases. Species J ignava and Filifactor alocis in the gastric microbiota were enriched (ORs = 3.27 and 1.43, P = .005 and .035, respectively), while S mutans, S parasanguinis and S sanguinis were under-represented (ORs = 0.61-0.75, P = .024-.046), in cases compared with controls. The lipopolysaccharide and ubiquinol biosynthesis pathways were more abundant in IM, while the sugar degradation pathways were under-represented in IM. The findings suggest potential roles of certain oral and gastric microbiota, which are correlated with regulation of pathways associated with inflammation, in the development of gastric precancerous lesions.

Clinical and genomic signatures of rising SARS-CoV-2 Delta breakthrough infections in New York.

In 2021, Delta has become the predominant SARS-CoV-2 variant worldwide. While vaccines effectively prevent COVID-19 hospitalization and death, vaccine breakthrough infections increasingly occur. The precise role of clinical and genomic determinants in Delta infections is not known, and whether they contribute to increased rates of breakthrough infections compared to unvaccinated controls. Here, we show a steep and near complete replacement of circulating variants with Delta between May and August 2021 in metropolitan New York. We observed an increase of the Delta sublineage AY.25, its spike mutation S112L, and nsp12 mutation F192V in breakthroughs. Delta infections were associated with younger age and lower hospitalization rates than Alpha. Delta breakthroughs increased significantly with time since vaccination, and, after adjusting for confounders, they rose at similar rates as in unvaccinated individuals. Our data indicate a limited impact of vaccine escape in favor of Delta's increased epidemic growth in times of waning vaccine protection.

Effect of antibiotic treatment on Oxalobacter formigenes colonization of the gut microbiome and urinary oxalate excretion.

The incidence of kidney stones is increasing in the US population. Oxalate, a major factor for stone formation, is degraded by gut bacteria reducing its intestinal absorption. Intestinal O. formigenes colonization has been associated with a lower risk for recurrent kidney stones in humans. In the current study, we used a clinical trial of the eradication of Helicobacter pylori to assess the effects of an antibiotic course on O. formigenes colonization, urine electrolytes, and the composition of the intestinal microbiome. Of 69 healthy adult subjects recruited, 19 received antibiotics for H. pylori eradication, while 46 were followed as controls. Serial fecal samples were examined for O. formigenes presence and microbiota characteristics. Urine, collected serially fasting and following a standard meal, was tested for oxalate and electrolyte concentrations. O. formigenes prevalence was 50%. Colonization was significantly and persistently suppressed in antibiotic-exposed subjects but remained stable in controls. Urinary pH increased after antibiotics, but urinary oxalate did not differ between the control and treatment groups. In subjects not on antibiotics, the O. formigenes-positive samples had higher alpha-diversity and significantly differed in Beta-diversity from the O. formigenes-negative samples. Specific taxa varied in abundance in relation to urinary oxalate levels. These studies identified significant antibiotic effects on O. formigenes colonization and urinary electrolytes and showed that overall microbiome structure differed in subjects according to O. formigenes presence. Identifying a consortium of bacterial taxa associated with urinary oxalate may provide clues for the primary prevention of kidney stones in healthy adults.

Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in workload,which created a strain on the staff and limited resources. Further, methods to better understand and characterise the predictors of morbidity and mortality was needed. METHODS: We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3395 hospital admissions with COVID-19. Multiple methods were applied, and final model was selected based on performance. A variable importance algorithm was used for interpretability, and understanding of performance and predictors was applied to the best model. We built a model with an area under the receiver operating characteristic curve of 83-97 to identify predictors and patients with high risk of mortality due to COVID-19. Oximetry, respirations, blood urea nitrogen, lymphocyte per cent, calcium, troponin and neutrophil percentage were important features, and key ranges were identified that contributed to a 50% increase in patients' mortality prediction score. With an increasing negative predictive value starting 0.90 after the second day of admission suggests we might be able to more confidently identify likely survivors DISCUSSION: This study serves as a use case of a machine learning methods with visualisations to aide clinicians with a better understanding of the model and predictors of mortality. CONCLUSION: As we continue to understand COVID-19, computer assisted algorithms might be able to improve the care of patients.

Trends in COVID-19 Risk-Adjusted Mortality Rates.

Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.

Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City.

Importance: Black and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. Objective: To compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. Design, Setting, and Participants: This retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status. Exposures: Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). Main Outcomes and Measures: The likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). Results: Among 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). Conclusions and Relevance: In this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients.

The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables. In retrospective and prospective validation, the model achieves high average precision (88.6% 95% CI: [88.4-88.7] and 90.8% [90.8-90.8]) and discrimination (95.1% [95.1-95.2] and 86.8% [86.8-86.9]) respectively. We implemented and integrated the model into the EHR, achieving a positive predictive value of 93.3% with 41% sensitivity. Preliminary results suggest clinicians are adopting these scores into their clinical workflows.

Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.

OBJECTIVE: To describe outcomes of people admitted to hospital with coronavirus disease 2019 (covid-19) in the United States, and the clinical and laboratory characteristics associated with severity of illness. DESIGN: Prospective cohort study. SETTING: Single academic medical center in New York City and Long Island. PARTICIPANTS: 5279 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between 1 March 2020 and 8 April 2020. The final date of follow up was 5 May 2020. MAIN OUTCOME MEASURES: Outcomes were admission to hospital, critical illness (intensive care, mechanical ventilation, discharge to hospice care, or death), and discharge to hospice care or death. Predictors included patient characteristics, medical history, vital signs, and laboratory results. Multivariable logistic regression was conducted to identify risk factors for adverse outcomes, and competing risk survival analysis for mortality. RESULTS: Of 11 544 people tested for SARS-Cov-2, 5566 (48.2%) were positive. After exclusions, 5279 were included. 2741 of these 5279 (51.9%) were admitted to hospital, of whom 1904 (69.5%) were discharged alive without hospice care and 665 (24.3%) were discharged to hospice care or died. Of 647 (23.6%) patients requiring mechanical ventilation, 391 (60.4%) died and 170 (26.2%) were extubated or discharged. The strongest risk for hospital admission was associated with age, with an odds ratio of >2 for all age groups older than 44 years and 37.9 (95% confidence interval 26.1 to 56.0) for ages 75 years and older. Other risks were heart failure (4.4, 2.6 to 8.0), male sex (2.8, 2.4 to 3.2), chronic kidney disease (2.6, 1.9 to 3.6), and any increase in body mass index (BMI) (eg, for BMI >40: 2.5, 1.8 to 3.4). The strongest risks for critical illness besides age were associated with heart failure (1.9, 1.4 to 2.5), BMI >40 (1.5, 1.0 to 2.2), and male sex (1.5, 1.3 to 1.8). Admission oxygen saturation of <88% (3.7, 2.8 to 4.8), troponin level >1 (4.8, 2.1 to 10.9), C reactive protein level >200 (5.1, 2.8 to 9.2), and D-dimer level >2500 (3.9, 2.6 to 6.0) were, however, more strongly associated with critical illness than age or comorbidities. Risk of critical illness decreased significantly over the study period. Similar associations were found for mortality alone. CONCLUSIONS: Age and comorbidities were found to be strong predictors of hospital admission and to a lesser extent of critical illness and mortality in people with covid-19; however, impairment of oxygen on admission and markers of inflammation were most strongly associated with critical illness and mortality. Outcomes seem to be improving over time, potentially suggesting improvements in care.

Colorectal Cancer Among Gout Patients Undergoing Colonoscopy.

BACKGROUND/OBJECTIVE: The connection between gout and various cancers remains unclear. We assessed the relationship between gout and colorectal cancer in a population of veterans. METHODS: We reviewed the Computerized Patient Record System of the VA New York Harbor Health Care System to assess the 10-year occurrence of colorectal cancer in patients with gout undergoing colonoscopy, versus patients with osteoarthritis but no gout. RESULTS: Gout and osteoarthritis subjects were similar in age, ethnicity, body mass index, and smoking history. Among 581 gout and 598 osteoarthritis subjects with documented colonoscopies, the 10-year prevalence of colorectal cancer was significantly lower in gout (0.8%) versus osteoarthritis (3.7%) (p = 0.0008) patients. Differences in colorectal cancer rates remained significant after stratifying for nonsteroidal anti-inflammatory drug use. Among gout subjects, use of colchicine and/or allopurinol, as well as the presence/absence of concomitant osteoarthritis, did not influence colorectal cancer occurrence. On subanalysis, differences in colorectal cancer occurrence between gout and osteoarthritis subjects persisted among those who underwent diagnostic (0.5% in gout vs 4.6% in osteoarthritis subjects, p < 0.001) but not screening (0.9% in gout subjects vs 1% in osteoarthritis subjects, p = 1.0) colonoscopy. There was no significant difference in nonmalignant colorectal polyp occurrence between gout and osteoarthritis subjects. CONCLUSIONS: Subjects with gout had decreased colonoscopy-documented occurrence of colorectal cancer compared with osteoarthritis subjects, suggesting a possible protective effect.

Bending the cost curve: time series analysis of a value transformation programme at an academic medical centre.

BACKGROUND: Reducing costs while increasing or maintaining quality is crucial to delivering high value care. OBJECTIVE: To assess the impact of a hospital value-based management programme on cost and quality. DESIGN: Time series analysis of non-psychiatric, non-rehabilitation, non-newborn patients discharged between 1 September 2011 and 31 December 2017 from a US urban, academic medical centre. INTERVENTION: NYU Langone Health instituted an institution-wide programme in April 2014 to increase value of healthcare, defined as health outcomes achieved per dollar spent. Key features included joint clinical and operational leadership; granular and transparent cost accounting; dedicated project support staff; information technology support; and a departmental shared savings programme. MEASUREMENTS: Change in variable direct costs; secondary outcomes included changes in length of stay, readmission and in-hospital mortality. RESULTS: The programme chartered 74 projects targeting opportunities in supply chain management (eg, surgical trays), operational efficiency (eg, discharge optimisation), care of outlier patients (eg, those at end of life) and resource utilisation (eg, blood management). The study cohort included 160 434 hospitalisations. Adjusted variable costs decreased 7.7% over the study period. Admissions with medical diagnosis related groups (DRG) declined an average 0.20% per month relative to baseline. Admissions with surgical DRGs had an early increase in costs of 2.7% followed by 0.37% decrease in costs per month. Mean expense per hospitalisation improved from 13% above median for teaching hospitals to 2% above median. Length of stay decreased by 0.25% per month relative to prior trends (95% CI -0.34 to 0.17): approximately half a day by the end of the study period. There were no significant changes in 30-day same-hospital readmission or in-hospital mortality. Estimated institutional savings after intervention costs were approximately $53.9 million. LIMITATIONS: Observational analysis. CONCLUSION: A systematic programme to increase healthcare value by lowering the cost of care without compromising quality is achievable and sustainable over several years.