Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.

OBJECTIVE: To overcome the limitations associated with the collection and curation of COVID-19 outcome data in biobanks, this study proposes the use of polygenic risk scores (PRS) as reliable proxies of COVID-19 severity across three large biobanks: the Michigan Genomics Initiative (MGI), UK Biobank (UKB), and NIH All of Us. The goal is to identify associations between pre-existing conditions and COVID-19 severity. METHODS: Drawing on a sample of more than 500,000 individuals from the three biobanks, we conducted a phenome-wide association study (PheWAS) to identify associations between a PRS for COVID-19 severity, derived from a genome-wide association study on COVID-19 hospitalization, and clinical pre-existing, pre-pandemic phenotypes. We performed cohort-specific PRS PheWAS and a subsequent fixed-effects meta-analysis. RESULTS: The current study uncovered 23 pre-existing conditions significantly associated with the COVID-19 severity PRS in cohort-specific analyses, of which 21 were observed in the UKB cohort and two in the MGI cohort. The meta-analysis yielded 27 significant phenotypes predominantly related to obesity, metabolic disorders, and cardiovascular conditions. After adjusting for body mass index, several clinical phenotypes, such as hypercholesterolemia and gastrointestinal disorders, remained associated with an increased risk of hospitalization following COVID-19 infection. CONCLUSION: By employing PRS as a proxy for COVID-19 severity, we corroborated known risk factors and identified novel associations between pre-existing clinical phenotypes and COVID-19 severity. Our study highlights the potential value of using PRS when actual outcome data may be limited or inadequate for robust analyses.

Uptake of COVID-19 and influenza vaccines in relation to preexisting chronic conditions in the European countries.

BACKGROUND: The suboptimal uptake of COVID-19 and influenza vaccines among those with non-communicable chronic diseases is a public health concern, because it poses a higher risk of severe illness for individuals with underlying health conditions, emphasizing the need to address barriers to vaccination and ensure adequate protection for this vulnerable population. In the present study, we aimed to identify whether people with chronic illnesses are more likely to get vaccinated against COVID-19 and influenza in the European Union. METHODS: Cross-sectional data on 49,253 men (n = 20,569) and women (n = 28,684) were obtained from the ninth round of the Survey of Health, Ageing and Retirement in Europe (June - August, 2021). The outcome variables were self-reported COVID-19 and influenza vaccine uptake status. The association between the uptake of the vaccines and six preexisting conditions including high blood pressure, high blood cholesterol, chronic lung disease, diabetes, chronic bronchitis, and asthma was estimated using binary logistic regression methods. RESULTS: The vaccination coverage for COVID-19 ranged from close to 100% in Denmark (98.2%) and Malta (98.2%) to less than 50% in Bulgaria (19.1%) and Romania (32.7%). The countries with the highest percentage of participants with the influenza vaccine included Malta (66.7%), Spain (63.7%) and the Netherlands (62.5%), and those with the lowest percentage included Bulgaria (3.7%), Slovakia (5.8%) and Poland (9.2%). Participants with high blood pressure were 3% less likely [Risk difference (RD) = -0.03, 95% CI = -0.04, -0.03] to report taking COVID-19 and influenza [RD = -0.03, 95% CI= -0.04, -0.01] vaccine. Those with chronic lung disease were 4% less likely [RD = -0.04, 95% CI= -0.06, -0.03] to report taking COVID-19 and 2% less likely [RD= -0.02, 95% CI = -0.04, -0.01] to report taking influenza vaccine. Men and women with high blood pressure were 3% less likely to have reported taking both of the vaccines. CONCLUSIONS: Current findings indicate a suboptimal uptake of COVID-19 and influenza vaccines among adult men and women in the EU countries. Those with preexisting conditions, including high blood pressure and chronic lung disease are less likely to take the vaccines.

Pre-existing conditions associated with post-acute sequelae of COVID-19.

Post-acute sequelae of COVID-19 (PASC) are conditions that occur or remain at least 28 days after SARS-CoV-2 infection. While some risk factors for PASC have been identified, little is known about pre-existing conditions that render one susceptible to developing PASC. Data from participants (n = 1224) in a longitudinal COVID-19 cohort study in Arizona were used to investigate comorbid conditions associated with PASC. After adjustment of the models for age, BMI, gender, race, and smoking, the following pre-existing conditions were statistically significantly associated with the development of PASC: asthma (OR = 1.54; 95% CI = 1.10-2.15); chronic constipation (OR = 4.29; 95% CI = 1.15-16.00); reflux (OR = 1.54; 95% CI = 1.01-2.34); rheumatoid arthritis (OR = 3.69; 95%CI = 1.15-11.82); seasonal allergies (OR = 1.56; 95% CI = 1.22-1.98); and depression/anxiety (OR = 1.72; 95% CI = 1.17-2.52). When grouping conditions together, statistically significant associations with PASC were observed for respiratory (OR = 1.47; 95% CI = 1.06-2.14); gastrointestinal (OR = 1.62; 95% CI = 1.16-2.26), and autoimmune conditions (OR = 4.38; 95% CI = 1.59-12.06). After adjustment for severity of acute SARS-CoV-2 infection and depression/anxiety, seasonal allergies (OR = 1.48; 95% CI 1.15-1.91) and autoimmune disease (OR = 3.78; 95% CI - 1.31-10.91) remained significantly associated with risk for PASC. These findings indicate that numerous pre-existing conditions may be associated with an increased risk for the development of PASC. Patients with these conditions should consider taking extra steps to avoid infection.

Nanomaterial-induced toxicity in pathophysiological models representative of individuals with pre-existing medical conditions.

The integration of nanomaterials (NMs) into an ever-expanding number of daily used products has proven to be highly desirable in numerous industries and applications. Unfortunately, the same "nano" specific physicochemical properties, which make these materials attractive, may also contribute to hazards for individuals exposed to these materials. In 2021, it was estimated that 7 out of 10 deaths globally were accredited to chronic diseases, such as chronic liver disease, asthma, and cardiovascular-related illnesses. Crucially, it is also understood that a significant proportion of global populace numbering in the billions are currently living with a range of chronic undiagnosed health conditions. Due to the significant number of individuals affected, it is important that people suffering from chronic disease also be considered and incorporated in NM hazard assessment strategies. This review examined and analyzed the literature that focused on NM-induced adverse health effects in models which are representative of individuals exhibiting pre-existing medical conditions with focus on the pulmonary, cardiovascular, hepatic, gastrointestinal, and central nervous systems. The overall objective of this review was to outline available data, highlighting the important role of pre-existing disease in NM-induced toxicity with the aim of establishing a weight of evidence approach to inform the public on the potential hazards posed by NMs in both healthy and compromised persons in general population.

Comorbidities in newly diagnosed epilepsy: Pre-existing health conditions are common and complex across age groups.

OBJECTIVES: People with epilepsy have a higher prevalence of medical and psychiatric comorbidities compared to the general population. Comorbidities are associated with poor epilepsy outcomes, and there have been recommendations for screening and early identification to improve clinical management. Data from 'First Seizure Clinics' (FSCs) with expert epileptological review can inform about disorders already present at the point of diagnosis of epilepsy or unprovoked seizures. Here, we aimed to describe pre-existing conditions with a focus on psychiatric, substance use, cardiac, neurological, and cancer health domains. METHODS: We included 1383 adults who received a new diagnosis of epilepsy or unprovoked seizures at Austin Hospital (AH) or Royal Melbourne Hospital (RMH) (Australia) FSCs from 2000 to 2010. Data were audited from FSC records, primarily detailed interviews undertaken by epileptologists. Logistic regression examined age distribution and other risk factors. RESULTS: The median age at FSC presentation was 37 years (IQR 26-53, range 18-94). Pre-existing conditions were reported by 40 %; from 32 % in the youngest group (18-30 years) to 53 % in the oldest (65+ years). Psychiatric (18 %) and substance use (16 %) disorders were most common, with higher prevalence among patients 18 to 65 years of age compared to those older than 65 years (p < 0.001). Cardiac, neurological, or cancer conditions were reported by 3-6 %, most often amongst those older than 65 years (p < 0.01). Eight percent (n = 112) reported disorders in >1 health domain. The commonest combination was a psychiatric condition with substance use disorder. Of the sixty-two patients reporting this combination, 61 were ≤65 years of age. CONCLUSIONS: Pre-existing health conditions are present in a substantial proportion of patients diagnosed with epilepsy or unprovoked seizures. Disorders are highest amongst elders, but one-third of younger adults also reported positive histories. These are predominantly psychiatric and/or substance use disorders, conditions strongly associated with poor outcomes in the general population. These findings inform post-diagnosis planning and management, as well as research examining post-diagnostic outcomes and associations between comorbidities and epilepsy.

Critical windows of exposure to air pollution and gestational diabetes: assessing effect modification by maternal pre-existing conditions and environmental factors.

BACKGROUND: Ambient air pollution has been associated with gestational diabetes (GD), but critical windows of exposure and whether maternal pre-existing conditions and other environmental factors modify the associations remains inconclusive. METHODS: We conducted a retrospective cohort study of all singleton live birth that occurred between April 1st 2006 and March 31st 2018 in Ontario, Canada. Ambient air pollution data (i.e., fine particulate matter with a diameter ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3)) were assigned to the study population in spatial resolution of approximately 1 km × 1 km. The Normalized Difference Vegetation Index (NDVI) and the Green View Index (GVI) were also used to characterize residential exposure to green space as well as the Active Living Environments (ALE) index to represent the active living friendliness. Multivariable Cox proportional hazards regression models were used to evaluate the associations. RESULTS: Among 1,310,807 pregnant individuals, 68,860 incident cases of GD were identified. We found the strongest associations between PM2.5 and GD in gestational weeks 7 to 18 (HR = 1.07 per IQR (2.7 µg/m3); 95% CI: 1.02 - 1.11)). For O3, we found two sensitive windows of exposure, with increased risk in the preconception period (HR = 1.03 per IQR increase (7.0 ppb) (95% CI: 1.01 - 1.06)) as well as gestational weeks 9 to 28 (HR 1.08 per IQR (95% CI: 1.04 -1.12)). We found that women with asthma were more at risk of GD when exposed to increasing levels of O3 (p- value for effect modification = 0.04). Exposure to air pollutants explained 20.1%, 1.4% and 4.6% of the associations between GVI, NDVI and ALE, respectively. CONCLUSION: An increase of PM2.5 exposure in early pregnancy and of O3 exposure during late first trimester and over the second trimester of pregnancy were associated with gestational diabetes whereas exposure to green space may confer a protective effect.

IMPLICATION OF THREAT FACTORS AND PREEXISTING DISORDERS IN DIFFERENT ISCHEMIC STROKE SUBGROUPS IN ELDERLY PEOPLE: A SYSTEMATIC STUDY.

Ischemic stroke is a major health issue, especially for the older population and it may have severe effects. Stroke diagnosis and treatment have advanced over the last 20 years, which has resulted in considerable reductions in death, long-term impairment, and the need for institutional care. Younger age groups have seen the majority of trials for acute, interventional, and preventive therapy. The purpose of this research was to identify distinct subgroups of older people who had suffered an ischemic stroke and examine the role that risk factors and previous illnesses played in their development. Ischemic stroke risk factors varied by age, gender and exhibited their own unique features. Smoking, cholesterol, and psychological/emotional stress were shown to have the greatest prevalence (p<0.06) among stroke patients aged 45-60. Smoking is associated with a significant (p<0.07) decline in health in elderly people. Our results imply that there are significant patterns of risk factors and preexisting illnesses among the various subgroups of older people who have had an ischemic stroke. Atherosclerotic (large-artery) and cardio embolic (small-artery) ischemic strokes were shown to be the most prevalent among the elderly. Strong associations were found between these subtypes and other risk factors, including higher cholesterol, diabetes, high blood pressure, and atrial fibrillation. This research emphasizes the need for individualized preventative methods and therapeutic therapy, as well as the need to recognize the variability of ischemic stroke in the elderly.

Preexisting Condition Protections Under the Affordable Care Act: Changes in Insurance Coverage, Premium Contributions, and Out-of-Pocket Spending.

OBJECTIVES: In January 2014, the Affordable Care Act (ACA) preexisting condition protections prohibited coverage denials, premium increases, and claim denials on the basis of preexisting conditions. This study aimed to examine changes in coverage and premiums and out-of-pocket spending after the implementation of the preexisting condition protections under the ACA. METHODS: We identified adults aged 18 to 64 years with (n = 59 041) and without preexisting conditions (n = 61 970) from the 2011-2013 and 2015-2017 Medical Expenditure Panel Survey. We used a difference-in-differences and a difference-in-difference-in-differences approach to assess the associations of preexisting condition protections and changes in insurance coverage, premium contributions, and out-of-pocket spending after the ACA. Simple and multivariable logistic or multivariable 2-part models were fitted for the full sample and stratified by family income (low ≤138% federal poverty level [FPL]; middle 139%-400% FPL; and high > 400 FPL). RESULTS: The ACA increased nongroup insurance coverage to a similar extent for individuals with or without preexisting conditions at all income levels. Decreases in premium contributions were observed to a similar extent among families with nongroup private coverage regardless of declinable preexisting condition status, whereas no significant changes were observed among families with group coverage. We found greater decreases in out-of-pocket spending for individuals with preexisting conditions than those without conditions among both individuals covered by nongroup and group insurance, and a greater difference was observed among those covered by nongroup insurance (difference-in-difference-in-differences -$279; 95% confidence interval -$528 to -$29). CONCLUSIONS: The ACA protections were associated with decreases in out-of-pocket spending among adults with preexisting conditions.

Access to health care and mental health-Evidence from the ACA preexisting conditions provision.

This study evaluates the impact of the Affordable Care Act (ACA) preexisting conditions provision on mental health. The 2014 policy ensured individuals with preexisting health conditions the right to obtain insurance coverage. Using longitudinal data from the Panel Study of Income Dynamics between 2007 and 2017 and estimating difference-in-differences models, our study provides evidence that the policy reduced severe mental distress by 1.44 percentage points (baseline mean: 8.09%) among individuals with preexisting physical health conditions. Exploiting pre-ACA, state-level variation in policies providing insurance coverage options to people with preexisting conditions, we find that this improvement in mental well-being is highly associated with the presence of high-risk pools before 2014, which provided individuals with prior health conditions access to coverage. Specifically, we show that our main results are driven by individuals with preexisting health conditions living in the 16 states that did not have high-risk pools. Furthermore, gender-specific analysis shows that the reduction in mental distress is primarily observable among women. When examining potential mechanisms, our analysis provides evidence that increases in insurance coverage, reductions in healthcare expenditures, and improvements in physical health can explain the positive effects of the provision on mental well-being.

Maternal Intensive Care Unit Admission as an Indicator of Severe Acute Maternal Morbidity: A Population-Based Study.

BACKGROUND: Severe acute maternal morbidity (SAMM) accounts for any life-threatening complication during pregnancy or after delivery. Measuring and monitoring SAMM seem critical to assessing the quality of maternal health care. The objectives were to explore the validity of intensive care unit (ICU) admission as an indicator of SAMM by characterizing the profile of women admitted to an ICU and of their ICU stay, according to the association with other SAMM criterion. METHODS: We performed a secondary analysis of the 2540 women with SAMM included in the epidemiology of severe acute maternal morbidity (EPIMOMS) multiregional prospective population-based study (2012-2013, n = 182,309 deliveries). The EPIMOMS definition of SAMM, based on national experts' consensus, is a combination of diagnosis, organ dysfunctions, and intervention criteria, including ICU admission. Among women with SAMM, we identified characteristics associated with maternal ICU admission with or with no other SAMM criterion compared with ICU admission, by using multivariable multinomial logistic regression models. RESULTS: Overall, 511 women were admitted to an ICU during or up to 42 days after pregnancy, for a population-based rate of 2.8 of 1000 deliveries (511/182,309; 95% confidence interval [CI], 2.6-3.1); 15.5% of them (79/511; 95% CI, 12.4-18.9) had no other SAMM criterion compared with ICU admission. Among women with SAMM, the odds of ICU admission with no other morbidity criterion were increased in women with preexisting medical conditions (adjusted odds ratio (aOR), 2.13; 95% CI, 1.17-3.86) and cesarean before labor (aOR, 3.12; 95% CI, 1.47-6.64). Women admitted to ICU with no other SAMM criterion had more often decompensation of a preexisting condition, no interventions for organ support, and a shorter length of stay than women admitted with other SAMM criteria. CONCLUSIONS: Among women with SAMM, 1 in 5 is admitted to an ICU; 15.5% of those admitted in ICU have no other SAMM criterion and a less acute condition. These results challenge the use of ICU admission as a criterion of SAMM.

The impact of pre-existing conditions and perceived health status on mental health during the COVID-19 pandemic.

BACKGROUND: Patients with pre-existing conditions and poor health status are vulnerable for adverse health sequalae during the COVID-19 pandemic. We investigated the association of pre-existing medical conditions and self-perceived health status with the risk of mental health complications during the COVID-19 pandemic. METHODS: In October-December, 2020, 1036 respondents completed online survey that included assessment of pre-existing conditions, self-perceived health status, depressive (Patient Health Questionnaire-8 score ≥ 10), anxiety (Generalized Anxiety Disorders-7 score ≥ 10) and post-traumatic stress (Impact of Events Scale Revised) symptoms, alcohol use (AUDIT), and COVID-19 fear (COVID-19 Fears Questionnaires for Chronic Medical Conditions). RESULTS: Study participants were predominantly women (83%), younger than 61 years of age (94%). Thirty-six percent of respondents had a pre-existing condition and 5% considered their health status as bad or very bad. Pre-existing conditions and poor perceived health status were associated with increased risk for moderate to severe depressive and anxiety symptoms, fear of COVID-19 and post-traumatic stress symptoms, independently from respondents' age, gender, living area, smoking status, exercise, alcohol consumption and diet. CONCLUSIONS: Pre-existing medical conditions and poor perceived health status are associated with increased risk of poor mental health status during the COVID-19 pandemic.

Pre-existing health conditions and severe COVID-19 outcomes: an umbrella review approach and meta-analysis of global evidence.

BACKGROUND: This study applies an umbrella review approach to summarise the global evidence on the risk of severe COVID-19 outcomes in patients with pre-existing health conditions. METHODS: Systematic reviews (SRs) were identified in PubMed, Embase/Medline and seven pre-print servers until December 11, 2020. Due to the absence of age-adjusted risk effects stratified by geographical regions, a re-analysis of the evidence was conducted. Primary studies were extracted from SRs and evaluated for inclusion in the re-analysis. Studies were included if they reported risk estimates (odds ratio (OR), hazard ratio (HR), relative risk (RR)) for hospitalisation, intensive care unit admission, intubation or death. Estimated associations were extracted from the primary studies for reported pre-existing conditions. Meta-analyses were performed stratified for each outcome by regions of the World Health Organization. The evidence certainty was assessed using GRADE. Registration number CRD42020215846. RESULTS: In total, 160 primary studies from 120 SRs contributed 464 estimates for 42 pre-existing conditions. Most studies were conducted in North America, European, and Western Pacific regions. Evidence from Africa, South/Latin America, and the Eastern Mediterranean region was scarce. No evidence was available from the South-East Asia region. Diabetes (HR range 1.2-2.0 (CI range 1.1-2.8)), obesity (OR range 1.5-1.75 (CI range 1.1-2.3)), heart failure (HR range 1.3-3.3 (CI range 0.9-8.2)), COPD (HR range 1.12-2.2 (CI range 1.1-3.2)) and dementia (HR range 1.4-7.7 (CI range 1.2-39.6)) were associated with fatal COVID-19 in different regions, although the estimates varied. Evidence from Europe and North America showed that liver cirrhosis (OR range 3.2-5.9 (CI range 0.9-27.7)) and active cancer (OR range 1.6-4.7 (CI range 0.5-14.9)) were also associated with increased risk of death. Association between HIV and undesirable COVID-19 outcomes showed regional heterogeneity, with an increased risk of death in Africa (HR 1.7 (CI 1.3-2.2)). GRADE certainty was moderate to high for most associations. CONCLUSION: Risk of undesirable COVID-19 health outcomes is consistently increased in certain patient subgroups across geographical regions, showing high variability in others. The results can be used to inform COVID-19 vaccine prioritisation or other intervention strategies.

Preexisting respiratory diseases and clinical outcomes in COVID-19: a multihospital cohort study on predominantly African American population.

BACKGROUND: Comorbidities play a key role in severe disease outcomes in COVID-19 patients. However, the literature on preexisting respiratory diseases and COVID-19, accounting for other possible confounders, is limited. The primary objective of this study was to determine the association between preexisting respiratory diseases and severe disease outcomes among COVID-19 patients. Secondary aim was to investigate any correlation between smoking and clinical outcomes in COVID-19 patients. METHODS:  This is a multihospital retrospective cohort study on 1871 adult patients between March 10, 2020, and June 30, 2020, with laboratory confirmed COVID-19 diagnosis. The main outcomes of the study were severe disease outcomes i.e. mortality, need for mechanical ventilation, and intensive care unit (ICU) admission. During statistical analysis, possible confounders such as age, sex, race, BMI, and comorbidities including, hypertension, coronary artery disease, congestive heart failure, diabetes, any history of cancer and prior liver disease, chronic kidney disease, end-stage renal disease on dialysis, hyperlipidemia and history of prior stroke, were accounted for. RESULTS:  A total of 1871 patients (mean (SD) age, 64.11 (16) years; 965(51.6%) males; 1494 (79.9%) African Americans; 809 (43.2%) with ≥ 3 comorbidities) were included in the study. During their stay at the hospital, 613 patients (32.8%) died, 489 (26.1%) needed mechanical ventilation, and 592 (31.6%) required ICU admission. In fully adjusted models, patients with preexisting respiratory diseases had significantly higher mortality (adjusted Odds ratio (aOR), 1.36; 95% CI, 1.08-1.72; p = 0.01), higher rate of ICU admission (aOR, 1.34; 95% CI, 1.07-1.68; p = 0.009) and increased need for mechanical ventilation (aOR, 1.36; 95% CI, 1.07-1.72; p = 0.01). Additionally, patients with a history of smoking had significantly higher need for ICU admission (aOR, 1.25; 95% CI, 1.01-1.55; p = 0.03) in fully adjusted models. CONCLUSION:  Preexisting respiratory diseases are an important predictor for mortality and severe disease outcomes, in COVID-19 patients. These results can help facilitate efficient resource allocation for critical care services.

The Association of Work-related Stress According to the Demand-Control Model With Aggravation of Pre-existing Disease During the First State of COVID-19 Emergency in Japan.

BACKGROUND: The job environment has changed a lot during the period of the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to investigate the association between work-related stress and aggravation of pre-existing disease in workers during the first state of COVID-19 emergency in Japan. METHODS: Data were obtained from a large internet survey conducted between August 25 and September 30, 2020 in Japan. Participants who reported that they had a job as well as current history of disease(s) (ie, pre-existing conditions) were included (n = 3,090). Aggravation of pre-existing disease during the state of emergency was self-reported. Work-related stress from April 2020 (since the state of COVID-19 emergency) was assessed according to a job demand-control model. Multivariable logistic regression models were used to analyze the association. RESULTS: Aggravation of pre-existing diseases was reported by 334 participants (11%). The numbers of participants with high demand and low control were 112 (18%) and 100 (14%), respectively. Compared to medium demand, high demand was significantly associated with aggravation of pre-existing diseases (odds ratio 1.77; 95% confidence interval, 1.30-2.42). Low control compared to medium control was also significantly associated with aggravation of pre-existing diseases (odds ratio 1.39; 95% confidence interval, 1.02-1.92). CONCLUSION: Work-related stress during the first state of COVID-19 emergency was associated with aggravation of pre-existing disease during that period.

Quantifying the impact of pre-existing conditions on the stage of oesophagogastric cancer at diagnosis: a primary care cohort study using electronic medical records.

BACKGROUND: Pre-existing conditions interfere with cancer diagnosis by offering diagnostic alternatives, competing for clinical attention or through patient surveillance. OBJECTIVE: To investigate associations between oesophagogastric cancer stage and pre-existing conditions. METHODS: Retrospective cohort study using Clinical Practice Research Datalink (CPRD) data, with English cancer registry linkage. Participants aged ≥40 years had consulted primary care in the year before their incident diagnosis of oesophagogastric cancer in 01/01/2010-31/12/2015. CPRD records pre-diagnosis were searched for codes denoting clinical features of oesophagogastric cancer and for pre-existing conditions, including those providing plausible diagnostic alternatives for those features. Logistic regression analysed associations between stage and multimorbidity (≥2 conditions; reference category: no multimorbidity) and having 'diagnostic alternative(s)', controlling for age, sex, deprivation and cancer site. RESULTS: Of 2444 participants provided, 695 (28%) were excluded for missing stage, leaving 1749 for analysis (1265/1749, 72.3% had advanced-stage disease). Multimorbidity was associated with stage [odds ratio 0.63, 95% confidence interval (CI) 0.47-0.85, P = 0.002], with moderate evidence of an interaction term with sex (1.76, 1.08-2.86, P = 0.024). There was no association between alternative explanations and stage (odds ratio 1.18, 95% CI 0.87-1.60, P = 0.278). CONCLUSIONS: In men, multimorbidity is associated with a reduced chance of advanced-stage oesophagogastric cancer, to levels seen collectively for women.

Diagnosing cancer is complicated by existing medical conditions. Diagnosis may be delayed if conditions explain cancer symptoms, or dominate appointments. Diagnosis may be quicker if conditions increase doctor­patient contact. We studied the association between existing illness and stage (early or advanced) of diagnosis with cancer of the stomach or gullet. We studied the primary-care records of patients aged ≥40 years, diagnosed in 01/01/2010­31/12/2015, and got stage from English cancer registry data. We searched the primary-care records for cancer symptoms (e.g. difficulty swallowing), and for 27 conditions that were common or explained cancer symptoms (e.g. difficulty swallowing following a stroke). We analysed cancer stage, looking at age, sex, multimorbidity (two or more conditions) and explanations for symptoms. We studied 1749 patients, of whom 1265 (72.3%) had advanced-stage cancer. The chance of advanced stage was similar in women with (71%, 95% CI 66­75%) or without (69%, 62­76%) multimorbidity. It was lower for men with (70%, 67­74%) than without (79%, 75­83%) multimorbidity. Stage of cancer was not affected by having explanations for cancer symptoms. In summary, for men, multimorbidity is associated with a reduced chance of advanced-stage cancer of the stomach or gullet to levels seen collectively for women.

Chronic anticoagulation is not associated with a reduced risk of acute kidney injury in hospitalised Covid-19 patients.

BACKGROUND: Coronavirus-19 (COVID-19) has been declared a global pandemic by the World Health Organisation. Severe disease typically presents with respiratory failure but Acute Kidney Injury (AKI) and a hypercoagulable state can also occur. Early reports suggest that thrombosis may be linked with AKI. We studied the development of AKI and outcomes of patients with COVID-19 taking chronic anticoagulation therapy. METHODS: Electronic records were reviewed for all adult patients admitted to Manchester University Foundation Trust Hospitals between March 10 and April 302,020 with a diagnosis of COVID-19. Patients with end-stage kidney disease were excluded. AKI was classified as per KDIGO criteria. RESULTS: Of the 1032 patients with COVID-19 studied,164 (15.9%) were taking anticoagulant therapy prior to admission. There were similar rates of AKI between those on anticoagulants and those not anticoagulated (23.8% versus 19.7%) with no difference in the severity of AKI or requirement of renal replacement therapy between groups (1.2% versus 3.5%). Risk factors for AKI included hypertension, pre-existing renal disease and male sex. There was a higher mortality in those taking anticoagulant therapy (40.2% versus 30%). Patients taking anticoagulants were less likely to be admitted to the Intensive Care Unit (8.5% versus 17.4%) and to receive mechanical ventilation (42.9% versus 78.1%). CONCLUSION: Patients on chronic anticoagulant therapy did not have a reduced incidence or severity of AKI suggesting that AKI is unlikely to be thrombotic in nature. Therapeutic anticoagulation is currently still under investigation in randomised controlled studies to determine whether it has a potential role in COVID-19 treatment.

Identifying new-onset conditions and pre-existing conditions using lookback periods in Australian health administrative datasets.

BACKGROUND: The condition onset flag (COF) variable was introduced into the hospitalization coding practice in 2008 to help distinguish between the new and pre-existing conditions. However, Australian datasets collected prior to 2008 lack the COF, potentially leading to data waste. The aim of this study was to determine if an algorithm to lookback across the previous admissions could make this distinction. METHODS: All patients requiring kidney replacement therapy (KRT) identified in the Australia and New Zealand Dialysis and Transplant Registry in New South Wales, South Australia and Tasmania between July 2008 and December 2015 were linked with hospital admission datasets using probabilistic linkage. Three different lookback periods entailing either one, two or three admissions prior to the index admission were investigated. Conditions identified in an index admission but not in the lookback periods were classified as a new-onset condition. Conditions identified in both the index admission and the lookback period were deemed to be pre-existing. The degrees of agreement were determined using the kappa statistic. Conditions examined for new onset were myocardial infarction, pulmonary embolism and pneumonia. Conditions examined for prior existence were diabetes mellitus, hypertension and kidney failure. Secondary analyses evaluated whether the conditions identified as pre-existing using COF were captured consistently in the subsequent admissions. RESULTS: 11 140 patients on KRT with 69 403 admissions were analysed. Lookback over a single admission interval (Period 1) provided the highest rates of true positives with COF for all three new-onset conditions, ranging from 89% to 100%. The levels of agreement were almost perfect for all conditions (k = 0.94-1.00). This was consistent across the different time eras. All lookback periods identified additional new-onset conditions that were not classified by COF: Lookback Period 1 picked up a further 474 myocardial infarction, 84 pulmonary embolism and 1092 pneumonia episodes. Lookback Period 1 had the highest percentage of true positives when identifying the pre-existing conditions (64-80%). The level of agreement was moderate to strong and was similar across the time eras. Secondary analysis showed that not all pre-existing conditions identified using COF carried forward to the subsequent admission (61-82%) but increased when looking forward across >1 admission (87-95%). CONCLUSION: The described algorithm using a lookback period is a pragmatic, reliable and robust means of identifying the new-onset and pre-existing patient conditions, thereby enriching the existing datasets predating the availability of the COF. The findings also highlight the value of concatenating a series of hospital patient admissions to more comprehensively adjudicate the pre-existing conditions, rather than assessing the index admission alone.

Preexisting Conditions That Kill Us.

To protect human life, science and public health need to guide public policy. We call for an end to the anti-science, anti-prevention, and anti-regulatory policies that have resulted in countless preexisting conditions and deaths. Reactive responses are not a substitute for primary prevention; we must invest in environmental and public health protections.

Preexisting conditions in older adults with mild traumatic brain injuries.

OBJECTIVE: This study examined the prevalence of preexisting conditions that could affect premorbid brain health, cognition, and functional independence among older adults with mild traumatic brain injury (MTBI), and the relationship between preexisting conditions, injury characteristics, and emergency department (ED) discharge location (home versus continued care). METHODS: Older adults (N = 1,427; 55-104 years-old; 47.4% men) who underwent head computed tomography (CT) after acute head trauma were recruited from the ED. Researchers documented preexisting medical conditions retrospectively from hospital records. RESULTS: Multiple preexisting conditions increased in frequency with greater age, including circulatory and nervous system diseases and preexisting abnormalities on head CT. Psychiatric and substance use disorders (SUDs) decreased in frequency with greater age. Among participants with uncomplicated MTBI and GCS = 15, preexisting nervous system diseases and preexisting CT abnormalities were associated with higher odds of continued care for all participants, whereas psychiatric disorders and SUDs were only associated with higher odds of continued care among participants <70 years-old. Preexisting circulatory diseases, loss of consciousness, and amnesia were unassociated with discharge location. CONCLUSIONS: Preexisting medical conditions that could affect brain and cognitive health occur commonly among older adults who sustain MTBIs. These conditions can confound research examining post-injury outcomes within this age group.

Primary De novo ductal adenocarcinoma of the lacrimal gland.

BACKGROUND: Primary ductal adenocarcinoma of the lacrimal gland is a rare and aggressive malignant epithelial lacrimal gland neoplasm, morphologically and phenotypically resembles salivary duct carcinoma, and both strongly resemble infiltrating ductal carcinoma of breast. METHOD: Retrospective Chart review of cases of malignant lacrimal gland tumors from 2013 July to 2020 July. Authors describe the clinico radiological, morphological and immunohistochemical features of primary ductal adenocarcinoma (PDA) of lacrimal gland. Extensive review of literature of PDA of lacrimal gland and salivary gland ductal carcinoma has been performed. RESULTS: Retrospective chart review of the last 7 years yielded 22 malignant lacrimal gland neoplasms of which 4 cases demonstrated features of primary ductal adenocarcinoma of lacrimal gland, 2/4 cases showed an evidence of a pre existing pleomorphic adenoma and 2 were found to be de novo ductal adenocarcinomas. PDA of lacrimal gland showed expression of CK7, CK19, AR, HER2, cyclin D1 and were negative for CK5/14, CK 20, ER, PR, PSA, TTF-1, S-100 and SMA. Expression of GCDFP-15 was noted in one case. The presence of multiple events of loco-regional recurrences and/or distant metastasis necessitated a multidisciplinary approach. CONCLUSIONS: Authors have expressed the need of clinical correlation; thorough tissue sampling and extensive immunohistochemical work up in identification of de novo PDA's and their molecular subtypes. A multi-institutional study might help in formulating the diagnostic criteria, identification of actionable targets, and thus study the role of targeted therapy in this rare and aggressive tumor which may result in better patient outcomes.