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1.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21267723

RESUMEN

ObjectiveThis study aimed to estimate the incidence of new diabetes mellitus (DM) and cardiovascular diseases (CVD) up to one year after Covid-19 compared with matched controls. MethodsA cohort study was conducted using electronic records for 1,473 family practices with a population of 14.9 million. Covid-19 patients without DM or CVD were individually matched with controls and followed up to October 2021. A difference-in-difference analysis estimated the net effect of Covid-19 allowing for baseline differences and covariates. ResultsThere were 372,816 Covid-19 patients, with 2,935 CVD and 3,139 DM events, and 372,816 matched controls with 1,193 CVD and 1,861 DM events following the index date. Net incidence of DM increased in acute Covid-19 up to four weeks from index date (adjusted rate ratio, RR 1.71, 1.40 to 2.10) and remained elevated in post-acute (five to 12 weeks from index date; RR 1.17, 1.01 to 1.36) and long-Covid-19 (13 to 52 weeks, 1.20, 1.09 to 1.31). Acute Covid-19 was associated with net increased CVD incidence (RR 6.02, 95% confidence interval 4.84 to 7.47) including pulmonary embolism (RR 14.5, 7.72 to 27.4), atrial arrythmias (6.58, 3.78 to 11.4) and venous thromboses (5.44, 3.22 to 9.17). CVD incidence declined in post-acute Covid-19 (1.68, 1.41 to 2.01) and showed no net increase in long Covid-19 (0.95, 0.85 to 1.06). ConclusionsDM incidence remains elevated up to one year following Covid-19. CVD is increased early after Covid-19 mainly from pulmonary embolism, atrial arrhythmias and venous thromboses.

2.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20201731

RESUMEN

ObjectivesTo evaluate antihypertensive medications and COVID-19 diagnosis and mortality, accounting for healthcare seeking behaviour. DesignA population-based case control study with additional cohort analysis. SettingPrimary care patients from the UK Clinical Practice Research Datalink (CPRD). Participants16 866 patients with COVID-19 events in the CPRD from 29th January to June 25th 2020 and 70 137 matched controls. Main outcome measuresWe explored associations between COVID-19 diagnosis and prescriptions for angiotensin converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), beta-blockers (B), calcium-channel blockers (C), thiazide diuretics (D) and other antihypertensive drugs (O). We evaluated all-cause mortality among COVID-19 cases. Analyses were adjusted for covariates and consultation frequency. ResultsIn covariate adjusted analyses, ACEIs were associated with lower odds of COVID-19 diagnosis (0.82, 95% confidence interval 0.77 to 0.88) as were ARBs, 0.87 (0.80 to 0.95) with little attenuation from adjustment for consultation frequency. In fully adjusted analyses, C and D were also associated with lower odds of COVID-19. Increased odds of COVID-19 for B (1.19, 1.12 to 1.26), were attenuated after adjustment for consultation frequency (1.01, 0.95 to 1.08). In adjusted analyses, patients treated with ACEIs or ARBs had similar mortality to patients treated with classes B, C, D or O (1.00, 0.83 to 1.20) or patients receiving no antihypertensive therapy (0.99, 0.83 to 1.18). ConclusionsAssociations were sensitive to adjustment for confounding and healthcare seeking, but there was no evidence that antihypertensive therapy is associated with increased risk of COVID-19 diagnosis or mortality; most classes of antihypertensive therapy showed negative associations with COVID-19 diagnosis.

3.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20078006

RESUMEN

BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score. MethodsTraining cohorts comprised 1276 patients admitted to Kings College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. ResultsA baseline model of NEWS2 + age had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWMESSAGESC_SCPLOWO_LIThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients. C_LIO_LIRisk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death. C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites. C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches. C_LI

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