Search

Background The link between workplace bullying and poor mental health is well-known. However, little is known about the prospective and potentially reciprocal association between workplace bullying and mental health-related sickness absence. This 2-year prospective study examined bidirectional associations between exposure to workplace bullying and sickness absence due to common mental disorders (SA-CMD) while controlling for confounding factors from both work and private life. Methods The study was based on propensity score-matched samples (N = 3216 and N = 552) from the Swedish Longitudinal Occupational Survey of Health, using surveys from years 2012, 2014 and 2016. Self-reported exposure to workplace bullying was linked to registry-based information regarding medically certified SA-CMD (≥ 14 consecutive days). The associations were examined by means of Cox proportional hazards regression and via conditional logistic regression analysis. Hazard ratios and odds ratios with 95% confidence intervals were estimated. Results Exposure to workplace bullying was associated with an increased risk of incident SA-CMD (HR: 1.3, 95% CI: 1.0–1.8), after accounting for the influence of job demands, decision authority, previous SA-CMD, as well as other sociodemographic covariates. However, we found no statistically significant association between SA-CMD and subsequent workplace bullying (OR 1.2, 95% CI 0.7–1.9). Conclusions The results support an association between self-reported workplace bullying and SA-CMD, independent of other sociodemographic factors and workplace stressors. Preventing workplace bullying could alleviate a share of the individual and societal burden caused by SA globally., Open access funding provided by Stockholm University. The Swedish Research Council for Health, Working Life and Welfare (FORTE) supported this work (grant number 2019–01318). This work utilised data from SLOSH which is part of the REWHARD consortium supported by the Swedish Research Council (VR #2021–00154).

OBJECTIVES: To describe the utilization of early ketamine use among patients mechanically ventilated for COVID-19, and examine associations with in-hospital mortality and other clinical outcomes. DESIGN: Retrospective cohort study. SETTING: Six hundred ten hospitals contributing data to the Premier Healthcare Database between April 2020 and June 2021. PATIENTS: Adults with COVID-19 and greater than or equal to 2 consecutive days of mechanical ventilation within 5 days of hospitalization. INTERVENTION: The exposures were early ketamine use initiated within 2 days of intubation and continued for greater than 1 day. MEASUREMENTS: Primary was hospital mortality. Secondary outcomes included length of stay (LOS) in the hospital and ICUs, ventilator days, vasopressor days, renal replacement therapy (RRT), and total hospital cost. The propensity score matching analysis was used to adjust for confounders. MAIN RESULTS: Among 42,954 patients, 1,423 (3.3%) were exposed to early ketamine use. After propensity score matching including 1,390 patients in each group, recipients of ketamine infusions were associated with higher hospital mortality (52.5% vs. 45.9%, risk ratio: 1.14, [1.06-1.23]), longer median ICU stay (13 vs. 12 d, mean ratio [MR]: 1.15 [1.08-1.23]), and longer ventilator days (12 vs. 11 d, MR: 1.19 [1.12-1.27]). There were no associations for hospital LOS (17 [10-27] vs. 17 [9-28], MR: 1.05 [0.99-1.12]), vasopressor days (4 vs. 4, MR: 1.04 [0.95-1.14]), and RRT (22.9% vs. 21.7%, RR: 1.05 [0.92-1.21]). Total hospital cost was higher (median $72,481 vs. $65,584, MR: 1.11 [1.05-1.19]). CONCLUSIONS: In a diverse sample of U.S. hospitals, about one in 30 patients mechanically ventilated with COVID-19 received ketamine infusions. Early ketamine may have an association with higher hospital mortality, increased total cost, ICU stay, and ventilator days, but no associations for hospital LOS, vasopressor days, and RRT. However, confounding by the severity of illness might oc

The Woven EndoBridge (WEB) device is primarily used for treating wide-neck intracranial bifurcation aneurysms under 10 mm. Limited data exists on its efficacy for large aneurysms. We aim to assess angiographic and clinical outcomes of the WEB device in treating large versus small aneurysms. We conducted a retrospective review of the WorldWide WEB Consortium database, from 2011 to 2022, across 30 academic institutions globally. Propensity score matching (PSM) was employed to compare small and large aneurysms on baseline characteristics. A total of 898 patients were included. There was no significant difference observed in clinical presentations, smoking status, pretreatment mRS, presence of multiple aneurysms, bifurcation location, or prior treatment between the two groups. After PSM, 302 matched pairs showed significantly lower last follow-up adequate occlusion rates (81% vs 90%, p = 0.006) and higher retreatment rates (12% vs 3.6%, p < 0.001) in the large aneurysm group. These findings may inform treatment decisions and patient counseling. Future studies are needed to further explore this area.

Purpose This study evaluated the long-term safety of roflumilast in patients with chronic obstructive pulmonary disease or chronic bronchitis using electronic healthcare databases from Germany, Norway, Sweden, and the United States (US). Patients and Methods The study population consisted of patients aged ≥40 years who had been exposed to roflumilast and a matched cohort unexposed to roflumilast. The matching was based on sex, age, calendar year of cohort entry date (2010–2011, 2012, or 2013), and a propensity score that included variables such as demographics, markers of chronic obstructive pulmonary disease (COPD) severity and morbidity, and comorbidities. In comparison to the unexposed matched cohort (never use), three exposure definitions were used for the exposed matched cohort: ever use, use status (current, recent, past use), and cumulative duration of use. The main outcome was 5-year all-cause mortality. Cox regression models were used to estimate crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CI). Results 112,541 unexposed and 23,239 exposed patients across countries were included. Some variables remained unbalanced after matching, indicating higher COPD disease severity among the exposed patients. Adjusted HRs of 5-year all-cause mortality for “ever use” of roflumilast, compared to “never use”, were 1.12 (95% CI, 1.08–1.17) in Germany, 1.00 (95% CI, 0.92–1.08) in Norway, 0.98 (95% CI, 0.92–1.04) in Sweden, and 1.16 (95% CI, 1.12–1.20) in the US. Compared to never users, there was a decrease in 5-year mortality risk observed among “current users” in Germany (HR: 0.93, 95% CI: 0.88–0.98), Norway (HR: 0.77, 95% CI: 0.67–0.87), and Sweden (HR: 0.80, 95% CI: 0.73–0.88). Conclusion There was no observed increase in 5-year mortality risk with the use of roflumilast in Sweden or Norway. A small increase in 5-year mortality risk was observed in Germany and the US in the ever versus never comparison, likely due to residual confounding by indica

Purpose This study evaluated the long-term safety of roflumilast in patients with chronic obstructive pulmonary disease or chronic bronchitis using electronic healthcare databases from Germany, Norway, Sweden, and the United States (US). Patients and Methods The study population consisted of patients aged ≥40 years who had been exposed to roflumilast and a matched cohort unexposed to roflumilast. The matching was based on sex, age, calendar year of cohort entry date (2010–2011, 2012, or 2013), and a propensity score that included variables such as demographics, markers of chronic obstructive pulmonary disease (COPD) severity and morbidity, and comorbidities. In comparison to the unexposed matched cohort (never use), three exposure definitions were used for the exposed matched cohort: ever use, use status (current, recent, past use), and cumulative duration of use. The main outcome was 5-year all-cause mortality. Cox regression models were used to estimate crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CI). Results 112,541 unexposed and 23,239 exposed patients across countries were included. Some variables remained unbalanced after matching, indicating higher COPD disease severity among the exposed patients. Adjusted HRs of 5-year all-cause mortality for “ever use” of roflumilast, compared to “never use”, were 1.12 (95% CI, 1.08–1.17) in Germany, 1.00 (95% CI, 0.92–1.08) in Norway, 0.98 (95% CI, 0.92–1.04) in Sweden, and 1.16 (95% CI, 1.12–1.20) in the US. Compared to never users, there was a decrease in 5-year mortality risk observed among “current users” in Germany (HR: 0.93, 95% CI: 0.88–0.98), Norway (HR: 0.77, 95% CI: 0.67–0.87), and Sweden (HR: 0.80, 95% CI: 0.73–0.88). Conclusion There was no observed increase in 5-year mortality risk with the use of roflumilast in Sweden or Norway. A small increase in 5-year mortality risk was observed in Germany and the US in the ever versus never comparison, likely due to residual confounding by indica

Purpose This study evaluated the long-term safety of roflumilast in patients with chronic obstructive pulmonary disease or chronic bronchitis using electronic healthcare databases from Germany, Norway, Sweden, and the United States (US). Patients and Methods The study population consisted of patients aged ≥40 years who had been exposed to roflumilast and a matched cohort unexposed to roflumilast. The matching was based on sex, age, calendar year of cohort entry date (2010–2011, 2012, or 2013), and a propensity score that included variables such as demographics, markers of chronic obstructive pulmonary disease (COPD) severity and morbidity, and comorbidities. In comparison to the unexposed matched cohort (never use), three exposure definitions were used for the exposed matched cohort: ever use, use status (current, recent, past use), and cumulative duration of use. The main outcome was 5-year all-cause mortality. Cox regression models were used to estimate crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CI). Results 112,541 unexposed and 23,239 exposed patients across countries were included. Some variables remained unbalanced after matching, indicating higher COPD disease severity among the exposed patients. Adjusted HRs of 5-year all-cause mortality for “ever use” of roflumilast, compared to “never use”, were 1.12 (95% CI, 1.08–1.17) in Germany, 1.00 (95% CI, 0.92–1.08) in Norway, 0.98 (95% CI, 0.92–1.04) in Sweden, and 1.16 (95% CI, 1.12–1.20) in the US. Compared to never users, there was a decrease in 5-year mortality risk observed among “current users” in Germany (HR: 0.93, 95% CI: 0.88–0.98), Norway (HR: 0.77, 95% CI: 0.67–0.87), and Sweden (HR: 0.80, 95% CI: 0.73–0.88). Conclusion There was no observed increase in 5-year mortality risk with the use of roflumilast in Sweden or Norway. A small increase in 5-year mortality risk was observed in Germany and the US in the ever versus never comparison, likely due to residual confounding by indica

Purpose This study evaluated the long-term safety of roflumilast in patients with chronic obstructive pulmonary disease or chronic bronchitis using electronic healthcare databases from Germany, Norway, Sweden, and the United States (US). Patients and Methods The study population consisted of patients aged ≥40 years who had been exposed to roflumilast and a matched cohort unexposed to roflumilast. The matching was based on sex, age, calendar year of cohort entry date (2010–2011, 2012, or 2013), and a propensity score that included variables such as demographics, markers of chronic obstructive pulmonary disease (COPD) severity and morbidity, and comorbidities. In comparison to the unexposed matched cohort (never use), three exposure definitions were used for the exposed matched cohort: ever use, use status (current, recent, past use), and cumulative duration of use. The main outcome was 5-year all-cause mortality. Cox regression models were used to estimate crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CI). Results 112,541 unexposed and 23,239 exposed patients across countries were included. Some variables remained unbalanced after matching, indicating higher COPD disease severity among the exposed patients. Adjusted HRs of 5-year all-cause mortality for “ever use” of roflumilast, compared to “never use”, were 1.12 (95% CI, 1.08–1.17) in Germany, 1.00 (95% CI, 0.92–1.08) in Norway, 0.98 (95% CI, 0.92–1.04) in Sweden, and 1.16 (95% CI, 1.12–1.20) in the US. Compared to never users, there was a decrease in 5-year mortality risk observed among “current users” in Germany (HR: 0.93, 95% CI: 0.88–0.98), Norway (HR: 0.77, 95% CI: 0.67–0.87), and Sweden (HR: 0.80, 95% CI: 0.73–0.88). Conclusion There was no observed increase in 5-year mortality risk with the use of roflumilast in Sweden or Norway. A small increase in 5-year mortality risk was observed in Germany and the US in the ever versus never comparison, likely due to residual confounding by indica

Background: In Italy, surgeons continue to drain the abdominal cavity in more than 50 per cent of patients after colorectal resection. The aim of this study was to evaluate the impact of abdominal drain placement on early adverse events in patients undergoing elective colorectal surgery. Methods: A database was retrospectively analysed through a 1:1 propensity score-matching model including 21 covariates. The primary endpoint was the postoperative duration of stay, and the secondary endpoints were surgical site infections, infectious morbidity rate defined as surgical site infections plus pulmonary infections plus urinary infections, anastomotic leakage, overall morbidity rate, major morbidity rate, reoperation and mortality rates. The results of multiple logistic regression analyses were presented as odds ratios (OR) and 95 per cent c.i. Results: A total of 6157 patients were analysed to produce two well-balanced groups of 1802 patients: group (A), no abdominal drain(s) and group (B), abdominal drain(s). Group A versus group B showed a significantly lower risk of postoperative duration of stay >6 days (OR 0.60; 95 per cent c.i. 0.51–0.70; P < 0.001). A mean postoperative duration of stay difference of 0.86 days was detected between groups. No difference was recorded between the two groups for all the other endpoints. Conclusion: This study confirms that placement of abdominal drain(s) after elective colorectal surgery is associated with a non-clinically significant longer (0.86 days) postoperative duration of stay but has no impact on any other secondary outcomes, confirming that abdominal drains should not be used routinely in colorectal surgery.

This paper evaluates, for the first time, the impact of the School Meal Program (PAE) on the scores of the Ser Bachiller test for the period 2015-2019, in Ecuador. For this, a difference-in-differences (DiD) meth­od is used in combination with propensity score matching (PSM). First, matching with student-level information is used to compare individuals who receive the treatment with those who do not. This is done by means of the nearest neighbor criterion and inverse probability weighting. Finally, the average grades are calculated at the level of Educational Units, and DiD procedure is performed at the level of Educational Units in the study period, obtaining evidence that there is a positive impact of the PAE on the grades of beneficiary students., En este trabajo se evalua por primera vez el impacto del Programa de Alimentación Escolar (PAE) en las calificaciones de la prueba Ser Bachiller para el periodo comprendido entre el 2015 al 2019, en Ecua­dor. Para esto, se utiliza un método de diferencias en diferencias (DiD) en combinación con un emparejamiento por puntaje de propensión (PSM). Primero, se utiliza el emparejamiento con la información a nivel de estudiantes para comparar a los individuos que reciben el tratamiento con aquellos que no lo reciben. Esto se realiza por medio del criterio vecinos cercanos y ponderación de probabilidad inversa. Finalmente, se calcula el promedio de calificaciones a nivel de unidades educativas y se realiza el procedimiento de DiD a nivel de unidades educativas en el periodo de estudio, obteniendo evidencia de que existe un impacto positivo del PAE en las calificaciones de los estudiantes beneficiarios

AIM: To assess whether there were differences in resuscitation efforts and outcomes for medical intensive care unit (MICU) in-hospital cardiac arrest (IHCA) during the COVID-19 pandemic when compared to pre-pandemic. METHODS: Comparing COVID-19 MICU-IHCA patients (03/2020 to 10/2020) to non-COVID-19 MICU IHCA (01/2014 to 12/2018) at Clevleand Clinic Health System (CCHS) of NE Ohio. Propensity score matching analysis (PSMA) was used to create comparable groups. RESULTS: There were a total of 516 patients, 51 in COVID-19 MICU IHCA cohort and 465 in the non-COVID-19 MICU IHCA cohort. The mean (SD) age of the study population was 60.9 (16) years and 56% were males. In 92.1% (n = 475) patients, initial arrest rhythm was non-shockable. At the time of ICU admission, compared to the non-COVID-19 MICU-IHCA cohort, the COVID-19 MICU IHCA cohort had a lower mean APACHE III score (70 [32.9] vs 101.3 [39.6], P = <0.01). The COVID-19 cohort had a higher rate of survival to hospital discharge (12 [23.5%] vs 59 [12.7%], P = 0.03). Upon PSMA, the algorithm selected 40 COVID-19 patients and 200 non-COVID-19 patients. Imbalances in baseline characteristics, comorbidities, and APACHE III were well-balanced after matching. Survival rate after matching became non-significant; (10 [25%] vs 42 [21%], P = 0.67). Further, there were no significant differences in ICU or hospital length-of-stay or neurological outcomes at discharge for survivors in the two matched cohorts. CONCLUSION: It is imperative that COVID-19 patients receive unbiased and unrestricted resuscitation measures, without any discouragement.

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or flagging of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies.

In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting personalized medicine. The main goals of analyzing treatment effect heterogeneity include estimating treatment effects in clinically relevant subgroups and predicting whether a patient subpopulation might benefit from a particular treatment. Conventional approaches often evaluate the subgroup treatment effects via parametric modeling and can thus be susceptible to model mis-specifications. In this paper, we take a model-free semiparametric perspective and aim to efficiently evaluate the heterogeneous treatment effects of multiple subgroups simultaneously under the one-step targeted maximum-likelihood estimation (TMLE) framework. When the number of subgroups is large, we further expand this path of research by looking at a variation of the one-step TMLE that is robust to the presence of small estimated propensity scores in finite samples. From our simulations, our method demonstrates substantial finite sample improvements compared to conventional methods. In a case study, our method unveils the potential treatment effect heterogeneity of rs12916-T allele (a proxy for statin usage) in decreasing Alzheimers disease risk.

Background: Coronary artery calcium (CAC) has been widely recognized as an important predictor of cardiovascular disease (CVD). Given the finite resources, it is important to identify individuals who would receive the most benefit from detecting positive CAC by screening. However, the evidence is limited as to whether the burden of positive CAC on CVD differs by multi-dimensional individual characteristics. We sought to investigate the heterogeneity in the association between positive coronary artery calcium (CAC) and incident cardiovascular disease (CVD). Methods: This cohort study included adults aged ≥45 years free of cardiovascular disease from the Multi-Ethnic Study of Atherosclerosis. After propensity score matching in a 1:1 ratio, we applied a machine-learning causal forest model to (i) evaluate the heterogeneity in the association between positive CAC and incident CVD and (ii) predict the increase in CVD risk at 10-year when CAC>0 (vs. CAC=0) at the individual level. We then compared the estimated increase in CVD risk when CAC>0 to the absolute 10-year atherosclerotic CVD (ASCVD) risk calculated by the 2013 ACC/AHA pooled cohort equations. Results: Across 3, 328 adults in our propensity score-matched analysis, our causal forest model showed the heterogeneity in the association between CAC>0 and incident CVD. We found a dose-response relationship of the estimated increase in CVD risk when CAC>0 with higher 10-year ASCVD risk. Almost all individuals (2293/2428 [94.4%]) with borderline or higher ASCVD risk showed ≥2.5% increase in CVD risk when CAC>0. Even among 900 adults with low ASCVD risk, 689 (69.2%) showed ≥2.5% increase in CVD risk when CAC>0; these individuals were more likely to be male, Hispanic, and have unfavorable CVD risk factors than others. Conclusions: The expected increases in CVD risk when CAC>0 were heterogeneous across individuals. Moreover, nearly 70% of people with low ASCVD risk showed a large increase in CVD risk when CAC>0, highlightin

BACKGROUND: In experimental animal studies, exposure to general anesthesia in early childhood may results in changes in infant brain morphology and behavior, potentially leading to the development of autistic behaviors in the long-term. However, in clinical studies the role of exposure to general anesthesia in early childhood and the risk of autism is unknown.METHODS: This is a population-based cohort study including all children aged 0-5 years of age exposed to general anesthesia between 2001 and 2014 and a corresponding matched population without such an exposure. Propensity score calculation was based on 49 variables (including age of parents, malformations, APGAR Score, and family income, among others). Quasi-Poisson regression was used to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for the association between exposure to general anesthesia and autism or autism spectrum disorder.RESULTS: In total, 401,750 children exposed to general anesthesia were compared with 1,187,796 unexposed individu-als. Autism or autism spectrum disorder were more common in the children exposed to general anesthesia as compared to unexposed children (1.65% and 0.98%, respectively, P<0.01). There was a statistically significant higher risk of autism or autism spectrum disorder in children exposed to general anesthesia as compared to unexposed children also after pro-pensity score adjustment (RR 1.62, 95% CI: 1.57-1.67).CONCLUSIONS: Exposure to general anesthesia in early childhood was associated with an increased risk of autism or autism spectrum disorder. Future studies are needed to asses if general anesthesia may cause autism or if the association is due to other factors.(Cite this article as: Pikwer A, Yang B, Granstr delta m M, Mattsson N, Sadr-Azodi O. General anesthesia in early childhood and possible association with autism: a population-based matched cohort study. Minerva Anestesiol 2023;89:22-31. DOI: 10.23736/S0375-9393.22.16543-0)

BACKGROUND: In experimental animal studies, exposure to general anesthesia in early childhood may results in changes in infant brain morphology and behavior, potentially leading to the development of autistic behaviors in the long-term. However, in clinical studies the role of exposure to general anesthesia in early childhood and the risk of autism is unknown.METHODS: This is a population-based cohort study including all children aged 0-5 years of age exposed to general anesthesia between 2001 and 2014 and a corresponding matched population without such an exposure. Propensity score calculation was based on 49 variables (including age of parents, malformations, APGAR Score, and family income, among others). Quasi-Poisson regression was used to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for the association between exposure to general anesthesia and autism or autism spectrum disorder.RESULTS: In total, 401,750 children exposed to general anesthesia were compared with 1,187,796 unexposed individu-als. Autism or autism spectrum disorder were more common in the children exposed to general anesthesia as compared to unexposed children (1.65% and 0.98%, respectively, P<0.01). There was a statistically significant higher risk of autism or autism spectrum disorder in children exposed to general anesthesia as compared to unexposed children also after pro-pensity score adjustment (RR 1.62, 95% CI: 1.57-1.67).CONCLUSIONS: Exposure to general anesthesia in early childhood was associated with an increased risk of autism or autism spectrum disorder. Future studies are needed to asses if general anesthesia may cause autism or if the association is due to other factors.(Cite this article as: Pikwer A, Yang B, Granstr delta m M, Mattsson N, Sadr-Azodi O. General anesthesia in early childhood and possible association with autism: a population-based matched cohort study. Minerva Anestesiol 2023;89:22-31. DOI: 10.23736/S0375-9393.22.16543-0)

BACKGROUND: In experimental animal studies, exposure to general anesthesia in early childhood may results in changes in infant brain morphology and behavior, potentially leading to the development of autistic behaviors in the long-term. However, in clinical studies the role of exposure to general anesthesia in early childhood and the risk of autism is unknown.METHODS: This is a population-based cohort study including all children aged 0-5 years of age exposed to general anesthesia between 2001 and 2014 and a corresponding matched population without such an exposure. Propensity score calculation was based on 49 variables (including age of parents, malformations, APGAR Score, and family income, among others). Quasi-Poisson regression was used to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for the association between exposure to general anesthesia and autism or autism spectrum disorder.RESULTS: In total, 401,750 children exposed to general anesthesia were compared with 1,187,796 unexposed individu-als. Autism or autism spectrum disorder were more common in the children exposed to general anesthesia as compared to unexposed children (1.65% and 0.98%, respectively, P<0.01). There was a statistically significant higher risk of autism or autism spectrum disorder in children exposed to general anesthesia as compared to unexposed children also after pro-pensity score adjustment (RR 1.62, 95% CI: 1.57-1.67).CONCLUSIONS: Exposure to general anesthesia in early childhood was associated with an increased risk of autism or autism spectrum disorder. Future studies are needed to asses if general anesthesia may cause autism or if the association is due to other factors.(Cite this article as: Pikwer A, Yang B, Granstr delta m M, Mattsson N, Sadr-Azodi O. General anesthesia in early childhood and possible association with autism: a population-based matched cohort study. Minerva Anestesiol 2023;89:22-31. DOI: 10.23736/S0375-9393.22.16543-0)

BackgroundCoronary artery calcium (CAC) has been widely recognized as an important predictor of cardiovascular disease (CVD). Given the finite resources, it is important to identify individuals who would receive the most benefit from detecting positive CAC by screening. However, the evidence is limited as to whether the burden of positive CAC on CVD differs by multidimensional individual characteristics. We sought to investigate the heterogeneity in the association between positive CAC and incident CVD.MethodsThis cohort study included adults from MESA (Multi-Ethnic Study of Atherosclerosis) ages ≥45 years and free of cardiovascular disease. After propensity score matching in a 1:1 ratio, we applied a machine learning causal forest model to (1) evaluate the heterogeneity in the association between positive CAC and incident CVD, and (2) predict the increase in CVD risk at 10-years when CAC>0 (versus CAC=0) at the individual level. We then compared the estimated increase in CVD risk when CAC>0 to the absolute 10-year atherosclerotic CVD (ASCVD) risk calculated by the 2013 American College of Cardiology/American Heart Association pooled cohort equations.ResultsAcross 3328 adults in our propensity score-matched analysis, our causal forest model showed the heterogeneity in the association between CAC>0 and incident CVD. We found a dose-response relationship of the estimated increase in CVD risk when CAC>0 with higher 10-year ASCVD risk. Almost all individuals (2293 of 2428 [94.4%]) with borderline risk of ASCVD or higher showed ≥2.5% increase in CVD risk when CAC>0. Even among 900 adults with low ASCVD risk, 689 (69.2%) showed ≥2.5% increase in CVD risk when CAC>0; these individuals were more likely to be male, Hispanic, and have unfavorable CVD risk factors than others.ConclusionsThe expected increases in CVD risk when CAC>0 were heterogeneous across individuals. Moreover, nearly 70% of people with low ASCVD risk showed a large increase in CVD risk

AimsThe safety and feasibility of combining percutaneous catheter ablation (CA) for atrial fibrillation with left atrial appendage occlusion (LAAO) as a single procedure in the USA have not been investigated. We analyzed the US National Readmission Database (NRD) to investigate the incidence of combined LAAO + CA and compare major adverse cardiovascular events (MACEs) with matched LAAO-only and CA-only patients.Methods and resultsIn this retrospective study from NRD data, we identified patients undergoing combined LAAO and CA procedures on the same day in the USA from 2016 to 2019. A 1:1 propensity score match was performed to identify patients undergoing LAAO-only and CA-only procedures. The number of LAAO + CA procedures increased from 28 (2016) to 119 (2019). LAAO + CA patients (n = 375, mean age 74 ± 9.2 years, 53.4% were males) had non-significant higher MACE (8.1%) when compared with LAAO-only (n = 407, 5.3%) or CA-only patients (n = 406, 7.4%), which was primarily driven by higher rate of pericardial effusion (4.3%). All-cause 30-day readmission rates among LAAO + CA patients (10.7%) were similar when compared with LAAO-only (12.7%) or CA-only (17.5%) patients. The most frequent primary reason for readmissions among LAAO + CA and LAAO-only cohorts was heart failure (24.6 and 31.5%, respectively), while among the CA-only cohort, it was paroxysmal atrial fibrillation (25.7%).ConclusionWe report an 63% annual growth (from 28 procedures) in combined LAAO and CA procedures in the USA. There were no significant difference in MACE and all-cause 30-day readmission rates among LAAO + CA patients compared with matched LAAO-only or CA-only patients.

BACKGROUND: The potential benefit of transcatheter aortic valve replacement (TAVR) in patients with nonsevere aortic stenosis (AS) and heart failure is controversial. This study aimed to assess outcomes of patients with nonsevere low-gradient AS (LGAS) and reduced left ventricular ejection fraction undergoing TAVR or medical management. METHODS: Patients undergoing TAVR for LGAS and reduced left ventricular ejection fraction (<50%) were included in a multinational registry. True-severe low-gradient AS (TS-LGAS) and pseudo-severe low-gradient AS (PS-LGAS) were classified according to computed tomography-derived aortic valve calcification thresholds. A medical control group with reduced left ventricular ejection fraction and moderate AS or PS-LGAS was used (Medical-Mod). Adjusted outcomes between all groups were compared. Among patients with nonsevere AS (moderate or PS-LGAS), outcomes after TAVR and medical therapy were compared using propensity score-matching. RESULTS: A total of 706 LGAS patients undergoing TAVR (TS-LGAS, N=527; PS-LGAS, N=179) and 470 Medical-Mod patients were included. After adjustment, both TAVR groups showed superior survival compared with Medical-Mod patients (all P<0.001), while no difference was found between TS-LGAS and PS-LGAS TAVR patients (P=0.96). After propensity score-matching among patients with nonsevere AS, PS-LGAS TAVR patients showed superior 2-year overall (65.4%) and cardiovascular survival (80.4%) compared with Medical-Mod patients (48.8% and 58.5%, both P≤0.004). In a multivariable analysis including all patients with nonsevere AS, TAVR was an independent predictor of survival (hazard ratio, 0.39 [95% CI, 0.27–0.55]; P<0.0001). CONCLUSIONS: Among patients with nonsevere AS and reduced left ventricular ejection fraction, TAVR represents a major predictor of superior survival. These results reinforce the need for randomized-controlled trials comparing TAVR versus medical management in heart failure patients with nonsevere AS.

BACKGROUND: In experimental animal studies, exposure to general anesthesia in early childhood may results in changes in infant brain morphology and behavior, potentially leading to the development of autistic behaviors in the long-term. However, in clinical studies the role of exposure to general anesthesia in early childhood and the risk of autism is unknown.METHODS: This is a population-based cohort study including all children aged 0-5 years of age exposed to general anesthesia between 2001 and 2014 and a corresponding matched population without such an exposure. Propensity score calculation was based on 49 variables (including age of parents, malformations, APGAR Score, and family income, among others). Quasi-Poisson regression was used to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for the association between exposure to general anesthesia and autism or autism spectrum disorder.RESULTS: In total, 401,750 children exposed to general anesthesia were compared with 1,187,796 unexposed individu-als. Autism or autism spectrum disorder were more common in the children exposed to general anesthesia as compared to unexposed children (1.65% and 0.98%, respectively, P<0.01). There was a statistically significant higher risk of autism or autism spectrum disorder in children exposed to general anesthesia as compared to unexposed children also after pro-pensity score adjustment (RR 1.62, 95% CI: 1.57-1.67).CONCLUSIONS: Exposure to general anesthesia in early childhood was associated with an increased risk of autism or autism spectrum disorder. Future studies are needed to asses if general anesthesia may cause autism or if the association is due to other factors.(Cite this article as: Pikwer A, Yang B, Granstr delta m M, Mattsson N, Sadr-Azodi O. General anesthesia in early childhood and possible association with autism: a population-based matched cohort study. Minerva Anestesiol 2023;89:22-31. DOI: 10.23736/S0375-9393.22.16543-0)

Background: This study was designed to assess the impact of postoperative atrial fibrillation (POAF) on short- and long-term outcomes after cardiac surgery. Methods: We prospectively assessed POAF concerning outcomes in 379 adult patients who had undergone cardiac surgery in two heart surgery centers with a follow-up period of one year for every patient. The effects of POAF on postoperative events were evaluated using Logistic regression, Cox regression (adjusted for propensity score), and Kaplan-Meier analysis. Results: The incidence of POAF was 27.2%. Multivariable logistic regression analysis revealed POAF was associated with an increased risk of 6-month (OR = 5.36; CI: 1.51–18.94; p = 0.009), and 1-year mortality (OR = 4.56; CI: 1.29–16.04; p = 0.018) as well as Major Adverse Cardiocerebral Events (MACEs; acute MI, cardiac arrest, low cardiac output after surgery, third-degree atrioventricular block or stroke; OR = 3.02; CI: 1.29–7.05; p = 0.011), Intensive Care Unit (ICU) stay > 3 days (OR = 2.39; CI: 1.14–5.00; p = 0.021), and postoperative stay > 14 days (OR = 3.12; CI: 1.65–5.90; p < 0.001). Multivariable Cox regression analysis showed POAF as an independent predictor of mortality at one year (HR = 2.86; CI: 1.05–7.75; p = 0.038). Discharge plans including statin and beta-blocker had an independent association with a reduced mortality at one year (HR = 0.22; CI: 0.05–0.96; p = 0.045; HR = 0.16; CI: 0.03–0.87; p = 0.034, respectively). Conclusions: POAF is associated with an increased risk of morbidity, all-cause mortality, and hospital duration. Statins and beta-blockers that were included in discharge plans had an independent association with reduction in 1-year all-cause mortality., Hospital practice, 51(3), pp.141-148; 2023

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or “flagging” of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies.

Nonprobability samples, for example observational studies, online opt-in surveys, or register data, do not come from a sampling design and therefore may suffer from selection bias. To correct for selection bias, Elliott and Valliant (EV) proposed a pseudo-weight estimation method that applies a two-sample setup for a probability sample and a nonprobability sample drawn from the same population, sharing some common auxiliary variables. By estimating the propensities of inclusion in the nonprobability sample given the two samples, we may correct the selection bias by (pseudo) design-based approaches. This paper expands the original method, allowing for large sampling fractions in either sample or for high expected overlap between selected units in each sample, conditions often present in administrative data sets and more frequently occurring with Big Data.

Background: Transcatheter mitral valve replacement (TMVR) is an emerging therapeutic alternative for patients with secondary mitral regurgitation (MR). Outcomes of TMVR versus guideline-directed medical therapy (GDMT) have not been investigated for this population. This study aimed to compare clinical outcomes of patients with secondary MR undergoing TMVR versus GDMT alone. Methods: The CHOICE-MI registry (Choice of Optimal Transcatheter Treatment for Mitral Insufficiency) included patients with MR undergoing TMVR using dedicated devices. Patients with MR pathogeneses other than secondary MR were excluded. Patients treated with GDMT alone were derived from the control arm of the COAPT trial (Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients With Functional Mitral Regurgitation). We compared outcomes between the TMVR and GDMT groups, using propensity score matching to adjust for baseline differences. Results: After propensity score matching, 97 patient pairs undergoing TMVR (72.9±8.7 years; 60.8% men; transapical access, 91.8%) versus GDMT (73.1±11.0 years; 59.8% men) were compared. At 1 and 2 years, residual MR was ≤1+ in all patients of the TMVR group compared with 6.9% and 7.7%, respectively, in those receiving GDMT alone (both P<0.001). The 2-year rate of heart failure hospitalization was significantly lower in the TMVR group (32.8% versus 54.4%; hazard ratio, 0.59 [95% CI, 0.35–0.99]; P=0.04). Among survivors, a higher proportion of patients were in the New York Heart Association functional class I or II in the TMVR group at 1 year (78.2% versus 59.7%; P=0.03) and at 2 years (77.8% versus 53.2%; P=0.09). Two-year mortality was similar in the 2 groups (TMVR versus GDMT, 36.8% versus 40.8%; hazard ratio, 1.01 [95% CI, 0.62–1.64]; P=0.98). Conclusions: In this observational comparison, over 2-year follow-up, TMVR using mostly transapical devices in patients with secondar, Background: Transcatheter mitral valve replacement (TMVR) is an emerging therapeutic alternative for patients with secondary mitral regurgitation (MR). Outcomes of TMVR versus guideline-directed medical therapy (GDMT) have not been investigated for this population. This study aimed to compare clinical outcomes of patients with secondary MR undergoing TMVR versus GDMT alone. Methods: The CHOICE-MI registry (Choice of Optimal Transcatheter Treatment for Mitral Insufficiency) included patients with MR undergoing TMVR using dedicated devices. Patients with MR pathogeneses other than secondary MR were excluded. Patients treated with GDMT alone were derived from the control arm of the COAPT trial (Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients With Functional Mitral Regurgitation). We compared outcomes between the TMVR and GDMT groups, using propensity score matching to adjust for baseline differences. Results: After propensity score matching, 97 patient pairs undergoing TMVR (72.9±8.7 years; 60.8% men; transapical access, 91.8%) versus GDMT (73.1±11.0 years; 59.8% men) were compared. At 1 and 2 years, residual MR was ≤1+ in all patients of the TMVR group compared with 6.9% and 7.7%, respectively, in those receiving GDMT alone (both P<0.001). The 2-year rate of heart failure hospitalization was significantly lower in the TMVR group (32.8% versus 54.4%; hazard ratio, 0.59 [95% CI, 0.35-0.99]; P=0.04). Among survivors, a higher proportion of patients were in the New York Heart Association functional class I or II in the TMVR group at 1 year (78.2% versus 59.7%; P=0.03) and at 2 years (77.8% versus 53.2%; P=0.09). Two-year mortality was similar in the 2 groups (TMVR versus GDMT, 36.8% versus 40.8%; hazard ratio, 1.01 [95% CI, 0.62-1.64]; P=0.98). Conclusions: In this observational comparison, over 2-year follow-up, TMVR using mostly transapical devices in patients with secondary MR was associated with significant red

BACKGROUND: In experimental animal studies, exposure to general anesthesia in early childhood may results in changes in infant brain morphology and behavior, potentially leading to the development of autistic behaviors in the long-term. However, in clinical studies the role of exposure to general anesthesia in early childhood and the risk of autism is unknown.METHODS: This is a population-based cohort study including all children aged 0-5 years of age exposed to general anesthesia between 2001 and 2014 and a corresponding matched population without such an exposure. Propensity score calculation was based on 49 variables (including age of parents, malformations, APGAR Score, and family income, among others). Quasi-Poisson regression was used to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for the association between exposure to general anesthesia and autism or autism spectrum disorder.RESULTS: In total, 401,750 children exposed to general anesthesia were compared with 1,187,796 unexposed individu-als. Autism or autism spectrum disorder were more common in the children exposed to general anesthesia as compared to unexposed children (1.65% and 0.98%, respectively, P<0.01). There was a statistically significant higher risk of autism or autism spectrum disorder in children exposed to general anesthesia as compared to unexposed children also after pro-pensity score adjustment (RR 1.62, 95% CI: 1.57-1.67).CONCLUSIONS: Exposure to general anesthesia in early childhood was associated with an increased risk of autism or autism spectrum disorder. Future studies are needed to asses if general anesthesia may cause autism or if the association is due to other factors.(Cite this article as: Pikwer A, Yang B, Granstr delta m M, Mattsson N, Sadr-Azodi O. General anesthesia in early childhood and possible association with autism: a population-based matched cohort study. Minerva Anestesiol 2023;89:22-31. DOI: 10.23736/S0375-9393.22.16543-0)

Intensive pond aquaculture production is increasing and playing a major role in global aquaculture production, especially in developing countries. Empirical evidence shows that the access to and exchange of fresh water in tilapia pond aquaculture is important for making pond production ecologically more sound, efficient and productive. This study investigates productivity and efficiency differences between farms with access to open water resources and farms without access using data obtained from 311 interviews with tilapia farmers in Bangladesh. Propensity Score Matching (PSM) and meta-frontier DEA have been employed to estimate productivity and efficiency differences between the groups. Results show that farms located in areas with access to open water resources are significantly more efficient, but a bit surprisingly less productive than farms located in areas with deficit access to water resources. Furthermore, output could be increased by 29% and 40% without increasing input in areas with good access and limited access to water, respectively. Thus, promoting intensive aquaculture pond production in areas with access to water resources should focus on how to increase productivity, while areas with limited access should focus on optimal use of input in order to improve water quality and efficiency.

AIM: The study aimed to compare five-year overall survival in a national cohort of patients undergoing curative abdominal resection for colon cancer by minimally invasive surgery (MIS) or open (OPEN) technique. METHODS: All patients diagnosed between 2010 and 2016 in Sweden with pathological UICC stage I-III colon cancer localized in the cecum, ascending colon, hepatic flexure or sigmoid colon, and those who underwent curative right sided hemicolectomy, sigmoid resection or high anterior resection by MIS or OPEN were included. Patients were identified in the Swedish Colorectal Cancer Registry from which all data was retrieved. The analyses were performed as intention-to-treat and the relationship between surgical technique (MIS or OPEN) and overall mortality within five years was analysed. For the primary research question a non-inferiority hypothesis was assumed with a statistical power of 90%, a one-side type I error of 2.5%, and a non-inferiority margin of 2%. For the secondary analyses, multilevel survival regression models with the patients matched by propensity scores were employed, adjusted for patient- and tumuor-related variables. RESULTS: A total of 11605 pathological UICC cancer stage I-III patients were included with 3297 MIS (28.4%) and 8308 OPEN (71.6%) and were followed until December 31, 2020. The primary analysis demonstrated superiority for MIS compared to OPEN. The multilevel survival regression analyses confirmed that five-year overall survival was higher in MIS with a hazard ratio (HR) of 0.874 (95% confidence interval (CI): 0.791-0.965), and if excluding pT4, outcome was similar, with a HR of 0.847 (95% CI: 0.756-0.948). CONCLUSION: This observational study demonstrated that MIS was favourable to OPEN with regard to five-year overall survival. These results support the use of laparoscopic colon cancer surgery in routine practise., Funding agency:Research Committee, Region Örebro County, Örebro

Background & aims: The Dietary Approaches to Stop Hypertension (DASH) diet has been shown to effectively reduce blood pressure and body weight, but its effectiveness for reducing (cardiovascular) mortality rates has never been assessed in a clinical trial. Causal effects of dietary interventions are difficult to measure, due to practical limitations of randomized controlled diet trials. Target trial emulation can be used to improve causal inference in observational data. The aim of this study was to emulate a target trial assessing the relationship between compliance with the DASH diet and cardiovascular and all-cause mortality risk in patients with established CVD. Methods: Using data from the Alpha Omega Cohort, we emulated a DASH diet trial in patients with a history of myocardial infarction (MI). Inverse probability of treatment weighting (IPTW) was used to balance confounders over DASH-compliant and non-DASH-compliant participants. Hazard ratios (HRs) were estimated with IPT-weighted Cox models. Results: Of 4365 patients (79% male, median age 69 years, >80% treated with lipid- and blood pressure-lowering medication), 598 were classified as DASH-compliant (compliance score ≥5 out of 9). During a median follow-up of 12.4 years, 2035 deaths occurred of which 903 (44%) were of cardiovascular origin. DASH compliance was not associated with all-cause mortality (HR 0.92, 95%CI 0.0.80–1.06) and cardiovascular mortality (HR 0.90, 95%CI 0.72–1.11). Conclusions: In an emulated target trial on the DASH diet in the Alpha Omega cohort no relation was found between DASH compliance and risk of all-cause and cardiovascular mortality in patients with a history of MI. The DASH diet's effects may have been modified in this population by concomitant use of blood pressure-lowering medications.

Background and Objectives COVID-19–related inflammation, endothelial dysfunction, and coagulopathy may increase the bleeding risk and lower the efficacy of revascularization treatments in patients with acute ischemic stroke (AIS). We aimed to evaluate the safety and outcomes of revascularization treatments in patients with AIS and COVID-19. Methods This was a retrospective multicenter cohort study of consecutive patients with AIS receiving intravenous thrombolysis (IVT) and/or endovascular treatment (EVT) between March 2020 and June 2021 tested for severe acute respiratory syndrome coronavirus 2 infection. With a doubly robust model combining propensity score weighting and multivariate regression, we studied the association of COVID-19 with intracranial bleeding complications and clinical outcomes. Subgroup analyses were performed according to treatment groups (IVT-only and EVT). Results Of a total of 15,128 included patients from 105 centers, 853 (5.6%) were diagnosed with COVID-19; of those, 5,848 (38.7%) patients received IVT-only and 9,280 (61.3%) EVT (with or without IVT). Patients with COVID-19 had a higher rate of symptomatic intracerebral hemorrhage (SICH) (adjusted OR 1.53; 95% CI 1.16–2.01), symptomatic subarachnoid hemorrhage (SSAH) (OR 1.80; 95% CI 1.20–2.69), SICH and/or SSAH combined (OR 1.56; 95% CI 1.23–1.99), 24-hour mortality (OR 2.47; 95% CI 1.58–3.86), and 3-month mortality (OR 1.88; 95% CI 1.52–2.33). Patients with COVID-19 also had an unfavorable shift in the distribution of the modified Rankin score at 3 months (OR 1.42; 95% CI 1.26–1.60). Discussion Patients with AIS and COVID-19 showed higher rates of intracranial bleeding complications and worse clinical outcomes after revascularization treatments than contemporaneous non–COVID-19 patients receiving treatment. Current available data do not allow direct conclusions to be drawn on the effectiveness of revascularization treatments in patients with COVID-19 or to establish different treatment r

Background: Transcatheter mitral valve replacement (TMVR) is an emerging therapeutic alternative for patients with secondary mitral regurgitation (MR). Outcomes of TMVR versus guideline-directed medical therapy (GDMT) have not been investigated for this population. This study aimed to compare clinical outcomes of patients with secondary MR undergoing TMVR versus GDMT alone. Methods: The CHOICE-MI registry (Choice of Optimal Transcatheter Treatment for Mitral Insufficiency) included patients with MR undergoing TMVR using dedicated devices. Patients with MR pathogeneses other than secondary MR were excluded. Patients treated with GDMT alone were derived from the control arm of the COAPT trial (Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients With Functional Mitral Regurgitation). We compared outcomes between the TMVR and GDMT groups, using propensity score matching to adjust for baseline differences. Results: After propensity score matching, 97 patient pairs undergoing TMVR (72.9±8.7 years; 60.8% men; transapical access, 91.8%) versus GDMT (73.1±11.0 years; 59.8% men) were compared. At 1 and 2 years, residual MR was ≤1+ in all patients of the TMVR group compared with 6.9% and 7.7%, respectively, in those receiving GDMT alone (both P<0.001). The 2-year rate of heart failure hospitalization was significantly lower in the TMVR group (32.8% versus 54.4%; hazard ratio, 0.59 [95% CI, 0.35–0.99]; P=0.04). Among survivors, a higher proportion of patients were in the New York Heart Association functional class I or II in the TMVR group at 1 year (78.2% versus 59.7%; P=0.03) and at 2 years (77.8% versus 53.2%; P=0.09). Two-year mortality was similar in the 2 groups (TMVR versus GDMT, 36.8% versus 40.8%; hazard ratio, 1.01 [95% CI, 0.62–1.64]; P=0.98). Conclusions: In this observational comparison, over 2-year follow-up, TMVR using mostly transapical devices in patients with secondar, Background: Transcatheter mitral valve replacement (TMVR) is an emerging therapeutic alternative for patients with secondary mitral regurgitation (MR). Outcomes of TMVR versus guideline-directed medical therapy (GDMT) have not been investigated for this population. This study aimed to compare clinical outcomes of patients with secondary MR undergoing TMVR versus GDMT alone. Methods: The CHOICE-MI registry (Choice of Optimal Transcatheter Treatment for Mitral Insufficiency) included patients with MR undergoing TMVR using dedicated devices. Patients with MR pathogeneses other than secondary MR were excluded. Patients treated with GDMT alone were derived from the control arm of the COAPT trial (Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients With Functional Mitral Regurgitation). We compared outcomes between the TMVR and GDMT groups, using propensity score matching to adjust for baseline differences. Results: After propensity score matching, 97 patient pairs undergoing TMVR (72.9±8.7 years; 60.8% men; transapical access, 91.8%) versus GDMT (73.1±11.0 years; 59.8% men) were compared. At 1 and 2 years, residual MR was ≤1+ in all patients of the TMVR group compared with 6.9% and 7.7%, respectively, in those receiving GDMT alone (both P<0.001). The 2-year rate of heart failure hospitalization was significantly lower in the TMVR group (32.8% versus 54.4%; hazard ratio, 0.59 [95% CI, 0.35-0.99]; P=0.04). Among survivors, a higher proportion of patients were in the New York Heart Association functional class I or II in the TMVR group at 1 year (78.2% versus 59.7%; P=0.03) and at 2 years (77.8% versus 53.2%; P=0.09). Two-year mortality was similar in the 2 groups (TMVR versus GDMT, 36.8% versus 40.8%; hazard ratio, 1.01 [95% CI, 0.62-1.64]; P=0.98). Conclusions: In this observational comparison, over 2-year follow-up, TMVR using mostly transapical devices in patients with secondary MR was associated with significant red

Background The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes.Methods This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation.Results Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observ

BACKGROUND: Several studies have confirmed associations between air pollution and overall mortality, but it is unclear to what extent these associations reflect causal relationships. Moreover, few studies to our knowledge have accounted for complex mixtures of air pollution. In this study, we evaluate the causal effects of a mixture of air pollutants on overall mortality in a large, prospective cohort of Dutch individuals.METHODS: We evaluated 86,882 individuals from the LIFEWORK study, assessing overall mortality between 2013 and 2017 through national registry linkage. We predicted outdoor concentration of five air pollutants (PM2.5, PM10, NO2, PM2.5 absorbance, and oxidative potential) with land-use regression. We used logistic regression and mixture modeling (weighted quantile sum and boosted regression tree models) to identify potential confounders, assess pollutants' relevance in the mixture-outcome association, and investigate interactions and nonlinearities. Based on these results, we built a multivariate generalized propensity score model to estimate the causal effects of pollutant mixtures.RESULTS: Regression model results were influenced by multicollinearity. Weighted quantile sum and boosted regression tree models indicated that all components contributed to a positive linear association with the outcome, with PM2.5 being the most relevant contributor. In the multivariate propensity score model, PM2.5 (OR=1.18, 95% CI: 1.08-1.29) and PM10 (OR=1.02, 95% CI: 0.91-1.14) were associated with increased odds of mortality per interquartile range increase.CONCLUSION: Using novel methods for causal inference and mixture modeling in a large prospective cohort, this study strengthened the causal interpretation of air pollution effects on overall mortality, emphasizing the primary role of PM2.5 within the pollutant mixture.

[Purpose] To investigate the 2-year effectiveness of reduced-fluence photodynamic therapy (rf-PDT) for chronic central serous chorioretinopathy (cCSC). [Design] Retrospective cohort study. [Participants] A total of 223 consecutive patients with newly diagnosed cCSC with active serous retinal detachment (SRD) were included from May 2007 to June 2017 and followed up for at least 2 years. Patients who underwent ocular treatment other than cataract surgery before the beginning of recruitment and those who had macular neovascularization at baseline were excluded. [Methods] All patients underwent a comprehensive ophthalmic evaluation, including measurements of best-corrected visual acuity (BCVA), slit-lamp examination, dilated fundus examination, color fundus photography, fundus autofluorescence, fluorescein angiography, indocyanine green angiography, and spectral-domain OCT. An inverse probability of treatment weighting (IPTW) methodology was applied to balance 18 baseline characteristics between patients who received rf-PDT (rf-PDT group) and those who did not receive treatment (controls). Inverse probability of treatment weighting survival analysis and regression were performed. [Main Outcome Measures] The proportion of patients whose BCVA at 24 months was the same or improved compared with the baseline visual acuity (VA) (VA maintenance rate). [Results] A total of 155 eyes (rf-PDT group: 74; controls: 81) were analyzed. The patients’ backgrounds were well balanced after IPTW with standardized differences of < 0.10. An IPTW regression analysis revealed that the VA maintenance rate was significantly higher in the rf-PDT group than in the controls (93.6% vs. 70.9%, P < 0.001, 12 months; 85.7% vs. 69.8%, P = 0.019, 24 months). The rf-PDT group tended to show better VA improvement, but was not statistically significant (–0.06 vs. –0.008, P = 0.07, 12 months; –0.06 vs. –0.03, P = 0.32, 24 months). An IPTW Cox regression showed a significantly higher rate of complete SRD rem

AbstractCausal inference is capable of estimating the treatment effect (i.e., the causal effect of treatment on the outcome) to benefit the decision making in various domains. One fundamental challenge in this research is that the treatment assignment bias in observational data. To increase the validity of observational studies on causal inference, representation-based methods as the state-of-the-art have demonstrated the superior performance of treatment effect estimation. Most representation-based methods assume all observed covariates are pre-treatment (i.e., not affected by the treatment) and learn a balanced representation from these observed covariates for estimating treatment effect. Unfortunately, this assumption is often too strict a requirement in practice, as some covariates are changed by doing an intervention on treatment (i.e., post-treatment). By contrast, the balanced representation learned from unchanged covariates thus biases the treatment effect estimation. In light of this, we propose a deep treatment-adaptive architecture (DTANet) that can address the post-treatment covariates and provide a unbiased treatment effect estimation. Generally speaking, the contributions of this work are threefold. First, our theoretical results guarantee DTANet can identify treatment effect from observations. Second, we introduce a novel regularization of orthogonality projection to ensure that the learned confounding representation is invariant and not being contaminated by the treatment, meanwhile mediate variable representation is informative and discriminative for predicting the outcome. Finally, we build on the optimal transport and learn a treatment-invariant representation for the unobserved confounders to alleviate the confounding bias.

Commonly used semi-parametric estimators of causal effects, specify parametric models for the propensity score and the conditional outcome. An example is an augmented inverse probability weighting estimator, frequently referred to as a doubly robust estimator, since it is consistent if at least one of the two models is correctly specified. However, in many observational studies the role of the parametric models is often not to provide a representation of the data generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper we propose a crude analytical approach to study the large sample bias of estimators when the models are assumed to be approximations of the data generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two inverse probability weighting (IPW) estimators, using a misspecified propensity score model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression and the propensity score. For the two IPW estimators we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models are better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecificiation of the outcome model is moderate the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations we include three simulation stud

Commonly used semi-parametric estimators of causal effects, specify parametric models for the propensity score and the conditional outcome. An example is an augmented inverse probability weighting estimator, frequently referred to as a doubly robust estimator, since it is consistent if at least one of the two models is correctly specified. However, in many observational studies the role of the parametric models is often not to provide a representation of the data generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper we propose a crude analytical approach to study the large sample bias of estimators when the models are assumed to be approximations of the data generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two inverse probability weighting (IPW) estimators, using a misspecified propensity score model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression and the propensity score. For the two IPW estimators we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models are better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecificiation of the outcome model is moderate the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations we include three simulation stud

Commonly used semi-parametric estimators of causal effects, specify parametric models for the propensity score and the conditional outcome. An example is an augmented inverse probability weighting estimator, frequently referred to as a doubly robust estimator, since it is consistent if at least one of the two models is correctly specified. However, in many observational studies the role of the parametric models is often not to provide a representation of the data generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper we propose a crude analytical approach to study the large sample bias of estimators when the models are assumed to be approximations of the data generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two inverse probability weighting (IPW) estimators, using a misspecified propensity score model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression and the propensity score. For the two IPW estimators we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models are better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecificiation of the outcome model is moderate the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations we include three simulation stud

The use of automated procedures has recently become popular in the causal inference literature. Naive implementations of automatic procedures stand in contrast to the perspective advocated in Imbens and Rubin's Causal Inference. Imbens and Rubin suggest that researchers should make modelling decisions informed by subjective knowledge. We make use of simulated data to compare Imbens and Rubin's approach to naive implementations of two automatic procedures: Genetic Matching and Entropy Balancing. In addition we perform a small Monte Carlo simulation, based on one of the simulated data sets. Using the simulated data sets and the Monte Carlo simulations, we illustrate and explore benefits and drawbacks of the different approaches. We argue that there are benefits to make use of design-decisions grounded in subjective knowledge.

We estimated the effect of pneumococcal vaccination (PV) on acute lower respiratory tract infections (LRTIs) in various age and risk groups using different methods within a causal inference methodological framework. We used data from a general practitioners' morbidity registry for the year 2019. Both traditional statistical methods (regression-based and propensity score methods) and machine learning techniques were deployed. Multiple imputation was used to account for missing data. Relative risks (RRs) with 95% confidence intervals were estimated. Sensitivity analyses were performed to account for the severity of LRTIs and differences in vaccination registration. All methods showed a standardized mean difference below 0.1 for each covariate. No method was found to be superior to another. PV (combination of conjugate and polysaccharide vaccine) had an overall protective effect for severe LRTIs. PV was protective in different age and risk groups, especially in people aged 50-84 years with an intermediate risk group. Using several techniques, PV was found to prevent severe LRTIs and confirmed the recommendations of the Belgian Superior Health Council.

In medicine, retrospective cohort studies are used to compare treatments to one another. We hypothesize that the outcomes of retrospective comparative effectiveness research studies can be heavily influenced by biostatistical analytic choices, thereby leading to inconsistent conclusions. We selected a clinical scenario currently under investigation: survival in metastatic prostate, breast or lung cancer after systemic vs systemic + definitive local therapy. We ran >300 000 regression models (each representing a publishable study). Each model had various forms of analytic choices (to account for bias): propensity score matching, left truncation adjustment, landmark analysis and covariate combinations. There were 72 549 lung, 14 904 prostate and 13 857 breast cancer patients included. In the most basic analysis, which omitted propensity score matching, left truncation adjustment and landmark analysis, all of the HRs were <1 (generally, 0.60-0.95, favoring addition of local therapy), with all P-values <.001. Left truncation adjustment landmark analysis produced results with nonsignificant P-values. The combination of propensity score matching, left truncation adjustment, landmark analysis and covariate combinations generally produced P-values that were >.05 and/or HRs that were >1 (favoring systemic therapy alone). The use of more statistical methods to reduce the selection bias caused reported HR ranges to approach 1.0. By varying analytic choices in comparative effectiveness research, we generated contrary outcomes. Our results suggest that some retrospective observational studies may find a treatment improves outcomes for patients, while another similar study may find it does not, simply based on analytical choices.

In medicine, retrospective cohort studies are used to compare treatments to one another. We hypothesize that the outcomes of retrospective comparative effectiveness research studies can be heavily influenced by biostatistical analytic choices, thereby leading to inconsistent conclusions. We selected a clinical scenario currently under investigation: survival in metastatic prostate, breast or lung cancer after systemic vs systemic + definitive local therapy. We ran >300 000 regression models (each representing a publishable study). Each model had various forms of analytic choices (to account for bias): propensity score matching, left truncation adjustment, landmark analysis and covariate combinations. There were 72 549 lung, 14 904 prostate and 13 857 breast cancer patients included. In the most basic analysis, which omitted propensity score matching, left truncation adjustment and landmark analysis, all of the HRs were <1 (generally, 0.60-0.95, favoring addition of local therapy), with all P-values <.001. Left truncation adjustment landmark analysis produced results with nonsignificant P-values. The combination of propensity score matching, left truncation adjustment, landmark analysis and covariate combinations generally produced P-values that were >.05 and/or HRs that were >1 (favoring systemic therapy alone). The use of more statistical methods to reduce the selection bias caused reported HR ranges to approach 1.0. By varying analytic choices in comparative effectiveness research, we generated contrary outcomes. Our results suggest that some retrospective observational studies may find a treatment improves outcomes for patients, while another similar study may find it does not, simply based on analytical choices.

Commonly used semi-parametric estimators of causal effects, specify parametric models for the propensity score and the conditional outcome. An example is an augmented inverse probability weighting estimator, frequently referred to as a doubly robust estimator, since it is consistent if at least one of the two models is correctly specified. However, in many observational studies the role of the parametric models is often not to provide a representation of the data generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper we propose a crude analytical approach to study the large sample bias of estimators when the models are assumed to be approximations of the data generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two inverse probability weighting (IPW) estimators, using a misspecified propensity score model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression and the propensity score. For the two IPW estimators we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models are better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecificiation of the outcome model is moderate the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations we include three simulation stud

Background: Acute clinical events, such as pneumonia, may impact physical functionality but their effect on cognition and the possible duration of this effect remains to be quantified. This study investigated the impact of pneumonia on cognitive trajectories and dementia development in older people. Methods: Data were obtained from 60+ years old individuals, who were assessed from 2001 to 2018 in the population-based SNAC-K study (Sweden). Participants were eligible if they were not institutionalized, had no dementia, and did not experience pneumonia 5 years prior to baseline (N = 2 063). A propensity score was derived to match 1:3 participants hospitalized with a diagnosis of pneumonia (N = 178), to nonexposed participants (N = 534). Mixed linear models were used to model cognitive decline. The hazard of dementia, clinically diagnosed by physicians following Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV, was estimated using Cox regression models. Results: We found a transient impact of pneumonia on cognitive decline in the first 2.5 years (B = −0.94, 95% confidence interval [CI] −1.75, −0.15). The hazard ratio (HR) for dementia was not statistically significantly increased in pneumonia participants (HR = 1.17, 95%CI 0.82, 1.66). Conclusions: The transient impact of pneumonia on cognitive function suggests an increased need of health care for patients after a pneumonia-related hospitalization and reinforces the relevance of pneumonia prevention.

BackgroundDespite their well-established benefits for the prevention of cardiovascular disease, robust evidence on the effects of statins on cognition is largely inconclusive. We apply various study designs and analytical approaches to mimic randomized controlled trial effects from observational data.MethodsWe used observational data from 5 580 participants enrolled in the Cardiovascular Health Study from 1989/1990 to 1999/2000. We conceptualized the cohort as an overlapping sequence of nonrandomized trials. We compared multiple selection (eligible population, prevalent users, new users) and analytic approaches (multivariable adjustment, inverse-probability treatment weights, propensity score matching) to evaluate the association between statin use and 5-year change in global cognitive function, assessed using the Modified Mini-Mental State Examination (3MSE).ResultsWhen comparing prevalent users to nonusers (N = 2 772), statin use was associated with slower cognitive decline over 5 years (adjusted annual change in 3MSE = 0.34 points/year; 95% CI: 0.05-0.63). Compared to prevalent user design, estimates from new user designs (eg, comparing eligible statin initiators to noninitiators) were attenuated showing either null or negative association, though not significant. For example, in a propensity score-matched sample of statin-eligible individuals (N = 454), the annual 3MS change comparing statin initiators to noninitiators was -0.21 points/year (95% CI: -0.81 to 0.39).ConclusionsThe association of statin use and cognitive decline is attenuated toward the null when using rigorous analytical approaches that more closely mimic randomized controlled trials. Point estimates, even within the same study, may vary depending on the analytical methods used. Further studies that leverage natural or quasi experiments around statin use are needed to replicate our findings.

Study objectiveThis study aimed to explore oral ondansetron usage and impact on outcomes in clinical practice.MethodsThis observational study was a planned secondary analysis of 2 trials conducted in 10 US and 6 Canadian institutions between 2014 and 2017. Children 3 to 48 months old with gastroenteritis and ≥3 episodes of vomiting in the 24 hours preceding emergency department (ED) presentation were included. Oral ondansetron was administered at the discretion of the provider. The principal outcomes were intravenous fluid administration and hospitalization at the index visit and during the subsequent 72 hours and diarrhea and vomiting frequency during the 24 hours following the ED visit.ResultsIn total, 794 children were included. The median age was 16.0 months (interquartile range 10.0 to 26.0), and 50.1% (398/794) received oral ondansetron. In propensity-adjusted analysis (n=528), children administered oral ondansetron were less likely to receive intravenous fluids at the index visit (adjusted odds ratio [aOR] 0.50; 95% confidence interval [CI] 0.29 to 0.88). There were no differences in the frequencies of intravenous fluid administration within the first 72 hours (aOR 0.65; 95% CI 0.39 to 1.10) or hospitalization at the index visit (aOR 0.31; 95% CI 0.09 to 1.10) or the subsequent 72 hours (aOR 0.52; 95% CI 0.21 to 1.28). Episodes of vomiting (aRR 0.86; 95% CI 0.63 to 1.19) and diarrhea (aRR 1.11; 95% CI 0.93 to 1.32) during the 24 hours following ED discharge also did not differ.ConclusionAmong preschool-aged children with gastroenteritis seeking ED care, oral ondansetron administration was associated with a reduction in index ED visit intravenous fluid administration; it was not associated with intravenous fluids administered within 72 hours, hospitalization, or vomiting and diarrhea in the 24 hours following discharge.

PurposeEnd-stage renal disease (ESRD) is a well-recognized risk factor for the development of sudden cardiac arrest (SCA). There is limited data on baseline characteristics and outcomes after an in-hospital SCA event in ESRD patients.MethodsFor the purpose of this study, data were obtained from the National Inpatient Sample from January 2007 to December 2017. In-hospital SCA was identified using the International Classification of Disease, 9th Revision, Clinical Modification and International Classification of Disease, 10th Revision, Clinical Modification codes of 99.60, 99.63, and 5A12012. ESRD patients were subsequently identified using codes of 585.6 and N18.6. Baseline characteristics and outcomes were compared among ESRD and non-ESRD patients in crude and propensity score (PS)-matched cohorts. Predictors of mortality in ESRD patients after an in-hospital SCA event were analyzed using a multivariate logistic regression model.ResultsA total of 1,412,985 patients sustained in-hospital SCA during our study period. ESRD patients with in-hospital SCA were younger and had a higher burden of key co-morbidities. Mortality was similar in ESRD and non-ESRD patients in PS-matched cohort (70.4% vs. 70.7%, p = 0.45) with an overall downward trend over our study years. Advanced age, Black race, and key co-morbidities independently predicted increased mortality while prior implantable defibrillator was associated with decreased mortality in ESRD patients after an in-hospital SCA event.ConclusionsIn the context of in-hospital SCA, mortality is similar in ESRD and non-ESRD patients in adjusted analysis. Adequate risk factor modification could further mitigate the risk of in-hospital SCA among ESRD patients.

Background Many patients with severe aortic stenosis (AS) and an indication for aortic valve replacement (AVR) do not undergo treatment. The reasons for this have not been well studied in the transcatheter AVR era. We sought to determine how patient- and process-specific factors affected AVR use in patients with severe AS. Methods and Results We identified ambulatory patients from 2016 to 2018 demonstrating severe AS, defined by aortic valve area [Formula: see text]1.0 cm2. Propensity scoring analysis with inverse probability of treatment weighting was used to evaluate associations between predictors and the odds of undergoing AVR at 365 days and subsequent mortality at 730 days. Of 324 patients with an indication for AVR (79.3±9.7 years, 57.4% men), 140 patients (43.2%) did not undergo AVR. The odds of AVR were reduced in patients aged >90 years (odds ratio [OR], 0.24 [95% CI, 0.08-0.69]; P=0.01), greater comorbid conditions (OR, 0.88 per 1-point increase in Combined Comorbidity Index [95% CI, 0.79-0.97]; P=0.01), low-flow, low-gradient AS with preserved left ventricular ejection fraction (OR, 0.11 [95% CI, 0.06-0.21]), and low-gradient AS with reduced left ventricular ejection fraction (OR, 0.18 [95% CI, 0.08-0.40]) and were increased if the transthoracic echocardiogram ordering provider was a cardiologist (OR, 2.46 [95% CI, 1.38-4.38]). Patients who underwent AVR gained an average of 85.8 days of life (95% CI, 40.9-130.6) at 730 days. Conclusions The proportion of ambulatory patients with severe AS and an indication for AVR who do not receive AVR remains significant. Efforts are needed to maximize the recognition of severe AS, especially low-gradient subtypes, and to encourage patient referral to multidisciplinary heart valve teams.

The latest data from the United States Renal Data Systems show over 134,000 individuals with end-stage kidney disease (ESKD) starting dialysis in the year 2019. ESKD patients on dialysis, the default treatment strategy, have high mortality and hospitalization, especially in the first year of dialysis. An alternative treatment strategy is (non-dialysis) conservative management (CM). The relative effectiveness of CM with respect to various patient outcomes, including survival, hospitalization, and health-related quality of life among others, especially in elderly ESKD or advanced chronic kidney disease patients with serious comorbidities, is an active area of research. A technical challenge inherent in comparing patient outcomes between CM and dialysis patient groups is that the start of follow-up time is "not defined" for patients on CM because they do not initiate dialysis. One solution is the use of putative dialysis initiation (PDI) time. In this work, we examine the validity of the use of PDI time to determine the start of follow-up for longitudinal retrospective and prospective cohort studies involving CM. We propose and assess the efficacy of estimating PDI time using linear mixed effects model of kidney function decline over time via simulation studies. We also illustrate how the estimated PDI time can be used to effectively estimate the survival distribution.