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Objective We sought to determine the rate of postoperative supraventricular tachycardia (POSVT) in patients undergoing pulmonary lobectomy, and its association with adverse outcomes. Methods Using the State Inpatient Database, from the Healthcare Cost and Utilization Project, we reviewed lobectomies performed (2009-2011) in California, Florida, and New York, to determine POSVT incidence. Patients were grouped by presence or absence of POSVT, with or without other complications. Stroke rates were analyzed independently from other complications. Multivariable regression analysis was used to determine factors associated with POSVT. Results Among 20,695 lobectomies performed, 2449 (11.8%) patients had POSVT, including 1116 (5.4%) with isolated POSVT and 1333 (6.4%) with POSVT with other complications. Clinical predictors of POSVT included age ≥75 years, male gender, white race, chronic obstructive pulmonary disease, congestive heart failure, thoracotomy surgical approach, and pulmonary complications. POSVT was associated with an increase of: stroke (odds ratio [OR] 1.74; 95% confidence interval [CI] 1.03-2.94); in-hospital death (OR 1.85; 95% CI 1.45-2.35); LOS (OR 1.33; 95% CI 1.29-1.37); and readmission (OR 1.29; 95% CI 1.04-1.60). The stroke rate was <1% in patients who had isolated POSVT, and 1.5% in patients with POSVT with other complications. Patients with isolated POSVT had increased readmission and LOS, and a marginal increase in stroke rate, compared with patients with an uncomplicated course. Conclusions POSVT is common in patients undergoing pulmonary lobectomy and is associated with adverse outcomes. Comparative studies are needed to determine whether strict adherence to recently published guidelines will decrease the rate of stroke, readmission, and death after POSVT in thoracic surgical patients. [ABSTRACT FROM AUTHOR]

Background Readmission rates after major procedures are used to benchmark quality of care. We sought to identify readmission diagnoses and factors associated with readmission in patients undergoing pulmonary lobectomy. Methods Analyzing the State Inpatient Databases (Healthcare Cost and Utilization Project), we reviewed all lobectomies performed from 2009 to 2011 in California, Florida, and New York. The group was subdivided into open (OL) versus minimally invasive lobectomy (MIL; thoracoscopic/robotic). We used unique identifiers to determine 30- and 90-day readmission rates and diagnoses and performed regression analysis to determine factors associated with readmission. Results A total of 22,647 lobectomies were identified (58.8% OL vs 41.2% MIL; median age, 68 years; median length of stay, 6 days). Most patients (59.8%) had routine discharge home (home health care, 29.4%; transfer to other facility, 8.8%; mortality, 1.9%). The 30-day readmission rate was 11.5% (OL 12.0% vs MIL 10.8%, p = 0.01), while the 90-day readmission rate was 19.8% (OL 21.1% vs MIL 17.9%, p < 0.001). The most common readmission diagnoses were pulmonary (24.1%), cardiovascular (16.3%), and complications related to surgical/medical procedures (15.1%). Preoperative factors associated with readmission included male gender (odds ratio, 1.19), Medicaid payer (odds ratio, 1.29), and several individual comorbidities. Surgical approach and postoperative complications were not independently associated with readmission. Conclusions Readmission is a frequent event after pulmonary lobectomy and is strongly associated with preoperative demographic factors and comorbidities. Resources and services should be directed to patients at risk for readmission and multicomponent care pathways developed that may circumvent the need for repeat hospitalization. [ABSTRACT FROM AUTHOR]

Abstract: Background context: Despite increasing utilization of surgical spine fusions, a paucity of literature addressing perioperative complications after revision posterior spinal fusion (RPSF) versus primary posterior spine fusion (PPSF) of the thoracic and lumbar spine exists. Purpose: To examine demographics of patients undergoing PPSF and RPSF of the thoracic and lumbar spine, assess the incidence of perioperative morbidity and mortality, and determine independent risk factors for in-hospital death. Study design/setting: Analysis of nationally representative data collected for the National Inpatient Sample (NIS). Patient sample: All discharges included in the NIS with a procedure code for posterior thoracic and lumbar spine fusion from 1998 to 2006. Outcome measures: In-hospital mortality and morbidity. Methods: Data collected for each year between 1998 and 2006 for the NIS were analyzed. Discharges with a procedure code for thoracic and lumbar spine fusion were included in the sample. The prevalence of patient- as well as health care–related demographics was evaluated by procedure type (primary vs. revision). Frequencies of procedure-related complications and in-hospital mortality were analyzed. Independent predictors for in-hospital mortality were determined. Results: We identified 222,549 PPSF and 12,474 RPSF discharges between 1998 and 2006. Patients undergoing PPSF were significantly younger (51.23 years; confidence interval [CI]=51.16, 51.31) and had lower average comorbidity indices (0.40; CI=0.39, 0.41) than those undergoing RPSF (52.69 years; CI=52.43, 52.97) and (0.44; CI=0.43, 0.45), p<.0001. The incidence of procedure-related complications was 16.02% among RPSF compared with 13.44% in PPSF patients (p<.0001). In-hospital mortality rates after PPSF were approximately twice those of RPSF (0.28% vs. 0.15%, p=.006). Adjusted risk factors for increased in-hospital mortality included PPSF compared with RPSF, male gender, and increasing age. A number of comorbidities, complications, and specific surgical indications increased the risk for perioperative death. Conclusion: Despite being performed in generally younger and healthier patients and having lower perioperative morbidity, PPSF procedures are associated with increased mortality compared with RPSF procedures. The findings of this study can be used for risk stratification, accurate patient consultation, and hypothesis formation for future research. [Copyright &y& Elsevier]

Study Objective: To confirm the relationship between primary payer status as a predictor of increased perioperative risks and post-operative outcomes after total hip replacements.Design: Retrospective cohort study.Setting: Administrative database study using 2007-2011 data from California, Florida, and New York from the State Inpatient Databases (SID), Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality.Patients: 295,572 patients age≥18years old who underwent total hip replacement with non-missing insurance data were collected, using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnoses and procedures code (ICD-9-CM code 81.51).Interventions: Patients underwent total hip replacement.Measurements: Patients were cohorted by insurance type as either Medicare, Medicaid, Uninsured, Other, and Private Insurance. Demographic characteristics and comorbidities were compared. Unadjusted rates of in-hospital mortality, postoperative complications, LOS, 30-day, and 90-day readmission status were compared. Adjusted odds ratios were calculated for our outcomes using multivariate linear and logistic regression models fitted to our data.Main Results: Medicaid patients incurred a 125% increase in the odds of in-hospital mortality compared to those with Private Insurance (OR 2.25, 99% CI 1.01-5.01). Medicaid payer status was associated with the highest statistically significant adjusted odds of mortality, any complication (OR, 1.26), cardiovascular complications (OR, 1.37), and infectious complications (OR, 1.66) when compared with Private Insurance. Medicaid patients had the highest statistically significant adjusted odds of 30-day (OR, 1.63) and 90-day readmission (OR, 1.58) and the longest adjusted LOS.Conclusions: We found higher unadjusted rates and risk adjusted odds ratios of postoperative mortality, morbidity, LOS, and readmissions for patients with Medicaid insurance as compared to patients with Private Insurance. Our study shows that primary payer status serves as a predictor of perioperative risks and that primary payer status should be viewed as a peri-operative risk factor. [ABSTRACT FROM AUTHOR]