Stuart R Lipsitz

Brigham and Women's Hospital , Boston, Massachusetts, United States

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Publications (441)2169.41 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: To identify the timing and relative frequency of common postoperative complications in a contemporary, diverse surgical population and develop a mnemonic for teaching and clinical decision support. We enrolled a cohort of general and vascular surgical patients undergoing elective, inpatient surgery in the American College of Surgeons National Surgical Quality Improvement Program database between 2005 and 2011. Index complications were noted by postoperative day (POD). Timing and incidence were compared within each day. Among 614,525 patients, 51,173 (9.88%) experienced the following index complications over 30 days: pneumonia (n = 5947), urinary tract infection (n = 9459), superficial surgical site infection (sSSI) (n = 20,460), deep/organ space surgical site infection (dSSI) infection (n = 11,847), venous thromboembolism (n = 4478), kidney injury (n = 2620), and myocardial infarction (n = 1813). Median time to complication differed significantly for index complications (p < 0.0001). On POD 0, the most common complication was myocardial infarction (incidence 4.26/10,000 patient days; 95% CI: 3.75-4.78). On POD 1 and 2, pneumonia was the most common complication, with peak incidence on POD 2 (20.36; 95% CI: 19.22-21.51). On POD 3, pneumonia (16.3; 95% CI: 15.27-17.33) and urinary tract infection (15.5; 95% CI: 14.49-16.51) were significantly more common than other complications. On POD 4, the most common complication was sSSI (16.24; 95% CI: 15.20-17.28). From POD 5 to POD 30, sSSI and dSSI were the 2 most common complications. Risk of venous thromboembolism declined only slightly through POD 30. We propose a mnemonic for postoperative complication timing and frequency, independent of fever, as follows: Waves (myocardial infarction), Wind (pneumonia), Water (urinary tract), Wound (sSSI and dSSI), and Walking (venous thromboembolism) in the order of likelihood. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
    Journal of Surgical Education 12/2014; · 1.39 Impact Factor
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    ABSTRACT: Blood pressure (BP) control rates are suboptimal. We evaluated the effectiveness of 2 behavioral interventions to improve BP control via a 3-arm, randomized controlled trial of 533 adults with repeated uncontrolled BP, despite antihypertensive drug treatment for ≥6 months. The interventions were a tailored stage-matched intervention (SMI) or a nontailored health education intervention (HEI) of 6 monthly calls targeting diet, exercise, and medication. Control was usual care (UC). There were no baseline group differences. Baseline BP control was 42.6%, 40.6%, and 44.6% in SMI, HEI, and UC (P=0.74), respectively; systolic BP (with SEs) was 136 (0.89), 137 (1.33), and 137 (0.96) mm Hg. Six-month control was 64.6% (SMI), 54.3% (HEI), and 45.8% (UC) (P values for pairwise comparisons versus UC, 0.001 [SMI] and 0.108 [HEI]). At 6 months, systolic BP (SE) was 131.2 (1.05), 131.8 (0.99), and 134.7 (1.02) for SMI, HEI, and UC, respectively (P values for pairwise comparisons versus UC, 0.009 for SMI and 0.047 for HEI). SMI led to lower systolic BP and better BP control than UC. SMI constitutes a new, potent approach to assist patients with uncontrolled hypertension to reach BP goals. © 2014 American Heart Association, Inc.
    Hypertension 11/2014; · 7.63 Impact Factor
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    ABSTRACT: Bernoulli (or binomial) regression using a generalized linear model with a log link function, where the exponentiated regression parameters have interpretation as relative risks, is often more appropriate than logistic regression for prospective studies with common outcomes. In particular, many researchers regard relative risks to be more intuitively interpretable than odds ratios. However, for the log link, when the outcome is very prevalent, the likelihood may not have a unique maximum. To circumvent this problem, a 'COPY method' has been proposed, which is equivalent to creating for each subject an additional observation with the same covariates except the response variable has the outcome values interchanged (1's changed to 0's and 0's changed to 1's). The original response is given weight close to 1, while the new observation is given a positive weight close to 0; this approach always leads to convergence of the maximum likelihood algorithm, except for problems with convergence due to multicollinearity among covariates. Even though this method produces a unique maximum, when the outcome is very prevalent, and/or the sample size is relatively small, the COPY method can yield biased estimates. Here, we propose using the jackknife as a bias-reduction approach for the COPY method. The proposed method is motivated by a study of patients undergoing colorectal cancer surgery. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 11/2014; · 2.04 Impact Factor
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    ABSTRACT: Miscommunications are a leading cause of serious medical errors. Data from multicenter studies assessing programs designed to improve handoff of information about patient care are lacking.
    New England Journal of Medicine 11/2014; 371(19):1803-12. · 54.42 Impact Factor
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    ABSTRACT: Our purpose was to provide a metric by which evaluation criteria are prioritized during resident selection. In this study, we assessed which residency applicant qualities are deemed important by members of the American Association of Plastic Surgeons (AAPS).
    Journal of Surgical Education 09/2014; · 1.39 Impact Factor
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    ABSTRACT: The relationship between timing of postoperative complications on mortality is unknown. We investigated the time-variable mortality risks of common surgical complications.
    Journal of Surgical Research 08/2014; · 2.12 Impact Factor
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    ABSTRACT: Audits provide a rational framework for quality improvement by systematically assessing clinical practices against accepted standards with the aim to develop recommendations and interventions that target modifiable deficiencies in care. Most childbirth-associated mortality audits in developing countries are focused on a single facility and, up to now, the avoidable factors in maternal and perinatal deaths cataloged in these reports have not been pooled and analyzed. We sought to identity the most frequent avoidable factors in childbirth-related deaths globally through a systematic review of all published mortality audits in low and lower-middle income countries.
    BMC Pregnancy and Childbirth 08/2014; 14(1):280. · 2.15 Impact Factor
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    ABSTRACT: Introduction Invasive procedures are resource-intense and may be associated with substantial morbidity. These harms must be carefully balanced with the benefits gained in life expectancy and quality of life. Prior research has demonstrated an increasing aggressiveness of care in cancer patients at the end of life. To better characterize surgical care in this setting, we sought to examine trends in the use of invasive procedures in patients diagnosed with metastatic cancer on presentation. Materials & Methods Using SEER-Medicare data, we identified invasive procedure claims from 1994-2009 for patients diagnosed with incident stage IV breast, colorectal, lung, and prostate cancer patients in 1995-2006. We grouped procedures into surgically relevant categories, using an adaptation of the Clinical Classifications Software (CCS), and measured utilization and relative changes over time. Results Of stage IV patients diagnosed in 2002-2006, 96% underwent a procedure during the course of their cancer care including 63% after the diagnostic period, and 25% in the last month of life. Between 1996 and 2006, minimal change was observed in utilization during the diagnostic period (+1.5%). However, there were significant increases during continuing care (+20.7%) and the last month of life (+21.5%). Procedures consistent with primary tumor resection decreased, while those with probable palliative intent and those unrelated to cancer increased. Conclusions Nearly all patients who present with metastatic cancer undergo invasive procedures. While overall utilization is increasing, the specific procedure types indicate that it may be appropriate, enhancing the quality of life in this vulnerable population.
    Journal of Surgical Research 08/2014; · 2.12 Impact Factor
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    ABSTRACT: Although demographic, clinicopathologic, and socioeconomic differences may affect treatment and outcomes of prostate cancer, the effect of mental health disorders remains unclear. We assessed the effect of previously diagnosed depression on outcomes of men with newly diagnosed prostate cancer.
    Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 07/2014;
  • Garrett M Fitzmaurice, Stuart R Lipsitz
    Biostatistics 07/2014; · 2.24 Impact Factor
  • JAMA surgery. 06/2014;
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    ABSTRACT: For either the equivalence trial or the non-inferiority trial with survivor outcomes from two treatment groups, the most popular testing procedure is the extension (e.g., Wellek, A log-rank test for equivalence of two survivor functions, Biometrics, 1993; 49: 877-881) of log-rank based test under proportional hazards model. We show that the actual type I error rate for the popular procedure of Wellek is higher than the intended nominal rate when survival responses from two treatment arms satisfy the proportional odds survival model. When the true model is proportional odds survival model, we show that the hypothesis of equivalence of two survival functions can be formulated as a statistical hypothesis involving only the survival odds ratio parameter. We further show that our new equivalence test, formulation, and related procedures are applicable even in the presence of additional covariates beyond treatment arms, and the associated equivalence test procedures have correct type I error rates under the proportional hazards model as well as the proportional odds survival model. These results show that use of our test will be a safer statistical practice for equivalence trials of survival responses than the commonly used log-rank based tests.
    Statistical Methods in Medical Research 06/2014; · 2.96 Impact Factor
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    ABSTRACT: Often, the reader of a published paper is interested in a comparison of parameters that has not been presented. It is not possible to make inferences beyond point estimation since the standard error for the contrast of the estimated parameters depends upon the (unreported) correlation. This study explores approaches to obtain valid confidence intervals when the correlation [Formula: see text] is unknown. We illustrate three proposed approaches using data from the National Health Interview Survey. The three approaches include the Bonferroni method and the standard confidence interval assuming [Formula: see text] (most conservative) or [Formula: see text] (when the correlation is known to be non-negative). The Bonferroni approach is found to be the most conservative. For the difference in two estimated parameter, the standard confidence interval assuming [Formula: see text] yields a 95% confidence interval that is approximately 12.5% narrower than the Bonferroni confidence interval; when the correlation is known to be positive, the standard 95% confidence interval assuming [Formula: see text] is approximately 38% narrower than the Bonferroni. In summary, this article demonstrates simple methods to determine confidence intervals for unreported comparisons. We suggest use of the standard confidence interval assuming [Formula: see text] if no information is available or [Formula: see text] if the correlation is known to be non-negative.
    PLoS ONE 05/2014; 9(5):e98498. · 3.53 Impact Factor
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    ABSTRACT: To examine the impact of radical prostatectomy (RP) operative time on outcomes and cost, we performed a population-based assessment of operative time as a predictor of outcomes. Although operative time has been used as a metric to evaluate RP surgeon learning curves, the effect of RP operative times on outcomes remains understudied. We used US Surveillance, Epidemiology, and End Results-Medicare linked data to identify 7534 men aged ≥66 years diagnosed with prostate cancer during 2003-2007 who underwent RP for localized prostate cancer through 2009. We categorized RP operative time into quartiles (short, intermediate, long, and very long) and used propensity score analyses to assess its impact on perioperative complications, mortality, length of hospitalization, readmissions, emergency room visits, and costs. Quartiles ranged from 0 to 172 minutes for short, 173 to 214 minutes for intermediate, 215 to 268 minutes for long, and ≥269 minutes for very long RP operative times. After propensity score adjustment, longer operative time was associated with more surgery-related complications (short, 12.0%; intermediate, 12.3%; long, 14.4%; and very long, 22.8%; P <.001), longer median (interquartile range) length of stay in days (short, 2 [2-3]; intermediate, 2 [2-3]; long, 2 [1-3]; and very long, 2 [1-3]; P <.001), and higher median costs (short, $10,647; intermediate, $10,957; long, $11,405; and very long, $11,966; P <.001). Longer RP operative time is associated with more complications, longer lengths of hospital stay, and higher costs. Increasing operative efficiency may reduce complications, length of stay, and health-care costs.
    Urology 04/2014; · 2.13 Impact Factor
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    ABSTRACT: Relative risks (RRs) are often considered the preferred measures of association in prospective studies, especially when the binary outcome of interest is common. In particular, many researchers regard RRs to be more intuitively interpretable than odds ratios. Although RR regression is a special case of generalized linear models, specifically with a log link function for the binomial (or Bernoulli) outcome, the resulting log-binomial regression does not respect the natural parameter constraints. Because log-binomial regression does not ensure that predicted probabilities are mapped to the [0,1] range, maximum likelihood (ML) estimation is often subject to numerical instability that leads to convergence problems. To circumvent these problems, a number of alternative approaches for estimating RR regression parameters have been proposed. One approach that has been widely studied is the use of Poisson regression estimating equations. The estimating equations for Poisson regression yield consistent, albeit inefficient, estimators of the RR regression parameters. We consider the relative efficiency of the Poisson regression estimator and develop an alternative, almost efficient estimator for the RR regression parameters. The proposed method uses near-optimal weights based on a Maclaurin series (Taylor series expanded around zero) approximation to the true Bernoulli or binomial weight function. This yields an almost efficient estimator while avoiding convergence problems. We examine the asymptotic relative efficiency of the proposed estimator for an increase in the number of terms in the series. Using simulations, we demonstrate the potential for convergence problems with standard ML estimation of the log-binomial regression model and illustrate how this is overcome using the proposed estimator. We apply the proposed estimator to a study of predictors of pre-operative use of beta blockers among patients undergoing colorectal surgery after diagnosis of colon cancer.
    Biostatistics 04/2014; · 2.24 Impact Factor
  • The Journal of Urology 04/2014; 191(4):e708-e709. · 3.75 Impact Factor
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    ABSTRACT: The primary goal of an operation for rectal cancer is to cure cancer and, where possible, preserve continence. A wide range of sphincter preservation rates have been reported. This study evaluated hospital variation in the use of low anterior resection (LAR), local excision (LE), and abdominoperineal resection (APR) in the treatment of elderly rectal cancer patients. Using Surveillance, Epidemiology, and End Results-Medicare linked data, we identified 4959 patients older than 65 y with stage I-III rectal cancer diagnosed from 2000-2005 who underwent operative intervention at one of 370 hospitals. We evaluated the distribution of hospital-specific procedure rates and used generalized mixed models with random hospital effects to examine the influence of patient characteristics and hospital on operation type, using APR as a reference. The median hospital performed APR on 33% of elderly patients with rectal cancer. Hospital was a stronger predictor of LAR receipt than any patient characteristic, explaining 32% of procedure choice, but not a strong predictor of LE, explaining only 3.8%. Receipt of LE was primarily related to tumor size and tumor stage, which combined explained 31% of procedure variation. Receipt of LE is primarily determined by patient characteristics. In contrast, the hospital where surgery is performed significantly influences whether a patient undergoes an LAR or APR. Understanding the factors that cause this institutional variation is crucial to ensuring equitable availability of sphincter preservation.
    Journal of Surgical Research 03/2014; · 2.12 Impact Factor
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    ABSTRACT: To characterize population-based practice patterns, disease-specific and overall mortality, and cost associated with salvage cryotherapy (SCT) vs salvage radical prostatectomy (SRP). We retrospectively identified 440 men who failed primary radiation therapy and subsequently underwent SCT (n = 341, 77.5%) or SRP (n = 99, 22.5%) between 1992 and 2009 from Surveillance, Epidemiology, and End Results-Medicare linked data. Propensity score analyses were used to compare overall and prostate cancer-specific mortality and associated Medicare expenditures for SRP vs SCT. Men undergoing SCT were more likely to be white (P <.001), less likely to be high school graduates (P = .008), and experienced shorter median time from diagnosis to salvage therapy (44.1 vs 60.1, P <.001) and from primary radiotherapy to salvage therapy (38.7 vs 55.8 months, P <.001). In adjusted analyses, overall mortality was higher (21.6 vs 6.1 deaths/100 person years, P <.001) for SRP vs SCT. There was a trend for higher prostate cancer-specific death rates with SRP vs SCT (6.5 vs 1.4 deaths/100 person years, P = .061). Medicare expenditures for SRP vs SCT were more than 2-fold higher ($19,543 vs $8,088, P <.001). SRP vs SCT is associated with higher overall mortality and greater health care expenditures. However, longer follow-up is needed to assess long-term functional outcomes and cancer control.
    Urology 03/2014; 83(3):653-7. · 2.13 Impact Factor
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    ABSTRACT: Hospitals show wide variation in outcomes and systems of care. It is unclear whether hospital complexity-the range of services and technologies provided-affects outcomes and in what direction. We sought to determine whether complexity was associated with inpatient surgical mortality. Using national Medicare data, we identified all fee-for-service inpatients who underwent 1 of 5 common high-risk surgical procedures in 2008-2009 and measured complexity by the number of unique primary diagnoses admitted to each hospital over the 2-year period. We calculated 30-day postoperative mortality rates, adjusting for patient and hospital characteristics, and used multivariable Poisson regression models to test for an association between hospital complexity and mortality rates. We then used this model to generate predicted mortality rates for low-volume and high-volume hospitals across the spectrum of hospital complexity. A total of 2691 hospitals were analyzed, representing a total of 382,372 admissions. After adjusting for hospital characteristics, including hospital volume, increasing hospital complexity was associated with lower surgical mortality rates. Patients receiving care at the hospitals in the lowest quintile of unique diagnoses had a 27% higher risk of death than those at the highest quintile. The effect of complexity was largest for low-volume hospitals, which were capable of achieving mortality rates similar to high-volume hospitals when in the most complex quintile. Hospital complexity matters and is associated with lower surgical mortality rates, independent of hospital volume. The effect of complexity on outcomes for nonsurgical services warrants investigation.
    Medical care 03/2014; 52(3):235-42. · 2.94 Impact Factor
  • Revue d Épidémiologie et de Santé Publique 03/2014; 62:S80. · 0.66 Impact Factor

Publication Stats

10k Citations
2,169.41 Total Impact Points

Institutions

  • 1992–2014
    • Brigham and Women's Hospital
      • • Department of Medicine
      • • Department of Surgery
      • • Center for Brain Mind Medicine
      Boston, Massachusetts, United States
    • University of Hawaiʻi at Mānoa
      • Department of Public Health Sciences and Epidemiology
      Honolulu, HI, United States
  • 1991–2014
    • Harvard Medical School
      • • Department of Surgery
      • • Department of Medicine
      Boston, Massachusetts, United States
  • 2013
    • University of California, Los Angeles
      • Department of Urology
      Los Angeles, CA, United States
  • 2012–2013
    • University of Wisconsin–Madison
      • Department of Surgery
      Madison, Wisconsin, United States
    • St. Joseph Hospital, Orange
      Orange, California, United States
  • 2011–2013
    • Georgetown University
      • • Department of Urology
      • • Department of Urology (MedStar)
      Washington, D. C., DC, United States
    • Brown University
      • Alpert Medical School
      Providence, RI, United States
    • The University of Chicago Medical Center
      • Section of Urology
      Chicago, Illinois, United States
    • University of Massachusetts Boston
      Boston, Massachusetts, United States
    • Emory University
      • Goizueta Business School
      Atlanta, GA, United States
  • 2004–2013
    • University of Miami Miller School of Medicine
      • • Pediatric Clinical Research
      • • Department of Pediatrics
      Miami, FL, United States
  • 1995–2013
    • Boston Children's Hospital
      • Department of Pediatric Surgery
      Boston, Massachusetts, United States
  • 1992–2013
    • Dana-Farber Cancer Institute
      • • Lank Center for Genitourinary Oncology
      • • Department of Biostatistics and Computational Biology
      Boston, Massachusetts, United States
  • 1987–2013
    • Harvard University
      • • Department of Health Policy and Management
      • • Department of Biostatistics
      Boston, MA, United States
  • 2005–2012
    • University of Miami
      • • Department of Pediatrics
      • • Miller School of Medicine
      Coral Gables, FL, United States
    • New York University
      New York City, New York, United States
  • 2001–2012
    • Medical University of South Carolina
      • • Department of Urology
      • • Division of Biostatistics and Epidemiology
      • • Department of Medicine
      Charleston, SC, United States
  • 2009–2011
    • Florida State University
      • Department of Statistics
      Tallahassee, FL, United States
    • The State Of New Jersey
      Trenton, New Jersey, United States
    • University of Texas MD Anderson Cancer Center
      Houston, Texas, United States
    • Massachusetts General Hospital
      Boston, Massachusetts, United States
    • University of California, San Francisco
      • Division of Vascular & Endovascular Surgery
      San Francisco, CA, United States
    • University of Pittsburgh
      • School of Medicine
      Pittsburgh, PA, United States
  • 2010
    • Carleton University
      • School of Mathematical & Statistics
      Ottawa, Ontario, Canada
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
    • Hospital of the University of Pennsylvania
      • Department of Biostatistics and Epidemiology
      Philadelphia, Pennsylvania, United States
  • 2007–2009
    • Partners HealthCare
      Boston, Massachusetts, United States
    • University of Florida
      Gainesville, Florida, United States
  • 2002–2004
    • University of Rochester
      • • Department of Community and Preventive Medicine
      • • Division of Pediatric Cardiology
      Rochester, NY, United States
    • University of Connecticut
      • Department of Statistics
      Mansfield City, CT, United States
    • University of Chicago
      Chicago, Illinois, United States
    • University of North Carolina at Chapel Hill
      • Department of Biostatistics
      Chapel Hill, NC, United States
  • 1999
    • University of Illinois at Chicago
      Chicago, Illinois, United States
  • 1997
    • Fred Hutchinson Cancer Research Center
      • Southwest Oncology Group Statistical Center
      Seattle, Washington, United States
  • 1990–1996
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States