ABSTRACT
A 57-year-old Southeast Asian woman with a remote history of adenoid cystic carcinoma (ACC) of the right labium superius oris (upper lip) presented to the hospital with vague epigastric pain. On workup, she was found to have multiple pleural nodules. Histopathology confirmed the diagnosis of metastatic ACC. After 8 months of active surveillance, evidence of disease progression was found and the patient was started on pembrolizumab. Follow-up after starting pembrolizumab showed stable disease with no significant side effects.
Subject(s)
Carcinoma, Adenoid Cystic/pathology , Lip Neoplasms/pathology , Pleural Neoplasms/secondary , Antibodies, Monoclonal, Humanized/therapeutic use , Antineoplastic Agents, Immunological/therapeutic use , Carcinoma, Adenoid Cystic/surgery , Diagnosis, Differential , Female , Humans , Lip/pathology , Lip/surgery , Lip Neoplasms/surgery , Middle Aged , Pleural Cavity/pathology , Pleural Neoplasms/diagnosis , Pleural Neoplasms/drug therapyABSTRACT
Limbal Stem Cells are a unique cell line located at the corneal limbus. They are responsible for regenerating and restoring corneal epithelial layers. Limbal stem cell transplantation is a promising technique that has been used to treat several hereditary and acquired corneal diseases. Cornea tissue lack vascularity. Hence, there were no special restrictions on collecting ocular tissues from donors with a diagnosis of metastatic melanoma. We are reporting a case of a patient who developed an ocular melanoma after she had limbal stem cell transplantation from a donor with history of melanoma. After this case, Eye Bank Association of America updated the donor criteria to exclude donors with any history of melanoma.
ABSTRACT
OBJECTIVES: To develop a risk-prediction model for acute kidney injury (AKI) in patients undergoing vascular surgery. DESIGN: A retrospective cohort study. SETTING: A tertiary referral center. PARTICIPANTS: Participants included 845 adult patients who underwent vascular surgery between January 3, 2003, and May 29, 2008. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The median age of patients was 72 years (interquartile range 65-80 years), and 653 patients (77%) were male. AKI developed in 258 (30.5%) patients. Patients with AKI had lower estimated glomerular filtration rates (60±21 v 72±21, p<0.001), were older (73 [68-78] years v 71 [65-80] years, p = 0.01), had a higher prevalence of hypertension (81% v 73%, p = 0.02), and were more likely to undergo emergency surgery (5% v 2%, p = 0.02). Patients with AKI also received more diuretics (p<0.001) and ß-blockers (p = 0.003) prior to surgery. The multivariate AKI risk-prediction model with preoperative variables (estimated glomerular filtration rate, previous vascular interventions, use of preoperative diuretics and ß-blockers, and emergency surgery) showed an area under the receiver operating characteristic curve of 0.67 (95% confidence interval, 0.628-0.710); a model with additional intraoperative variables (procedure duration, fluid balance, and plasma and platelet transfusion) had an area under the receiver operating characteristic curve of 0.72 (95% confidence interval, 0.685-0.760). CONCLUSIONS: As AKI is a very common complication after vascular surgery, a risk-prediction model was derived to assess the likelihood of postoperative AKI. If validated in an independent cohort, this model may be used to facilitate targeted interventions in vascular surgery patients at high risk for AKI.
Subject(s)
Acute Kidney Injury/diagnosis , Acute Kidney Injury/epidemiology , Postoperative Complications/diagnosis , Postoperative Complications/epidemiology , Vascular Surgical Procedures/adverse effects , Aged , Aged, 80 and over , Cohort Studies , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , Risk FactorsABSTRACT
INTRODUCTION: We recently presented a prediction score providing decision support with the often-challenging early differential diagnosis of acute lung injury (ALI) vs cardiogenic pulmonary edema (CPE). To facilitate clinical adoption, our objective was to prospectively validate its performance in an independent cohort. METHODS: Over 9 months, adult patients consecutively admitted to any intensive care unit of a tertiary-care center developing acute pulmonary edema were identified in real-time using validated electronic surveillance. For eligible patients, predictors were abstracted from medical records within 48 hours of the alert. Post-hoc expert review blinded to the prediction score established gold standard diagnosis. RESULTS: Of 1,516 patients identified by electronic surveillance, data were abstracted for 249 patients (93% within 48 hours of disease onset), of which expert review (kappa 0.93) classified 72 as ALI, 73 as CPE and excluded 104 as "other". With an area under the curve (AUC) of 0.81 (95% confidence interval = 0.73 to 0.88) the prediction score showed similar discrimination as in prior cohorts (development AUC = 0.81, P = 0.91; retrospective validation AUC = 0.80, P = 0.92). Hosmer-Lemeshow test was significant (P = 0.01), but across eight previously defined score ranges probabilities of ALI vs CPE were the same as in the development cohort (P = 0.60). Results were the same when comparing acute respiratory distress syndrome (ARDS, Berlin definition) vs CPE. CONCLUSION: The clinical prediction score reliably differentiates ARDS/ALI vs CPE. Pooled results provide precise estimates of the score's performance which can be used to screen patient populations or to assess the probability of ALI/ARDS vs CPE in specific patients. The score may thus facilitate early inclusion into research studies and expedite prompt treatment.
Subject(s)
Acute Lung Injury/diagnosis , Decision Support Techniques , Pulmonary Edema/diagnosis , Respiratory Distress Syndrome/diagnosis , Shock, Cardiogenic/diagnosis , Acute Lung Injury/epidemiology , Adult , Aged , Diagnosis, Differential , Female , Humans , Male , Middle Aged , Prospective Studies , Pulmonary Edema/epidemiology , Respiratory Distress Syndrome/epidemiology , Retrospective Studies , Shock, Cardiogenic/epidemiologyABSTRACT
OBJECTIVE: To examine the association between blood component transfusions and the incidence of major postoperative infections in patients undergoing esophageal resection surgery. DESIGN: Retrospective cohort study. SETTING: Single academic tertiary referral center. PARTICIPANTS: All patients who underwent esophagectomy from 2005 through 2009. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the incidence of major postoperative infection, defined as pneumonia, bloodstream infection, and/or a surgical site infection occurring within 30 days postoperatively. In total, 465 patients were evaluated. One hundred thirty-eight patients (29.7%) received a blood transfusion before the onset of a major postoperative infection or during a similar exposure interval in those with no such complications. Univariate analysis showed a significant association between any blood component transfusion and postoperative infection (transfused v nontransfused 31.9% v 13.2%; odds ratio = 3.1, 95% confidence interval = 1.9-5.0; p < 0.01). This association was lost on multivariate analysis. Subgroup analysis with multivariate adjustment identified a significant association between high plasma volume blood component transfusions and postoperative infection (odds ratio = 4.2, 95% confidence interval = 1.2-15.8; p = 0.03). With multivariate adjustment, red blood cell administration was no longer associated with major postoperative infectious complications. CONCLUSIONS: High plasma volume blood component transfusions were associated with the development of major postoperative infectious complications in patients undergoing esophageal resection surgery. In contrast, red blood cell transfusion was not associated with infectious complications.
Subject(s)
Blood Component Transfusion/adverse effects , Esophagectomy/adverse effects , Pneumonia/epidemiology , Postoperative Complications/epidemiology , Sepsis/epidemiology , Surgical Wound Infection/epidemiology , Aged , Cohort Studies , Female , Humans , Male , Middle Aged , Multivariate Analysis , Retrospective StudiesABSTRACT
BACKGROUND: At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. METHODS: In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard. RESULTS: Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio(2) ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13). CONCLUSIONS: A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use.
Subject(s)
Acute Lung Injury/diagnosis , Critical Illness , Decision Support Systems, Clinical/statistics & numerical data , Decision Support Techniques , Early Diagnosis , Pulmonary Edema/diagnosis , Shock, Cardiogenic/complications , Acute Lung Injury/etiology , Aged , Aged, 80 and over , Diagnosis, Differential , Female , Follow-Up Studies , Humans , Male , Middle Aged , Pulmonary Edema/etiology , Reproducibility of Results , Retrospective Studies , Risk Factors , Shock, Cardiogenic/diagnosisABSTRACT
BACKGROUND: Acute lung injury (ALI) is a serious postoperative complication with limited treatment options. A preoperative risk-prediction model would assist clinicians and scientists interested in ALI. The objective of this investigation was to develop a surgical lung injury prediction (SLIP) model to predict risk of postoperative ALI based on readily available preoperative risk factors. METHODS: Secondary analysis of a prospective cohort investigation including adult patients undergoing high-risk surgery. Preoperative risk factors for postoperative ALI were identified and evaluated for inclusion in the SLIP model. Multivariate logistic regression was used to develop the model. Model performance was assessed with the area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test. RESULTS: Out of 4,366 patients, 113 (2.6%) developed early postoperative ALI. Predictors of postoperative ALI in multivariate analysis that were maintained in the final SLIP model included high-risk cardiac, vascular, or thoracic surgery, diabetes mellitus, chronic obstructive pulmonary disease, gastroesophageal reflux disease, and alcohol abuse. The SLIP score distinguished patients who developed early postoperative ALI from those who did not with an area under the receiver operating characteristic curve (95% CI) of 0.82 (0.78-0.86). The model was well calibrated (Hosmer-Lemeshow, P = 0.55). Internal validation using 10-fold cross-validation noted minimal loss of diagnostic accuracy with a mean ± SD area under the receiver operating characteristic curve of 0.79 ± 0.08. CONCLUSIONS: Using readily available preoperative risk factors, we developed the SLIP scoring system to predict risk of early postoperative ALI.
Subject(s)
Acute Lung Injury/diagnosis , Postoperative Complications/diagnosis , Respiratory Distress Syndrome/diagnosis , Surgical Procedures, Operative/adverse effects , Acute Lung Injury/etiology , Aged , Cardiac Surgical Procedures/adverse effects , Cohort Studies , Databases, Factual , Electronic Health Records , Female , Humans , Internet , Likelihood Functions , Male , Middle Aged , Models, Statistical , Predictive Value of Tests , Prognosis , Prospective Studies , ROC Curve , Respiratory Distress Syndrome/etiology , Risk Factors , Thoracic Surgical Procedures/adverse effects , Treatment Outcome , Vascular Surgical Procedures/adverse effectsABSTRACT
OBJECTIVE: To develop and validate time-efficient automated electronic search strategies for identifying preoperative risk factors for postoperative acute lung injury. PATIENTS AND METHODS: This secondary analysis of a prospective cohort study included 249 patients undergoing high-risk surgery between November 1, 2005, and August 31, 2006. Two independent data-extraction strategies were compared. The first strategy used a manual review of medical records and the second a Web-based query-building tool. Web-based searches were derived and refined in a derivation cohort of 83 patients and subsequently validated in an independent cohort of 166 patients. Agreement between the 2 search strategies was assessed with percent agreement and Cohen κ statistics. RESULTS: Cohen κ statistics ranged from 0.34 (95% confidence interval, 0.00-0.86) for amiodarone to 0.85 for cirrhosis (95% confidence interval, 0.57-1.00). Agreement between manual and automated electronic data extraction was almost complete for 3 variables (diabetes mellitus, cirrhosis, H(2)-receptor antagonists), substantial for 3 (chronic obstructive pulmonary disease, proton pump inhibitors, statins), moderate for gastroesophageal reflux disease, and fair for 2 variables (restrictive lung disease and amiodarone). Automated electronic queries outperformed manual data collection in terms of sensitivities (median, 100% [range, 77%-100%] vs median, 87% [range, 0%-100%]). The specificities were uniformly high (≥ 96%) for both search strategies. CONCLUSION: Automated electronic query building is an iterative process that ultimately results in accurate, highly efficient data extraction. These strategies may be useful for both clinicians and researchers when determining the risk of time-sensitive conditions such as postoperative acute lung injury.