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Thyroid surgery at high-quality hospitals is associated with fewer complications. We evaluated the impact of referring older adults with thyroid cancer to higher-performing local hospitals.We performed a simulation study of Surveillance, Epidemiology, and End Results-Medicare patients, aged ≥66 years, who underwent a thyroidectomy for well-differentiated thyroid cancer (2013-2017). An 80% sample was used to calculate each hospital's risk-standardized 30-day serious adverse event rate, dividing hospitals into quartiles by performance. Hospitals located ≤30 miles of the remaining 20% of patients were compared, and 30-day serious adverse event rates and costs were simulated as if patients were treated at higher-quality hospitals using logistic regression with each alternative hospital's fixed-effect.We identified 8,946 patients who underwent thyroid resection at 843 hospitals. Average risk-adjusted serious adverse event rates ranged from 13.9% to 52.9% between quartile 1 and 4 hospitals (P.001). We identified higher-quality hospitals for 43.7% of patients. Simulating care at the best local hospital reduced predicted serious adverse event rates from 25.6% (95% confidence interval, 24.7-26.4) to 16.2% (95% confidence interval, 15.5-16.8; P.001), while modestly lowering average costs from $12,883 (95% confidence interval, 12,500-13,267) to $12,679 (95% confidence interval, 12,304-13,056; P = .029).Simulated care at higher-performing hospitals decreased serious adverse event rates after thyroid resection. Optimizing hospital selection may reduce postoperative morbidity without compromising preferences for local treatment.

PURPOSE Staging information is essential for colorectal cancer research. Medicare claims are an important source of population-level data but currently lack oncologic stage. We aimed to develop a claims-based model to identify stage at diagnosis in patients with colorectal cancer. METHODS We included patients age 66 years or older with colorectal cancer in the SEER-Medicare registry. Using patients diagnosed from 2014 to 2016, we developed models (multinomial logistic regression, elastic net regression, and random forest) to classify patients into stage I-II, III, or IV on the basis of demographics, diagnoses, and treatment utilization identified in Medicare claims. Models developed in a training cohort (2014-2016) were applied to a testing cohort (2017), and performance was evaluated using cancer stage listed in the SEER registry as the reference standard. RESULTS The cohort of patients with 30,543 colorectal cancer included 14,935 (48.9%) patients with stage I-II, 9,203 (30.1%) with stage III, and 6,405 (21%) with stage IV disease. A claims-based model using elastic net regression had a scaled Brier score (SBS) of 0.45 (95% CI, 0.43 to 0.46). Performance was strongest for classifying stage IV (SBS, 0.62; 95% CI, 0.59 to 0.64; sensitivity, 93%; 95% CI, 91 to 94) followed by stage I-II (SBS, 0.45; 95% CI, 0.44 to 0.47; sensitivity, 86%; 95% CI, 85 to 76) and stage III (SBS, 0.32; 95% CI, 0.30 to 0.33; sensitivity, 62%; 95% CI, 61 to 64). CONCLUSION Machine learning models effectively classified colorectal cancer stage using Medicare claims. These models extend the ability of claims-based research to risk-adjust and stratify by stage.

Qualifying comorbidity sets (QCS) are tools used to identify multimorbid patients at increased surgical risk. It is unknown how the QCS framework for multimorbidity affects surgical risk in different racial groups.This retrospective cohort study included Medicare patients age ≥65.5 who underwent an emergency general surgery operation from 2015 to 2018. Our exposure was race and multimorbidity, included in our model as an interaction term. The primary outcome of the study was 30-day mortality. Secondary outcomes included routine discharge, 30-day readmission, length of stay, and complications.In total, 163,148 patients who underwent and operation were included in this study. Of these, 13,852 (8.5%, p 0.001) were Black, and 149,296 (91.5%, p 0.001) were White. Black multimorbid patients had no significant differences in 30-day mortality, routine discharge or 30-day readmission when compared to White multimorbid patients after risk-adjustment. Black multimorbid patients had significantly lower odds of complications (OR 0.89, p = 0.014) compared to White multimorbid patients.Our study of universally insured patients highlights the critical role of pre-operative health status and its association with surgical outcomes.

In normohormonal primary hyperparathyroidism, parathyroid hormone levels are normal but inappropriately elevated for the degree of hypercalcemia. The study goals were to determine intraoperative parathyroid hormone parameters predictive of (1) cure and (2) hypocalcemia in this subgroup.We performed a retrospective cohort study comparing patients who underwent parathyroidectomy (2002-2019) for normohormonal and classic primary hyperparathyroidism. The primary outcomes were cure (calcium10.3 mg/dL) and hypocalcemia (≤8.4 mg/dL) ≥6 months postoperatively.In the study, 127 of 1,087 patients (11.7%) had normohormonal primary hyperparathyroidism. The groups experienced similar rates of cure (91.3% vs 94.1%, P = .23) and hypocalcemia (3.9% vs 2.9%, P = .53). However, intraoperative parathyroid hormone decline in cured patients was lower in those with normohormonal primary hyperparathyroidism (66.4% vs 84.5%, P.0001). Receiver operating characteristic curves provided Youden's indices of 52% and 75% (cure) and 75% and 88% (hypocalcemia) for patients with normohormonal and classic primary hyperparathyroidism, respectively. Cure rates with ≥50% intraoperative parathyroid hormone decline were similar (94.1% vs 95.0%, P = .72), but hypocalcemia was more prevalent in patients with normohormonal primary hyperparathyroidism and ≥70% intraoperative parathyroid hormone decline (10.4% vs 3.3%, P = .01).In patients with normohormonal primary hyperparathyroidism, intraoperative parathyroid hormone declines of ≥50% and ≥70% were predictive of postoperative cure and hypocalcemia, respectively. These parameters may inform intraoperative decision making and postoperative management.

ImportanceVariation in outcomes across hospitals adversely affects surgical patients. The use of high-quality hospitals varies by population, which may contribute to surgical disparities.ObjectiveTo simulate the implications of data-driven hospital selection for social welfare among patients who underwent colorectal cancer surgery.Design, Setting, and ParticipantsThis economic evaluation used the hospital inpatient file from the Florida Agency for Health Care Administration. Surgical outcomes of patients who were treated between January 1, 2016, and December 31, 2018 (training cohort), were used to estimate hospital performance. Costs and benefits of care at alternative hospitals were assessed in patients who were treated between January 1, 2019, and December 31, 2019 (testing cohort). The cohorts comprised patients 18 years or older who underwent elective colorectal resection for benign or malignant neoplasms. Data were analyzed from March to October 2022.ExposuresUsing hierarchical logistic regression, we estimated the implications of hospital selection for in-hospital mortality risk in patients in the training cohort. These estimates were applied to patients in the testing cohort using bayesian simulations to compare outcomes at each patient’s highest-performing and chosen local hospitals. Analyses were stratified by race and ethnicity to evaluate the potential implications for equity.Main Outcomes and MeasuresThe primary outcome was the mean patient-level change in social welfare, a composite measure balancing the value of reduced mortality with associated costs of care at higher-performing hospitals.ResultsA total of 21 098 patients (mean [SD] age, 67.3 [12.0] years; 10 782 males [51.1%]; 2232 Black [10.6%] and 18 866 White [89.4%] individuals) who were treated at 178 hospitals were included. A higher-quality local hospital was identified for 3057 of 5000 patients (61.1%) in the testing cohort. Selecting the highest-performing hospital was associated with a 26.5% (95% CI, 24.5%-29.0%) relative reduction and 0.24% (95% CI, 0.23%-0.25%) absolute reduction in mortality risk. A mean amount of $1953 (95% CI, $1744-$2162) was gained in social welfare per patient treated. Simulated reassignment to a higher-quality local hospital was associated with a 23.5% (95% CI, 19.3%-32.9%) relative reduction and 0.26% (95% CI, 0.21%-0.30%) absolute reduction in mortality risk for Black patients, with $2427 (95% CI, $1697-$3158) gained in social welfare.Conclusions and RelevanceIn this economic evaluation, using procedure-specific hospital performance as the primary factor in the selection of a local hospital for colorectal cancer surgery was associated with improved outcomes for both patients and society. Surgical outcomes data can be used to transform care and guide policy in colorectal cancer.

Neuronal activity sculpts brain development by inducing the transcription of genes such as brain-derived neurotrophic factor (Bdnf) that modulate the function of synapses. Sensory experience is transduced into changes in gene transcription via the activation of calcium signaling pathways downstream of both L-type voltage-gated calcium channels (L-VGCCs) and NMDA-type glutamate receptors (NMDARs). These signaling pathways converge on the regulation of transcription factors including calcium-response factor (CaRF). Although CaRF is dispensable for the transcriptional induction of Bdnf following the activation of L-VGCCs, here we show that the loss of CaRF leads to enhanced NMDAR-dependent transcription of Bdnf as well as Arc. We identify the NMDAR subunit-encoding gene Grin3a as a regulatory target of CaRF, and we show that expression of both Carf and Grin3a is depressed by the elevation of intracellular calcium, linking the function of this transcriptional regulatory pathway to neuronal activity. We find that light-dependent activation of Bdnf and Arc transcription is enhanced in the visual cortex of young CaRF knockout mice, suggesting a role for CaRF-dependent dampening of NMDAR-dependent transcription in the developing brain. Finally, we demonstrate that enhanced Bdnf expression in CaRF-lacking neurons increases inhibitory synapse formation. Taken together, these data reveal a novel role for CaRF as an upstream regulator of NMDAR-dependent gene transcription and synapse formation in the developing brain. NMDARs promote brain development by inducing the transcription of genes, including brain-derived neurotrophic factor (BDNF). We show that the transcription factor calcium-response factor (CaRF) limits NMDAR-dependent BDNF induction by regulating expression of the NMDAR subunit GluN3A. Loss of CaRF leads to enhanced BDNF-dependent GABAergic synapse formation indicating the importance of this process for brain development. Our observation that both CaRF and GluN3A are down-regulated by intracellular calcium suggests that this may be a mechanism for experience-dependent modulation of synapse formation.