Health status improvement after surgical correction of primary hyperparathyroidism in patients with high and low preoperative calcium levels

doi:10.1016/S0039-6060(99)70224-2

Surgery

Volume 125, Issue 6, June 1999, Pages 608-614

https://doi.org/10.1016/S0039-6060(99)70224-2 Get rights and content

Abstract

Background: We conducted a prospective cohort study to determine whether there are differences in functional health status between patients with low (<10.9 mg/dL) and high (≥10.9 mg/dL) serum calcium levels before surgical correction of primary hyperparathyroidism (HPT) and to compare changes in health status after correction of primary HPT. Methods: The SF-36 Health Survey, which provides demographic and condition-specific information, was used to obtain information on patients with primary HPT seen in a university hospital endocrine surgery clinic over a 4-year period before operation and again 2 months and 6 months after operation. Results: A total of 155 patients were studied; 86 had calcium levels <10.9 mg/dL (normal <10.5 mg/dL) and 69 had serum calcium levels ≥10.9 mg/dL (range 10.9 to 13.4 mg/dL). One hundred four patients completed 6-month reports, 55 with low calcium levels and 49 with high calcium levels. Both high and low calcium groups showed marked and virtually identical impairment of functional health status. Both groups showed marked improvement in health status at 2 months and additional improvement at 6 months, returning to normal or near normal in 6 of 8 SF-36 domains. Conclusions: Patients with primary hyperparathyroidism have significant functional health status impairment independent of the level of serum calcium. Dramatic improvement is seen after surgical correction. Referral for surgical treatment of primary HPT should not be delayed until serum calcium is elevated, as recommended in the 1990 National Institutes of Health consensus statement. (Surgery 1999;125:608-14.)

Section snippets

Patients and methods

Starting in March 1994, a convenience sample of patients with primary HPT seen by the endocrine surgery division at University of Michigan Health Systems was asked to complete the SF-36 questionnaire and to provide additional demographic and condition-specific information for study. The plan for obtaining informed consent and for patient participation in the study was approved by the University of Michigan Medical School Institutional Review Board. Patients agreeing to participate were asked by

Results

One hundred fifty-five patients with primary hyperparathyroidism who entered the study between 1994 and 1998 had complete baseline data including preoperative calcium levels. Eighty-six had serum calcium levels <10.9 mg/dL (normal <10.5 mg/dL). These were designated as having “low” calcium levels. Sixty-nine patients had serum calcium levels equal to or greater than 10.9 mg/dL (range 10.9 to 13.4 mg/dL) and were designated as having “high” preoperative calcium levels.

One hundred four patients

Discussion

The major finding of this study is that, with use of the SF-36 Health Survey and condition-specific questionnaires, patients with primary HPT reported profound deficits in functional health status and well-being. These deficits spanned both physical and mental function and were quantitatively and qualitatively similar regardless of whether the level of serum calcium was above or below 10.9 mg/dL.

After surgical correction of primary HPT, patients reported that functional health status improved

Conclusions

The SF-36 Health Survey is highly sensitive to the multidimensional changes in functional health status in patients with primary HPT. Our data suggest that patients with both high and low calcium levels have equivalent, significant functional health status deficits. Both groups of patients improve dramatically after surgical correction of primary HPT, but patients with lower levels of serum calcium preoperatively report less pain 6 months after operation and may achieve better health status

Acknowledgements

We thank Melissa Peterson, RN, MS, and Jane Wilson Coon, RN, DNSc, for their support and assistance in the early phases of this work.

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Development of a machine learning model for the diagnosis of atypical primary hyperparathyroidism
2024, Endocrine and Metabolic Science
Atypical primary hyperparathyroidism (PHPT), which includes normocalcemic and normohormonal variants, can be a diagnostic challenge. We sought to create a machine learning model to predict the probability of a patient having atypical presentations of PHPT.
A model was constructed using logistic regression of PHPT patients and were compared to controls. Variables included sex, body mass index (BMI), calcium, PTH, 25-hydroxyvitamin D, phosphorus, chloride, sodium, alkaline phosphatase, and creatinine. The performance of the model was evaluated using the area under the curve (AUC).
The study included 4987 controls and 433 patients with atypical PHPT. Calcium, PTH, vitamin D, phosphorus, BMI, and sex were found to significantly contribute to the performance of the model, achieving an AUC of 0.999. The sensitivity, specificity, positive and negative predictive values were 92.9 %, 99.7 %, 96.3 % and 99.4 %, respectively.
Machine learning can reliably aid in the recognition of PHPT in patients with atypical variants.
When evaluating patients with atypical variants of primary hyperparathyroidism, the clinician needs to be able to identify subtle relationships in the patient laboratory test to make the diagnosis. These relationships can be found with machine learning and incorporated to predictive models which can ease and improve the diagnosis.
Primary Hyperparathyroidism: Pathophysiology, Surgical Indications, and Preoperative Workup
2021, Surgery of the Thyroid and Parathyroid Glands
Primary hyperparathyroidism (PHPT) has evolved as a clinical entity over the past hundred years. PHPT was originally described as a highly symptomatic disease, characterized by overt renal and skeletal complications. With the emergence of the multichannel autoanalyzer, a less symptomatic phenotype emerged, which some would call an “asymptomatic” disease with incidentally noted hypercalcemia. Yet this disorder, too, has very specific effects on end organs of the hyperparathyroid process. More recently, secular trends in the measurement of bone density have led to the recognition of yet another phenotype of PHPT, one in which parathyroid hormone is consistently elevated but serum calcium is normal. This phenotype is termed normocalcemic PHPT. The medical community has learned much about the effect of PHPT on the kidney, the skeleton, and the cardiovascular system; in addition, the breadth of knowledge has expanded about PHPT’s neuropsychological manifestations as well as the effect of parathyroidectomy to reverse some but not all such manifestations. Emerging data have allowed the development of progressively refined sets of guidelines for the management of and surgical intervention for asymptomatic disease. The state of our knowledge about the manifestations and natural history of normocalcemic primary hyperparathyroidism is more rudimentary, and evidence-based guidelines are lacking. This chapter will review available data on the presentation, natural history with and without surgery, and nonsurgical options in the management of patients with primary hyperparathyroidism today.
Improving diagnostic recognition of primary hyperparathyroidism with machine learning
2017, Surgery (United States)
Citation Excerpt :
Compared with observation, Almqvist et al37 determined that early parathyroidectomy decreased the patients’ long-term risk of hip and other bone fractures. Longstanding PHPT also has been associated with poorer quality of life, psychiatric illnesses, left ventricular hypertrophy, and an increased mortality risk from cardiovascular disease.38-45 Additionally, parathyroidectomy is more cost-effective than observation.46
Parathyroidectomy offers the only cure for primary hyperparathyroidism, but today only 50% of primary hyperparathyroidism patients are referred for operation, in large part, because the condition is widely under-recognized. The diagnosis of primary hyperparathyroidism can be especially challenging with mild biochemical indices. Machine learning is a collection of methods in which computers build predictive algorithms based on labeled examples. With the aim of facilitating diagnosis, we tested the ability of machine learning to distinguish primary hyperparathyroidism from normal physiology using clinical and laboratory data.
This retrospective cohort study used a labeled training set and 10-fold cross-validation to evaluate accuracy of the algorithm. Measures of accuracy included area under the receiver operating characteristic curve, precision (sensitivity), and positive and negative predictive value. Several different algorithms and ensembles of algorithms were tested using the Weka platform. Among 11,830 patients managed operatively at 3 high-volume endocrine surgery programs from March 2001 to August 2013, 6,777 underwent parathyroidectomy for confirmed primary hyperparathyroidism, and 5,053 control patients without primary hyperparathyroidism underwent thyroidectomy. Test-set accuracies for machine learning models were determined using 10-fold cross-validation. Age, sex, and serum levels of preoperative calcium, phosphate, parathyroid hormone, vitamin D, and creatinine were defined as potential predictors of primary hyperparathyroidism. Mild primary hyperparathyroidism was defined as primary hyperparathyroidism with normal preoperative calcium or parathyroid hormone levels.
After testing a variety of machine learning algorithms, Bayesian network models proved most accurate, classifying correctly 95.2% of all primary hyperparathyroidism patients (area under receiver operating characteristic = 0.989). Omitting parathyroid hormone from the model did not decrease the accuracy significantly (area under receiver operating characteristic = 0.985). In mild disease cases, however, the Bayesian network model classified correctly 71.1% of patients with normal calcium and 92.1% with normal parathyroid hormone levels preoperatively. Bayesian networking and AdaBoost improved the accuracy of all parathyroid hormone patients to 97.2% cases (area under receiver operating characteristic = 0.994), and 91.9% of primary hyperparathyroidism patients with mild disease. This was significantly improved relative to Bayesian networking alone (P < .0001).
Machine learning can diagnose accurately primary hyperparathyroidism without human input even in mild disease. Incorporation of this tool into electronic medical record systems may aid in recognition of this under-diagnosed disorder.
Patient-Reported Outcomes Measurement Information System (PROMIS) Use in Surgical Care: A Scoping Study
2017, Journal of the American College of Surgeons
Surgeons recognize the importance of patient reported outcomes in the evaluation of health care. Documenting health related quality of life (HRQOL) can enhance surgical quality improvement efforts. Systematic documentation of HRQOL began in 1963. Currently, multiple varied and unstandardized instruments make it difficult to compare quality of life measures across studies. The NIH developed the Patient Reported Outcomes Measurement Information System (PROMIS) to provide a standardized assessment designed to complement traditional outcomes measures.
We used systematic scoping methodology to investigate the characteristics of PROMIS use in studies assessing quality of life measures as surgical outcomes.
A systematic search of PubMed revealed 21 publications describing the use of PROMIS to assess surgical outcomes. The 121 study publications reported observations on 2,561 patients. Twenty-nine percent of patients had injuries, 33% had neoplasms, and 38% included other patients having neither injuries nor neoplasms. General surgery/gynecology/plastic surgery had 8 publications, orthopaedic surgery had 9 publications, and neurosurgery had 4 publications. Most studies included additional measures. There were 25 instruments used in addition to PROMIS.
This study revealed that PROMIS performed efficiently, accurately, and reliably in assessing patient-reported HRQOL in multidisciplinary surgical publications.
Parathyroidectomy for primary hyperparathyroidism improves sleep quality: A prospective study
2017, Surgery (United States)
This prospective survey study assessed changes in sleep quality in patients with primary hyperparathyroidism after parathyroidectomy.
Patients undergoing parathyroidectomy for primary hyperparathyroidism (n = 110) or thyroidectomy for benign euthyroid disease (control group; n = 45) were recruited between June 2013 and June 2015 and completed the Pittsburgh Sleep Quality Index preoperatively and at 1- and 6 months postoperatively. “Poor” sleep quality was defined as a score >5; a clinically important and relevant improvement was a ≥3-point decrease.
Preoperatively, parathyroid patients had worse sleep quality than thyroid patients (mean 8.1 vs 5.3; P < .001); 76 (69%) parathyroid and 23 (51%) thyroid patients reported poor sleep quality (P = .03). Postoperatively, only parathyroid patients demonstrated improvement in sleep quality; mean scores did not differ between the parathyroid and thyroid groups at 1 month (6.3 vs 5.3; P = .12) or 6 months (5.8 vs 4.6; P = .11). The proportion of patients with a clinically important improvement in sleep quality was greater in the parathyroid group at 1 month (37% vs 10%; P < .001) and 6 months (40% vs 17%; P = .01). Importantly, there was no difference in the proportion of patients with poor sleep quality between the 2 groups at 1 month (50% vs 40%; P = .32) and 6 months (40% vs 29%; P = .22).
More than two-thirds of patients with primary hyperparathyroidism report poor sleep quality. After parathyroidectomy, over one-third experienced improvement, typically within the first month postoperatively.
Parathyroidectomy for asymptomatic primary hyperparathyroidism: A revised cost-effectiveness analysis incorporating fracture risk reduction
2017, Surgery (United States)
Recent data demonstrate decreased fracture risk after operation for asymptomatic primary hyperparathyroidism. We performed a revised cost-effectiveness analysis comparing parathyroidectomy versus observation while incorporating fracture risk reduction.
A Markov transition-state model was created comparing parathyroidectomy and guideline-based medical observation for a 60-year-old female patient with mild asymptomatic primary hyperparathyroidism. Costs were estimated using published Medicare reimbursement data. Treatment strategy outcomes, including risk of fracture, were identified by literature review. Quality adjustment factors were used to weight treatment outcomes. A threshold of $100,000/quality-adjusted life year was used to determine cost-effectiveness. Sensitivity analyses and Monte Carlo simulation were performed to examine the effect of uncertainty on the model.
Parathyroidectomy was the dominant strategy (less costly and more effective) with an incremental cost savings of $1,721 and an incremental effectiveness of 0.185 quality-adjusted life years. Parathyroidectomy remained dominant when the relative risk reduction of fracture after operation was ≥14%, the cost of fracture was ≥$7,600, or the probability of recurrent laryngeal nerve injury was <12.5%. Monte Carlo simulation showed parathyroidectomy was cost-effective in 995/1,000 hypothetical patients.
When fracture risk reduction is considered, parathyroidectomy for mild asymptomatic primary hyperparathyroidism is the dominant strategy when compared to observation.

View all citing articles on Scopus

^☆: Supported by the University of Michigan Health System Small Grant Program.

^☆☆: Reprint requests: Richard E. Burney, MD, TC2922 University Hospital, 1500 E Medical Center Dr, Ann Arbor, MI 48109-0331.

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Surgical outcomes researchHealth status improvement after surgical correction of primary hyperparathyroidism in patients with high and low preoperative calcium levels☆,☆☆

Abstract

Section snippets

Patients and methods

Results

Discussion

Conclusions

Acknowledgements

Surgery

Lancet

Surg Clin North Am

Am J Med

Biol Psychiatry

Am J Med

Surgery

Surgery

Surgery

J Am Coll Surg

Proceedings of the NIH consensus development conference on diagnosis and management of asymptomatic primary hyperparathyroidism

J Bone Miner Res

The MOS 36-item short-form health survey (SF-36), I: conceptual framework and item selection

Med Care

Surgical outcomes research
Health status improvement after surgical correction of primary hyperparathyroidism in patients with high and low preoperative calcium levels☆,☆☆