Stratifying Risk for Renal Insufficiency Among Lithium-Treated Patients: An Electronic Health Record Study

Evaluation of Renal Functions of Inpatients With Mental Disorders

The current study aimed to investigate the renal functions of inpatients with mental disorders. Data for this retrospective and descriptive study were collected from January 2021 to April 2021 from the records of patients who were hospitalized in the psychiatry clinic of a training and research hospital between 2018 and 2020. The study sample comprised hospital records of 376 patients. A significant negative relationship was determined between patients' glomerular filtration rate (GFR) and glucose level, duration of mental disorder, number of hospitalizations, and duration of medication use (p < 0.05). According to the analysis of patients' renal functions, mean GFR was statistically significantly lower in women with physical chronic diseases and diagnosed with personality disorders. Psychiatric-mental health nurses should evaluate and monitor renal functions of individuals with mental disorders and take precautions before kidney diseases develop. [Journal of Psychosocial Nursing and Mental Health Services, 62(2), 47-55.].

Quality of laboratory biomarker monitoring during treatment with lithium in patients with bipolar disorder

BACKGROUND

Clinical guidelines recommend monitoring of creatinine and lithium throughout treatment with lithium. We here assessed the extent to which this occurs in healthcare in Sweden.

METHODS

This is an observational study of all adults with bipolar disorder starting lithium therapy in Stockholm, Sweden, during 2007-2018. The main outcome was monitoring of blood lithium and creatinine at therapy initiation and/or once annually. The secondary outcome was monitoring of calcium and thyroid-stimulating hormone (TSH). Patients were followed up until therapy cessation, death, out-migration, or to the end of 2018.

RESULTS

We identified 4428 adults with bipolar disorder who started lithium therapy and were followed up for up to 11 years. Their median age was 39 years, and 63% were women. The median duration on lithium therapy was 4.3 (IQR: 1.9-7.45) years, and the majority who discontinued therapy started another mood stabilizer soon after. Overall, 21% started lithium therapy without assessing the serum/plasma concentration of creatinine. The proportion of people who did not have both lithium and creatinine measured increased from 21% in the first year to 33% in the eleventh year. The proportion with annual testing for TSH or calcium was slightly lower. As few as 16% of patients had both lithium and creatinine tested once annually during their complete time on lithium.

CONCLUSIONS

In a Swedish community sample, lithium and creatinine monitoring was inconsistent with guideline recommendations that call for measurement of annual biomarker levels.

Coding for Physical Restraint Status Among Hospitalized Patients: a 2019 National Inpatient Sample Analysis

BACKGROUND

The reduction of physical restraint utilization in the hospital setting is a key goal of high-quality care, but little is known about the rate of restraint use in general hospitals in the USA.

OBJECTIVE

This study reports the rate of physical restraint coding among acute care hospital discharges in the USA and explores associated demographic and diagnostic factors.

DESIGN

The National Inpatient Sample, a de-identified all-payors database of acute care hospital discharges in the USA, was queried for patients aged 18 and older with a diagnosis code for physical restraint status in 2019.

PARTICIPANTS

Hospitalized patients aged 18 and older.

MAIN MEASURES

Demographics, discharge diagnoses, in-hospital mortality, length of stay, total hospital charges.

KEY RESULTS

In total, 220,470 (95% CI: 208,114 to 232,826) hospitalizations, or 0.7% of overall hospitalizations, included a discharge code for physical restraint status. There was a 700-fold difference in coding for restraint utilization based on diagnosis, with 7.4% of patients with encephalitis receiving restraint diagnosis codes compared to < 0.01% of patients with uncomplicated diabetes. In an adjusted model, male sex was associated with an odds ratio of 1.4 (95% CI: 1.4 to 1.5) for restraint utilization coding, and Black race was associated with an odds ratio of 1.3 (95% CI: 1.2 to 1.4) relative to white race.

CONCLUSIONS

In the general hospital setting, there is variability in physical restraint coding by sex, race, and clinical diagnosis. More research is needed into the appropriate utilization of restraints in the hospital setting and possible inequities in restraint utilization.

Psychotropic Drugs and Adverse Kidney Effects: A Systematic Review of the Past Decade of Research

BACKGROUND AND OBJECTIVE

Psychotropic drugs are a heterogenous group of treatments prescribed for many psychiatric disorders, often for long periods. Their effects on the kidney and its functioning are complex and a source of significant research and debate. This article aims to review recent evidence of the acute and chronic kidney adverse events of diverse psychotropes.

METHODS

A systematic search of randomized controlled trials and large observational studies (n ≥ 100) reporting the effects of psychotropic drugs on the kidney was conducted. The MEDLINE, PsycInfo, and EMBASE databases from 2011 to 2021, inclusive, were broadly searched with few restrictions and no prespecified outcomes. Two or more independent reviewers assessed and summarized all eligible studies, including risks of bias and levels of evidence.

RESULTS

In all, 1999 abstracts were screened for eligibility and 47 articles were included, which examined lithium (33), antiepileptics (10), antipsychotics (13), and antidepressants (9). No studies examining kidney adverse effects of other psychotropes, such as benzodiazepines, met inclusion criteria. Study populations were adult (8), geriatric (9), and mixed (30). Lithium was almost unanimously associated with (1) chronic kidney disease and (2) nephrogenic diabetes insipidus in methodologically diverse studies. The most supported risk factors for declining kidney functioning with lithium were advanced age, duration of lithium treatment, acute lithium toxicity, female sex, medications with known renal interactions, diabetes mellitus/hyperglycemia, and overall medical comorbidity. Supratherapeutic lithium concentrations are both the causes and consequences of acute kidney injury. Once significant chronic kidney disease has developed, four studies found that replacing lithium with other mood stabilizers does not slow progression, and the evolution to end-stage kidney disease is rare overall with modern practices. Compared to lithium, fewer studies examined antipsychotics and antiepileptics but found relatively less direct kidney harms. Antidepressants were not associated with acute or chronic kidney harms.

CONCLUSIONS

Despite the heterogeneity of findings, owing to varying methodologies and research challenges, recent studies strongly suggest that lithium is associated with an increased risk of chronic kidney disease and nephrogenic diabetes insipidus, especially in older adults and long-term lithium users. Clinicians should balance the harms of lithium against its established benefits, and ensure adequate monitoring and management of comorbidities in all patients. Weaker evidence suggests that antiepileptics such as valproate and antipsychotics result in comparatively less harm to the kidney than lithium, but warrant monitoring because of multiple direct and indirect mechanisms for potential kidney adverse events. Antidepressants do not have clear kidney adverse effects and appear safe (though potentially less effective) in the setting of kidney disease. Other classes of psychotropic drugs have received little research interest. Further research is warranted, particularly into specific antiepileptics and antipsychotics, and careful attention should be paid to mitigating important sources of bias such as confounding by indication.

The low risk for early renal damage during lithium treatment has not changed over time

BACKGROUND

Modern lithium management guidelines were introduced to improve the renal prognosis of lithium patients.

AIMS

To examine whether prospects for severe renal impairment (defined as chronic kidney disease at least stage 4 (CKD4)), in long-term lithium patients, have changed over time after the introduction of lithium monitoring guidelines.

METHODS

The time to and hazard for CKD4 were compared between three patient cohorts who started long-term lithium in three consecutive decades: 1980s, 1990s and 2000s. The follow-up time was 10 years after completion of 1-year treatment. The data were collected from Sahlgrenska University Hospital's laboratory database.

RESULTS

In all, 2169 patients were included: 623 in Cohort 1 (started lithium during 1980s), 874 in Cohort 2 (1990s) and 672 in Cohort 3 (2000s). Compliance with lithium monitoring guidelines improved, and mean serum lithium decreased, through the cohorts. In all, 22 patients developed CKD4 during follow-up. The time to CKD4 was the same in all three cohorts (overall: 10.96 years, 95% confidence interval: 10.94-11 years). Age and serum creatinine concentration at start were significant risk factors, while sex had no prognostic value. After adjusting for the significant covariates, there was no statistically significant difference in the hazard for CKD4 between the three cohorts.

CONCLUSION

The risk for severe renal damage during the first decade of long-term lithium is low, but has not changed over time. Our data suggest that improved compliance with lithium guidelines is not reflected in less risk for severe renal damage.

Prevalence of impaired kidney function in patients with long-term lithium treatment: A systematic review and meta-analysis

OBJECTIVES

Although lithium renal effects have been extensively investigated, prevalence rates of chronic kidney disease (CKD) in lithium-treated patients vary. Our aim was to provide prevalence estimates and related moderators.

METHODS

We performed a systematic review in PubMed/Embase until November 01, 2021, conducting a random effects meta-analysis of studies evaluating CKD prevalence rates in lithium-treated patients calculating overall prevalence ±95% confidence intervals (CIs). Meta-regression analyses included sex, age, body mass index, smoking, hypertension, diabetes, cardiovascular disease, lithium-treatment dose, duration, and blood levels. Subgroup analyses included sample size, diagnoses, and study design. Pooled odds ratios (OR) were estimated for studies including patients receiving nonlithium treatment. Study quality was assessed using the Newcastle-Ottawa scale.

RESULTS

Five, nine, and six trials were rated as high, fair, and low quality, respectively. In 20 studies (n = 25,907 patients), we estimated an overall prevalence of 25.5% (95% CI = 19.8-32.2) of impaired kidney function; despite lack of differences (p = 0.18), prevalence rates were higher in elderly samples than mixed samples of elderly and nonelderly (35.6%, 95% CI = 21.4-52.9, k = 2, n = 3,161 vs. 25.1%, 95% CI = 19.1-31.3, k = 18, n = 22,746). Prevalence rates were associated with longer lithium treatment duration (p = 0.04). Cross-sectional studies provided lower rates than retrospective studies (14.5%, 95% CI = 13.5-15.5, k = 6, n = 4,758 vs. 29.5%, 95% CI = 22.1-38.0, k = 12, n = 17,988, p < 0.001). Compared with 722,529 patients receiving nonlithium treatment, the OR of impaired kidney function in 14,187 lithium-treated patients was 2.09 (95% CI = 1.24-3.51, k = 8, p = 0.005).

CONCLUSIONS

One-fourth of patients receiving long-term lithium may develop impaired kidney function, although research suffers from substantial heterogeneity between studies. This risk may be twofold higher compared with nonlithium treatment and may increase for a longer lithium treatment duration.

Determinants of Kidney Function and Accuracy of Kidney Microcysts Detection in Patients Treated With Lithium Salts for Bipolar Disorder

Objectives: Early kidney damage during lithium treatment in bipolar disorder is still hypothetical. We aimed at identifying the determinants of a decreased measured glomerular filtration rate (mGFR) and the accuracy of kidney MRI imaging in its detection.

Methods: In this cross-sectional cohort study, 217 consecutive lithium-treated patients underwent mGFR and kidney MRI with half-Fourier turbo spin-echo and Single-shot with long echo time sequences.

Results: Median age was 51 [27–62] years, and median lithium treatment duration was 5 [2–14] years. 52% of patients had a stage 2 CKD. In multivariable analysis, the determinants of a lower mGFR were a longer lithium treatment duration (β −0.8 [−1; −0.6] ml/min/1.73 m² GFR decrease for each year of treatment), a higher age (β −0.4 [−0.6; −0.3] ml/min/1.73 m² for each year of age, p < 0.001), albuminuria (β −3.97 [−6.6; −1.3], p = 0.003), hypertension (β −6.85 [−12.6; −1.1], p = 0.02) and hypothyroidism (β −7.1 [−11.7; −2.5], p = 0.003). Serum lithium concentration was not associated with mGFR. Renal MRI displayed renal microcyst(s) in 51% of patients, detected as early as 1 year after lithium treatment initiation. mGFR and lithium treatment duration were strongly correlated in patients with microcyst(s) (r = −0.64, p < 0.001), but not in patients with no microcysts (r = −0.24, p = 0.09). The presence of microcysts was associated with the detection of an mGFR <45 ml/min/1.73 m² (AUC 0.893, p < 0.001, sensitivity 80%, specificity 81% for a cut-off value of five microcysts).

Conclusion: Lithium treatment duration and hypothyroidism strongly impacted mGFR independently of age, especially in patients with microcysts. MRI might help detect early lithium-induced kidney damage and inform preventive strategies.

Real-world evidence of age-independent electroconvulsive therapy efficacy: A retrospective cohort study

OBJECTIVES

Electroconvulsive therapy (ECT) is an effective treatment for depressive disorders and approved for use in adolescents and adults, but it is unclear whether efficacy or cognitive side effect burden differs with age or if effectiveness in usual clinical practice matches that in prospective studies. We examined the effects of ECT on depression and cognition in a large clinical cohort.

METHODS

A retrospective cohort study of patients ages 16 and older receiving ECT between 2011 and 2020 and who were evaluated with the Quick Inventory of Depressive Symptomatology (QIDS), the Behavior and Symptom Identification Scale-24 (BASIS-24), and the Montreal Cognitive Assessment (MoCA) at baseline and after treatment #10.

RESULTS

Among 1698 patients, ECT was associated with a decrease in depression symptoms (QIDS reduction from 17.1 ± 4.9 to 10.1 ± 5.2) and improvement in self-reported mental health (BASIS-24 scores improved from 1.92 ± 0.55 to 1.17 ± 0.60). There was a reduction in MoCA scores from 25.8 ± 3.1 to 25.4 ± 3.1. In multivariate models, age was not associated with a differential QIDS or BASIS-24 response, but older age was associated with a lesser reduction in MoCA.

CONCLUSION

Among 1698 patients aged 16 and older, ECT was associated with improvement in depression and overall self-reported mental health, with a slight decrease in cognition. Age was not associated with changes in efficacy, but older age was associated with a lesser cognitive change as measured by the MoCA. These results provide normative data of real-world effectiveness of ECT, and add further support to its utility in patients with severe psychiatric illness.

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom

Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiology, and dermatology. However, the use of AI in mental health care and neurobiological research has been modest. Given the high morbidity and mortality in people with psychiatric disorders, coupled with a worsening shortage of mental health care providers, there is an urgent need for AI to help identify high-risk individuals and provide interventions to prevent and treat mental illnesses. While published research on AI in neuropsychiatry is rather limited, there is a growing number of successful examples of AI's use with electronic health records, brain imaging, sensor-based monitoring systems, and social media platforms to predict, classify, or subgroup mental illnesses as well as problems such as suicidality. This article is the product of a study group held at the American College of Neuropsychopharmacology conference in 2019. It provides an overview of AI approaches in mental health care, seeking to help with clinical diagnosis, prognosis, and treatment, as well as clinical and technological challenges, focusing on multiple illustrative publications. Although AI could help redefine mental illnesses more objectively, identify them at a prodromal stage, personalize treatments, and empower patients in their own care, it must address issues of bias, privacy, transparency, and other ethical concerns. These aspirations reflect human wisdom, which is more strongly associated than intelligence with individual and societal well-being. Thus, the future AI or artificial wisdom could provide technology that enables more compassionate and ethically sound care to diverse groups of people.

The importance of monitoring renal function and concomitant medication to avoid toxicity in patients taking lithium

Lithium, which is used for bipolar disorder, can cause toxicity. There are two categories of lithium toxicity, namely, overdose-related and not overdose-related. However, the treatment and prognosis of each type of toxicity are not clearly understood. We, therefore, compared the clinical characteristics of patients with overdose-related and not overdose-related lithium toxicity. Relevant data were obtained from the medical records of 16 patients with lithium toxicity, and renal function and concomitant medications were retrospectively compared between the two groups. We also compared the treatment for, manifestations of, and duration of hospitalization between the two types of lithium toxicity. The not overdose-related group more frequently had a low creatinine clearance (<50 mL/min) than did the overdose-related group (P = 0.01). Multivariable regression analysis demonstrated that creatinine clearance <50 mL/min was a significant predictor of lithium toxicity in the not overdose-related group (P = 0.01). Tremor and dysarthria occurred only in the not overdose-related group, and duration of hospitalization was significantly longer in the not overdose-related than overdose-related group (P = 0.01). Clinicians must monitor the renal function of patients taking lithium, even when in compliance with the prescribed dosage, because they are at long-term risk of lithium toxicity.

When and how to use lithium

BACKGROUND

Lithium is an old proven medication, but it is infrequently used in current practice. This review examines evidence for its benefits and risks and provides clinical guidance to its use.

METHOD

Narrative review.

RESULTS

Besides its benefit in bipolar illness, lithium has important underappreciated proven benefits in prevention of unipolar depression and suicide. Emerging data support neurobiological benefits for cognition and possible dementia prevention. Likely benefits also exist in low doses for mood temperaments (cyclothymia and hyperthymia). High doses (over 1.0 mmol/L) should be avoided since they increase side effects, complications associated with long-term use, and risk of toxicity. Conversely, low dosing can be legitimate, especially for suicide and dementia prevention. Nuisance side effects of lithium may affect adherence, and medically serious side-effects can occur. Managing strategies are available for side effects.

CONCLUSION

Lithium is the most effective medication in psychiatry, because it has disease-modifying, not just symptomatic, effects. It is effective not only for bipolar illness but also for prevention of suicide, episodes of unipolar depression, mood temperaments, and possibly dementia. Its many benefits need better appreciation, while lowered dosing can reduce risks.

Assessment of kidney health and exposure to mixture pollutants in the Mexican indigenous population

The indigenous population is one of the most vulnerable to suffer from contaminated environments. One of the target organs to suffer early deterioration from exposure to toxins is the kidney. The objective of this article was to evaluate biomarkers of exposure to organic and inorganic toxins and biomarkers of early kidney damage in urine from an indigenous Tenek population in Mexico. The biomarkers of exposure were Li, Be, Al, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Mo, Sn, Ba, and Pb evaluated by ICP-MS and hippuric acid for toluene exposure evaluated by UV-coupled with liquid chromatography; the biomarkers of kidney damage were cystatin C (Cys-C), osteopontin (OPN), retinol-binding protein-4 (RPB-4), and neutrophil gelatinase-associated lipocalin (NGAL). Thirty-one urine samples were obtained from indigenous people; 16, 42, 45.1, and 45.2% of the population exceeded the reference values for Pb, Zn, As, and hippuric acid respectively. Our results demonstrate significant correlations between the metals tested and the proteins associated with renal damage; Cys-C, OPN, and RPB4 showed a significant correlation with Li, B, and Mo, as well as hippuric acid in the case of Cys-C and Zn in OPN and RPB-4; NGAL did not present significant correlations with any of the pollutants of the study. This pilot study contributes to the evidence of great inequity in health associated to environmental pollution matters faced by indigenous people and addresses the need of initiatives for mitigation under the perspective that health is a fundamental human right.

Diagnostic tests and treatment procedures performed prior to cardiovascular death in individuals with severe mental illness

OBJECTIVE

To examine whether severe mental illnesses (i.e., schizophrenia or bipolar disorder) affected diagnostic testing and treatment for cardiovascular diseases in primary and specialized health care.

METHODS

We performed a nationwide study of 72 385 individuals who died from cardiovascular disease, of whom 1487 had been diagnosed with severe mental illnesses. Log-binomial regression analysis was applied to study the impact of severe mental illnesses on the uptake of diagnostic tests (e.g., 24-h blood pressure, glucose/HbA1c measurements, electrocardiography, echocardiography, coronary angiography, and ultrasound of peripheral vessels) and invasive cardiovascular treatments (i.e., revascularization, arrhythmia treatment, and vascular surgery).

RESULTS

Patients with and without severe mental illnesses had similar prevalences of cardiovascular diagnostic tests performed in primary care, but patients with schizophrenia had lower prevalences of specialized cardiovascular examinations (prevalence ratio (PR) 0.78; 95% CI 0.73-0.85). Subjects with severe mental illnesses had lower prevalences of invasive cardiovascular treatments (schizophrenia, PR 0.58; 95% CI 0.49-0.70, bipolar disorder, PR 0.78; 95% CI 0.66-0.92). The prevalence of invasive cardiovascular treatments was similar in patients with and without severe mental illnesses when cardiovascular disease was diagnosed before death.

CONCLUSION

Better access to specialized cardiovascular examinations is important to ensure equal cardiovascular treatments among individuals with severe mental illnesses.

Systematic review and practical guideline for the prevention and management of the renal side effects of lithium therapy

Lithium is the first line therapy of bipolar mood disorder. Lithium-induced nephrogenic diabetes insipidus (Li-NDI) and lithium nephropathy (Li-NP, i.e., renal insufficiency) are prevalent side effects of lithium therapy, with significant morbidity. The objective of this systematic review is to provide an overview of preventive and management strategies for Li-NDI and Li-NP. For this, the PRISMA guideline for systematic reviews was used. Papers on the prevention and/or treatment of Li-NDI or Li-NP, and (influenceable) risk factors for development of Li-NDI or Li-NP were included. We found that the amount of evidence on prevention and treatment of Li-NDI and Li-NP is scarce. To prevent Li-NDI and Li-NP we advise to use a once-daily dosing schedule, target the lowest serum lithium level that is effective and prevent lithium intoxication. We emphasize the importance of monitoring for Li-NDI and Li-NP, as early diagnosis and treatment can prevent further progression and permanent damage. Collaboration between psychiatrist, nephrologist and patients themselves is essential. In patients with Li-NDI and/or Li-NP cessation of lithium therapy and/or switch to another mood stabilizer should be considered. In patients with Li-NDI, off label therapy with amiloride can be useful.

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force

OBJECTIVES

The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD.

METHOD

A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD.

RESULTS

The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding.

CONCLUSION

Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings.

Impact of Long-Term Lithium Treatment on Renal Function in Patients With Bipolar Disorder Based on Novel Biomarkers

BACKGROUND

Lithium in the form of lithium carbonate (Li2CO3) has become one of the most effective and widely prescribed drugs for mood stabilization. However, lithium has adverse effects on renal tubular functions, such as decreased concentrating function of the kidneys, and even occasional symptoms of nephrogenous diabetes insipidus occur with additional evidence of glomerular disruption in lithium-treated patients.

METHODS

We assessed the kidney function of patients with bipolar disorder who are under long-term lithium treatment using novel markers of kidney damage such as plasma neutrophil gelatinase-associated lipocalin, cystatin C, albuminuria, estimated glomerular filtration rate, Chronic Kidney Disease-Epidemiology Investigation using creatinine and cystatin C, and serum and urinary osmolality, and compared the results with those of age-matched patients with bipolar disorder not treated with lithium. The study enrolled 120 patients with bipolar disorder, consisting of 80 (30 male and 50 female patients) who have been receiving lithium for 0.5 to 20 (mean, 7) years and 40 (10 male and 30 female patients) who had never been exposed to lithium treatment.

RESULTS

Patients treated with lithium had significantly decreased urine osmolality (mean ± SD, 405 ± 164 vs 667 ± 174 mmol/kg) and urine-to-serum osmolality ratio (1.35 ± 0.61 vs 2.25 ± 0.96). No significant difference was found in creatinine, estimated glomerular filtration rate values calculated using the Chronic Kidney Disease-Epidemiology Investigation using creatinine and cystatin C, neutrophil gelatinase-associated lipocalin, cystatin C, and albuminuria between both groups. We found no significant difference in renal biomarkers between patients treated with lithium for 6 to 24 months and those treated for 25 to 240 months.

CONCLUSIONS

We found significantly decreased kidney concentrating ability in the long-term lithium-treated patients compared with the control group. Other renal function markers did not indicate any significant signs of renal dysfunction.

Increased synapse elimination by microglia in schizophrenia patient-derived models of synaptic pruning

Synapse density is reduced in postmortem cortical tissue from schizophrenia patients, which is suggestive of increased synapse elimination. Using a reprogrammed in vitro model of microglia-mediated synapse engulfment, we demonstrate increased synapse elimination in patient-derived neural cultures and isolated synaptosomes. This excessive synaptic pruning reflects abnormalities in both microglia-like cells and synaptic structures. Further, we find that schizophrenia risk-associated variants within the human complement component 4 locus are associated with increased neuronal complement deposition and synapse uptake; however, they do not fully explain the observed increase in synapse uptake. Finally, we demonstrate that the antibiotic minocycline reduces microglia-mediated synapse uptake in vitro and its use is associated with a modest decrease in incident schizophrenia risk compared to other antibiotics in a cohort of young adults drawn from electronic health records. These findings point to excessive pruning as a potential target for delaying or preventing the onset of schizophrenia in high-risk individuals.

Factors related to lithium blood concentrations in Chinese Han patients with bipolar disorder

Background: The goal of this study was to identify the physiological factors related to the blood concentration of lithium in Chinese Han patients with bipolar disorder (BD). Materials and methods: A total of 186 Chinese Han patients with BD were assessed. Patients were recruited from the Anhui Mental Health Center. The concentrations of serum lithium were measured by a Dimension RxL Max biochemistry analyzer. Physiological factors, including body weight, body mass index (BMI), and routine laboratory parameters, were collected. Relationships between the serum lithium concentration and relevant clinical data were analyzed by Pearson correlation tests, and the independent relationships were determined by multivariate linear regression analysis. Results: Pearson correlation analysis showed that serum lithium concentrations were positively correlated with creatinine concentrations (r=0.147, P=0.046), Mg²⁺ concentrations (r=0.151, P=0.04), and the percentage of neutrophils (r=0.178, P=0.015) and negatively correlated with high-density lipoprotein (HDL) concentrations (r=-0.142, P=0.05), apolipoprotein A1 concentrations (r=-0.169, P=0.02), and Na⁺ concentrations (r=-0.148, P=0.046) in 186 patients with BD. Furthermore, multivariate linear regression analysis showed that serum lithium concentrations were negatively associated with Na⁺ concentrations and positively associated with the percentage of neutrophils. Conclusion: These results suggest that physiological factors, including creatinine, HDL, apolipoprotein A1, Na⁺, and Mg²⁺ concentrations and percentage of neutrophils, might be related to serum lithium concentrations and provide a basis for parameter selection of lithium population pharmacokinetics in Chinese Han patients with BD.

Lithium and nephrotoxicity: a literature review of approaches to clinical management and risk stratification

Background

Despite lithium being the most efficacious treatment for bipolar disorder, its use has been decreasing at least in part due to concerns about its potential to cause significant nephrotoxicity. Whilst the ability of lithium to cause nephrogenic diabetes insipidus is well established, its ability to cause chronic kidney disease is a much more vexing issue, with various studies suggesting both positive and negative causality. Despite these differences, the weight of evidence suggests that lithium has the potential to cause end stage kidney disease, albeit over a prolonged period.

Methods

A search strategy for this review was developed to identify appropriate studies, sourced from the electronic databases EMBASE, PubMed (NLM) and MEDLINE. Search terms included lithium with the AND operator to combine with nephrotoxicity or nephropathy or chronic kidney disease or nephrogenic diabetes insipidus or renal and pathophysiology.

Results

The risks for the development of lithium induced nephropathy are less well defined but appear to include the length of duration of therapy as well as increasing age, as well as episodes of over dosage/elevated lithium levels. Whilst guidelines exist for the routine monitoring of lithium levels and renal function, it remains unclear when nephrological evaluation should occur, as well as when cessation of lithium therapy is appropriate balancing the significant attendant mental health risks as well as the potential for progression to occur despite cessation of therapy against the risks and morbidity of bipolar disorder itself.

Conclusion

This paper will elucidate on the current evidence pertaining to the topic of the clinical management of lithium induced nephrotoxicity and provide a guide for clinicians who are faced with the long-term management of these patients.

The use of electronic health records for psychiatric phenotyping and genomics

The widespread adoption of electronic health record (EHRs) in healthcare systems has created a vast and continuously growing resource of clinical data and provides new opportunities for population-based research. In particular, the linking of EHRs to biospecimens and genomic data in biobanks may help address what has become a rate-limiting study for genetic research: the need for large sample sizes. The principal roadblock to capitalizing on these resources is the need to establish the validity of phenotypes extracted from the EHR. For psychiatric genetic research, this represents a particular challenge given that diagnosis is based on patient reports and clinician observations that may not be well-captured in billing codes or narrative records. This review addresses the opportunities and pitfalls in EHR-based phenotyping with a focus on their application to psychiatric genetic research. A growing number of studies have demonstrated that diagnostic algorithms with high positive predictive value can be derived from EHRs, especially when structured data are supplemented by text mining approaches. Such algorithms enable semi-automated phenotyping for large-scale case-control studies. In addition, the scale and scope of EHR databases have been used successfully to identify phenotypic subgroups and derive algorithms for longitudinal risk prediction. EHR-based genomics are particularly well-suited to rapid look-up replication of putative risk genes, studies of pleiotropy (phenomewide association studies or PheWAS), investigations of genetic networks and overlap across the phenome, and pharmacogenomic research. EHR phenotyping has been relatively under-utilized in psychiatric genomic research but may become a key component of efforts to advance precision psychiatry.

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder

The Canadian Network for Mood and Anxiety Treatments (CANMAT) previously published treatment guidelines for bipolar disorder in 2005, along with international commentaries and subsequent updates in 2007, 2009, and 2013. The last two updates were published in collaboration with the International Society for Bipolar Disorders (ISBD). These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments. These advances have been translated into clear and easy to use recommendations for first, second, and third- line treatments, with consideration given to levels of evidence for efficacy, clinical support based on experience, and consensus ratings of safety, tolerability, and treatment-emergent switch risk. New to these guidelines, hierarchical rankings were created for first and second- line treatments recommended for acute mania, acute depression, and maintenance treatment in bipolar I disorder. Created by considering the impact of each treatment across all phases of illness, this hierarchy will further assist clinicians in making evidence-based treatment decisions. Lithium, quetiapine, divalproex, asenapine, aripiprazole, paliperidone, risperidone, and cariprazine alone or in combination are recommended as first-line treatments for acute mania. First-line options for bipolar I depression include quetiapine, lurasidone plus lithium or divalproex, lithium, lamotrigine, lurasidone, or adjunctive lamotrigine. While medications that have been shown to be effective for the acute phase should generally be continued for the maintenance phase in bipolar I disorder, there are some exceptions (such as with antidepressants); and available data suggest that lithium, quetiapine, divalproex, lamotrigine, asenapine, and aripiprazole monotherapy or combination treatments should be considered first-line for those initiating or switching treatment during the maintenance phase. In addition to addressing issues in bipolar I disorder, these guidelines also provide an overview of, and recommendations for, clinical management of bipolar II disorder, as well as advice on specific populations, such as women at various stages of the reproductive cycle, children and adolescents, and older adults. There are also discussions on the impact of specific psychiatric and medical comorbidities such as substance use, anxiety, and metabolic disorders. Finally, an overview of issues related to safety and monitoring is provided. The CANMAT and ISBD groups hope that these guidelines become a valuable tool for practitioners across the globe.

Long-term lithium treatment in bipolar disorder: effects on glomerular filtration rate and other metabolic parameters

Background

Concerns about potential adverse effects of long-term exposure to lithium as a mood-stabilizing treatment notably include altered renal function. However, the incidence of severe renal dysfunction; rate of decline over time; effects of lithium dose, serum concentration, and duration of treatment; relative effects of lithium exposure vs. aging; and contributions of sex and other factors all remain unclear.

Methods

Accordingly, we acquired data from 12 collaborating international sites and 312 bipolar disorder patients (6142 person-years, 2669 assays) treated with lithium carbonate for 8–48 (mean 18) years and aged 20–89 (mean 56) years. We evaluated changes of estimated glomerular filtration rate (eGFR) as well as serum creatinine, urea–nitrogen, and glucose concentrations, white blood cell count, and body-mass index, and tested associations of eGFR with selected factors, using standard bivariate contrasts and regression modeling.

Results

Overall, 29.5% of subjects experienced at least one low value of eGFR (<60 mL/min/1.73 m²), most after ≥15 years of treatment and age > 55; risk of ≥2 low values was 18.1%; none experienced end-stage renal failure. eGFR declined by 0.71%/year of age and 0.92%/year of treatment, both by 19% more among women than men. Mean serum creatinine increased from 0.87 to 1.17 mg/dL, BUN from 23.7 to 33.1 mg/dL, glucose from 88 to 122 mg/dL, and BMI from 25.9 to 26.6 kg/m². By multivariate regression, risk factors for declining eGFR ranked: longer lithium treatment, lower lithium dose, higher serum lithium concentration, older age, and medical comorbidity. Later low eGFR was also predicted by lower initial eGFR, and starting lithium at age ≥ 40 years.

Limitations

Control data for age-matched subjects not exposed to lithium were lacking.

Conclusions

Long-term lithium treatment was associated with gradual decline of renal functioning (eGFR) by about 30% more than that was associated with aging alone. Risk of subnormal eGFR was from 18.1% (≥2 low values) to 29.5% (≥1 low value), requiring about 30 years of exposure. Additional risk factors for low eGFR were higher serum lithium level, longer lithium treatment, lower initial eGFR, and medical comorbidity, as well as older age.

The impact of machine learning techniques in the study of bipolar disorder: A systematic review

Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation.

Medical Complications of Psychiatric Treatment: An Update

Psychiatric medications are used commonly in hospitalized patients and are particularly indicated in patients who are critically ill to manage many conditions. Due to their many indications in the intensive care unit (ICU), psychiatric medications should be closely monitored in these medically compromised patients for adverse reactions and medical complications because they may affect essentially all organ systems. These range from life-threatening reactions to other less significant effects, such as sedation, to other detrimental complications, such as pancreatitis. Knowledge of psychopharmacology as well as the diagnosis and treatment of these complications is imperative in treating patients in the ICU.

Big data for bipolar disorder

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

Abandoning personalization to get to precision in the pharmacotherapy of depression

Effectiveness studies and analyses of naturalistic cohorts demonstrate that many patients with major depressive disorder do not experience symptomatic remission with antidepressant treatments. In an effort to better match patients with effective treatments, numerous investigations of predictors or moderators of treatment response have been reported over the past five decades, including clinical features as well as biological measures. However, none of these have entered routine clinical practice; instead, clinicians typically personalize treatment on the basis of patient preferences as well as their own. Here, we review the reasons why it has been challenging to identify and deploy treatment-specific predictors of response, and suggest strategies that may be required to achieve true precision in the pharmacotherapy of depression. We emphasize the need for changes in how depression care is delivered, measured, and used to inform future practice.

Core Concepts Involving Adverse Psychotropic Drug Effects: Assessment, Implications, and Management

Adverse effects from psychiatric drugs can profoundly influence treatment adherence and outcomes. Good care involves addressing adverse effects no differently than any other component of treatment. Knowledge about adverse effect assessment and management fosters a proper context that helps clinicians not sacrifice a drug's potential therapeutic benefits because of greater concerns about its tolerability. This article provides an overview of basic concepts related to the assessment and management of suspected adverse effects from psychotropic drugs. Key points are discussed regarding clinical, pharmacogenetic, pharmacokinetic, and pharmacodynamic risk factors for treatment-emergent adverse effects, alongside recommendations for their systematic assessment.

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach

OBJECTIVE

A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide.

METHOD

A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to 'train' a machine learning algorithm. The resulting algorithm was utilized in identifying novel or 'unseen' individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated.

RESULTS

All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65% and 72% (p<0.05). In particular, the relevance vector machine (RVM) algorithm correctly predicted 103 out of 144 subjects translating into 72% accuracy (72.1% sensitivity and 71.3% specificity) and an area under the curve of 0.77 (p<0.0001). The most relevant predictor variables in distinguishing attempters from non-attempters included previous hospitalizations for depression, a history of psychosis, cocaine dependence and post-traumatic stress disorder (PTSD) comorbidity.

CONCLUSION

Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide.