Artificial intelligence-powered clinical decision making within gastrointestinal surgery: A systematic review

BACKGROUND

Clinical decision-making in gastrointestinal surgery is complex due to the unpredictability of tumoral behavior and postoperative complications. Artificial intelligence (AI) could aid in clinical decision-making by predicting these surgical outcomes. The current status of AI-based clinical decision-making within gastrointestinal surgery is unknown in recent literature. This review aims to provide an overview of AI models used for clinical decision-making within gastrointestinal surgery.

METHODS

A systematic literature search was performed in databases PubMed, EMBASE, Cochrane, and Web of Science. To be eligible for inclusion, studies needed to use AI models for clinical decision-making involving patients undergoing gastrointestinal surgery. Studies reporting on reviews, children, and study abstracts were excluded. The Probast risk of bias tool was used to evaluate the methodological quality of AI methods.

RESULTS

Out of 1073 studies, 10 articles were eligible for inclusion. AI models have been used to make clinical decisions between surgical procedures, selection of chemotherapy, selection of postoperative follow up programs, and implementation of a temporary ileostomy. Most studies have used a Random Forest or Gradient Boosting model with AUCs up to 0.97. All studies involved a retrospective study design, in which external validation was performed in one study.

CONCLUSIONS

This review shows that AI models have the potentiality to select the most optimal treatments for patients undergoing gastrointestinal surgery. Clinical benefits could be gained if AI models were used for clinical decision-making. However, prospective studies and randomized controlled trials will reveal the definitive role of AI models in clinical decision-making.

Pharmacological prevention and treatment of opioid-induced constipation in cancer patients: A systematic review and meta-analysis

BACKGROUND

Cancer-related pain often requires opioid treatment with opioid-induced constipation (OIC) as its most frequent gastrointestinal side-effect. Both for prevention and treatment of OIC osmotic (e.g. polyethylene glycol) and stimulant (e.g. bisacodyl) laxatives are widely used. Newer drugs such as the peripherally acting µ-opioid receptor antagonists (PAMORAs) and naloxone in a fixed combination with oxycodone have become available for the management of OIC. This systematic review and meta-analysis aims to give an overview of the scientific evidence on pharmacological strategies for the prevention and treatment of OIC in cancer patients.

METHODS

A systematic search in PubMed, Embase, Web of Science and the Cochrane Library was completed from inception up to 22 October 2022. Randomized and non-randomized studies were systematically selected. Bowel function and adverse drug events were assessed.

RESULTS

Twenty trials (prevention: five RCTs and three cohort studies; treatment: ten RCTs and two comparative cohort studies) were included in the review. Regarding the prevention of OIC, three RCTs compared laxatives with other laxatives, finding no clear differences in effectivity of the laxatives used. One cohort study showed a significant benefit of magnesium oxide compared with no laxative. One RCT found a significant benefit for the PAMORA naldemedine compared with magnesium oxide. Preventive use of oxycodone/naloxone did not show a significant difference in two out of three other studies compared to oxycodone or fentanyl. A meta-analysis was not possible. Regarding the treatment of OIC, two RCTs compared laxatives, of which one RCT found that polyethylene glycol was significantly more effective than sennosides. Seven studies compared an opioid antagonist (naloxone, methylnaltrexone or naldemedine) with placebo and three studies compared different dosages of opioid antagonists. These studies with opioid antagonists were used for the meta-analysis. Oxycodone/naloxone showed a significant improvement in Bowel Function Index compared to oxycodone with laxatives (MD -13.68; 95 % CI -18.38 to -8.98; I2 = 58 %). Adverse drug event rates were similar amongst both groups, except for nausea in favour of oxycodone/naloxone (RR 0.51; 95 % CI 0.31-0.83; I2 = 0 %). Naldemedine (NAL) and methylnaltrexone (MNTX) demonstrated significantly higher response rates compared to placebo (NAL: RR 2.07, 95 % CI 1.64-2.61, I2 = 0 %; MNTX: RR 3.83, 95 % CI 2.81-5.22, I2 = 0 %). With regard to adverse events, abdominal pain was more present in treatment with methylnaltrexone and diarrhea was significantly more present in treatment with naldemedine. Different dosages of methylnaltrexone were not significantly different with regard to both efficacy and adverse drug event rates.

CONCLUSIONS

Magnesium oxide and naldemedine are most likely effective for prevention of OIC in cancer patients. Naloxone in a fixed combination with oxycodone, naldemedine and methylnaltrexone effectively treat OIC in cancer patients with acceptable adverse events. However, their effect has not been compared to standard (osmotic and stimulant) laxatives. More studies comparing standard laxatives with each other and with opioid antagonists are necessary before recommendations for clinical practice can be made.

A systematic review of (semi-)automatic quality control of T1-weighted MRI scans

PURPOSE

Artifacts in magnetic resonance imaging (MRI) scans degrade image quality and thus negatively affect the outcome measures of clinical and research scanning. Considering the time-consuming and subjective nature of visual quality control (QC), multiple (semi-)automatic QC algorithms have been developed. This systematic review presents an overview of the available (semi-)automatic QC algorithms and software packages designed for raw, structural T1-weighted (T1w) MRI datasets. The objective of this review was to identify the differences among these algorithms in terms of their features of interest, performance, and benchmarks.

METHODS

We queried PubMed, EMBASE (Ovid), and Web of Science databases on the fifth of January 2023, and cross-checked reference lists of retrieved papers. Bias assessment was performed using PROBAST (Prediction model Risk Of Bias ASsessment Tool).

RESULTS

A total of 18 distinct algorithms were identified, demonstrating significant variations in methods, features, datasets, and benchmarks. The algorithms were categorized into rule-based, classical machine learning-based, and deep learning-based approaches. Numerous unique features were defined, which can be roughly divided into features capturing entropy, contrast, and normative measures.

CONCLUSION

Due to dataset-specific optimization, it is challenging to draw broad conclusions about comparative performance. Additionally, large variations exist in the used datasets and benchmarks, further hindering direct algorithm comparison. The findings emphasize the need for standardization and comparative studies for advancing QC in MR imaging. Efforts should focus on identifying a dataset-independent measure as well as algorithm-independent methods for assessing the relative performance of different approaches.

Outcomes after Surgical Treatment for Rectal Atresia in Children: Is There a Preferred Approach? A Systematic Review

Rectal atresia (RA) affects only 1 to 2% of all children with anorectal malformations. No consensus on optimal treatment strategy is yet achieved. Therefore, the aim of this systematic review is to summarize all surgical interventions for RA and outcomes described in the current literature. A literature search was conducted in PubMed, Embase, Web of Science, and Cochrane Library on January 24, 2022. All studies describing treatment for RA in children (< 18 years) were included. Operation technique and postoperative complications were listed. Only descriptive analysis was anticipated. Quality of the studies was assessed using Johanna Briggs Institute critical appraisal checklist for case reports and series. The search yielded 6,716 studies of which, after duplicate removal, 4,028 were excluded based on title and abstract screening. After full-text assessment, 22 of 90 studies were included, yielding 70 patients. Posterior sagittal anorectoplasty (PSARP) and pull-through were most performed (43/70 and 18/70 patients, respectively). Four patients experienced postoperative complications: anal stenosis (n = 1), anastomotic stenosis (n = 2), and death due to a pulmonary complication (n = 1). In the low-quality literature available, most patients with RA are treated with PSARP or pull-through technique. A low complication rate of both has been described but follow-up was often not mentioned. Larger well-designed studies should be performed to determine optimal treatment strategy for children with RA. This study reflects level of evidence V.

Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review

Rational

Deep learning (DL) has demonstrated a remarkable performance in diagnostic imaging for various diseases and modalities and therefore has a high potential to be used as a clinical tool. However, current practice shows low deployment of these algorithms in clinical practice, because DL algorithms lack transparency and trust due to their underlying black-box mechanism. For successful employment, explainable artificial intelligence (XAI) could be introduced to close the gap between the medical professionals and the DL algorithms. In this literature review, XAI methods available for magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET) imaging are discussed and future suggestions are made.

Methods

PubMed, Embase.com and Clarivate Analytics/Web of Science Core Collection were screened. Articles were considered eligible for inclusion if XAI was used (and well described) to describe the behavior of a DL model used in MR, CT and PET imaging.

Results

A total of 75 articles were included of which 54 and 17 articles described post and ad hoc XAI methods, respectively, and 4 articles described both XAI methods. Major variations in performance is seen between the methods. Overall, post hoc XAI lacks the ability to provide class-discriminative and target-specific explanation. Ad hoc XAI seems to tackle this because of its intrinsic ability to explain. However, quality control of the XAI methods is rarely applied and therefore systematic comparison between the methods is difficult.

Conclusion

There is currently no clear consensus on how XAI should be deployed in order to close the gap between medical professionals and DL algorithms for clinical implementation. We advocate for systematic technical and clinical quality assessment of XAI methods. Also, to ensure end-to-end unbiased and safe integration of XAI in clinical workflow, (anatomical) data minimization and quality control methods should be included.

Urinary volatile organic compounds for colorectal cancer screening, a systematic review and meta-analysis

BACKGROUND

The faecal immunochemical test (FIT) suffers from suboptimal performance and participation in colorectal cancer (CRC) screening. Urinary volatile organic compounds (VOCs) may be a useful alternative. We aimed to determine the diagnostic potential of urinary VOCs for CRC/adenomas. By relating VOCs to known pathways, we aimed to gain insight into the pathophysiology of colorectal neoplasia.

METHODS

A systematic search was performed in PubMed, EMBASE and Web of Science. Original studies on urinary VOCs for CRC/adenoma detection with a control group were included. QUADAS-2 tool was used for quality assessment. Meta-analysis was performed by adopting a bivariate model for sensitivity/specificity. Fagan's nomogram estimated the performance of combined FIT-VOC. Neoplasm-associated VOCs were linked to pathways using the KEGG database.

RESULTS

Sixteen studies-involving 837 CRC patients and 1618 controls-were included; 11 performed chemical identification and 7 chemical fingerprinting. In all studies, urinary VOCs discriminated CRC from controls. Pooled sensitivity and specificity for CRC based on chemical fingerprinting were 84% (95% CI 73-91%) and 70% (95% CI 63-77%), respectively. The most distinctive individual VOC was butanal (AUC 0.98). The estimated probability of having CRC following negative FIT was 0.38%, whereas 0.09% following negative FIT-VOC. Combined FIT-VOC would detect 33% more CRCs. In total 100 CRC-associated urinary VOCs were identified; particularly hydrocarbons, carboxylic acids, aldehydes/ketones and amino acids, and predominantly involved in TCA-cycle or alanine/aspartate/glutamine/glutamate/phenylalanine/tyrosine/tryptophan metabolism, which is supported by previous research on (colorectal)cancer biology. The potential of urinary VOCs to detect precancerous adenomas or gain insight into their pathophysiology appeared understudied.

CONCLUSION

Urinary VOCs hold potential for non-invasive CRC screening. Multicentre validation studies are needed, especially focusing on adenoma detection. Urinary VOCs elucidate underlying pathophysiologic processes.

The quality of geriatric rehabilitation from the patients' perspective: a scoping review

BACKGROUND

the efficacy and outcomes of geriatric rehabilitation (GR) have previously been investigated. However, a systematic synthesis of the aspects that are important to patients regarding the quality of GR does not exist.

OBJECTIVE

the aim of this scoping review was to systematically synthesise the patients' perspective on the quality of GR.

METHODS

we followed the Scoping Review framework and gathered literature including a qualitative study design from multiple databases. The inclusion criteria were: a qualitative study design; a geriatric population; that patients had participated in a geriatric rehabilitation programme and that geriatric rehabilitation was assessed by the patient. The results sections of the included studies were analysed using a thematic analysis approach.

RESULTS

twenty articles were included in this review. The main themes identified were: (i) the need for information about the rehabilitation process, (ii) the need for telling one's story, (iii) the need for support (physical, psychological, social and how to cope with limitations), (iv) the need for shared decision-making and autonomy, (v) the need for a stimulating rehabilitation environment and (vi) the need for rehabilitation at home.

CONCLUSION

in this study, we identified the aspects that determine the quality of rehabilitation from the patient's perspective, which may lead to a more holistic perspective on the quality of GR.

How to improve inpatient sleep in regular care wards: a systematic review and meta-analysis of sleep disturbers and non-pharmacological interventions

OBJECTIVE

To determine factors affecting inpatient sleep and assess the range and effectiveness of non-pharmacological interventions aimed at improving the sleep of patients admitted to regular care wards.

METHODS

A systematic literature search was conducted in five scientific databases, including articles published from inception to June 23rd, 2023. Eligible studies evaluated sleep disturbing factors or the effect of non-pharmacological intervention(s). Meta-analyses on intervention studies were conducted using a random effects model. Certainty of evidence was assessed using the GRADE approach.

RESULTS

Out of 591 potentially eligible studies, 229 were included in this review. Sleep disturbers were identified in 153 studies, and 102 studies were eligible for meta-analysis. Common factors contributing to poor sleep included noise, light, care-related interruptions, pain, and anxiety. The meta-analyses revealed large pooled effects in favor of sleep for the use of eye masks and earplugs, headphones and white noise, aromatherapy, massage, muscle relaxation and breathing exercises, and advanced nursing strategies. However, the certainty of the evidence ranged from moderate to very low.

CONCLUSION

Inpatient sleep is often disturbed by patient-related, care-related, and environmental factors. While there are promising non-pharmacological interventions, the overall quality of studies, heterogeneity in study populations, and differences in outcome measures present challenges for drawing definitive conclusions.

Machine learning applications in upper gastrointestinal cancer surgery: a systematic review

BACKGROUND

Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Therefore, this systematic review aims to provide a comprehensive overview of ML applications within upper gastrointestinal surgery for malignancies.

METHODS

A systematic search was performed in PubMed, EMBASE, Cochrane, and Web of Science. Studies were only included when they described machine learning in upper gastrointestinal surgery for malignancies. The Cochrane risk-of-bias tool was used to determine the methodological quality of studies. The accuracy and area under the curve were evaluated, representing the predictive performances of ML models.

RESULTS

From a total of 1821 articles, 27 studies met the inclusion criteria. Most studies received a moderate risk-of-bias score. The majority of these studies focused on neural networks (n = 9), multiple machine learning (n = 8), and random forests (n = 3). Remaining studies involved radiomics (n = 3), support vector machines (n = 3), and decision trees (n = 1). Purposes of ML included predominantly prediction of metastasis, detection of risk factors, prediction of survival, and prediction of postoperative complications. Other purposes were predictions of TNM staging, chemotherapy response, tumor resectability, and optimal therapy.

CONCLUSIONS

Machine Learning algorithms seem to contribute to the prediction of postoperative complications and the course of disease after upper gastrointestinal surgery for malignancies. However, due to the retrospective character of ML studies, these results require trials or prospective studies to validate this application of ML.

Pharmacological Optimization of PSMA-Based Radioligand Therapy

Prostate cancer (PCa) is the most common malignancy in men of middle and older age. The standard treatment strategy for PCa ranges from active surveillance in low-grade, localized PCa to radical prostatectomy, external beam radiation therapy, hormonal treatment and chemotherapy. Recently, the use of prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) for metastatic castration-resistant PCa has been approved. PSMA is predominantly, but not exclusively, expressed on PCa cells. Because of its high expression in PCa, PSMA is a promising target for diagnostics and therapy. To understand the currently used RLT, knowledge about pharmacokinetics (PK) and pharmacodynamics (PD) of the PSMA ligand and the PSMA protein itself is crucial. PK and PD properties of the ligand and its target determine the duration and extent of the effect. Knowledge on the concentration-time profile, the target affinity and target abundance may help to predict the effect of RLT. Increased specific binding of radioligands to PSMA on PCa cells may be associated with better treatment response, where nonspecific binding may increase the risk of toxicity in healthy organs. Optimization of the radioligand, as well as synergistic effects of concomitant agents and an improved dosing strategy, may lead to more individualized treatment and better overall survival.

Sleep in hospitalized pediatric and adult patients – A systematic review and meta-analysis

Background

Sleep is essential for recovery from illness. As a result, researchers have shown a growing interest in the sleep of hospitalized patients. Although many studies have been conducted over the past years, an up to date systematic review of the results is missing.

Objective

The objective of this systematic review was to assess sleep quality and quantity of hospitalized patients and sleep disturbing factors.

Methods

A systematic literature search was conducted within four scientific databases. The search focused on synonyms of 'sleep’ and 'hospitalization’. Papers written in English or Dutch from inception to April 25th,2022 were included for hospitalized patients >1 year of age. Papers exclusively reporting about patients receiving palliative, obstetric or psychiatric care were excluded, as well as patients in rehabilitation and intensive care settings, and long-term hospitalized geriatric patients. This review was performed in accordance with the PRISMA guidelines.

Results

Out of 542 full text studies assessed for eligibility, 203 were included, describing sleep quality and/or quantity of 17,964 patients. The median sample size of the studies was 51 patients (IQR 67, range 6–1472). An exploratory meta-analysis of the Total Sleep Time showed an average of 7.2 h (95%-CI 4.3, 10.2) in hospitalized children, 5.7 h (95%-CI 4.8, 6.7) in adults and 5.8 h (95%-CI 5.3, 6.4) in older patients (>60y). In addition, a meta-analysis of the Wake After Sleep Onset (WASO) showed a combined high average of 1.8 h (95%-CI 0.7, 2.9). Overall sleep quality was poor, also due to nocturnal awakenings. The most frequently cited external factors for poor sleep were noise and number of patients in the room. Among the variety of internal/disease-related factors, pain and anxiety were most frequently mentioned to be associated with poor sleep.

Conclusion

Of all studies, 76% reported poor sleep quality and insufficient sleep duration in hospitalized patients. Children sleep on average 0.7–3.8 h less in the hospital than recommended. Hospitalized adults sleep 1.3–3.2 h less than recommended for healthy people. This underscores the need for interventions to improve sleep during hospitalization to support recovery.

•

An overview of the magnitude of sleep deprivation in hospitalized patients.

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A meta-analysis of studies reporting on some of the main sleep outcomes.

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An overview of internal and external factors affecting sleep in hospitalized patients.

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Guidance for potential interventions to improve sleep during clinical admission.

•

Uncovers a knowledge gap regarding the sleep quality of hospitalized children and daytime sleep of hospitalized adults.

Experiences of living with leprosy: A systematic review and qualitative evidence synthesis

OBJECTIVE

The objective of the review was to identify, appraise, and synthesise qualitative studies on the lived experience of individuals diagnosed with leprosy, the impact of the disease, and how they coped with the disease burden.

INTRODUCTION

Leprosy is a chronic disease with long-term biopsychosocial impact and is a leading cause of preventable disabilities. It traps the individuals with leprosy in a vicious circle of disease, stigma, and poverty. The efforts to reduce stigma and discrimination and improve their quality of life have not kept pace with the success of the multidrug treatment.

INCLUSION CRITERIA

This review considered published literature on the lived experience of individuals diagnosed with leprosy. There were no limitations on gender, background, or country. All qualitative or mixed-methods studies were accepted.

METHODS

The review followed the JBI meta-aggregation approach for qualitative systematic reviews. A structured literature search was undertaken using multiple electronic databases: PubMed, Embase, Web of Science, and CINAHL.

RESULTS

The search identified 723 publications, and there were 446 articles after deduplication. Forty-nine studies met the inclusion criteria. The final 173 findings were synthesised into ten categories and aggregated into four synthesised findings: biophysical impact, social impact, economic impact, and mental and emotional impact. These synthesised findings were consistent across the included studies from a patient's perspective. The way people coped with leprosy depended on their interpretation of the disease and its treatment. It affected their help-seeking behaviour and their adherence to treatment and self-care. The review has identified a multi-domain effect on the affected individuals, which goes beyond the biological and physical effects, looking at the social issues, specific difficulties, emotions, and economic hardships.

CONCLUSIONS

The researchers, health professionals, and policymakers could use the synthesised findings to address the concerns and needs of the leprosy-affected individuals and offer appropriate support to manage their lives.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO Registration number: CRD42021243223.

Artificial Intelligence in Bariatric Surgery: Current Status and Future Perspectives

Background

Machine learning (ML) has been successful in several fields of healthcare, however the use of ML within bariatric surgery seems to be limited. In this systematic review, an overview of ML applications within bariatric surgery is provided.

Methods

The databases PubMed, EMBASE, Cochrane, and Web of Science were searched for articles describing ML in bariatric surgery. The Cochrane risk of bias tool and the PROBAST tool were used to evaluate the methodological quality of included studies.

Results

The majority of applied ML algorithms predicted postoperative complications and weight loss with accuracies up to 98%.

Conclusions

In conclusion, ML algorithms have shown promising capabilities in the prediction of surgical outcomes after bariatric surgery. Nevertheless, the clinical introduction of ML is dependent upon the external validation of ML.

[18F]FDG-PET/CT in Staphylococcus aureus bacteremia: a systematic review

OBJECTIVES

[18F]FDG-PET/CT is used for diagnosing metastatic infections in Staphylococcus aureus bacteremia (SAB) and guidance of antibiotic treatment. The impact of [18F]FDG-PET/CT on outcomes remains to be determined. The aim of this systematic review was to summarize the effects of [18F]FDG-PET/CT on all-cause mortality and new diagnostic findingsin SAB.

METHODS

We systematically searched PubMed, EMBASE.com, Web of Science, and Wiley's Cochrane library from inception to 29 January 2021. Eligible studies were randomized controlled trials, clinically controlled trials, prospective and retrospective cohort studies, and case-control studies investigating the effects of [18F]FDG-PET/CT in hospitalized adult patients with SAB. We excluded studies lacking a control group without [18F]FDG-PET/CT. Risk of bias was assessed using the ROBINS-I tool and certainty of evidence using the GRADE approach by two independent reviewers.

RESULTS

We identified 1956 studies, of which five were included in our qualitative synthesis, including a total of 880 SAB patients. All studies were non-randomized and at moderate or serious risk of bias. Four studies, including a total of 804 patients, reported lower mortality in SAB patients that underwent [18F]FDG-PET/CT. One study including 102 patients reported more detected metastatic foci in the participants in whom [18F]FDG-PET/CT was performed.

DISCUSSION

We found low certainty of evidence that [18F]FDG-PET/CT reduces mortality in patients with SAB. This effect is possibly explained by a higher frequency of findings guiding optimal antibiotic treatment and source control interventions.

Machine Learning Algorithms for Predicting Surgical Outcomes after Colorectal Surgery: A Systematic Review

BACKGROUND

Machine learning (ML) has been introduced in various fields of healthcare. In colorectal surgery, the role of ML has yet to be reported. In this systematic review, an overview of machine learning models predicting surgical outcomes after colorectal surgery is provided.

METHODS

Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using machine learning models for patients undergoing colorectal surgery. To be eligible for inclusion, studies needed to apply machine learning models for patients undergoing colorectal surgery. Absence of machine learning or colorectal surgery or studies reporting on reviews, children, study abstracts were excluded. The Probast risk of bias tool was used to evaluate the methodological quality of machine learning models.

RESULTS

A total of 1821 studies were analysed, resulting in the inclusion of 31 articles. A vast proportion of ML algorithms have been used to predict the course of disease and response to neoadjuvant chemoradiotherapy. Radiomics have been applied most frequently, along with predictive accuracies up to 91%. However, most studies included a retrospective study design without external validation or calibration.

CONCLUSIONS

Machine learning models have shown promising potential in predicting surgical outcomes after colorectal surgery. However, large-scale data is warranted to bridge the gap between calibration and external validation. Clinical implementation is needed to demonstrate the contribution of ML within daily practice.

The Effect of Pasteurization on the Antioxidant Properties of Human Milk: A Literature Review

High rates of oxidative stress are common in preterm born infants and have short- and long-term consequences. The antioxidant properties of human milk limits the consequences of excessive oxidative damage. However, as the mother's own milk it is not always available, donor milk may be provided as the best alternative. Donor milk needs to be pasteurized before use to ensure safety. Although pasteurization is necessary for safety reasons, it may affect the activity and concentration of several biological factors, including antioxidants. This literature review describes the effect of different pasteurization methods on antioxidant properties of human milk and aims to provide evidence to guide donor milk banks in choosing the best pasteurization method from an antioxidant perspective. The current literature suggests that Holder pasteurization reduces the antioxidant properties of human milk. Alternative pasteurization methods seem promising as less reduction is observed in several studies.

Fetal akinesia deformation sequence and massive perivillous fibrin deposition resulting in fetal death in six fetuses from one consanguineous couple, including literature review

Background

Massive perivillous fibrin deposition (MPFD) is associated with adverse pregnancy outcomes and is mainly caused by maternal factors with limited involvement of fetal or genetic causes. We present one consanguineous couple with six fetuses developing Fetal Akinesia Deformation Sequence (FADS) and MPFD, with a possible underlying genetic cause. This prompted a literature review on prevalence of FADS and MPFD.

Methods

Fetal ultrasound examination, motor assessment, genetic testing, postmortem examination, and placenta histology are presented (2009–2019). Literature was reviewed for the association between congenital anomalies and MPFD.

Results

All six fetuses developed normally during the first trimester. Thereafter, growth restriction, persistent flexed position, abnormal motility, and contractures in 4/6, consistent with FADS occurred. All placentas showed histologically confirmed MPFD. Genetic analyses in the five available cases showed homozygosity for two variants of unknown significance in two genes, VARS1 (OMIM*192150) and ABCF1 (OMIM*603429). Both parents are heterozygous for these variants. From 63/1999 manuscripts, 403 fetal outcomes were mobilized. In 14/403 fetuses, congenital abnormalities in association with MPFD were seen of which two fetuses with contractures/FADS facial anomalies.

Conclusion

The low prevalence of fetal contractures/FADS facial anomalies in association with MPFD in the literature review supports the possible fetal or genetic contribution causing FADS and MPFD in our family. This study with literature review supports the finding that fetal, fetoplacental, and/or genetic components may play a role in causing a part of MPFDs.